Podcasts about series exploring ethics health

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Privacy-preserving computation can help hospitals and researchers use sensitive health data without exposing it. Farinaz Koushanfar, Ph.D., UC San Diego, explains how secure computation and distributed learning make it possible to collaborate on medical data while protecting patient privacy. Koushanfar examines secure multi-party computation, zero-knowledge proofs, and federated and split learning, helping clarify how health systems can work together despite data silos, incompatibility, security threats, and re-identification risk. This work helps explain how medical AI can learn from private data more safely and points toward more secure, robust, and trustworthy healthcare systems. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41367]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Youth mental health is increasingly shaped by how teens use AI for emotional support outside clinical care. Cinnamon Bloss, Ph.D., UC San Diego, explains how growing use of conversational AI reflects major gaps in care and changing preferences for support. Bloss examines the appeal of AI's accessibility and nonjudgmental responses, concerns about replacing human connection, and the need to monitor harms, helping clarify how AI fits into a fast-changing mental health landscape. She also points to the importance of listening to young people, improving AI credibility and transparency, expanding safety and privacy discussions in schools, and preparing clinicians and online safety workers for this new reality. This work helps explain why teens are turning to AI and points toward a more thoughtful balance between safety and access to mental health support. Series: "Exploring Ethics" [Health and Medicine] [Science] [Show ID: 41366]

Bias in health AI can shape who gets care, how fairly risk is measured, and whether automation helps or harms patients. Karandeep Singh, M.D., M.M.S.C. explains that predictive AI can reflect historical, representation, measurement, learning, evaluation, and deployment bias, especially when models are trained on limited populations or use flawed proxies for illness and access to care. Singh also describes generative AI as a system trained first to predict text and then to follow instructions, with bias entering through training data, instruction tuning, prompts, and outside information sources. Alongside these risks, he highlights practical uses such as AI-assisted sepsis quality review and patient outreach workflows, while emphasizing governance, human oversight, disclosure, and careful measurement of whether these tools actually improve care. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41365]

Bias in health AI can shape who gets care, how fairly risk is measured, and whether automation helps or harms patients. Karandeep Singh, M.D., M.M.S.C. explains that predictive AI can reflect historical, representation, measurement, learning, evaluation, and deployment bias, especially when models are trained on limited populations or use flawed proxies for illness and access to care. Singh also describes generative AI as a system trained first to predict text and then to follow instructions, with bias entering through training data, instruction tuning, prompts, and outside information sources. Alongside these risks, he highlights practical uses such as AI-assisted sepsis quality review and patient outreach workflows, while emphasizing governance, human oversight, disclosure, and careful measurement of whether these tools actually improve care. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41365]

Bias in health AI can shape who gets care, how fairly risk is measured, and whether automation helps or harms patients. Karandeep Singh, M.D., M.M.S.C. explains that predictive AI can reflect historical, representation, measurement, learning, evaluation, and deployment bias, especially when models are trained on limited populations or use flawed proxies for illness and access to care. Singh also describes generative AI as a system trained first to predict text and then to follow instructions, with bias entering through training data, instruction tuning, prompts, and outside information sources. Alongside these risks, he highlights practical uses such as AI-assisted sepsis quality review and patient outreach workflows, while emphasizing governance, human oversight, disclosure, and careful measurement of whether these tools actually improve care. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41365]

Bias in health AI can shape who gets care, how fairly risk is measured, and whether automation helps or harms patients. Karandeep Singh, M.D., M.M.S.C. explains that predictive AI can reflect historical, representation, measurement, learning, evaluation, and deployment bias, especially when models are trained on limited populations or use flawed proxies for illness and access to care. Singh also describes generative AI as a system trained first to predict text and then to follow instructions, with bias entering through training data, instruction tuning, prompts, and outside information sources. Alongside these risks, he highlights practical uses such as AI-assisted sepsis quality review and patient outreach workflows, while emphasizing governance, human oversight, disclosure, and careful measurement of whether these tools actually improve care. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41365]

Bias in health AI can shape who gets care, how fairly risk is measured, and whether automation helps or harms patients. Karandeep Singh, M.D., M.M.S.C. explains that predictive AI can reflect historical, representation, measurement, learning, evaluation, and deployment bias, especially when models are trained on limited populations or use flawed proxies for illness and access to care. Singh also describes generative AI as a system trained first to predict text and then to follow instructions, with bias entering through training data, instruction tuning, prompts, and outside information sources. Alongside these risks, he highlights practical uses such as AI-assisted sepsis quality review and patient outreach workflows, while emphasizing governance, human oversight, disclosure, and careful measurement of whether these tools actually improve care. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41365]

