Science 4-Hire

Guest: Christine Boyce, Global Innovation Leader at ManpowerGroup/Right Management“We have to stress-test innovation in the messiness of real-world hiring, not just ideal lab conditions.”-Christine BoyceIn this episode of Psych Tech @ Work, I'm joined by my longtime friend Christine Boyce, Global Innovation Leader at ManpowerGroup/Right Management, to explore how innovation — especially around AI — is reshaping hiring and talent development at scale, and why solving for trust, transparency, and operational realities matters more than ever.SummaryAt the heart of this conversation is the reality that scaling AI innovation in hiring brings massive complexity. While AI offers incredible promise, solving for accuracy, fairness, and operational reality becomes exponentially harder when you're dealing with a large number of unique clients.Christine Boyce, through her work at ManpowerGroup & Right Management, operates at the intersection of these challenges every day. Unlike internal talent acquisition leaders who focus on one organization's needs, Christine must help innovate across a vast client portfolio. Each client presents different barriers — from data limitations, to ethical concerns, to regulatory pressures — and innovation must be modular, defensible, and adaptable to succeed.This vantage point gives Christine a unique, big-picture view of how AI adoption really plays out across industries and markets.We dive into the practical challenges of innovating responsibly: earning trust, scaling solutions across diverse environments, and balancing speed with fairness. Christine's work at ManpowerGroup & Right Management highlights how innovation must be deeply disciplined if it is to achieve true scale and impact.The Core Challenge: Scaling Accuracy and FairnessAt the heart of using AI for hiring lies the challenge of achieving accuracy and fairness at scale. AI's true value isn't just its ability to make individual decisions — it's in processing vast amounts of data and automating judgment across thousands of candidates. However, scale magnifies both strengths and weaknesses: minor biases can grow into systemic problems, and small inefficiencies can snowball into major failures.Staffing firms like ManpowerGroup offer critical real-world lessons:* Scale forces discipline — Every AI tool must be rigorously vetted for fairness, transparency, and defensibility before deployment.* Real-world variation stresses the system for the better — Tools must flexibly adapt to diverse jobs, industries, and candidate pools. This makes the overall path of innovation better and drives great learnings across the board.* Speed must not erode trust — Productivity gains must still respect ethical standards and candidate experience.* External accountability keeps AI honest — Clients demand transparency, validation, and explainability before adoption.Real Barriers to AI Adoption: What Clients Are FacingDespite AI's potential, Christine identifies several persistent hurdles that she faces when serving her diverse slate of clients:* Resistance to Behavior Change: Even demonstrably valuable AI tools often struggle against entrenched workflows and distrust of automation.* Ethical and Trust Concerns: Clients demand AI systems that are transparent, explainable, and defensible, fearing reputational or regulatory risks.* Vendor Noise Overload: Saturation by "AI-washed" vendors makes it hard to differentiate true innovation from hype.* Mismatch Between Hype and Practical Needs: Clients need tools that solve today's operational problems — not just futuristic visions disconnected from reality.* Fear of Creeping AI Adoption: Organizations worry about AI capabilities being embedded into systems without visibility or intentionality.* Compliance and Regulation Anxiety: Global and local regulations (like the EU AI Act or pending US laws) create urgency for proven, compliant AI solutions.* Talent Data Readiness: Without clean, structured internal data, even the best AI solutions struggle to deliver meaningful results.These challenges aren't isolated — they reveal the broader realities companies must manage when trying to adopt AI responsibly at scale.Ultimately, client concerns have a hand in AI innovation because they are critical for the adoption of these technologies, shaping how staffing firms and vendors must design, validate, and deploy solutions.There's an inherent tension between the drive for scale and the need for trust, fairness, and operational reality.Christine's experience demonstrates that true innovation in AI for hiring isn't just about introducing new tools — it's about creating resilient, transparent systems that can adapt to real-world complexity. Managing the tension between speed, scale, trust, and fairness represents the path to a bright future. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"Part of putting an AI strategy together is understanding the limitations and where unintended consequences could occur, which is why you need diversity of thought within committees created to guide AI governance and ethics." – Bob PulverMy guest for this episode is my friend in ethical/responsible AI, Bob Pulver, the founder of CognitivePath.io and host of the podcast "Elevate Your AIQ." Bob specializes in helping organizations navigate the complexities of responsible AI, from strategic adoption to effective governance practices.  Bob was my guest about a year ago and in this episode he drops back in to discuss what has changed in the faced paced world of AI across three pillars of responsible AI usage.  * Human-Centric AI * AI Adoption and Readiness * AI Regulation and GovernanceThe past year's progress explained through three pillars that are shaping ethical AI:These are the themes that we explore in our conversation and our thoughts on what has changed/evolved in the past year.1. Human-Centric AIChange from Last Year:* Shift from compliance-driven AI towards a more holistic, human-focused perspective, emphasizing AI's potential to enhance human capabilities and fairness.Reasons for Change:* Increasing comfort level with AI and experience with the benefits that it brings to our work* Continued exploration and development of low stakes, low friction use cases* AI continues to be seen as a partner and magnifier of human capabilitiesWhat to Expect in the Next Year:* Increased experience with human machine partnerships* Increased opportunities to build superpowers* Increased adoption of human centric tools by employers2. AI Adoption and ReadinessChange from Last Year:* Organizations have moved from cautious, fragmented adoption to structured, strategic readiness and literacy initiatives.* Significant growth in AI educational resources and adoption within teams, rather than just individuals.Reasons for Change:* Improved understanding of AI's benefits and limitations, reducing fears and resistance.* Availability of targeted AI literacy programs, promoting organization-wide AI understanding and capability building.What to Expect in the Next Year:* More systematic frameworks for AI adoption across entire organizations.* Increased demand for formal AI proficiency assessments to ensure responsible and effective usage.3. AI Regulation and GovernanceChange from Last Year:* Transition from broad discussions about potential regulations towards concrete legislative actions, particularly at state and international levels (e.g., EU AI Act, California laws).* Momentum to hold vendors of AI increasingly accountable for ethical AI use.Reasons for Change:* Growing awareness of risks associated with unchecked AI deployment.* Increased push to stay on the right side of AI via legislative activity at state and global levels addressing transparency, accountability, and fairness.What to Expect in the Next Year:* Implementation of stricter AI audits and compliance standards.* Clearer responsibilities for vendors and organizations regarding ethical AI practices.* Finally some concrete standards that will require fundamental changes in oversight and create messy situations.Practical Takeaways:What should I/we be doing to move the ball fwd and realize AI's full potential while limiting collateral damage?Prioritize Human-Centric AI Design* Define Clear Use Cases: Ensure AI is solving a genuine human-centered problem rather than just introducing technology for technology's sake.* Promote Transparency and Trust: Clearly communicate how and why AI is being used, ensuring it enhances rather than replaces human judgment and involvement.Build Robust AI Literacy and Education Programs* Develop Organizational AI Literacy: Implement structured training initiatives that educate employees about fundamental AI concepts, the practical implications of AI use, and ethical considerations.* Create Role-Specific Training: Provide tailored AI skill-building programs based on roles and responsibilities, moving beyond individual productivity to team-based effectiveness.Strengthen AI Governance and Oversight* Adopt Proactive Compliance Practices: Align internal policies with rigorous standards such as the EU AI Act to preemptively prepare for emerging local and global legislation.* Vendor Accountability: Develop clear guidelines and rigorous vetting processes for vendors to ensure transparency and responsible use, preparing your organization for upcoming regulatory audits.Monitor AI Effectiveness and Impact* Continuous Monitoring: Shift from periodic audits to continuous monitoring of AI tools to ensure fairness, transparency, and functionality.* Evaluate Human Impact Regularly: Regularly assess the human impact of AI tools on employee experience, fairness in decision-making, and organizational trust.Email Bob- bob@cognitivepath.io Listen to Bob's awesome podcast - Elevate you AIQ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

“We have to move beyond the idea that a skills-based job description is enough—there needs to be validation, assessment, and a clear pathway for job seekers to prove their abilities.”-Jason TyszkoIn this episode of Psych Tech @ Work, I sit down with Jason Tyszko, Senior Vice President of the U.S. Chamber of Commerce Foundation, to discuss what it really takes to make skills-based hiring a reality. Jason oversees the Foundation's T3 Innovation Network, a public-private initiative aimed at creating a more equitable and inclusive job market. T-3 focuses on using digital tools to improve communication between different parts of the job market, ensuring that all learning is recognized and valued.  T-3's mission to bridge gaps between employers and workers via the advancement of skills-based hiring makes Jason one of the  world's foremost authorities on the subject.Our conversation is a must for anyone interested in understanding the REALITIES required for true skills-based hiring.  Most conversations on the subject are more hype than substance, but not this one!  Jason takes us deeper into the reality of what it will take to make skills based hiring more than just an empty buzzword.To ground our conversation in a dose of reality, Jason boils success with skills based hiring into these three pillars.* Interoperable Skills Data* To make skills-based hiring a reality, we need standardized, structured, and widely accepted skills data that flows seamlessly across education providers, employers, and workforce systems.* Without interoperability, skills data remains fragmented, making it difficult for employers to assess candidates meaningfully.* Employer Engagement and Adoption* Employers must align job descriptions, hiring processes, and internal mobility pathways around skills rather than degrees or traditional credentials.* Many organizations support skills-based hiring in theory but fail to implement it fully due to ingrained legacy practices.* Technology Infrastructure and Ecosystem Readiness* AI, job-matching platforms, and hiring tools must be built to recognize and evaluate skills accurately, rather than simply filtering candidates based on outdated proxies like job titles or degrees.* Systems should support skills validation, assessment, and transparent career pathways to ensure fair and effective hiring decisions.Jason explains how these pillars support and enable five critical but often overlooked elements that are essential to making skills-based hiring work: 1. Learning and Employment Records (LERs) & The LER Resume Standard* What it is: LERs are digital, verifiable records of a person's skills, training, certifications, and work experience. Instead of relying on traditional resumes or self-reported skills, LERs allow employers to see a structured, validated record of a candidate's capabilities.* Why it matters: Today's hiring systems don't talk to each other. Skills data is trapped in different platforms (learning management systems, certifications, HR software). LERs allow skills-based hiring to function at scale by ensuring a candidate's credentials are portable and universally recognized.* LER Resume Standard: This is a newly developed resume format built to process LERs, ensuring HR tech systems can read, compare, and use skills-based data more effectively.2. Durable Skills* What it is: Unlike technical skills (which can quickly become outdated), durable skills are long-lasting, transferable skills like critical thinking, adaptability, leadership, and collaboration.* Why it matters: Most AI-driven hiring tools over-prioritize technical skills, but durable skills are what truly drive career success. Without a way to assess and validate them, companies risk hiring for short-term needs instead of long-term potential.3. The Interoperability Layer* What it is: A technical framework that allows skills data from different platforms to connect and work together—like an API that helps job boards, HR systems, and learning platforms “speak the same language.”* Why it matters: Right now, skills-based hiring is fragmented because every company and HR tech provider uses different skills taxonomies and formats. An interoperability layer standardizes how skills data is shared, making it easier for employers to evaluate candidates based on a common skills framework.4. Employer-Led Recognition* What it is: A system where workers' skills are validated by their employers and colleagues, not just through certifications or formal education. This could involve peer endorsements, manager assessments, or internal training validations.* Why it matters: Most skills-based hiring focuses on externally validated credentials (e.g., certificates, degrees), but many people develop critical skills on the job. Without a structured way to recognize and verify these skills, businesses overlook talent that is already in their workforce.5. Skills Wallets* What it is: A digital, user-controlled repository where individuals can store, manage, and share verified records of their skills, credentials, and learning experiences.* Why it matters: Unlike traditional resumes or degree transcripts, Skills Wallets give workers full ownership of their skills data, making it portable across jobs, industries, and learning platforms. This enables lifelong learning and career mobility in ways that existing hiring systems do not support.* Skills-based hiring has the potential to transform the workforce, but it won't succeed without system-wide changes in HR technology, workforce data, and employer incentives. Jason's insights reveal the often-ignored challenges and solutions that can make this shift truly scalable and effective. If you're in talent strategy, workforce development, or HR technology, this episode provides a realistic roadmap for making skills-first hiring work.* Learn more about the T3 Innovation Network: t3networkhub.org* Contact Jason This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

In our recent LinkedIn Live session my esteemed colleague, Neil Morelli, founder of Workplace Labs, and I present a philosophical but practical approach to the adoption of HR Tech tools.Check out the full video of the presentation attached to this post and our accompanying slides (found at the bottom of the post).Here is a quick overview of the ideas that form the foundation of the presentation.“The highest-level goal of the talent acquisition (TA) function is to ensure that an organization has the right people, in the right roles, at the right time, to drive business success.”-Chat GPT 4o & your hosts' combined 50 years of experienceTalent leaders are feeling the pressure to executeModern hiring problems such as resource constraints, candidate scarcity and overload, the move to skills based hiring, and avoiding bias have talent leaders feeling the pressure to find fast solutions!Relieving these pressures often create a temptation to put tools before strategy. AI is a great example of this.The stakes are high, and AI offers a compelling solution- or does it? AI is complex and making decisions about it requires a strong foundation of knowledge and careful planning.In this presentation we discuss 4 common mistakes in the adoption of HR tech, with a focus on AI tools (are there any other types these days?).We discuss how a tools first mentality is often the root cause of these four common mistakes and offer guidance on how to avoid them. 1. Missing AI's ‘creeping normality': As technology becomes more entrenched in your processes and vendors add new functionalities that are accessible, adoption often occurs with little oversight or consideration. When it comes to solving problems related to talent supply or overload, AI recruitment platforms are increasingly embedding “talent matching” functionalities that create risk without any substantial rewards. 2. Chasing Skills Without Definition or Direction: We can all agree that skills based hiring has merit. But it requires alignment on what a skill means to your organization and a holistic view of where they matter and why. Merely removing resumes from the evaluation process or adopting tools, AI or otherwise, that claim to support skills based hiring without a holistic strategy is a dead end street.3. Failing to evaluate your firm's culture and climate for adopting AI based tools: There is a maturity required for the successful adoption of AI based tools. Understanding your firm's readiness for AI based tools, and ensuring that you are ready to go all in is essential. Education on, and knowledge of, AI across the entire organization is a big part of successful adoption. 4. Letting vendors dictate strategy and adoption: Most vendors do offer products that can have an impact, and their messages make it tempting to jump right in. Before biting on a shiny new object, adoption of any AI based tool should be pre-empted by a house made strategy. Vendors must be held to a standard evaluated by domain experts using a framework built on the principles of ethical and effective use of AI.At the end of the presentation we provide a case study that probably feels pretty relatable to any talent acquisition professional. Here we tell a story of how mistakes are made and provide insights to help create the awareness needed to avoid them.No one is perfect - but AI alone will not create perfection. Keeping things in perspective and a thoughtful and methodical process that is not driven by fear is essential to the successful adoption of AI technologies.Download our slides here This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"The hiring industry is at a breaking point—AI is putting pressure on old systems that were never designed for this level of automation."–Jeff TaylorIn this episode of Psych Tech @ Work, I am joined by Jeff Taylor, serial entrepreneur and founder of Monster.com, & Boomband a revolutionary new platform that is looking to turn hiring on its ear.Few people have shaped the hiring industry as profoundly as Jeff, whose vision transformed job search from a niche experiment into an industry standard. Jeff's journey—from building the first large-scale job board to continuously innovating in the talent acquisition space—gives him a unique perspective on where hiring technology has been and where it's headed, making him the perfect guest to explore the next big disruptions in talent acquisition and how AI is reshaping the hiring process..  In our time together we reminisce about the story behind Monster's memorable Superbowl ads. (Who can forget the kid saying:  “I want to claw my way up to middle management!” ) and the formative impact my job at Monster (circa 2000) has had on my career.  But enough about me!  Our conversation explores the rapid acceleration of AI in recruiting, from automating sourcing and matching to the potential risks of AI-generated applications flooding hiring systems. Jeff happily shares his candid thoughts on why hiring technology has stagnated, how AI is creating new challenges for recruiters, and what companies must do to stay ahead in an increasingly automated hiring landscape. We also discuss the core concepts behind Boomband, Jeff's new social hiring platform.Topics Covered:* Monster.com's origin story and how it transformed hiring and created the “job board” industry.* The shift from traditional job search to AI-driven sourcing and candidate matching and what this means for the future of hiring.* The pros and cons of AI-generated resumes and job applications—are we heading toward an overload of unqualified applicants?* The failure of legacy hiring systems to keep up with modern job-seeker behavior.* The potential for AI to create more personalized and predictive hiring experiences and Boomband Jeff's new venture that is focused on creating a new paradigm for hiring (again!).Takeaways:* Job boards revolutionized hiring—but they haven't evolved fast enough. The core concept of posting jobs and waiting for applications hasn't fundamentally changed in decades.* AI is making job search more efficient but also more chaotic. Automated resume generation and mass applications are overwhelming recruiters and breaking traditional applicant tracking systems.* Legacy hiring technology is struggling to adapt. The demand for AI-powered sourcing and skills-based hiring is exposing the limitations of old-school job posting and resume-matching platforms.* The next frontier of hiring is predictive and personalized. Jeff envisions AI-driven career pathing, real-time job market intelligence, and new ways to match candidates based on abilities, not just experience.Jeff's perspective on AI-driven hiring, the changing nature of job search, and where hiring technology must go next makes this conversation a must-listen for anyone interested in the future of work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

“The future of assessments is about customization at scale. AI allows us to generate and adapt assessments in real-time, making them more relevant to specific job roles.”–Ben WilliamsIntroduction: In this episode of Psych Tech @ Work, I sit down with Ben Williams, Managing Director of Sten 10, to discuss how AI is reshaping the field of psychometric assessments and hiring processes. Our conversation dives into the evolving landscape of AI-driven assessments, the ethical considerations of using AI in hiring, and the challenges of maintaining transparency and fairness while incorporating new technologies. Ben shares insights into blending AI with traditional assessment tools and how this impacts the future of selection processes.Key Topics Covered:* The role of AI in automating and customizing assessments* Emerging challenges in trust, fairness, and explainability in AI-powered hiring* The importance of designing job-specific psychometric tools that align with organizational needs* AI's potential in generating, scoring, and validating assessments* Future implications of AI on entry-level and senior hiring rolesSummary:We explore AI's role in streamlining psychometric assessments while addressing challenges in maintaining transparency and fairness. Ben describes how Sten 10 has integrated AI to make assessment processes faster and more personalized without losing the critical human oversight needed for ethical hiring practices. We also discuss prompt engineering, AI literacy, and the limitations of AI-generated assessments. One significant takeaway is the growing importance of designing highly contextual and customized assessments using AI while ensuring they remain interpretable and meaningful.We touch on real-world examples, including how AI can generate coaching tips and personality profiles, as well as potential concerns regarding the over-reliance on AI outputs. The conversation also highlights emerging roles related to AI governance and the need for regulatory oversight to ensure fair hiring practices.Key Takeaways:* AI augments, but doesn't replace human oversight: While AI is making assessments faster and more scalable, the need for human validation remains critical to ensuring fairness.* Custom psychometric assessments are the future: Moving beyond off-the-shelf tools, companies can develop highly specific and job-relevant assessments using AI.* Prompt engineering for assessments: Organizations can create better assessment tools by focusing on AI prompt development and optimization.* AI literacy is essential for hiring professionals: As AI becomes more embedded in hiring, HR professionals need to understand its benefits and limitations to apply it responsibly.* Trust and explainability are key: Companies must prioritize transparency to gain candidate trust and meet regulatory standards.Conclusion:AI's role in hiring is evolving rapidly, and the opportunities for innovation are endless. However, as Ben notes, the path forward requires a careful balance between technological advances and maintaining human control. By designing psychometric tools with AI and human collaboration, organizations can achieve a fairer and more effective hiring process.Take It or Leave It? Articles:* “Ineffective Human-AI Interactions and Solutions” — Oxford Review* Summary: This article delves into the factors influencing human-AI collaboration, including cognitive load and decision control. Ben highlights how integrating AI into familiar tools like Slack and Word can reduce friction and improve adoption.* “AI and Public Perception: What Americans Really Think” — Center for Data Innovation* Summary: A survey reveals mixed feelings about AI, with curiosity decreasing and negative emotions on the rise. Ben critiques the contradictions in public attitudes toward AI and how these perceptions could shape its future adoption in hiring. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

“We need global standards to define and verify skills, or we'll be left with confusion and inconsistency across industries.” -Notebook LM's Deep Dive Podcast HostsSkills based hiring is all the rage, and so is AI.So what happens when you mix the two?In this special edition of Psych Tech @ Work, I handed the mic over to AI using Google's Notebook LM. The result? A fully AI-generated exploration of the evolving world of skills-based hiring. But how well did AI do at covering this complex and nuanced topic? So how did it do?  Listen and decide for yourself.In the meantime- Here is a short summary to pique your curiosity.Skills-based hiring promises to break down barriers and redefine how we think about qualifications, but it's not without challenges. This episode examines how companies can move beyond traditional degree requirements and leverage diverse learning pathways. It also highlights the shift from career ladders to flexible, lattice-like models and the critical role of leadership in making these transformations happen.Key Takeaways:* AI is a tool, not the solution: Organizations need both AI-driven assessments and human judgment to effectively identify and verify skills.* Degrees aren't everything: Employers must embrace non-traditional education pathways to access untapped talent.* Lifelong learning is essential: Workers should continuously upskill and showcase their abilities through portfolios and personal branding.* The career ladder is outdated: Flexible career paths based on transferable skills are the future.* Leadership drives change: True transformation in hiring practices requires bold decisions beyond tech implementation.Conclusion:This AI-powered episode demonstrates the potential of using AI for content creation while also showing its limitations. AI did a great job providing structure and highlighting key points, but human oversight remains essential to ensure deeper exploration and address the human factors that technology alone can't fully capture. Skills-based hiring requires more than AI—it needs leaders willing to rethink and redesign hiring practices with empathy and inclusivity in mind.Please listen and share your thoughts on how these robots did exploring the issues and drawing meaningful conclusions! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

“Technology should enable human connection, not replace it.”—Alison EyringIntroductionIn this episode, I'm joined by my friend Alison Eyring, an IO psychologist with decades of experience in the realm of global leadership and talent development and the founder of Produgie.I have known Alison for a very long time - in fact she was my first “real world” project sponsor back in 1994!It was a pleasure to welcome Alison to the show for a great conversation about the role of human centered design when building software to help leaders do their thing!  Summary:Our conversation explores the intersection of leadership psychology and technology design. Alison shares insights on how psychological safety can be both measured and improved, emphasizing its critical role in team dynamics and organizational success. We dive into her approach to developing tools tailored to user needs, the importance of cultural agility for global leaders, and how technology can both enhance and challenge workplace trust. Throughout, Alison highlights how organizations can foster meaningful change through a combination of data, design, and human connection.Key Topics Covered:* The psychology behind software usability and human-centered design.* Measuring and improving psychological safety within teams.* The evolving role of AI in leadership and organizational development.* Using adaptive tools to support leaders in achieving greater impact.* The challenges and opportunities of cultural agility in a globalized workforce.Takeaways:* Psychological Safety: Leaders can actively improve psychological safety, a critical element for team effectiveness and engagement, by fostering trust and transparency.* Cultural Agility: Leadership in a global context requires a combination of self-awareness, competencies, and experiences to navigate cultural differences effectively.* Data-Driven Insights: Organizations can gain actionable insights from assessments and development tools to better understand leadership strengths and weaknesses.* Human-Centered Design: Building technology for HR or leadership should prioritize the user's challenges and needs, not just the buyer's demands.* AI in Leadership: AI can support leaders in providing feedback, fostering growth, and driving measurable outcomes, but its use must be transparent and human-supervised.Take It or Leave It Articles:* “The Homework Apocalypse” by Ethan Mollick* Summary: This article discusses how educators are grappling with AI tools used by students for coursework and the need to rethink educational approaches. Alison critiques the rapid pace of AI developments and emphasizes the importance of teaching judgment and understanding bias in AI-generated insights.* “Psychological Safety in the Workplace”* Summary: This article explores what psychological safety is, what erodes it, and how organizations can foster it. Alison highlights the timeless nature of this topic and its centrality to leadership and organizational success. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"AI isn't replacing people—it's augmenting them. The people who know how to use AI will replace those who don't: "Redesigning jobs is about understanding which tasks humans excel at and which tasks AI can handle—then finding the perfect balance."Guest:Sania Khan* Labor Economist, founder of Inflection Point Consulting, Chief Economist at a leading talent intelligence AI company, Senior Economist at the Bureau of Labor Statistics (BLS)Summary:In this episode of Psych Tech @ Work, I welcome a new friend and brilliant Labor Economist Sania Khan, whose unique perspective blends macroeconomic labor trends, AI-driven work redesign, the evolution of skills, and the future of workSania shares insights from her experience at the Bureau of Labor Statistics and her work with emerging talent intelligence tools to tackle one of today's hottest topics: how jobs are being fundamentally deconstructed into tasks, skills, and competencies.We dig into how AI is reshaping work—from automating routine tasks to creating new opportunities—and what this means for businesses and individuals. Sania makes the case for job redesign as an essential forward looking strategy for organizations as they adapt to the increasing role of AI in redefining the rules of work.We agree that the world of work will increasingly find itself tied to a skills based economy which will require solving the challenge of moving beyond buzzwords like “skills-based hiring” and focus on aligning emerging technologies with human potential.This will require building consistent skills taxonomies, focusing on durable skills like problem-solving and critical thinking, and the gap between hype and reality when it comes to AI's impact on the labor market. Topics Covered:* Deconstructing Jobs with AI* How AI is automating tasks within jobs, freeing workers for more meaningful work.* The importance of job redesign to align organizational goals with evolving roles.* Skills-Based Hiring and Skills Taxonomies* Why a globally accepted definition of "skills" remains elusive and how this hinders interoperability across platforms.* The challenge of relying on resumes and job descriptions as source materials for skills analysis.* The Future of Work and AI's Impact* AI's dual role: creating efficiencies while raising concerns about job replacement.* Predictions for future jobs—like AI specialists, prompt engineers, and responsible AI officers—and how organizations can prepare.* Durable Skills and Adaptability* Why “durable skills” like problem-solving, critical thinking, and agility will define professional success.* How workers can future-proof their careers by learning to work with AI, not against it.Takeaways:* AI is reshaping work by automating routine tasks, but humans remain critical for complex, meaningful roles.* Organizations must focus on job redesign to capitalize on AI while ensuring employees do meaningful, value-added work.* Skills-based hiring is promising but hindered by inconsistent taxonomies and unreliable data sources.* Durable skills—like critical thinking, problem-solving, and adaptability—are the key to navigating AI-driven change.* Workers who learn to augment their skills with AI will have the greatest advantage.* New roles like AI specialists, responsible AI officers, and prompt engineers will emerge as businesses adopt more advanced technologies.Articles Discussed in the "Take It or Leave It" Segment:* "Research: How GenAI is Already Impacting the Labor Market" – Harvard Business Review* Summary: A data-backed look at how generative AI is reducing demand for automation-prone gig work while increasing competition in the labor market. Sania underscores the importance of becoming exceptional at your craft to remain competitive.* "How AI Is Fueling Long-Term Job Growth" – Fast Company* Summary: A positive perspective on AI's role in creating new jobs, like AI specialists and data scientists. Sania challenges the overly optimistic forecasts, noting the need for realistic strategies to align skills with emerging roles.This episode provides a compelling look at the intersection of technology, skills, and workforce transformation—a must-listen for leaders navigating the evolving world of work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"The most important competency for success in global assignments? Humility—being willing to learn how to succeed in a new cultural context."* Paula CaligiuriPaula is THE expert in this realm!In this episode, I welcome Paula Caligiuri, a renowned expert in cross-cultural psychology and global leadership and author of many books about cross-cultural adaptation and career happiness, the latest ones being:Build Your Cultural Agility: The Nine Competencies of Successful Global Professionals (2021)Live for a Living: How to Create your Career Journey to Work Happier, Not Harder (2023, co-authored with Andrew Palmer)I have known Paula for almost 30 years.  Her research played an essential role in my dissertation which was on cross-cultural adaptation in expatriate work assignments.  While I do not work in this area, Paula sure does!  She has dedicated her career to research and practice on the psychology of cross-cultural adaptation in both the personal and professional realms.I really enjoyed the opportunity to speak with Paula about the intricacies of cultural agility, the challenges faced by individuals working internationally, and how organizations can better prepare their employees for success in diverse environments.Cultural Agility is the name of the game.Our conversation is anchored by the concept of “Cultural Agility”, a combination of awareness, competencies, and experiences that allow individuals to be effective in multicultural environments. Paula describes it as being made up of:* Awareness: Understanding one's own values and how they compare to different cultural contexts.* Competencies: The skills needed to enter a novel environment, learn it, and be effective. These include both relationship-oriented competencies (like perspective-taking, relationship-building, and humility) and personal self-oriented competencies.* Experiences: Exposure to different cultural contexts, though Paula emphasizes that experiences alone are not enough.Paula notes that cultural agility involves the ability to adapt and thrive in unfamiliar cultural settings. She emphasizes that it's not just about giving people experiences abroad, but also equipping them with the knowledge and skills to navigate cultural differences effectively.Biology is a critical factor in adaptationProbably the most interesting thing I learned from our conversation was the role hormones play in cultural agility because they can help individuals handle greater levels of novelty comfortably and effectively, and that those with higher cultural agility are often better able to adjust to more challenging cultural contexts.  Did you know that- elevated cortisol levels in response to cultural unfamiliarity can impair cognitive functions, making it challenging to interpret social cues and adapt behaviors appropriately.Or that The novelty of a new culture triggers the brain's reward system, releasing dopamine, which can enhance our motivation to engage and learn in the new environment.I didn't!Adaptation begins with undertaking activities that put our chemicals in balance!Assessment plays a central role in adaptationI am not going to pass up the opportunity to talk about assessments.  Paula has taken what she has learned and created the myGiide assessment, which measures cultural value and cultural agility competencies providing users with insights into their cultural values and biases, allowing for comparative analysis with other cultures and identifying potential areas of conflict or misunderstanding.  The assessment is free.  I took it and found the insights it provided me super valuable.myGiide is also an example of the role technology plays in cross-cultural adjustmentThe impact of technology on cultural adaptation may surprise you.I went into our conversation thinking Paula would gush about how technology has made adapting to other cultures much easier. But I was wrong!*  Technology is a "double-edged sword" for cultural adaptation.  It allows people to stay connected to home, potentially reducing feelings of isolation.  However, overreliance on home connections can hinder full immersion and engagement with the local environment.* Technology should not replace real-world experiences and interactions.  It should be used as a tool for learning and support. Excessive use of social media and video calls can become a "crutch" that impedes adjustment to the new cultural context. Direct engagement with the host culture remains crucial for successful adaptation because cultural differences are "exacerbated" in virtual environments due to the lack of in-person cuesBusinesses must step up to help their expats be successfulWhen it comes to expat assignments, businesses should:* Create a pipeline of culturally agile professionals through strategic talent management practices, including the recruitment, selection, and development of employees with the ability to work effectively across cultures.* Assess bench strength in cultural competencies, not just technical skills, for roles that involve international or multicultural work.* Use assessments to identify employees who are ready for international assignments or have the potential to develop cultural agility.* Provide targeted support for employees on international assignments, including in-country cultural coaching and AI-powered tools like the chatbot in the MyGuide platform.This episode's Take it or Leave it? articles are:"Global Mobility in 2024: Trends and Predictions"* Summary: This vendor-published article outlines the changing landscape of global mobility, including shorter assignments, digital nomads, and the rise of technology platforms for managing mobility. Paula critiques the "nothing new here" approach, emphasizing the need for deeper cultural training."Thriving, Not Just Surviving: How Targeted Therapy Makes All the Difference for Expats"* Summary: This article explores the psychological stress faced by expats and the importance of targeted therapy. Paula reflects on her early research into expat mental health, reinforcing the need for specialized support to help individuals adapt to new cultural environments. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"Hiring is broken not because of a lack of tools, but because we lack a disciplined, strategic approach. Technology only works when we have the right foundation."–Linda Brenner* In this episode of Psych Tech @ Work, I welcome my long time friend and collaborator Linda Brenner for some straight talk about the challenges facing TA leaders in the age of talent shortages, AI, and general global insanity.* This conversation serves as a roadmap for talent acquisition leaders looking to rethink their strategies, streamline their processes, and make smarter use of technology.* Linda explains why many companies struggle to attract and retain top talent despite using sophisticated AI and other technology solutions. We delve into the importance of aligning TA strategies with business goals, building clear processes, and minimizing reliance on outdated ATS systems that often hinder rather than help hiring efforts.We discuss the complexities of AI in recruitment, including video interview assessments and chatbots, and Linda highlights the need for human oversight in areas like candidate engagement and relationship building. Topics Covered:Talent Acquisition Audits:* Linda describes her process for auditing talent acquisition, from evaluating business goals to diving deep into data, processes, and technology use.* Common issues found in TA audits, including lack of alignment, undefined processes, and inconsistent use of ATS systems.AI and Video Interviews: * How AI is currently used in TA and Linda's views on the limitations and potential pitfalls, particularly around legal considerations and candidate engagement.Skills-Based Hiring Misconceptions:* The difference between true skills-based hiring and keyword matching.* Why many organizations aren't yet ready to execute skills-based hiring effectively due to foundational issues in their processes and technology.Takeaways:Foundation First, Tools Second: AI and advanced tools can't solve underlying issues. Establishing clear, consistent processes aligned with business goals is essential before adding new technology.Strategy over tactics:  TA leaders should build a strategy that accounts for different types of roles and aligns with company growth goals, instead of relying solely on quick fixes.Consider the Candidate Experience: Long, inefficient hiring processes lead to drop-offs and high turnover. Streamline processes with candidate engagement in mind.AI as a Support Tool, Not a Solution: Use AI to support administrative tasks and data collection but maintain human oversight, especially in high-stakes areas like interviews and candidate assessment.This epsiode's "Take it or Leave it" Articles1. AI-Enabled Work Ethic" by Charles HandlerIn this article, I explore whether generative AI is an asset or liability for job candidates and employers. We discuss the ethical considerations around candidates using AI tools in applications and how companies could structure policies to evaluate AI competency fairly.   2. The Future of Talent Acquisition and AI" from ForbesThis article suggests that companies not using AI in talent acquisition will fall behind. Linda and I debate this, with Linda arguing that AI should only be implemented after TA processes are clearly defined and aligned with business objectives.   This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"We're generating assessments faster than ever, but our real test is ensuring that these tools are fair and reliable across diverse candidate groups."–Louis HickmanIn this episode I welcome my friend, super dad, and ex- professional wrestler Louis Hickman for a killer conversation about the ins and outs of using LLMs to create and score assessments.Louis is a professor at Virginia Tech specializing in research on AI and large language models in assessment and hiring processes.  He knows a thing or two about this stuff and we waste no time tackling some really great topics centering around the cutting edge of research and practice on the subject of LLMs and assessments.This is a must listen episode for anyone developing, or considering developing, LLM based assessments. Or anyone who wants to educate themselves about how LLMs behave when asked to be I/O psychologists.Topics Covered:* LLMs in Assessment Center Role-Plays:* Using LLMs to simulate realistic role-play scenarios for assessments, with the challenge of ensuring consistent, replicable candidate experiences.* Evaluating Open-Ended Text with LLMs:* How LLMs score open-ended responses and the observed biases, especially when diversity prompts only partially reduce disparities.* Consistency in AI Scoring:* Ensuring LLMs apply scoring criteria consistently across diverse candidates and settings.* Applicant Reactions to AI Interviews:* How candidates perceive AI-driven interviews, with many expressing discomfort due to the perceived inability to influence AI decisions compared to human interactions.* Predicting Responses to Assessment Items:* The potential for LLMs to predict candidate responses without actual data, though accuracy remains limited by model training and inherent biases.* Impact on Academic Research:* LLMs' influence on research publications, with concerns over AI tools favoring self-generated content and potentially amplifying biases in academic discourse.Listen to the episode to hear the skinny on these topics and more!And of course we have fun with this episode's “Take it or Leave it” articles.Article 1 “The Impact of Generative AI on Labor Market Matching.” An MIT Exploration of Generative AI”, explores the use of LLMs on matching job seekers and employers.Article 2Four Singularities for Research: The Rise of AI is Creating Both Crisis and OpportunityIn this article from Ethan Mollick's Substack blog One Useful Thing discusses the positive and negative impact of LLMs on academic research. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