Bias in health AI can shape who gets care, how fairly risk is measured, and whether automation helps or harms patients. Karandeep Singh, M.D., M.M.S.C. explains that predictive AI can reflect historical, representation, measurement, learning, evaluation, and deployment bias, especially when models are trained on limited populations or use flawed proxies for illness and access to care. Singh also describes generative AI as a system trained first to predict text and then to follow instructions, with bias entering through training data, instruction tuning, prompts, and outside information sources. Alongside these risks, he highlights practical uses such as AI-assisted sepsis quality review and patient outreach workflows, while emphasizing governance, human oversight, disclosure, and careful measurement of whether these tools actually improve care. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41365]

Bias in health AI can shape who gets care, how fairly risk is measured, and whether automation helps or harms patients. Karandeep Singh, M.D., M.M.S.C. explains that predictive AI can reflect historical, representation, measurement, learning, evaluation, and deployment bias, especially when models are trained on limited populations or use flawed proxies for illness and access to care. Singh also describes generative AI as a system trained first to predict text and then to follow instructions, with bias entering through training data, instruction tuning, prompts, and outside information sources. Alongside these risks, he highlights practical uses such as AI-assisted sepsis quality review and patient outreach workflows, while emphasizing governance, human oversight, disclosure, and careful measurement of whether these tools actually improve care. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41365]

AI in healthcare raises urgent questions about bias, privacy, and power. Safiya U. Noble, Ph.D., examines how AI systems can reproduce social and racial inequities when they rely on incomplete data, hidden assumptions, and proxies such as healthcare spending. Noble points to problems in search engines, image generation, facial recognition, and medical algorithms, including cases where systems mislabel darker skin, fail more often on Black women, or favor white patients over sicker Black patients. She also highlights the risks of turning sensitive public and patient data over to large technology companies. Rather than treating AI as a neutral solution, Noble emphasizes the need for human judgment, community participation, stronger data protections, and smaller expert models with local control so healthcare decisions better reflect people's real lives and social context. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41364]

AI in healthcare raises urgent questions about bias, privacy, and power. Safiya U. Noble, Ph.D., examines how AI systems can reproduce social and racial inequities when they rely on incomplete data, hidden assumptions, and proxies such as healthcare spending. Noble points to problems in search engines, image generation, facial recognition, and medical algorithms, including cases where systems mislabel darker skin, fail more often on Black women, or favor white patients over sicker Black patients. She also highlights the risks of turning sensitive public and patient data over to large technology companies. Rather than treating AI as a neutral solution, Noble emphasizes the need for human judgment, community participation, stronger data protections, and smaller expert models with local control so healthcare decisions better reflect people's real lives and social context. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41364]

AI in healthcare raises urgent questions about bias, privacy, and power. Safiya U. Noble, Ph.D., examines how AI systems can reproduce social and racial inequities when they rely on incomplete data, hidden assumptions, and proxies such as healthcare spending. Noble points to problems in search engines, image generation, facial recognition, and medical algorithms, including cases where systems mislabel darker skin, fail more often on Black women, or favor white patients over sicker Black patients. She also highlights the risks of turning sensitive public and patient data over to large technology companies. Rather than treating AI as a neutral solution, Noble emphasizes the need for human judgment, community participation, stronger data protections, and smaller expert models with local control so healthcare decisions better reflect people's real lives and social context. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41364]

AI in healthcare raises urgent questions about bias, privacy, and power. Safiya U. Noble, Ph.D., examines how AI systems can reproduce social and racial inequities when they rely on incomplete data, hidden assumptions, and proxies such as healthcare spending. Noble points to problems in search engines, image generation, facial recognition, and medical algorithms, including cases where systems mislabel darker skin, fail more often on Black women, or favor white patients over sicker Black patients. She also highlights the risks of turning sensitive public and patient data over to large technology companies. Rather than treating AI as a neutral solution, Noble emphasizes the need for human judgment, community participation, stronger data protections, and smaller expert models with local control so healthcare decisions better reflect people's real lives and social context. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41364]

AI in healthcare raises urgent questions about bias, privacy, and power. Safiya U. Noble, Ph.D., examines how AI systems can reproduce social and racial inequities when they rely on incomplete data, hidden assumptions, and proxies such as healthcare spending. Noble points to problems in search engines, image generation, facial recognition, and medical algorithms, including cases where systems mislabel darker skin, fail more often on Black women, or favor white patients over sicker Black patients. She also highlights the risks of turning sensitive public and patient data over to large technology companies. Rather than treating AI as a neutral solution, Noble emphasizes the need for human judgment, community participation, stronger data protections, and smaller expert models with local control so healthcare decisions better reflect people's real lives and social context. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41364]