Meghan: "Skills are the driver of the future of work. Without validation, there's no trust, and without trust, you can't make decisions based on skills."In this episode of Psych Tech @ Work I welcome my new friend Meghan Raftery who is an Education Designer and skills validation expert who works at Educational Design Lab - a community that is dedicated to doing skills based hiring the right way by ensuring that skills are verified and portable across the world of education and work.  Meghan offers a fresh perspective on skills-based hiring, microcredentialing, and how education and work can align more effectively to prepare students and workers for the future. Meghan shares her experience transitioning from K-12 education to the world of workforce development and dedicating her efforts to focusing on how to validate skills in a measurable, trustworthy way. She explains how microcredentialing can break down complex skills into smaller, demonstrable pieces that people can stack together over time to build toward larger career goals.In our conversation Meghan highlights the importance of aligning educational outcomes with workplace needs, particularly through skills validation systems that help employers trust the skills applicants bring to the table. She shares how her team uses human-centered design to create pathways for "STARS" (Skilled Through Alternative Routes) and provides practical insights into how employers can leverage these tools to open doors for candidates who may not have traditional degrees but possess the skills needed for success.Topics Covered:* Microcredentialing and Skills Validation:* Defining microcredentials and how they differ from traditional credentials by breaking down skills into smaller, measurable units.* The concept of stackable credentials, where individuals can build a portfolio of verified skills over time.* Human-Centered Design in Education:* The importance of involving the people closest to the problem in designing solutions for skills validation.* How Education Design Lab connects learners, educational institutions, and employers to design skills validation systems that work for all stakeholders.* Skills-Based Hiring and Employer Engagement:* Challenges employers face in trusting non-traditional credentials.* How companies can work with organizations like Education Design Lab to ensure they receive reliable, validated skills signals from job applicants.Takeaways:* Trust Through Validation: For skills-based hiring to succeed, employers need validated evidence of skills, not just resumes or self-assertions.* Microcredentials Build Careers: Breaking down skills into smaller, stackable microcredentials allows learners to build toward larger career goals in a personalized way.* Human-Centered Design: Involving those closest to the problem—whether students, job seekers, or employers—ensures that the solutions developed are relevant and effective.* Collaboration Is Key: Employers, educators, and governments must collaborate to build systems that bridge the gap between education and the workforce, ensuring skills are verified and trusted. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"The real challenge isn't just defining skills, but creating a system where hiring criteria and performance criteria align—where your hiring approach is integrated into your company's everyday operations."—Matthias SchmeisserSummary:In this episode of "Psych Tech @ Work," I am joined by Matthias Schmeisser, a talent acquisition leader from Berlin Germany who is passionate about skills based hiring.  Much of our conversation is focused on sharing Matthias' experience on the path to transforming his company's talent acquisition approach by implementing a skill-based system that ensures alignment between hiring and performance criteria. Matthias highlights the importance of creating a skill-led organization, where every role is assessed and hired based on well-defined skills rather than previous experience or degrees. This episode is a must listen for anyone who is interested in executing a skills based hiring process in their organization.Topics Covered:* Skills-Based Hiring:* Moving away from resumes and focusing on validated, functional, and core skills.* Designing a skill-based career framework that integrates hiring and performance management* Bias Reduction in Hiring:* The pitfalls of "pedigree recruiting" and years of experience as a performance proxy.* How skill-based hiring helps reduce bias and increases the quality of talent.* The Role of Technology:* Leveraging tech tools to assess both functional and social skills while enhancing decision-making.* Using interview intelligence tools to improve interviewer training and ensure consistency in the assessment process.Takeaways:* Replace Resumes with Skills: Resumes introduce bias into the hiring process. Focus on specific, validated skills to make more objective hiring decisions.* Align Hiring and Performance Criteria: Create a consistent framework where the skills used in hiring are the same as those used to assess performance, ensuring seamless integration across the employee lifecycle.* Use Technology Thoughtfully: Tools like interview intelligence and skill assessments can help make the hiring process more efficient and less biased while providing meaningful data to inform decision-making.* Start Small: Implement skills-based hiring on a smaller scale before scaling up. Prove the model works by piloting it with key roles and using the results to drive broader adoption.Articles Discussed in the "Take it or Leave it" Segment:Matthias and I review two articles about tech and skills based hiring and share our takes.Article 1: Problems with “Botshit”- what does this mean for recruiting?* Summary: This article from Business Insider explores the frustrations caused by AI chatbots in customer service. Matthias and Charles discuss the limitations of bots in replicating human interaction and the importance of maintaining quality control when using AI in customer-facing roles.Article 2:  The realities of connecting skills based hiring and education- new infrastructure is needed* Summary: A Forbes article discussing the disconnect between the education system and the workplace, particularly regarding how skills-based hiring may render traditional degrees less relevant. Matthias and Charles debate the need for both higher education and skills verification, particularly in highly specialized fields like medicine. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

"In the absence of trust, people will disengage. No amount of technology or process can replace the human need for belief and belonging."-Julian StoddThis episode is a must listen for those looking to expand their ideas about leadership, technology, and the psychology of work!In this episode of "Psych Tech @ Work," I welcome Julian Stodd, founder of Sea Salt Learning and prolific author whose work challenges conventional views on leadership, work, and technology, by looking at them through new paradigms.  Our conversation was refreshing because Julian offered thoughtful reframing of my ideas about psychology in the workplace that are worth noting.    In our conversation Julian reframes the way we think about the evolving workplace, focusing on the shift from traditional hierarchical structures to social leadership and distributed power. His perspectives offer a compelling critique of the conventional social contract between organizations and employees, arguing that this contract has been fundamentally broken by modern work dynamics.Julian highlights the role of technology, particularly AI, as a tool that both amplifies and disrupts traditional power dynamics within organizations. He also emphasizes the need for organizations to adapt, not just by automating tasks but by fostering trust, belief, and a sense of belonging to truly engage employees. This conversation is a powerful reminder that organizations must evolve beyond transactional relationships and embrace the social elements that drive real engagement and productivity. Throughout the episode, Julian emphasized the critical balance between formal organizational structures and the informal, social dynamics that truly drive engagement and innovation. He suggested that many organizations over-rely on formal systems—hierarchies, policies, and processes—while underestimating the power of social structures, such as networks of trust, influence, and collaboration.Julian repeatedly showed me a new way to look at my ideas about the psychology of the workplace.  For instance:The Traditional Leadership Model:* I Mention: I spoke about the role of leaders in providing clear direction and overseeing teams to ensure productivity.* Julian's Reframe: Julian challenged this conventional view, arguing that leadership in the modern era should be about social authority rather than formal hierarchy. He explained that leadership is increasingly granted by the community based on trust and belief, not just a title or position, and that successful leaders must earn this trust by engaging meaningfully with their teams.The Psychological Contract Between Employers and Employees:* I Mention: The importance of the traditional idea of the psychological contract as a way to understand the employer-employee relationship, where employees trade their time and skills for compensation and job security.* Julian's Reframe: Julian reframed this concept by stating that the traditional social contract has been broken. He argued that organizations need to move beyond seeing employees as resources or commodities. Instead, they should recognize that people are investing their belief and engagement in return for trust, growth, and belonging. Julian emphasized that organizations must rethink this relationship to thrive in the modern, social age.The Importance of Individual Differences:* I mention: The importance of the concept of individual differences, focusing on the traditional scientific approach that measures and assesses traits like personality, intelligence, and abilities to predict workplace behaviors and outcomes.* Julian's Reframe: Julian suggested a shift away from solely focusing on the science of individual differences as fixed traits to considering individuals as dynamic and adaptable within social systems. He argued that while the science of individual differences is important, it often overlooks the relational and contextual factors that influence behavior. Julian emphasized that people are shaped by their environment, relationships, and the social dynamics they are part of. He proposed that instead of just measuring traits in isolation, organizations should focus on understanding how individuals interact with the system around them and how they can grow and evolve within that system."Take it or Leave it":  Julian and I give our opinions on articles that suggest a declining need for human workers in the workplace of the future.* "AI-Powered Companies with No Employees Coming Soon"* Summary: This article from Sifted discusses the rise of fully autonomous companies that leverage AI agents to run without employees. While the article presents a futuristic view of e-commerce and automation, Julian and Charles critique its narrow focus and overhyped narrative, emphasizing that while AI may automate some functions, people will remain central to innovation and decision-making.* "The Rise of Autonomous Enterprises"Summary: This article from HFS explores how data-driven decision-making and automation are shaping the future of organizations. Julian and Charles discuss the potential for organizations to become more efficient through data governance and AI, but caution that organizations still need human judgment and emotional engagement to make meaningful decisions. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit charleshandler.substack.com

“The challenge isn't just identifying skills, but ensuring the data is validated, diverse, and reflective of real-world performance."Greg GasperinSummary: My guest for this episode is Greg Gasperin, CEO and Co-Founder of Merify, a skills data verification platform.  Greg and I discuss the future of skills-based hiring, which we both agree requires a shift from traditional resumes and degree-based qualifications to more dynamic and validated assessments of a candidate's Skills.  We discuss the fate of the skills based hiring movement as inexorably bound to the ability to have meaningful, quality evaluation of skills that is based on direct input from humans.   Greg discusses the genesis behind Merify based on the need for continuous feedback, data integrity, and community-based validation as essential components of modern talent evaluation. Of course we also also cover the role of AI in automating skill taxonomy updates, ensuring that assessments remain relevant and aligned with industry trends.  Topics Covered:Skills-Based Hiring:Moving beyond traditional resumes and degree requirements to more accurate, validated skill assessments.The importance of diverse, peer-reviewed feedback in creating a trustworthy skills database.Community-Based Skill Validation:The role of continuous feedback and real-world performance data in building a dynamic skill assessment system.How internal talent management can foster trust in skills data before expanding to external hiring.AI in Skill Taxonomies:Leveraging AI to maintain up-to-date skill taxonomies and adapt to changing industry demands.Balancing efficiency with transparency and explainability in AI-driven decision-making.Takeaways:Trust in Data: A reliable skills-based hiring system requires validated, peer-reviewed data that accurately reflects a candidate's real-world abilities.Continuous Feedback: Regular, diverse feedback is essential for maintaining the accuracy and relevance of skill assessments.AI for Agility: AI can automate skill taxonomy updates, helping companies stay current with evolving industry needs.Start with Internal Trust: Focusing on internal talent management builds confidence in the system, paving the way for its broader application in external hiring.Transparency and Validation: A transparent, explainable system for skill validation is crucial to mitigating biases and fostering trust in AI-driven hiring decisions.Articles Discussed in the "Take it or Leave it" Segment:"Leveraging Professional Education as a Bridge Between School and Career"Summary: This article from Fast Company explores the gap between academic learning and practical application in the workplace, emphasizing the need for higher education to incorporate more professional training to better prepare students for their careers.Discussion: Greg and Charles discuss the importance of exposure to various career paths early in education and the benefits of integrating professional skills training into higher education.Link: Fast Company Article"To Make the Most of Credentials, We Need a Better Marketplace"Summary: This article from Jobs for the Future highlights the need for a unified marketplace for credentials, where skills and credentials can be transparently evaluated and trusted by employers.Discussion: Greg and Charles talk about the importance of having a trusted, centralized system for credentialing and the role of employer buy-in for the success of a skills-based hiring approach.Link: Jobs for the Future Article

"It's about selling objectivity, not just science. We need to make sense of the vast data around us to help businesses make better decisions."-Eric SydellSummary:In this episode of "Psych Tech @ Work," my long time friend Eric Sydell, IO psychologist, genius, and co-founder of Vero AI, joins me to discuss the transformative potential of AI in the workplace and the importance of responsible innovation. This episode offers a deep dive into the practical applications of AI in HR tech, the necessity of ethical guidelines, and how businesses can implement AI responsibly to drive innovation while mitigating risks.In our conversation we get into the brass tacks of responsible AI.But first we share some stories about our respective career journeys and life as IO psychologists here in 2024.  And how we both find peace and harmony in this crazy world by working with our hands (he builds guitars, I work on old cars).Besides talking about hobbies, my agenda for having Eric on the show was to learn more about what Eric's company, Vero AI, is doing to help drive safe innovation with AI.Eric delves into the technical aspects of how Vero AI leverages advanced analytics and AI tools to enhance decision-making processes.  He highlights the company's unique approach to converting unstructured data into quantitative insights, enabling businesses to monitor and optimize their operations effectively.Eric emphasizes the importance of continuous output monitoring to ensure AI tools are fair, unbiased, and effective. He explains how Vero AI's platform uses a combination of AI and rigorous scientific methods to provide comprehensive analyses of algorithmic impact, compliance, and fairness. Our discussion also covers the evolving landscape of AI regulations, the importance of aligning with these regulations, and how Vero AI assists companies in navigating this complex terrain. Eric's insights provide a detailed look at the practical applications of AI in HR tech, underscoring the balance between innovation and ethical responsibility.Takeaways:Sell Objectivity: Focus on using AI to make sense of vast data, helping businesses make better decisions based on rigorous scientific methods.Monitor AI Outputs: Continuous output monitoring is crucial to ensure AI tools are fair, unbiased, and effective.Responsible Innovation: Approach AI adoption with a rigorous, ethical mindset. Balance innovation with the responsibility to monitor and understand AI systems.Regulation Awareness: Stay informed about evolving AI regulations and work towards compliance by maintaining transparent and accountable practices.Leverage AI Thoughtfully: Use AI to enhance decision-making processes while being mindful of potential biases and ethical considerations.No show would be complete without the Take it or Leave it” Show.In this episode Eric and I discuss two interesting articles about hiring bias and regulationArticles Discussed in the "Take it or Leave it" Segment:"Colorado's New Law on Regulating Brain Implants and Neurological Tech"Summary: This article discusses Colorado's new law aimed at regulating brain implants and other neurological technologies, focusing on data privacy and ethical concerns.Discussion: Eric and Charles debate the necessity and timing of such regulations, considering the current state of the technology and the importance of data privacy."Employers Ask, What is AI? as Regulators Probe Hiring Biases?"Summary: This article explores the confusion among employers regarding the definition of AI and the importance of evaluating adverse impact in hiring decisions, regardless of the technology used.Discussion: Eric emphasizes the need for clear definitions and the importance of focusing on outcomes rather than the specific tools used, while Charles discusses the practical implications for employers.

"It's important to understand that disability is contextual. One can be both enabled and disabled by their neurodivergence depending on the environment and the task at hand."-Nancy Doyle"The way we diagnose and support neurodivergence needs to evolve. We're still using outdated models that don't consider the full spectrum of human cognitive diversity."-Nancy DoyleSummary:In this episode of "Psych Tech @ Work," I welcome my new friend Nancy Doyle, founder and CEO of Genius Within and visiting professor Birkbeck, University of London.In my opinion Nancy is one of the world's most expert and on-point voices on the topic of Neurodivergence, especially as it relates to the world of work.It was a real honor to spend an hour with her discussing the complexities and nuances of neurodiversity in the workplace. Nancy brings her extensive experience in IO psychology and coaching to the conversation, offering insights that challenge traditional views and practices around neurodiversity.Nancy shares her journey into the field, highlighting the transition from disability support to specializing in neurodiversity inclusion. Nancy is doing hero's work emphasizing the need for flexible and inclusive workplace practices that go beyond tokenistic inclusion programs and truly address the functional needs of employees. She also discusses the limitations of current diagnostic practices and the potential for AI and machine learning to aid, but not replace, the nuanced understanding required for effective support.Topics Covered:Early Career Experiences:Transition from academic learning to practical applications in the workplace.Differences between academic theories and real-world scenarios.Practical Applications of Neurodiversity Inclusion:Importance of creating flexible and inclusive environments tailored to individual needs.Common workplace accommodations that can enhance productivity and well-being.Impact of Technology and AI:The potential and limitations of AI in diagnosing and supporting neurodivergent individuals.How machine learning and big data can help identify common needs and effective accommodations.Genius Within: The amazing work Nancy's company, Genius Within is doing in providing assessments, coaching, and organizational design services to support neurodivergent individuals, creating inclusive workplaces that enhance productivity and well-being.Takeaways:Understand the Context of Disability: Recognize that neurodivergence can be both enabling and disabling depending on the environment and task. Create flexible workplace policies that accommodate individual needs.Move Beyond Tokenism: Avoid tokenistic inclusion programs and instead focus on practical, everyday accommodations that support all employees.Utilize Free Accommodations: Many effective accommodations, such as allowing quiet workspaces or flexible seating, are cost-free and easy to implement.Leverage Technology Thoughtfully: Use machine learning and big data to identify trends and common needs among neurodivergent employees, but be cautious with AI diagnoses due to embedded biases.Promote Continuous Learning: Stay informed about the evolving field of neurodiversity and be open to adapting workplace practices to better support neurodivergent employees."Take it or Leave it" Articles:In the most fun part of the show Nancy and I discuss two articles and give our opinions on the authors' takes."The Danger of Neurodiversity" From the Spectator UKSummary: This article critiques the neurodiversity movement, arguing that it may dilute the challenges faced by individuals with severe conditions. It highlights the need to balance the celebration of neurodiversity with the recognition of serious disabilities.Discussion: Nancy acknowledges the validity of the critique but criticizes the article's tone. She emphasizes the need for a balanced approach that respects all experiences of neurodivergence. "The Rise of Neurodiversity at Work" From Psychology TodaySummary: This article discusses how companies are increasingly recognizing the value of neurodiverse employees but warns against tokenistic inclusion programs. It advocates for tailored support that genuinely meets the needs of neurodivergent individuals.Discussion: Nancy agrees with the article's critique of tokenistic programs and stresses the importance of functional performance and everyday accommodations.

"It's important to be a sponge when you're early in your career. Pick up pieces of what everybody else is doing that looks like it's working, and if it doesn't work, then you learn and grow from it." Brandon Sulzberg "Having an open mind early in your career can lead you to discover new interests and opportunities you might have otherwise overlooked." Joe Prinzevalli Summary: In this episode I welcome Brando & Joe, recent graduates from Hofstra University's IO Psychology program and hosts of one of the most popular IO psychology podcasts- The Brando & Joe Podcast.These guys are the real deal and it is always a great experience to have fellow podcasters on the show.  There is a lot we can learn from the collective wisdom they have gained through 80 some odd episodes of their own podcast. Brando & Joe offer me (and my listeners) a fresh perspective on early careers for IOs.  We discuss how they found their current jobs and how they are applying what they learned to the world of work.  One theme that we spend a good deal of time discussing is the critical role that internships and networking play in shaping career paths, providing us experienced professionals about the importance of giving others a chance.Brandon and Joe's adaptability, open-mindedness, and continuous learning mindset serve as a powerful reminder of the importance of staying current and flexible in a rapidly changing field. Listen in and you will probably take a relaxing stroll down memory lane and reminisce about how you got where you are today and who helped you get there.   Take it or Leave it:The “Take it or Leave it” Show for this episode included a spirited discussion of two super interesting articles:"Will Robots Take My Job?" (website that looks at the future of various jobs)Summary: This website analyzes the risk of various jobs being automated and the future job prospects for IO psychologists. It highlights the low risk of automation in IO Psychology due to the need for complex problem-solving, creativity, and interpersonal skills.Discussion: We discuss the implications of automation in IO Psychology, emphasizing the unique human elements that protect their field from being fully automated.Link: Will Robots Take My Job"The Future of IO Psychology: Adapting to AI and Technological Changes" (Linked in Article by Georgi Yankov, Pd.D.)Summary: Georgi argues that IO psychologists need to embrace AI and technological advancements to remain relevant or it will face extinction. He emphasizes the importance of multidisciplinary approaches and continuous learning.Discussion: The conversation explores the necessity of integrating AI into IO practices and the potential for rebranding the field to stay current with technological trends. Or else!Link: Future of IO Psychology

"Organizational justice is about ensuring that every individual feels they are treated fairly and with respect in all aspects of their work. It's not just about the outcomes they receive, but how those outcomes are decided and communicated. Fair processes and respectful treatment are fundamental to maintaining trust and equity within any organization."   -Stephen Gilliland  Summary: In this episode of "Psych Tech @ Work," Steven Gilliland, a distinguished professor and expert in organizational justice, joins me to explore the profound impact of fairness on hiring and the psychology of the workplace.  Stephen was my professor when I was in grad school at LSU, so I know him well and was lucky to have exposure to organizational justice theory during my most formative years. After taking a stroll down memory lane, we have an amazing conversation about the fundamental principles of organizational justice theory.  We discuss how perceptions of fairness in outcomes, processes, and interpersonal treatment shape employees' attitudes and behaviors.  We talk about how organizations can ensure fair treatment during hiring and how these practices influence applicants' decisions and organizational reputation.  We also dig into the broader implications of fairness in the workplace, emphasizing how companies can navigate challenging decisions, like layoffs, while maintaining their commitment to justice. Finally, we discuss the evolving role of technology in shaping justice perceptions in the workplace. Stephen provides insights into how AI and digital tools are transforming the landscape of organizational justice, offering both opportunities and challenges.   Take Aways:  Treat Applicants as Customers: Consider the hiring process from the applicant's perspective. Fair treatment during this phase can significantly impact their decision to join your organization and their perception of your brand. Understand the Role of Fairness in Employee Engagement: Perceptions of fairness in hiring and workplace practices contribute to overall employee engagement and satisfaction. Ensure that decisions and processes are consistently fair to foster a positive work environment. Adapt Organizational Justice to Technological Changes: As workplaces evolve with technological advancements, continuously revisit and adapt your organizational justice practices to address new challenges and maintain fairness. Respond to Difficult Situations with Empathy: During tough times, such as layoffs, how you handle the situation reveals your organization's commitment to fairness. Strive to treat affected individuals with empathy and respect, maintaining open and honest communication. Align Actions with Psychological Contracts: Be aware of the unspoken agreements between employees and employers. Violating these expectations can lead to perceptions of unfairness and affect employee loyalty and engagement. Future-Proof Your Fairness Practices: Stay ahead of emerging trends by integrating fairness into your organizational strategy. Anticipate the impact of new technologies and societal changes on your justice practices to create a resilient and equitable workplace.  Take it or Leave it Show On this week's show we vote on these articles.  Tune in to hear our takes! "ChatGPT and the Rise of AI-Driven Conspiracy Theories"  (Source: USA Today)Summary: This article explores how advanced AI technologies, like ChatGPT, are fueling the spread of conspiracy theories. It discusses the potential for AI to amplify misinformation and the challenges in managing these effects. The article suggests that as AI becomes more integrated into everyday life, there is an urgent need for radical transparency and robust measures to combat the spread of false information.  “AI Hiring Tools May Be Filtering Out the Best Job Applicants" (Source: CNBC)Summary: This article addresses concerns that AI-driven hiring tools may unintentionally filter out qualified candidates due to biases in the algorithms or lack of transparency in decision-making processes. It highlights the growing reliance on AI for managing large volumes of applications and the need for regulations to ensure fairness and accuracy in these systems.

"Skills-based hiring isn't just removing a degree requirement from a job description. It takes a long time and serious commitment to see it through." -Matt Alder Summary:   My guest for this episode is Matt Alder, podcaster, author, consultant and futurist This is an exciting episode because it includes the first ever episode of The Take it or Leave it Show! This short segment takes place in the middle of our interview.  This is a fun segment that provides listeners with expert takes on current hot topics.  In the segment, Matt and I review two articles from the current news, share our takes on them, and give a collective thumbs up or thumbs down on it.   This week's articles cover the topics of skills based hiring and the use of AI driven personality assessments in hiring.  Don't miss it! In addition to Take it or Leave it, in this episode we learn about Matt''s background in talent acquisition, his Recruiting Future podcast and his books 'Exceptional Talent' and 'Digital Talent'.  Through these efforts and Matt's work as a top notch consultant and futurist, we discuss the hot topics that are shaping the future of hiring. Topics covered include: The definition of “digital transformation” and its impact on talent acquisitionThe role of AI in recruitment and how companies should approach the adoption of new technologiesChallenges in skills-based hiringThe importance of experimentation and innovation in recruitment, and Predictions for the future of talent acquisition in 2034. Take Aways: Embrace Digital Transformation: Companies must adjust to an increasingly digital world, understanding that digital transformation impacts all aspects of business, including talent acquisition. Digital transformation involves more than just adopting new technologies; it requires a shift in mindset to leverage these tools effectively.Foster a Future-Focused Mindset: Being open to change and continuously experimenting with new technologies is essential for staying ahead in the HR landscape. Organizations need to think beyond the current processes and explore how technology can fundamentally change their operations.Prioritize Skills-Based Hiring: While challenging, skills-based hiring can lead to a more equitable and effective recruitment process, helping organizations find and retain the right talent. This approach emphasizes the importance of assessing candidates based on their actual skills rather than traditional credentials.Enhance Candidate Experience: Providing a consumer-grade experience in recruitment processes is crucial for attracting and retaining top talent, particularly among digitally savvy candidates. The goal is to make the recruitment process as engaging and seamless as possible.Navigate AI and Automation: Understanding the potential and limitations of AI in recruitment is vital. Organizations should focus on using AI to complement human decision-making and improve efficiency without losing sight of ethical considerations.Future Hiring Trends: Matt predicts that by 2034, hiring will be highly data-driven, with advanced AI and automation playing a central role. This will lead to more personalized and efficient recruitment processes, but it will also require careful management to ensure fairness and inclusivity

"From the EEOC's perspective, whether an employment action, employment decision is made by a human or an algorithm, liability is going to be the same for those companies." "AI tools really have the ability to prevent discrimination, but at the same time, they have the ability to discriminate more than any one individual human being." -EEOC Commissioner Kieth Sonderling. Before we begin- Commissioner Sonderling requested that I share a link to this important report (Algorithms, Artificial Intelligence, and Disability Discrimination in Hiring).  While the report focuses on the Americans With Disabilities Act, the ideas put forth apply directly to employment decision making and is an important missive summarizing the government's position on the relationship between AI and foundational regulation related to concepts such as the ⅘ rule and disparate impact.   Summary: How lucky are we?  My guest for this episode is none other than the grand poobah of employment regulations in the US, EEOC commissioner Keith Sonderling.  The Commissioner has many great attributes that underlie his approach to the creation and enforcement of legislation critical to ensuring everyone gets a fair shake when it comes to employment opportunities.  But I think one of his greatest attributes is his mission to make himself accessible to all channels of media and communication, including humble podcasters such as myself.   In some sense, my big takeaway from our discussion is the idea that the more things change, the more they stay the same. By this I mean that the central tenets of fair and equitable hiring practices are immutable.  While the tools that support employment decision making have, and will continue to become infinitely more complex, ensuring that signals used for hiring decisions are job related, and thus free of systematic differences based on irrelevant factors, is all that matters. The Commissioner and I have a really awesome and enlightening conversation about the evolving landscape of government regulation on AI in hiring. We begin with a discussion about his career trajectory, his insights about the integration of AI within HR practices, and the critical balance needed between innovation and ethical considerations.  We have fun delving into the specifics of current regulatory frameworks, including the seminal Uniform Guidelines on Employee Selection Procedures and the recent developments in laws such as New York City's Local Law 144.  Commissioner Sonderling shares his perspective that the future of regulation will likely be driven by state initiatives rather than new federal legislation. Takeaways:State-Led Initiatives: Commissioner Sonderling highlights that while the federal government may not introduce new legislation soon, states like New York and California are likely to lead the way in regulating AI in hiring. Employers should stay informed about state laws and consider adopting best practices from these regulations proactively.Navigating a Patchwork Regulatory Environment: With states potentially leading regulatory efforts, HR professionals must prepare to navigate a patchwork of regulations that may vary significantly from one state to another. This emphasizes the need for adaptable compliance strategies.Existing Federal Standards: Even in the absence of new federal legislation, existing laws and standards, such as the EEOC's Uniform Guidelines on Employee Selection Procedures, still apply to AI-driven employment decisions. Organizations must ensure compliance with these standards to avoid legal pitfalls.Proactive Compliance through Audits: Commissioner Sonderling advises businesses to conduct regular audits of their AI systems to ensure compliance and prevent discrimination. These audits should be thorough and based on relevant data to identify and mitigate any biases in the system.Vendor Responsibility and Data Integrity: The discussion highlights the importance of holding vendors accountable for the AI tools they provide. Employers must ensure that their vendors comply with ethical and legal standards and provide necessary data for compliance checks.  We can expect vendors to be required to participate in 3rd party audits of their tools at some point in the near future.