AI in healthcare raises urgent questions about bias, privacy, and power. Safiya U. Noble, Ph.D., examines how AI systems can reproduce social and racial inequities when they rely on incomplete data, hidden assumptions, and proxies such as healthcare spending. Noble points to problems in search engines, image generation, facial recognition, and medical algorithms, including cases where systems mislabel darker skin, fail more often on Black women, or favor white patients over sicker Black patients. She also highlights the risks of turning sensitive public and patient data over to large technology companies. Rather than treating AI as a neutral solution, Noble emphasizes the need for human judgment, community participation, stronger data protections, and smaller expert models with local control so healthcare decisions better reflect people's real lives and social context. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41364]

AI in healthcare raises urgent questions about bias, privacy, and power. Safiya U. Noble, Ph.D., examines how AI systems can reproduce social and racial inequities when they rely on incomplete data, hidden assumptions, and proxies such as healthcare spending. Noble points to problems in search engines, image generation, facial recognition, and medical algorithms, including cases where systems mislabel darker skin, fail more often on Black women, or favor white patients over sicker Black patients. She also highlights the risks of turning sensitive public and patient data over to large technology companies. Rather than treating AI as a neutral solution, Noble emphasizes the need for human judgment, community participation, stronger data protections, and smaller expert models with local control so healthcare decisions better reflect people's real lives and social context. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 41364]

Cervical cancer remains a significant public health concern, but innovative approaches and community-based research are transforming prevention efforts, particularly immigrant communities. With over 600,000 new cases diagnosed annually, early detection and prevention strategies are crucial. However, accessibility and awareness gaps persist in immigrant communities due to language barriers, cultural stigma, and limited healthcare access. Community-based research plays a pivotal role in bridging these gaps. In engaging local populations through culturally sensitive outreach ensures that prevention strategies are accepted and effective. University of Miami Chief Health Equity Officer, Dr. Erin Kobetz, discusses how integrating cutting-edge technology with community engagement, moves us closer to reducing cervical cancer incidence and mortality rates, fostering a healthier future for immigrant populations. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40464]

Cervical cancer remains a significant public health concern, but innovative approaches and community-based research are transforming prevention efforts, particularly immigrant communities. With over 600,000 new cases diagnosed annually, early detection and prevention strategies are crucial. However, accessibility and awareness gaps persist in immigrant communities due to language barriers, cultural stigma, and limited healthcare access. Community-based research plays a pivotal role in bridging these gaps. In engaging local populations through culturally sensitive outreach ensures that prevention strategies are accepted and effective. University of Miami Chief Health Equity Officer, Dr. Erin Kobetz, discusses how integrating cutting-edge technology with community engagement, moves us closer to reducing cervical cancer incidence and mortality rates, fostering a healthier future for immigrant populations. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40464]

Cervical cancer remains a significant public health concern, but innovative approaches and community-based research are transforming prevention efforts, particularly immigrant communities. With over 600,000 new cases diagnosed annually, early detection and prevention strategies are crucial. However, accessibility and awareness gaps persist in immigrant communities due to language barriers, cultural stigma, and limited healthcare access. Community-based research plays a pivotal role in bridging these gaps. In engaging local populations through culturally sensitive outreach ensures that prevention strategies are accepted and effective. University of Miami Chief Health Equity Officer, Dr. Erin Kobetz, discusses how integrating cutting-edge technology with community engagement, moves us closer to reducing cervical cancer incidence and mortality rates, fostering a healthier future for immigrant populations. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40464]

Cervical cancer remains a significant public health concern, but innovative approaches and community-based research are transforming prevention efforts, particularly immigrant communities. With over 600,000 new cases diagnosed annually, early detection and prevention strategies are crucial. However, accessibility and awareness gaps persist in immigrant communities due to language barriers, cultural stigma, and limited healthcare access. Community-based research plays a pivotal role in bridging these gaps. In engaging local populations through culturally sensitive outreach ensures that prevention strategies are accepted and effective. University of Miami Chief Health Equity Officer, Dr. Erin Kobetz, discusses how integrating cutting-edge technology with community engagement, moves us closer to reducing cervical cancer incidence and mortality rates, fostering a healthier future for immigrant populations. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40464]

According to the World Health Organization (WHO) an estimated 1.3 billion people or 16% of the global population have a significant disability. A disability is a condition that can be mental or physical, and can affect a person's vision, movement, thinking, learning, communication, hearing, mental health or social relationships. However, not all disabilities are the same. Some disabilities are genetic, passed down from generation to generation, while others may have been caused by an incident out of the person's control. In this episode of Exploring Ethics, Professor Joseph Stramondo will discuss the narrative, identity and ethics of choosing disability. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40241]