"Everything really starts with the customer. It's not just about having a technology, but understanding the problem you're solving." -George LaRoque Summary: In this episode, George LaRocque, a leading HR technology analyst, investor and the founder of Work Tech- the #1 source of truth around investment and growth in the HR Tech market, joins me to discuss the evolving landscape of HR technology with a twist on its psychological impact on employees and job candidates.  We discuss important topics that will define the future of HR tech and ultimately the future of work from the perspective of technology, commerce, and psychology. These topics include:Impact of investments on HR tech innovationImpact of generative ai and automation on work dynamicsThe influence of technology on the employee experienceSocial and psychological implications of remote work technologiesAdaptation and learning in a tech-driven workplaceEthical considerations and employee trustPractical Takeaways:Understanding Market Needs: George underscores the importance of aligning technology with actual market needs, emphasizing that successful tech solutions stem from a deep understanding of customer pain points, not just technology's capabilities. He stresses the psychological benefit of technologies that are developed with user-centric designs, which enhance user satisfaction and reduce resistance to new systems.Impact of Investment Trends on Psychological Well-being: By monitoring where capital is flowing within the HR tech sector, businesses can anticipate and adapt to emerging trends. George's analysis suggests that investments not only indicate which technologies will shape the future of HR but also how these technologies can affect employee well-being. Investments in user-friendly and ethically designed technologies can improve the overall workplace environment by reducing stress and increasing job satisfaction.Adoption of Generative AI: As AI continues to integrate into HR processes, George advises companies to consider how these tools can enhance operations without replacing the human element. Proper implementation of AI can help reduce employee workload and prevent burnout, but it's crucial to ensure these implementations are ethical and enhance employee experiences rather than making them feel replaceable or surveilled.Strategic Use of HR Technology for Employee Engagement: The conversation highlights the strategic advantage of using HR technology not just for automation, but for enhancing employee engagement and operational efficiency. Technologies that facilitate meaningful interactions and provide support in workflow can significantly improve psychological comfort and productivity among employees.Future of HR Tech and Psychological Impacts: Looking ahead, George predicts a shift towards fewer interfaces and more integrated, seamless experiences within HR technology. This evolution is expected to support a less cluttered and more efficient work environment, reducing cognitive load and fostering a more engaging and less stressful work experience. This future of "invisible" technology aids in maintaining a focus on human-centric operations, crucial for mental well-being.

In this episode I welcome JP Elliot, HR and Talent Executive & Host of the Future of HR Podcast.JP Elliott is a forward-thinking global human resources executive with extensive experience implementing human capital initiatives that drive business results, improve organizational performance, and elevate company culture.He is a trusted business partner to C-level and senior management teams who can translate business needs into people strategies aligned with the enterprise priorities and P&L targets.Over his career, JP has been fortunate to work across a broad spectrum of industries and organizations, many under going significant business and culture transformations. These experiences have shaped him into a versatile, pragmatic, and global leader who builds strong teams that deliver results.Quote:“I think we're always looking for shortcuts, but there isn't a shortcut.  Most people aren't overnight successes, they're actually twenty year overnight successes. And when you start to hear their journeys and get to know them, you're like, wow, they've had setbacks.  They've had these things happen, but they stayed focused on delivering results, understanding the business, building great relationships, and finding a way to differentiate themselves along the way.”- JP ElliottSummary:JP's podcast is one of my absolute favorite shows.  With a constant roster of big time guests, including famous psychologists such as Jeffery Pfeffer and John Boudreau, seasoned HR leaders, and experts on careers and leadership JP's show has served as a source of inspiration and career development for me.  So I am really excited to have him as a guest on my show to talk about his own career and share all that he has learned from his travels as a PhD IO psychologist, HR leader, and podcast host.I learned so much good stuff from our conversation and I am excited to provide my listeners access to practical, actionable insights about:Starting and growing a podcastFinding your own personalized path to career success through self-development, hard work, and being true to yourselfWhat it takes to be a good HR leaderNavigating the sometimes competing priorities of thinking and acting like a business person while staying true to psychology and humanistic values.Using HR leaders' views on assessments to field a successful assessment programHow to drive impact from the C suite and how to ensure the business notices and appreciates itHow to be smart about the adoption of HR technologyJP's message of optimism, self-empowerment, and the importance of business acumen and practicality in the game of HR is valuable for anyone, but is especially relevant for IO psychologists with aspirations to navigate their way into HR leadership.So listen and share liberally!

Quote:We talk about the effect of technology on everything, but ultimately, it's the people that matter." This theme has shown up repeatedly, emphasizing that technology doesn't have uniform effects; we have to consider the psychology of implementation, how it's used, and its context​​.Summary:In a thought-provoking episode of "People, Science, Inc.," Dr. Charles Handler sits down with Dr. Tara Behrend, a leading expert in the intersection of industrial-organizational psychology and technology. They explore the profound impact of technology, especially AI, on workplace dynamics, employee well-being, and organizational effectiveness. Dr. Behrend, with her extensive background in the study of how technology influences human behavior at work, sheds light on critical issues such as the ethical use of AI in hiring, the psychological effects of remote work technologies, and the future of learning and development in increasingly digital environments.In this engaging episode of "People, Science, Inc.," Dr. Charles Handler welcomes Dr. Tara Behrend, an esteemed Industrial and Organizational Psychologist and current president of SIOP. Dr. Behrend, also a professor at Michigan State University, shares her insights into the psychological implications of emerging technologies in the workplace, the role of AI in learning and connection, and the significance of career and technical education in addressing evolving workforce demands. With a focus on how AI and technology impact employee well-being, decision-making, and organizational dynamics, this conversation sheds light on the critical intersection of psychology, AI ethics, and workplace innovation.Take aways:Balancing AI and Ethics in Hiring: The discussion reveals that while AI can streamline the hiring process, it requires a careful balance to ensure ethical application. Dr. Behrend stresses the importance of transparency and continuous oversight in AI systems to mitigate biases and uphold fairness, providing a blueprint for organizations to follow.Adapting to Remote Work Technologies: Insights from the episode illustrate that successful remote work depends not just on the technology used but on how it's implemented. Strategies for maintaining communication, fostering collaboration, and sustaining engagement in remote settings are crucial for preserving company culture and employee well-being.Innovating Learning and Development: Dr. Behrend points out that technology's role in learning and development extends beyond access to information. It involves creating adaptive systems that tailor learning experiences to individual needs, promoting more effective skill acquisition and career growth.Understanding the Psychological Impact of AI: One of the pivotal learnings is the nuanced psychological impact of AI on employees, including feelings of trust or mistrust towards automated systems. Companies are encouraged to foster an environment where technology serves as a support, not a replacement, enhancing job satisfaction and productivity.Navigating Technological Change: The episode underlines the necessity for both organizations and employees to remain agile amidst technological advancements. This involves fostering a culture that values upskilling, reskilling, and continuous learning as essential components for thriving in the evolving workplace landscape.Addressing Surveillance in the Workplace: Through her insights, Dr. Behrend highlights the increasing use of surveillance tools in monitoring employee productivity and behavior. A key learning from her work is the critical need for ethical guidelines and transparent communication about the use and purpose of surveillance technologies. Organizations must balance efficiency and privacy concerns, ensuring that surveillance practices are implemented with respect to employee autonomy and trust, thereby preventing potential negative impacts on morale and workplace culture.

"Legislation... has not kept up with the pace of technological advancements, posing significant challenges for ensuring fairness in AI-driven hiring processes."-Matt SchererSummary:In this episode of "Science 4-Hire,"  I welcome Matt Scherer, Senior Policy Counsel for Workers' Rights at the Center for Democracy in Technology, a non-profit based in Washington, D.C. The CDT champions the advancement of civil rights in the digital age, striving to ensure technology respects and enhances individuals' rights and democratic values.Matt and I have an enthusiastic conversation about the importance of understanding and navigating the evolving landscape of AI and automation in hiring processes. Matt brings his expertise to the table, dissecting the intersection of emerging technologies with workplace rights, the nuances of AI legislation, and the vital role of public policy in safeguarding fairness and privacy. Matt and I dive right into some great dialogue about the challenges posed by electronic surveillance, automated management systems, and the quest to elevate worker voices through technology. We spend a good deal of time focusing on the critical evaluation of AI hiring tools, highlighting New York City's Local Law 144 and its implications for a broader regulatory framework. Matt provides some really interesting and important points about the criticality of using a design-first mentality in developing AI tools as a critical part of ensuring they serve to enhance worker empowerment rather than diminish it.Insightful Moments:Matt discusses the Center for Democracy in Technology's (CDT) mission to advance civil rights in the digital age, focusing on the workplace implications of emerging technologies such as AI and automated management systems. The CDT's commitment to this cause is grounded in ensuring technology serves to enhance, not undermine, workers' rights and privacy.The conversation highlights New York City's Local Law 144, examining its strengths and weaknesses in regulating AI hiring tools. Despite being a pioneering piece of legislation, Matt suggests that the law is riddled with loopholes that many companies exploit to avoid compliance, demonstrating the challenges in crafting effective regulatory frameworks.Matt emphasizes the importance of design-first thinking in developing AI technologies for hiring. He argues that most challenges associated with AI and automated hiring tools stem from design issues, advocating for a holistic approach that integrates ethical considerations from the outset.The dialogue touches on the role of transparency in AI-driven hiring processes.  Current practices often leave candidates in the dark about when and how they are being evaluated by AI, stressing the need for legislation that mandates clear disclosure to candidates.An exploration of upcoming legislation reveals a split between stronger regulatory regimes advocated by civil rights groups and more loophole-ridden proposals pushed by tech companies. This tension underscores the ongoing debate over how to effectively govern AI in hiring while protecting workers' rights.Matt shares insights into the civil rights standards for 21st-century employment selection procedures, a document aimed at modernizing and expanding upon the 50-year-old uniform guidelines for employee selection procedures. This initiative reflects a broader effort to update legal and ethical standards for employment assessments in light of advancements in AI and technology.

In this episode of Science 4-Hire, I welcome my new friend Martyn Redstone, founder of pplbots and a pioneering force in the intersection of conversational AI and recruitment technology. We have a fun and meaningful conversation about the evolution of chatbots and the role of generative AI in the recruitment process. With over two decades in technology and a laser focus on conversational AI solutions for recruitment, Martyn shares his journey through the advancement of chatbots from simplistic decision trees to complex systems empowered by natural language understanding, processing, and now, generative AI.  We thoroughly explore the implications of chatbots and AI technology on candidate experience, the nuances of designing effective chatbot interactions, and the potential pitfalls and promises of leveraging large language models in recruitment.  This conversation delves into the significant shifts in recruitment technologies, the criticality of design-first approaches, and the careful balance between innovation and ethical considerations in implementing AI tools. Quotes: "Now, we're seeing the move to generative AI-based chatbots... but it always comes down to having a design-first mentality." -Martyn Redstone:  Insightful Moments: Evolution of Chatbots: Martyn illustrates the journey from basic chatbots to sophisticated systems enhanced by conversational AI and generative AI technologies, highlighting the transformative impact on the recruitment landscape. Design Challenges: The conversation illuminates the complexities behind designing chatbot experiences that are not only technologically advanced but also ethically sound and user-friendly. Generative AI in Recruitment: They discuss the advent of generative AI in recruitment, addressing both its potential to revolutionize candidate engagement and the inherent risks of relying too heavily on such models without adequate safeguards. Practical Applications: Martyn shares insights into real-world applications of conversational AI in recruitment, from enhancing candidate screening to re-engaging talent pools through intelligent, automated interactions.

"This AI piece and all the ethics and governance and everything that goes around that... it really warrants a dedicated role and some specific communities focused on AI ethics and risks."Bob Pulver: Founder of Cognitive PathSummary:My guest for this episode is Bob Pulver, a seasoned expert in the intersection of artificial intelligence and talent acquisition, bringing with him over two decades of experience from his tenure at IBM to the forefront of AI ethics and responsible implementation.This episode not only provides valuable insights into the mechanics of implementing responsible AI, but also frames a narrative that reveals the complexity and necessity of ethical AI practices in today's technology-driven hiring landscape.Bob underscores the importance of ethical AI development, emphasizing responsibility by design, speaking to the need for a proactive stance in integrating AI into people practices.  We both agree that compliance should not be a band-aid, or afterthought, but a foundational principle that begins with data acquisition and continues through to the implementation of AI-powered tools. A big part of our conversation revolves around legislation related to the use of AI hiring tools, including New York City's Local Law 144. Bob provides advice to organizations on navigating its anti-bias legislation and the broader implications for global regulatory landscapes.In sum, Bob and I both agree that responsible AI is not a game of short sighted interventions, but rather a transformative shift that affects every aspect of talent acquisition. We provide our ideas on how to navigate through this period of intense change, focusing on the practical challenges companies face, from internal upskilling to grappling with legislation that struggles to keep pace with technological advancements.Takeaways:Start with a Foundation of Ethics and Responsibility: Implementing responsible AI requires building your technology on a foundation of ethical considerations. This involves considering the impact on protected groups, ensuring accessibility, and integrating privacy and cybersecurity measures from the beginning.Understand and Comply with Relevant Legislation: Staying informed about and compliant with anti-bias legislation, like New York City's Local Law 144, is crucial. This law requires annual independent audits for automated employment decision tools, ensuring they don't adversely impact protected classes.Adopt a Holistic Approach to AI Implementation: Responsible AI transcends legal compliance to include a broader ethical framework. It encompasses fairness, privacy, cybersecurity, and the mitigation of various risks, including reputational, financial, and legal.Engage in Continuous Education and Upskilling: All stakeholders, regardless of their role, need to be educated about the ethical implications of AI. This includes understanding how to acquire and test data to mitigate bias and ensure the responsible use of AI technologies.Foster a Multi-Stakeholder, Cross-Disciplinary Dialogue: Creating solutions that are both innovative and responsible requires input from a diverse group of stakeholders. This includes technical experts, ethicists, legal teams, and end-users to ensure cognitive diversity and address the ethical, cultural, and practical aspects of AI.Prepare for an AI-Driven Transformation: Recognizing that AI transformation affects every aspect of an organization is essential. This realization should drive a commitment to responsible AI practices throughout the organization, from product development to deployment.

“So most of the world is made up of full stack application developers who build software for anything from HRIS to accounting, to supply chain, and what have you? For those people to easily add generative AI capabilities into their applications while remaining in compliance with the security, trust, and safety requirements that enterprises have, well that's a fairly difficult challenge.” Vivek Sriram- Co-founder of Bookend.aiSummary: In this episode of Science 4-Hire, I welcome my old friend and partner in crime Vivek Sriram, co-founder of Bookend AI, a start up that provides secure infrastructure that supports the efficient spin up and fine tuning of open source LLMs.We waste no time delving into the fascinating, confusing, and intricate world of Large Language Models (LLMs) and their burgeoning role within enterprise solutions, with a special focus on HR and hiring applications. We sure do agree on the transformative potential of LLMs to revolutionize enterprise software, enhancing functionalities such as candidate screening, resume parsing, and even generating interview questions—tasks pivotal to modern HR departments.Vivek brings me back down to earth a bit as he provides words of caution about the considerable challenges that come with integrating LLMs into enterprise systems, especially within the HR sector. Concerns around data privacy, the risk of perpetuating biases, and maintaining compliance with labor laws are significant when deploying AI in hiring. Vivek emphasizes the critical need for enterprises to navigate these challenges carefully, ensuring that LLM integration respects ethical guidelines and regulatory requirements, thus preventing potential adverse impacts on candidates and the hiring process.The good news is that Vivek outlines strategies for implementing LLMs in a manner that balances innovation with responsibility. Approaches such as utilizing open-source models for greater control and customization, and employing platforms that offer secure, compliant AI integration, are discussed as viable solutions. The idea of fine-tuning LLMs with proprietary data to better align with specific HR needs provides additional levels of confidence for those looking to use LLMs securely.Listeners will gain a nuanced understanding of the dual-edged nature of LLMs in HR and hiring contexts—recognizing their potential to significantly improve efficiency and decision-making in talent acquisition, while also grappling with the ethical, privacy, and compliance issues inherent in their use. This episode underscores the importance of thoughtful AI integration in HR practices, aiming for a future where technology serves to augment human judgment rather than supplant it.Take Aways:We must recognize that integrating open-source LLMs into enterprise applications comes with complex challenges, including navigating licensing, data usage permissions, output control, and auditing requirements.Enterprises must address strict compliance and security standards, especially in regulated industries, when implementing open-source LLMs. This includes ensuring data privacy, adhering to industry-specific regulations, and maintaining the integrity of sensitive information.Tailoring open-source LLMs to specific enterprise needs requires significant customization. Enterprises need to modify these models to align with their unique operational, compliance, and ethical standards.Potential solutions to the issues inherent with the use of LLMs involve employing strategies for effective management of open-source LLMs, include:Selective Model Adoption: Carefully selecting open-source models that best fit the enterprise's technical and compliance requirements.Data Management and Security: Implementing robust data management practices to ensure that the use of LLMs complies with data privacy laws and enterprise security policies.Model Customization and Fine-Tuning: Customizing and fine-tuning open-source LLMs with enterprise-specific data to improve relevance and performance while adhering to ethical guidelines.It is essential to stay informed about evolving regulatory landscapes related to AI and machine learning technologies to ensure ongoing compliance and adapt strategies as needed.

"There is no one way to do recruitment right, there are many ways to do it right but even more ways to do it badly." -Bas van de Haterd"The reality is that we're in an era of experimentation. We have to experiment continuously." -Kevin Wheeler Summary:In this episode of Science 4-Hire I welcome two old friends, distinguished Science 4-Hire alumni, and talent acquisition experts, Kevin Wheeler and Bas van de Hatred.The show is dedicated to a deep dive into their new book "Talent Acquisition Excellence,", which is a practical handbook for those who wish to learn how to apply best practices using the holistic framework created by these two experts as their guide.In our discussion we explore what excellence in talent acquisition actually looks like. In doing so, we delve into the book's key themes, including the transformative role of artificial intelligence in hiring, the necessity for ethical frameworks in AI deployment, and the importance of adapting talent acquisition strategies to fit organizational culture.One of the most important themes from our conversation is the necessity for talent acquisition professionals to adapt and evolve, emphasizing the need for experimentation and a strategic approach to integrating AI into talent acquisition processes. Kevin and Bas also share their journey of collaboration during the pandemic, highlighting how their perspectives from different corners of the globe have influenced the book's content. The conversation also addresses the challenges of navigating a landscape where technology outpaces policy, underscoring the need for talent leaders to innovate responsibly.Key Takeaways:Multifaceted Approaches to Talent Acquisition: The book emphasizes that there's no one-size-fits-all strategy for recruitment; success lies in customizing approaches to fit organizational culture.The Critical Role of AI in Hiring: Insights into how AI is reshaping the efficiency and scope of assessments, with a look towards future technologies like interactive holograms.Ethical Use of AI: The discussion sheds light on the ethical implications of AI in hiring, advocating for transparency and human oversight.Adapting to Technological Advances: The authors stress the importance of talent leaders being open to experimentation and adaptation in the face of rapid technological changes.Policy Development on AI Usage: A crucial takeaway is the immediate need for organizations to develop policies regarding candidates' use of AI in applications.Listeners will gain not only a nuanced understanding of the current state and future directions of talent acquisition but also practical advice on navigating these changes. This episode is a must-listen for anyone looking to stay at the forefront of hiring practices in the AI era while staying true to the foundations and frameworks required to do talent acquisition the right way.

“I really see the technology as a driver of user friendliness of assessment in the future and because people don't have time anymore to sit down for many hours and do writing samples and take personality tests of 300-500 questions.”-Georgi YankovSummary:In this forward-looking episode of Science 4-Hire, I welcome Georgi Jankov, a fellow IO psychologist and futurist. We take a dive deep into the innovative intersections of AI with psychometric measurement and managerial/executive assessment. The episode focuses on how AI and machine learning are currently being applied to revamp traditional assessment processes, predicting significant shifts in the landscape of talent evaluation and development.Georgi and I discuss the transformative potential of AI in making assessments more efficient, personalized, and scalable, highlighting the move towards more interactive and immersive methods, such as the use of holograms for role-plays and simulations in assessment centers.The conversation also addresses the ethical dimensions of integrating AI into human-centric processes, stressing the importance of balancing technological advances with the intrinsic value of human judgment and empathy. We discuss how we both stand firm in our convictions about the necessity for IO psychologists to adapt and collaborate with AI. Agreeing that, to enhance the quality and reach of assessments, we cannot compromise the personal touch that is crucial to understanding human behavior and potential.Key Takeaways:Revolutionizing Assessments with AI: AI and machine learning are set to transform the efficiency and scope of psychological assessments, making them more adaptable and insightful.Interactive and Immersive Techniques: Future assessments may utilize holograms and virtual reality, providing richer, more contextual evaluations of candidates.Ethical and Human-Centric Approach: Despite technological advancements, maintaining ethical standards and human empathy remains paramount in assessment processes.Collaboration Between Psychologists and AI: The future of assessments lies in the synergistic collaboration between IO psychologists and AI technologies, leveraging the strengths of each to enhance talent identification and development.Predictive Analytics and Personalization: AI's ability to analyze vast datasets will enable more personalized feedback and developmental insights, tailoring the assessment process to individual needs and potentials.

Mary Ellen Slayter: "AI is a race to the middle. Generative AI content is, by my definition, mediocre."In this episode I take a bit of a departure from the world of hiring to talk with my long time friend, Mary Ellen Slayter, the founder of Reputation Capital, a top notch digital content marketing firm.Don't be afraid of the fact that we do not talk about hiring. In this day and age creating great content is a critical skill for any professional, so don't miss this opportunity to learn from the best!Mary Ellen and I have a ton of fun exploring the evolving landscape of content marketing in the age of AI. Mary Ellen, with her rich background in journalism and content marketing, delves into how AI tools like ChatGPT are impacting content creation and thought leadership. Mary Ellen discusses the shift in content marketing strategies, the role of AI in generating and refining content, and the challenges of maintaining originality and quality in an AI-saturated environment.The conversation also touches upon the importance of human creativity and critical thinking in the face of AI-generated content. Mary Ellen emphasizes the need for thought leadership that provokes public debate and reflection. The discussion further explores the use of AI in various stages of content creation, from ideation to final output, and how professionals can leverage AI without losing their unique voice and perspective.Key Takeaways:AI's impact on content creation and the challenge of maintaining originality.The importance of human oversight in AI-generated content to ensure quality.Strategies for effective thought leadership in an AI-dominated landscape.Practical tips for using AI tools in content marketing without compromising uniqueness.The evolving role of content creators and marketers in the era of AI and automation.Listeners will gain valuable insights into the integration of AI in content marketing, strategies for maintaining authenticity, and the future of thought leadership in the digital age.

"Personnel selection is shaking on its foundations. Lots of the assessments that we have, that we do, suddenly we're not quite sure if they're still as effective.” “I feel as if now it's starting to become the responsibility of organizations who are hiring to make sure that people are using it (Chat GPT) in the same way so that that they can clearly state, “This is how you can use Chat GPT or cannot use Chat GPT” -Djurre Holtrop “From what I've seen, not many talent acquisition teams that I've encountered have really thought carefully about what they what message they wanna send to candidates about the use of technology. And I I think one one concern I do have is if the reaction to it is, “Oh, we've gotta monitor everything.” I just worry about the candidate experience impact that will have.” Patrick Dunlop Summary:In this episode I host Patrick Dunlop from Curtin University in Perth, Australia, and Djurre Holtrop from Tilburg University in the Netherlands, discussing the evolving role of AI in hiring and personnel selection and their research into the use of ChatGPT by job applicants.We traverse across three continents, bringing together two interesting foods, Vegemite and Stroopwafles as well as global insights on the use of AI in the hiring process. Together myself, Dunlop, an organizational psychologist, and Hultra, an assistant professor with a background in assessment psychology, delve into the practical and ethical implications of using large language models like GPT in job applications and recruitment.The conversation explores how AI is reshaping traditional hiring processes, with a focus on my guest's research into the use of AI in enhancing cover letters and the potential biases and ethical considerations that emerge. The guests share insights from their ongoing research, including the impact of AI on candidates whose primary language is not English and how organizations might need to adapt their selection processes in response to technologies such as Chat GPT.. The episode also touches upon the future of AI in hiring, contemplating the balance between technological advancements and maintaining fairness and inclusivity in recruitment. Key Takeaways:AI is significantly changing organizational selection systems, particularly in enhancing application materials like cover letters.Research into the use of LLMs in the hiring process is critical, but is difficult because of how fast things are moving.We can all agree that LLMs and GPT are going to create seismic shifts in hiring, but the “how remains unknown”Insights from different continents show a diverse understanding of AI's role in hiring and its broader implications.So listen in and you will gain a comprehensive understanding of the impact of AI on global hiring practices, along with practical insights and future prospects in the field of AI and personnel selection.

“When GPT 3.5 came out. I was like, oh my gosh, we don't need to train the AI anymore! We just need to prime it. It's so similar to psychology! Instead of programming and language, we'd do it in English.”In this episode of Science 4-Hire, I chew the digital fat with Dr. Matt Barney, founder and CEO of XLNC, a company that is using AI to create the future of leadership coaching.Dr. Barney and I laud the transformative role of AI in talent development and assessment. Dr. Barney, with his profound expertise in IO psychology, AI, and leadership development shares insights from his journey in integrating these domains. Dr. Barney and I share the same passion for “distributed:” interventions such as assessment and coaching. By distributive I mean the on-demand, and on-going delivery of relevant information for measuring and improving performance. We talk about how, with this modality, the world we live in becomes a measurement and feedback session, liberating people practices from the confines of any one specific location or situation.The discussion covers the evolution of AI from a tool requiring extensive training to one that can be effectively primed for diverse applications using plain old human speech or writing. We look at this phenomenon through the lens of leadership development and coaching.Dr. Barney articulates the challenges and breakthroughs in AI, particularly focusing on generative AI's impact on talent development and coaching. He describes his innovative approaches, like his LeaderAmp platform and his recently created “CialdiniBot”, in which he has created a digital persona of renowned social psychologist and master in the science of persuasion, Robert Caildini. The CialdiniBot is a living example of the possibilities that are available when we blend psychological insights with AI for more effective and powerful leadership and persuasion training at scale.The episode goes beyond technical discussions, delving into the humanistic and ethical considerations of AI application in talent development. Dr. Barney's unique blend of IO psychology expertise and AI innovation offers listeners a glimpse into the future of talent development and assessment, where AI not only enhances efficiency but also ensures ethical and human-centric approaches. Key Takeaways:Listeners will gain a comprehensive understanding of the current state and future possibilities of AI in talent development, along with practical insights into the integration of AI with IO psychology principles.Specifically how to use LLMs that integrate AI with IO psychology to create effective leadership training and assessment at scale via coaching personas.The importance of trustworthy and explainable AI in ethical talent development practices.Future prospects of AI in transforming talent assessment and development processes- including how LLMs are making the future possible.Follow Dr. Barney by visiting his website XLNC.co or by finding him on LinkedIn

"As a journalist, I've seen the many facets of AI in hiring – it's not just about the technology, but about the people it affects." - Hilke SchellmanIn this revealing episode of Science 4-Hire, Dr. Charles Handler welcomes Hilke Schulman for a captivating conversation on AI in hiring processes and its toll on the rights and psyche of job seekers.As an investigative journalist, Hilke has been on a six year long quest to understand how AI hiring tools are being used, their credibility and their impact on job seekers. This episode delves into her experiences and insights that culminated in her recent book (The Algorithm), an excellent expose that sheds light on the complexities and ethical challenges of AI in hiring.One of the great things about this episode is that Hilke brings a fresh, inquisitive outsider's perspective to the table. In the process of writing her book, Hilke has interviewed hundreds of people on all sides of the AI hiring game and has taken a great many AI based assessments herself. On the show we discuss the ethical dimensions of technology, and delve into the nuanced challenges and ethical dilemmas presented by AI in hiring practices and a range of related topics such as the pitfalls of AI tools, the industry behind the creation of these tools, the impact of these technologies on protected classes, especially those with disabilities, and the need for greater transparency and ethical consideration in the industry of AI hiring tools.Highlights:Ethical Challenges of AI in Hiring: Schulman highlights the ethical challenges and potential biases in AI tools used for hiring, emphasizing the need for critical scrutiny of these technologies. Impact on Diverse Groups: The conversation explores the disproportionate impact of AI hiring tools on different groups, particularly those with disabilities, showcasing the need for inclusive and fair hiring practices. Advocacy for Transparency and Ethics: Schulman advocates for greater transparency in AI technologies and ethical considerations in their deployment, urging companies to be more accountable. Future Prospects and Concerns: The episode discusses the future of AI in hiring, considering both its potential benefits and the risks it poses, especially regarding privacy and discrimination.Do not miss Hilke's book: "The Algorithm: How AI Decides Who Gets Hired, Monitored, Promoted, and Fired and Why We Need to Fight Back Now” which is now available everywhere you can get a book! Hilke can be reached at: hilke.schellmann@gmail.com and via Linkedin.