According to the World Health Organization (WHO) an estimated 1.3 billion people or 16% of the global population have a significant disability. A disability is a condition that can be mental or physical, and can affect a person's vision, movement, thinking, learning, communication, hearing, mental health or social relationships. However, not all disabilities are the same. Some disabilities are genetic, passed down from generation to generation, while others may have been caused by an incident out of the person's control. In this episode of Exploring Ethics, Professor Joseph Stramondo will discuss the narrative, identity and ethics of choosing disability. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40241]

According to the World Health Organization (WHO) an estimated 1.3 billion people or 16% of the global population have a significant disability. A disability is a condition that can be mental or physical, and can affect a person's vision, movement, thinking, learning, communication, hearing, mental health or social relationships. However, not all disabilities are the same. Some disabilities are genetic, passed down from generation to generation, while others may have been caused by an incident out of the person's control. In this episode of Exploring Ethics, Professor Joseph Stramondo will discuss the narrative, identity and ethics of choosing disability. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40241]

According to the World Health Organization (WHO) an estimated 1.3 billion people or 16% of the global population have a significant disability. A disability is a condition that can be mental or physical, and can affect a person's vision, movement, thinking, learning, communication, hearing, mental health or social relationships. However, not all disabilities are the same. Some disabilities are genetic, passed down from generation to generation, while others may have been caused by an incident out of the person's control. In this episode of Exploring Ethics, Professor Joseph Stramondo will discuss the narrative, identity and ethics of choosing disability. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40241]

According to the World Health Organization (WHO) an estimated 1.3 billion people or 16% of the global population have a significant disability. A disability is a condition that can be mental or physical, and can affect a person's vision, movement, thinking, learning, communication, hearing, mental health or social relationships. However, not all disabilities are the same. Some disabilities are genetic, passed down from generation to generation, while others may have been caused by an incident out of the person's control. In this episode of Exploring Ethics, Professor Joseph Stramondo will discuss the narrative, identity and ethics of choosing disability. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40241]

According to the World Health Organization (WHO) an estimated 1.3 billion people or 16% of the global population have a significant disability. A disability is a condition that can be mental or physical, and can affect a person's vision, movement, thinking, learning, communication, hearing, mental health or social relationships. However, not all disabilities are the same. Some disabilities are genetic, passed down from generation to generation, while others may have been caused by an incident out of the person's control. In this episode of Exploring Ethics, Professor Joseph Stramondo will discuss the narrative, identity and ethics of choosing disability. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40241]

According to the World Health Organization (WHO) an estimated 1.3 billion people or 16% of the global population have a significant disability. A disability is a condition that can be mental or physical, and can affect a person's vision, movement, thinking, learning, communication, hearing, mental health or social relationships. However, not all disabilities are the same. Some disabilities are genetic, passed down from generation to generation, while others may have been caused by an incident out of the person's control. In this episode of Exploring Ethics, Professor Joseph Stramondo will discuss the narrative, identity and ethics of choosing disability. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 40241]

Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]

Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]

Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]

Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]

Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]

Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]

Almost every child born in the United States undergoes state-mandated newborn screening within the first 48 hours of life. The blood collected from a "heel stick" helps test for 80 different serious but treatable genetic disorders. These disorders can be either genetic (passed down in families) or congenital (present at birth). But... what if we could go further? What if we could test a newborn's entire genetic sequence? Pediatric geneticist Ingrid Holm discusses the risks, benefits, costs and ethics of genomic sequencing in newborns. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 39266]

The Science & Technology Ethics Center (STEC) is proud to present a series of lectures and a panel discussion that explores the intersection of genomics, medical ethics, and patient rights. This thought-provoking session delves into the ethical considerations surrounding genetic testing, data privacy, and informed consent. It examines the challenges and opportunities presented by advancements in genomics and how they impact patient care. The panel will discuss the importance of advocating for patients' rights, ensuring equitable access to genetic information, and fostering a patient-centered approach in genomic medicine. Throughout this presentation, you will grasp a deeper understanding of the ethical complexities in genomics and the critical role of patient advocacy in shaping responsible and inclusive genomic practices. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 38940]

The Science & Technology Ethics Center (STEC) is proud to present a series of lectures and a panel discussion that explores the intersection of genomics, medical ethics, and patient rights. This thought-provoking session delves into the ethical considerations surrounding genetic testing, data privacy, and informed consent. It examines the challenges and opportunities presented by advancements in genomics and how they impact patient care. The panel will discuss the importance of advocating for patients' rights, ensuring equitable access to genetic information, and fostering a patient-centered approach in genomic medicine. Throughout this presentation, you will grasp a deeper understanding of the ethical complexities in genomics and the critical role of patient advocacy in shaping responsible and inclusive genomic practices. Series: "Exploring Ethics" [Health and Medicine] [Humanities] [Science] [Show ID: 38940]