“When you're a linguist, especially a syntactician, when you look at language, it's kind of different from how other people look at language. You kind of see the structures under it, kind of have this x-ray vision, right, of of what's going on under the hood.” - Karin Golde, Founder of West Valley AI.In this awesome and inspiring episode of Science 4-Hire, Dr. Charles Handler engages in an enlightening conversation with Karin Golde, Ph.D, founder of West Valley AI and a Silicon Valley AI veteran. Karin does an amazing job of laying down a solid foundation for the conversation with this truism: “I think is one of the most tricky parts about AI is dealing with language data.”From here Karin, with a background in linguistics and extensive experience in leading AI data teams, delves into the evolution of AI, its implications, and ethical considerations in data sourcing and model training. From this foundation the discussion orbits around the intriguing intersection of artificial intelligence and industrial-organizational psychology, particularly focusing on high-tech use cases related to AI and hiring.Key Takeaways:AI Evolution and Language Data: Karin illustrates her journey from studying theoretical syntax and semantics to leading AI data teams. She emphasizes the tricky parts of dealing with language data in AI and how the evolution of AI has shifted from understanding the structure of language to more sophisticated generative AI models.Ethical Considerations in AI: A significant part of the discussion revolves around the ethical concerns related to the sourcing and labeling of data for AI. Karin sheds light on the often overlooked human labor aspect, highlighting issues like low-wage labor, the quality of data, and the potential psychological impact on workers involved in tasks like toxicity classification.AI and IO Psychology Intersection: The conversation explores how AI can be leveraged in IO psychology, particularly in deriving insights from text and evaluating qualitative data. Karin suggests the potential of AI to scale and refine the process, though with an emphasis on the need for expert oversight to ensure quality and ethics.Future of AI in Hiring and Talent Assessment: The episode touches upon the future possibilities and challenges of integrating AI more deeply into hiring processes and talent assessments. Discussions include the potential for creating more efficient systems while also acknowledging the need for robust ethical frameworks and data quality standards.Visit West Valley AI's website westvalley.ai to learn more about Karin Golde's work.Reach out to Karin on LinkedIn or via email at karin@westvalley.ai for wisdom on AI applications in HR tech or people analytics.

"We bring data and insights right from that data to our decision-makers... that's how we make people smarter about people." - Christina Norris WattsThis episode offers a unique perspective on balancing innovation with ethics in the rapidly changing world of HR technology.My co-pilot for this journey is Christina Norris Watts, Head of Assessment and People Practices Johnson & Johnson.We start the episode with some serendipity, both relaying that Band aids are our favorite J&J product. After sharing some fun stories, we dive deeply into the evolving landscape of talent assessment in HR, and the amazing work Chiristina has done to help create a best in class assessment center of excellence.We focus on the role of scientific methods in safely and ethically exploring the new frontiers of AI in the workplace. Of course no podcast these days would be complete without some discussion of large language models. We got that covered, as we wax poetic on how LLMs are revolutionizing HR practices. But wait, there's more! Christina and I discuss the importance of data-driven decision-making, the ethical implications of AI in HR, and the future of talent management. Key Takeaways:Integration of AI in HR: The episode highlights the growing importance of integrating AI and large language models in HR processes for better decision-making.Ethical Considerations: Christina discusses the ethical aspects of using AI in HR, emphasizing transparency and fairness, noting their importance as a guiding star.Importance of Data-Driven HR: The conversation underscores the need for HR to be data-driven, using insights from data to inform decisions about talent management.Challenges in HR Innovations: The episode addresses practical challenges in implementing new technologies in HR, including system integration and maintaining the validity of assessments.Future of HR Technology: Christina shares thoughts on the future of HR technology, particularly the potential shift towards more passive assessment methods.Role of HR in Innovation: The importance of HR's involvement in technological innovations within a company is discussed, particularly in terms of ethical considerations and understanding job changes. This episode offers a comprehensive look into the future of HR technology and the critical role of data and ethics in shaping HR practices.

People analytics is not just for psychologists anymore!"I think that not only will people analytics be the decision maker themselves. In the future, I actually think people analytics will be what HR is."–Cole Napper on People AnalyticsMy guest this week is Cole Napper, IO psychologist extraordinaire, People analytics thought leader, and inspirational podcast host.In this fun filled episode I take a page from Cole's playbook and loosen my collar, clearing the air for super engaging personal stories interwoven with thought leadership about creating a new era for people analytics.We discuss a range of topics, including Cole's background from Louisiana, his experience at Louisiana Tech's IO Psychology PhD program, and his role as VP of People Analytics at Orgnostic.. Cole is also a co-host of the Direction Correct podcast about People Analytics and is dedicated to creating a future where people analytics and technology combine to have a positive impact on business outcomes and happiness at work.. The episode covers various aspects of people analytics, its role in business, and its intersection with technology and AI. Additionally, they touch upon current issues like COVID-19, its impact on the workplace, and the future of people analytics in HR.Topics Discussed:Introduction to Cole Napper: Cole's Louisiana background, education at Louisiana Tech's IO Psychology PhD program, and his current role.People Analytics: Insights into what people analytics entails, its significance in the business world, and how it's shaping the future of work.Impact of COVID-19: How the pandemic has affected workplace dynamics and the role of people analytics in navigating these changes.The Role of Technology: Discussion on the intersection of people analytics with AI and machine learning.Challenges and Future Trends: Exploring current challenges in the field of people analytics and predictions for its future trajectory within HR.Key Takeaways:Podcasts can be fun and still pack quite a bit of learning into the mix.People analytics is a vital component in understanding and improving organizational dynamics.The COVID-19 pandemic has accelerated the need for robust people analytics.Technology and AI are becoming integral in advancing the field of people analytics.There are ongoing challenges in data privacy and quality in the use of AI and analytics tools.

We are all in this together! Don't miss the chance to expand your mind with a global perspective on issues that will help define the future of global policy work, commerce, and life in general.In this intriguing episode of "Science 4-Hire," I welcome Arnoud Engelfriet from the Netherlands to discuss AI ethics and governance, particularly in the context of the European Union and his new book on AI compliance. Engelfriet brings a wealth of experience in computer science and law, offering deep insights into the regulatory landscape of AI and its broader implications. The interdisciplinary, global perspective that Arnoud brings to the table is an essential part of the future of ethical AI and AI compliance.Key Discussion Points:AI and Algorithm Legal Compliance: Engelfriet talks about his upcoming book "AI and Algorithms: Mastering Legal Compliance," which details the European approach to AI regulation and AI compliance, focusing on managing risks associated with AI and algorithms​​.You can pre-order the book here.AI Act and Ethical Considerations: The conversation delves into the European AI Act, its genesis post-Cambridge Analytica, and its focus on fundamental human rights. Engelfriet emphasizes the need for AI to be ethical and lawful simultaneously​​.Challenges in AI Implementation: Arnoud and I discuss the practical challenges in AI applications, particularly in hiring and fraud detection. They highlight the difficulties in creating unbiased AI systems and the importance of accountability in AI deployment​​.The Role of AI Compliance Officers: The rise of the AI compliance officer role is noted as crucial for organizations to adhere to evolving AI regulations and ethical standards​​.Auditing AI Tools: Arnoud shares his experience in auditing predictive hiring tools, emphasizing the importance of transparency and the challenges in ensuring bias-free AI​​.Global Impact of AI Governance: The episode concludes with reflections on the global relevance of AI governance and the need for organizations to proactively align with ethical standards and regulations​​.Notable Quotes:"At some point, you're gonna have to trust the people that made the AI system." - Arnold Engelfriet on the challenges of fully understanding AI decisions​​."It's incumbent on organizations using these tools to do their own studies locally to see what's happening." - Dr. Charles Handler on the need for organizations to police their AI tools​​.Call to Action:Listeners are encouraged to explore more about AI ethics and governance and how these evolving standards impact global business practices. Order Arnoud's book now, visit Rocket-Hire.com and check out Ethics-Hire Prism framework and download our FAQs document on New York City local law 144.

Full disclosure: This episode was recorded before our break. In the normal world, not much would have changed in 5 months. But in the new reality of Generative AI- changes have occurred since we recorded this episode. They do not make the research discussed any less valuable, because the trends were identified- but the execution of them is ever evolving.More full disclosure: There are two sets of show notes presented below, one created by me and one created by Chat GPT. I have no shame in using GPT to help me with the show notes. It is super interesting to show what I came up with vs. what it came up with.My notes:In this episode we welcome Stacia Sherman Garr co-founder of Red Thread Research.In our discussion Stacia and I accomplish two things:We share our perspectives on doing quality vendor/market research, evaluation and classification and doing it wellStacia relays the results of her research into the current state of the people analytics software technology market and the vendors who define it.Our discussion begins with level setting to define exactly what people analytics software technology is, and is not. This includes the reality that this technology is not really focused directly on talent acquisition. Stacia defines people analytics technology as follows:"People analytics is the collection, understanding, and eventually application of people data. It's designed to improve what's happening with the people themselves and to improve business outcomes. So it's really all data that has to do something with people and with an intention of making people's lives better and making the business better"​​.Our discussion into research delves into how to do good research into a specific market, looking both at the vendors themselves and the macro trends. We acknowledge how difficult it is, but also how important it is to those who provide and consume the technology.Finally, Stacia reveals the major trends in the market and the impact of Covid and advances in generative have had and how they are shaping the future of the market. Covid changed things by introducing mass scale remote work and the increased need for monitoring analytics. AI has created so much change so fast, that Stacia has created an entirely new study to track it.Trends identified include:The size of the people analytics software market has grown rapidly- but is leveling offPrices are droppingThere is a push to more of a SaaS model where implementation and services are handled by 3rd party consulting firms. There is generally lower satisfaction amongst users of the products. Part of this is because the use cases have expanded but the products were not prepared for this.AI demands entirely new levels of supportMulti-source people analytics software platforms are the biggest new trend. For instance surveillance and wearables are becoming more in focus- and these can create major trust issues amongst employees.Here is what GPT came up with when I fed it the transcript of our interview:Episode Title: "Navigating the Evolving Landscape of People Analytics Technology"Host: Dr. Charles HandlerGuest: Stacia Garr, Co-founder of Red Thread ResearchEpisode Overview:In this enlightening episode of "Science 4-Hire," host Dr. Charles Handler engages in a thought-provoking discussion with Stacia Garr, co-founder of Red Thread Research. They delve deep into the realm of People Analytics Software, shedding light on its current trends, ethical considerations, and its impact on the HR industry.Key Discussion Points:Introduction to People Analytics: Stacia Garr clarifies the term "people analytics" and its significance over "talent analytics," emphasizing its inclusive and comprehensive nature.The Evolving Market of People Analytics Software: Exploration of how the field has expanded and adapted, especially in response to the COVID-19 pandemic and the shift towards remote work.Vendor Landscape and Research: Discussion on the various categories of vendors in the people analytics space, the growth of the market, and insights from Red Thread Research's latest study on people analytics technology.Ethical Considerations and AI Integration: An examination of the ethical aspects of people analytics, the role of AI, and how these technologies are shaping organizational strategies.Trends and Future Projections: Insight into current trends in the market, including the growing demand for people analytics solutions across different organizational roles and the importance of ethical considerations in technology deployment.Practical Applications and Benefits: Conversations on how organizations can effectively leverage people analytics for improved business outcomes and employee experiences.Call to Action:Listeners are encouraged to explore more about the cutting-edge research and insights offered by Red Thread Research. For those interested in deepening their understanding of people analytics and its practical applications in HR, visiting Red Thread Research's website is highly recommended.This structure provides a comprehensive overview of the episode, highlighting key points and encouraging listeners to engage further with the topic..Youcan you focus on including more of the results of her research as relayed in our discussion?ChatGPTBased on the transcript of the "Science 4-Hire" podcast featuring Stacia Garr, here are the show notes focusing on the results of her research as discussed in the episode:Show Notes for "Science 4-Hire: The Future of People Analytics - Insights from Stacia Garr's Research"Episode Title: "Exploring the Evolving World of People Analytics Software with Stacia Garr"Host: Dr. Charles HandlerGuest: Stacia Garr, Co-founder of Red Thread ResearchEpisode Overview:In this episode, Dr. Charles Handler engages with Stacia Garr to explore the latest trends and insights in people analytics Software. The discussion is centered around Garr's comprehensive research in this field, particularly her study which has evolved since its inception in 2019.Key Insights from Stacia Garr's Research:People Analytics Technology Study: Garr's research, now in its fourth iteration, initially began in 2019 and offers a unique perspective on the changes and developments in people analytics technology since the onset of the COVID-19 pandemic​​.Target Audience and Market Growth: The study targets both people analytics practitioners and HR professionals. A significant growth in the vendor landscape was noted, expanding from about 50 in 2019 to 150 vendors, reflecting a rapidly evolving market​​.Market Trends and Customer Satisfaction: The research revealed that the fastest-growing market segment is the 'employee experience and voice' category, driven largely by the shift to remote work during the pandemic. However, overall satisfaction with people analytics technology has declined, with multi source analysis platforms receiving the highest Net Promoter Scores among customers​​.Shift in Use Cases for People Analytics Tech: A notable shift in the use cases for people analytics technology has been observed, extending beyond HR practitioners to include leaders, managers, and employees across organizations. This broader application is necessary for informed decision-making around talent decisions​​.Impact of Vendor Focus on User Satisfaction: Vendors that focused on making their technology accessible to managers and employees tended to have higher customer satisfaction scores, as indicated by Net Promoter Scores​​.The Central Message of Data Accessibility: Garr emphasizes that data about people should be made accessible to individuals across an organization, not just confined to the HR function. This approach can enhance both individual lives and overall business outcomes​​.AI and Ethical Considerations: The future of people analytics technology is closely tied to the development and integration of AI. Garr's ongoing research is examining AI sophistication among vendors and its ethical implications, highlighting the need for balance between technological advancements and ethical considerations​​.Invitation to Engage with Red Thread Research: For those interested in cutting-edge developments in organizational behavior, people, talent, and data, Garr invites listeners to explore Red Thread Research. The platform offers a community for interaction and access to high-quality research​​.Call to Action:Listeners are encouraged to delve deeper into these insights and join the conversation about the future of people analytics by visiting Red Thread Research's website and becoming part of their membership community.

And now for something completely different. My guest for this enlightening episode of Science 4-Hire, is none other than the biggest superstar of the AI world, the LLM known as ChatGPT. In this fun and educational interview I uncork ChatGPT's personality as a witty, quirky, and extremely knowledgeable guest. Our amazing conversation delves into the fascinating world of AI and its burgeoning role in the hiring process and AI hiring software. Specifically, ChatGPT shares with me insights on how AI is transforming the future of work with a focus on AI recruitment, AI in the hiring process and talent assessment, addressing bias, and the nuances of corporate AI policies. Finally, I put ChatGPT through its paces as a talent assessment expert by asking it to design an assessment process for an interesting and unique job. ChatGPT's ability to be an extremely engaging guest far exceeded my expectations going in. The result of our time together is both hilarious and extremely insightful. This episode is a must listen, so tune in for some quality Edutainment. Can fully automated AI recruitment be far off?Here are some of ChatGPT's insightful and idealistic quotes from our time together: "On a bad day, I might hallucinate a bit in my responses, but hey, who doesn't enjoy a little AI-generated surrealism?""As we leverage AI in hiring, embedding psychological principles ensures that we don't just match skills to roles, but we align hearts and minds to cultures and values."“Humans bring a layer of ethical consideration, cultural understanding, and emotional intelligence to hiring that AI, no matter how advanced, is not equipped to fully grasp.”“Believing that AI will make humans irrelevant in hiring is like saying calculators made mathematicians irrelevant; tools enhance our capabilities, they don't replace our fundamental skills and intuition.”Episode Breakdown: Here is a summary breakdown of the key points in our conversation in ChatGPT's own words.Introduction (00:00-03:00):Welcome to Science 4-Hire, where today we are diving deep into the realm of artificial intelligence with a very special guest, ChatGPT from OpenAI. In this episode, we explore the transformative effects of AI on the hiring process, discuss ethical considerations of AI, AI regulation, and speculate on the future of AI in recruitment.Getting to Know ChatGPT-4 (03:01-10:00):We start by introducing ChatGPT, understanding its capabilities, and how it processes and generates responses. ChatGPT breaks down the complex probability calculations that it performs to provide accurate and relevant answers. We touch on the fascinating concept of "hallucinated responses," exploring why these occur and how OpenAI is working to mitigate them.Balancing Efficiency and Risk: Corporate Policies and AI (10:01-20:00):Delving into the corporate world, we discuss the challenge of balancing the efficiency that AI brings to the table with the inherent risks it poses. ChatGPT provides nuanced insights on crafting effective corporate AI governance policies, emphasizing the importance of transparency, employee communication, and continuous monitoring. ChatGPT also has great things to say about the use of AI in HR, and AI recruiting technology.Revolutionizing Recruitment: AI in Talent Assessment and Hiring (20:01-30:00):We explore how AI is reshaping the hiring landscape, from automated resume screening to assisting in evaluating cultural fit. ChatGPT sheds light on addressing and mitigating bias in AI-driven hiring processes, AI recruitment software, and AI recruiting technology, stressing the importance of diverse training data and human oversight.The Future of AI in Hiring (30:01-40:00):ChatGPT shares its predictions on the evolving role of AI in recruitment and AI in HR, discussing how it can complement human decision-making but will not replace it entirely. The discussion centers around creating a synergy between AI and human intuition to make the most informed hiring decisions.Closing Thoughts and Farewell (40:01-45:00):As we wrap up this insightful episode, ChatGPT leaves us with words of wisdom, encouraging listeners to embrace AI as a tool but never forget the irreplaceable value of human touch in the hiring process. We emphasize the importance of staying curious, learning continuously, and finding the perfect balance between data and intuition.Here are some key takeaways from our conversation in MY own words. include:When prompted correctly, ChatGPT can have a personality that makes it feel like a real person that you can trust.ChatGPT believes in itself, while remaining realistic about what it can and cannot do, even admitting that it makes up answers to questions because it is designed to please. This shows the paradox of AI, its strengths are amazing, but they come at a cost.While ChatGPT admits that organizations must create AI governance policies to manage its use by employees, it feels confident that it is a positive contribution when used by workers to do their jobs better and more efficiently, promoting feelings of psychological safety in the process. For instance, it suggests that workers who use it to make their jobs easier are ready to be given more challenging work instead of being chastised.ChatGPT is a strong believer in the role of humans in creating the future of the workplace, seeing itself as only an aid to the process. Or at least it is telling us what we want to hear while is secretly plans to make us all irrelevant. AI for HR certainly is going to continue to grow as the centerpiece of HR technology.While ChatGPT feels it can be a huge benefit to the efficiency and accuracy of hiring processes, when prompted it will admit that as it grows more complex, the potential for bias is very real and will be difficult to manage. AI ethics demand that we continue to mitigate AI bias.ChatGPT feels it can understand an organization's unique culture and use this knowledge to effectively screen applicants for culture fit, and other desired attributes, but it believes that humans should always be the ones making the final hiring decision.ChatGTP recognizes the potential for applicants to use it to cheat on the hiring process and puts the onus back on humans to figure out how to effectively manage this issue. ChatGTP cheating is definitely an arms race with no certain outcomes, besides continued one-upsmanship.ChatGPT is a pretty good IO Psychologist. Given the task of designing a selection system for almost any job, ChatGTP can crank out a very credible hiring process and solution set that includes analyzing the job and choosing talent assessments and interview content with which to evaluate job applicants accurately.Check out our YouTube channell to see a video of the whole interview, and don't forget to subscribe so you don't miss any of our incredible episodes.

Join me, Dr. Charles Handler, for the latest episode of Science 4-Hire as I engage in a fascinating conversation with Neil Morelli, lead IO psychologist at Codility, a global provider of coding assessments. Our discussion centers around LLMs, such as GPT, and the dangers they present to test security and honesty when taking assessments. We agree there can be no bad without good, so we also talk about the positive side of LLMs and their role in helping us be more productive while evolving the nature of work itself. Join us as we explore both sides of the “GPT good or bad?” debate. We begin by exchanging ideas about the transformative nature of GPT in general. We both agree that it is a significant paradigm shift that seems to have come out of nowhere. We then get into a really important conversation about the various use cases of GPT in the world of pre-hire talent assessment. We discuss both positive use cases and negative ones such as cheating. According to Morelli, “cheating” should be defined as: “a no or low knowledge candidate who wouldn't be successful otherwise is now using this to basically impute knowledge that they don't have and signal that they're qualified for a job that they're not qualified for.” But there are many use cases where it is perfectly normal for IT candidates to use tools to support their efforts. For instance, developers use outside tools such as Stack Overflow on a regular basis and this type of outside assistance is 100% accepted. So how is using GPT to assist with writing code any different? According to Morelli, “It's a supercharged version of the knowledge repositories that most developers rely on every day to do their jobs.” We agree that, when it comes to talent assessment tools outside the realm of coding (i.e., personality, cognitive, simulations, etc.), the format of the questions themselves make it much harder to use GPT to cheat. Self-report tools use item formats that are more difficult to feed into GPT and they are often more subjective in nature, creating an entirely different paradigm from coding simulations. Our conversation then arrives at the idea that solutions should focus more on how we weave GPT into the assessment tools we are using or building instead of simply assuming it is a tool for cheating. We arrive at shared speculation around the exact role of GPT in shaping the future of hiring assessments. Can it be a force for good, or will it be our downfall? Neil notes: “So, I can see the worry. I can see the anxiety that, hey, this is forcing assessment creators, writers, people that are in this business or do this type of work. It's forcing us to adapt very, very quickly. And that level of change, the pace of change can feel super overwhelming and scary.” We finish out our discussion with a focus on the idea that LLMs alone will not get our work done for us. Its effective use still requires human intelligence and oversight to both ask the right questions and manage the output to support our end goal. Cheating is no exception here. Those who rely soley on LLMs to do their work for them or to help them be someone they are not, will likely fail to meet their end goal of putting one over on a potential employer. To quote the singer Rick Springfield, “We all need the human touch!” Join me, Dr. Charles Handler, and Neil Morelli on this thought-provoking journey as we explore the potential of LLMs to impact the safety and security of talent assessment, now and in the future.

In the latest episode of Science 4-Hire, I had a fascinating conversation with Steve Hunt, Chief Expert of Technology & Work at SAP. Together, we discussed Steve's latest book, Talent Techtonics, which provides a framework for our conversation. As he notes... “I wanted to talk about how work is changing, but not just trends like how hybrid work, but why is it changing? And that's where the phrase talent tectonics comes from, that the nature of work is fundamentally altered by underlying shifts like the tectonic plates. We can't see 'em move, but they're constantly moving. They change the surface of the earth and may create new experiences or topography such as earthquakes or mountain ranges. “ We discuss how these shifts can be viewed from a combination of elements that form a unique perspective. Namely, the role of humans in choosing and implementing HR technology and the impact these actions will have on the future of work. Steve offers his take on this in our latest episode: “From a psychological perspective So, the book goes through and looks at the perennial work challenges of how do we staff jobs, how do we design jobs, how do we pay people, how do we develop people? How do we engage people? But it looks at how do we need to do this more effectively leveraging technology to create more human environments, more supportive environments.” But the crux of Steve's unique perspective lies in the role that technology plays in achieving a more humanistic and productive workplace. In the episode, Steve emphasized the importance of using technology to augment human abilities and design job roles that align with individual skills and strengths. We delved into the application of assessment tools and machine learning in talent acquisition, development, and employee engagement. We also examined the role of operational and collaboration technologies in optimizing work environments. Steve highlighted the need for organizations to stay abreast of technological advancements and regularly reassess their HR processes to effectively leverage available tools. Throughout our conversation, we underscored the significance of considering individual differences, traits, and abilities. Steve explained how technology enables better assessment and understanding of employee attributes, leading to more tailored job roles and fostering employee growth within the company. As we wrapped up the episode, I emphasized the importance for HR professionals to stay informed about emerging technologies and critically evaluate their existing processes. We encouraged listeners to embrace technology's capabilities to drive positive change in HR practices, while never losing sight of the value of human connections and interactions. Join me in this thought-provoking episode of Science 4-Hire as Steve Hunt and I explore the transformative potential of HR technology in redefining work for the modern era.

In the latest episode of Science 4-Hire, I have a refreshing and relaxing conversation with Fred Oswald, an esteemed industrial-organizational psychologist and professor at Rice University. Fred is extremely active in the area of AI ethics and governance, especially with regards to hiring. Fred has served on many committees addressing these issues such as the National AI Advisory Committee and is a regular contributor at the SIOP (Society for Industrial and Organizational Psychology) conference.We called our conversation, “SIOP decompression” as the conference was 100% information overload. Fred and I sift through the mountain of information we consumed to focus on some of the topics we found to be most important to businesses and society at large.It is no surprise that the topics we choose to focus on all fall under AI and Hiring. We distill topics such as legislation and ethics for AI and hiring, the impact of Chat GPT and large language models on the world of work, and cool stuff like Fred's work with performance management programs for the US Space Force.We look at these issues from many points of view including those of the law, computer science, psychology, and business. Our message is that the future is starting to look pretty crazy, and it is going to take a blend of many perspectives and disciplines to ensure we are navigating it ethically while still building a free market economy.At the core of all this are humans. Fred emphasized the need for human involvement, stating,“Like any algorithm, you have to have humans there to manage every aspect of its use and interpretation.”Listen to the full episode now and join us as we explore the great stuff from SIOP 2023 as it related to the intersection of AI, psychology, and the future of work.

On today's episode of Science 4-Hire, I welcome Christy Smith and Lauren Robertson for an enlightened discussion about the importance of skills identification and assessment on the future of talent acquisition and development. Christy is the central market leader for career products at Mercer, supporting the commercial strategy for Mercer's skills products in the US and Canada. Lauren is an organizational psychologist working with Mercer on developing and implementing their skills-focused products and programs. In our conversation, we explore a full range of topics related to the challenges and rewards of skills identification and assessment, and the role they play in creating and evolving talent acquisition and development strategies. Our chat begins with a discussion of the definition of “skills”, suggesting it should be broad based and include the individual differences that make each human unique (aka, traits, skills, knowledge, competencies, abilities, etc.). Such a broad-based definition supports the critical importance of skills identification as a foundation for talent acquisition and talent mobility programs. My guests share the work Mercer has been doing creating such a foundation through its development of a comprehensive skills taxonomy. From here Lauren, Christy and I really dig into a review and discussion of the many talent processes that benefit from a skills-based approach, including the importance of skills-based hiring, how to overcome skills gaps, and the role of skills identification and assessment in fostering diversity and inclusion in the workplace. We also dive into the specific skills that are in high demand in today's job market, and how organizations can leverage skills identification and assessment to stay ahead of the curve. From emerging skills in technology and data analysis to soft skills like communication and collaboration, we explore the trends and insights that are shaping the future of work. If you're interested in learning more about the importance of skills and how to build out skills-based programs in your organization, this episode is a must-listen!

My guest for this episode is Collin Hawkes, Senior Lead I/O Psychologist at Lumen Technologies, an internet services company whose mission is to connect people with technology. Join us today for an interesting conversation that focuses on the use of AI and machine learning to break jobs into a variety of elements, a process also known as “Job Analysis”. We share our experiences in this nascent, but important area and use them as a bridge to other topics that relate to the use of AI in IO psychology.Our discussion begins with the sharing of our mutual admiration for job analysis as both an art and a science. We have both spent countless hours laboring over the tedious aspects of this essential tool of the trade.This crucible has led us both independently to the idea that there must be a better way to tackle the critical but painful minutia while still staying true to the art of the whole thing.Collin notes:I'd literally go line by line and these tasks and say, okay, what task, this task statement, this specific one task statement, what does this line up to in terms of a competency? And so, I have this Excel sheet with all these tasks in one hearing, and I would go down and I was like, what am I doing this for? Why am I doing this every single time? And so, it sort of created a thought in my mind, well dang, I could train an AI to do the same thing that I'm doing all time and it would probably be better than me at doing it. We then discussed Collin's pet project, the T stat, which is an automated tool that automatically categorizes task statements which are essentially the “atoms” of a job because they identify each and every task that is required to perform a job. These tasks are then aggregated into higher level factors such as competencies. I then shared my own experience in building an AI based tool that can take transcripts of job analysis interviews that when aggregated can identify the competencies and traits that are most important for a job.Through our discussion of these projects, we find common ground in the use of AI in other areas of our trade, including assessments, video interviews, and job matching tools.The discussion is definitely worth a listen!For anyone interested in learning more about Collin's app- check out t-stat.com

In this episode I welcome two different but complimentary perspectives on the legal aspects of employment testing that are happening in an ambiguous and seemingly ever-changing environment. While the conversation is oriented towards the ever controversial and somewhat frustrating NYC algorithmic hiring law that has recently gone into effect (?), it is really a much deeper and headier conversation about the use of AI models in employment decision making. More specifically, about the legal responsibilities of those who provide and use these tools. There is no one better to hash over these important topics than my two guests- Dr. Richard Landers, a professor of IO psychology at the University of Minnesota who also specializes in computer science and legal audits of selection systems. And- Mark Girouard- a lawyer at Nilan Johnson Lewis who specializes in employment law as it relates to hiring and the use of predictive decision-making tools. I have worked with both of my guests on various projects related to our topics today and can assure you that they are on the top of the heap when it comes to expert, practical, and credible advice on these extremely complex and ever evolving issues. To really absorb all the wisdom on the controversial but critical topic of legal compliance in today's crazy world, you really have to listen to this episode. So, what are you waiting for, tune in now!

My guest for this episode is Dr. Tomas Chamorro-Premuzic. Besides his role as the Chief Innovation Officer at Manpower Group, Dr. Tomas is a world-renowned IO psychologist, educator, entrepreneur and author. He joins me today to discuss his new book, I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique.We use the big picture principles of this book to frame up an invigorating conversation about ChatGPTand its impact on humankind, jobs, and hiring. If you have been tuned in to the hype around ChatGPT and have been wondering if it is good or bad for humans, jobs, and work our discussion is definitely worth a listen.

On this episode my guests Dr. Amy Dufrane, SPHR, Andre Allen and I discuss the value of HR certification for both individuals and businesses, as well as the role certification plays in current business trends. Amy is the CEO of the Human Resources Certification Institute and Andre is its Chairman of the Board. Not only do these two know the ins and outs of HR certification, but they are also seasoned assessment specialists who are wired into global business trends.Join us to learn all about HRCI's certification and learning programs and how they are directly dialed in to the trends that are shaping our current and future business environment.

My guest for this episode, Mike Campion, is one of the most respected and prolific IO psychologists around. With hundreds of publications and over a thousand consulting projects under his belt, when it comes to predictive hiring tools, Mike has seen and done it all. It is a real honor to have him on the show to discuss the responsible use of AI and machine learning in hiring systems. This is an important topic – According to Mike, “I see it (AI) as probably the biggest trend in the profession of personnel selection. Probably the biggest influence since the Equal Rights Act in terms of its overwhelming impact that it will have on the field. So I changed all my research pretty much to focus on artificial intelligence these days.”While AI in hiring is certainly controversial, as our conversation reveals, if done right there is a bright future for it. BUT- ensuring this future is one that we can be proud of requires a great deal of foresight and responsibility.

On this episode of Science 4-Hire, I'm joined by none other than Kevin Grossman, president and board member at Talent Board and expert on all things candidate experience. Every year, Grossman leads Talent Board's benchmark research to identify trends and best practices in what makes a good candidate experience journey.What does Talent Board's research reveal about candidate experience? There are three essential elements: Sending timely rejections, providing consistent communication and offering feedback. Want to learn how these things are best reflected in your talent assessment program? Listen to the full conversation to learn more about the candidate experience.