Podcast appearances and mentions of mike kuniavsky

We are living in a world where data has been used to influence almost every aspect of human life. Data and digitalization has changed the way we work with products and the way we produce products. We talked to an expert, Mike Kuniavsky a UX pioneer and lead researcher at Accenture, who works on applications that facilitate digital transformation in manufacturing.

Dr. Wendy Ju returns to the RoboPsych Podcast to discuss autonomous objects and their social ecosystems. Show Notes Ep. 61 - Dr. Wendy Ju on Autonomous Ecosystems Dr. Wendy Ju returns to the RoboPsych Podcast to speak with Carla Diana and Tom about designing social objects and their ecosystems. Wendy’s new academic position at Cornell Tech Wendy's book: The Design of Implicit Interactions Wendy's previous RoboPsych Podcast appearance Hugh Dubberly’s Ecosystems Presentation Dubberly’s Ecosytem Diagram Black Mirror bees episode Daniel Suarez, Kill Decision Ken Goldberg's work at UC Berkeley The coming “service avatars” from Mike Kuniavsky’s book, Smart Things Clayton Christensen's "jobs to be done" model Connect with us via email Connect with us via Twitter

Automated systems increasingly try to predict our behavior and needs; what do we do until they get good at it? The first talk in a new series from the team at PARC, 
the venerable research lab, UX designer and author Mike Kuniavsky takes a clear-eyed look at the benefits and risks of a future interwoven with algorithms. From May 02016.

It seems like every object in your home is getting "smart" -- and talking to the internet. What does it mean when your home is watching you? Leah Hitchings talks to Mike Kuniavsky.

The O'Reilly Design Podcast: Designing for IoT, service design, and predictive analytics.This week's episode of the Design Podcast features a conversation I had with Mike Kuniavsky last fall. Kuniavsky is a user experience designer, researcher, and author currently working at Parc. He's also a speaker at the upcoming O'Reilly online conference "Designing for the Internet of Things," September 15, 2016. In our chat, Kuniavsky talks about designing for the IoT, service design, and the mindshift needed to design for ecosystems.Here are some highlights: Every new medium is the old medium I was reading this book that was published by Philips Design on their Ambient Intelligence project. They actually thought through the entire Internet of Things thing about 15 years ago, and then they couldn't make any money on it, and all those people went away. Now it's actually a real thing. They left some really good documentation. I was reading the Philips Design book, and they had a very interesting point from mine and probably one of Tim O'Reilly's favorite theorists, Marshall McLuhan. McLuhan essentially said that the content of every new medium is the old medium. Every new medium subsumes the old medium of the content until you actually figure out what the new medium is. When television came about, the stuff that was initially on television was essentially radio, until they actually figured out what television was good for. When radio came out, it was people reading the newspaper on the radio, until they figured out what radio was good for. It's like that going all the way back. Right now, in the Internet of Things, we're in this place where the content of the Internet of Things is the pre-Internet of Things world. It's all of the things that are either currently not connected, which are everyday objects, or it's the electronic things which are being shoehorned. What we're trying to do is we're trying to get over that hump and trying to figure out what are the natively interesting qualities of the Internet of Things that make it really different than home automation, which has been around for 30 years and has been an abject failure on every front, or simply connecting appliances to the Internet. On UX design and service design We're really looking hard at service design as a model. The funny thing is, service design isn't even a mature thing. It's not like we can import an entire discipline. Service design was a just a couple puzzle pieces just a couple years ago. It wasn't a finished product as it is. We're trying to take those puzzle pieces and we're trying to say, OK, now what happens when all of these different components of a service, these different things that service design is looking at—they describe front of house, back of house, different kinds of players and actors within that space—what if we replaced some of those with devices? What if we replaced some of those things with sensors and actuators? What happens to the service in that situation? That's how we're trying to envision an entire ecosystem without actually having any of the pieces of it in place. There's this slippery slope between service design and UX design. I think UX design is more digital, and service design allows itself to include things like a poster that's on a wall in a lobby, or a little card that gets mailed to people, or a human being that they can talk to, and what does that human being say and under what circumstances do they say it. Service design takes a slightly broader view, whereas UX design is still—and I think usefully—focused largely on the digital aspect of it. Pattern matching and predictive analytics I'm interested in, broadly speaking, predictive analytics—I should say, machine learning, statistical modeling, but specifically in predictive statistical modeling, predictive machine learning. I think that really that is the new superpower. That is literally looking into the future with some degree of confidence. In a place where you would never normally be able to look into the future, like identifying how often I pick up my cup of coffee. My cup of coffee would never have been able to tell me that before. Now it can. Again, to some degree, and that's really interesting. That's really a different relationship. That's to me a big shift in our relationship to our everyday objects and their relationship to how they can—as per my earlier point—how they can make our lives better. That's why I'm really interested in the predictive stuff right now. We as humans have no idea how limited our sensors are, our own personal ability to sense the world. We're really good at pattern matching in certain ways, and we're really not very good in many other ways, and we've never really had a very good way to compensate for that. Now, to some extent, we do, and that's really interesting.

The O'Reilly Design Podcast: Designing for IoT, service design, and predictive analytics.This week's episode of the Design Podcast features a conversation I had with Mike Kuniavsky last fall. Kuniavsky is a user experience designer, researcher, and author currently working at Parc. He's also a speaker at the upcoming O'Reilly online conference "Designing for the Internet of Things," September 15, 2016. In our chat, Kuniavsky talks about designing for the IoT, service design, and the mindshift needed to design for ecosystems.Here are some highlights: Every new medium is the old medium I was reading this book that was published by Philips Design on their Ambient Intelligence project. They actually thought through the entire Internet of Things thing about 15 years ago, and then they couldn't make any money on it, and all those people went away. Now it's actually a real thing. They left some really good documentation. I was reading the Philips Design book, and they had a very interesting point from mine and probably one of Tim O'Reilly's favorite theorists, Marshall McLuhan. McLuhan essentially said that the content of every new medium is the old medium. Every new medium subsumes the old medium of the content until you actually figure out what the new medium is. When television came about, the stuff that was initially on television was essentially radio, until they actually figured out what television was good for. When radio came out, it was people reading the newspaper on the radio, until they figured out what radio was good for. It's like that going all the way back. Right now, in the Internet of Things, we're in this place where the content of the Internet of Things is the pre-Internet of Things world. It's all of the things that are either currently not connected, which are everyday objects, or it's the electronic things which are being shoehorned. What we're trying to do is we're trying to get over that hump and trying to figure out what are the natively interesting qualities of the Internet of Things that make it really different than home automation, which has been around for 30 years and has been an abject failure on every front, or simply connecting appliances to the Internet. On UX design and service design We're really looking hard at service design as a model. The funny thing is, service design isn't even a mature thing. It's not like we can import an entire discipline. Service design was a just a couple puzzle pieces just a couple years ago. It wasn't a finished product as it is. We're trying to take those puzzle pieces and we're trying to say, OK, now what happens when all of these different components of a service, these different things that service design is looking at—they describe front of house, back of house, different kinds of players and actors within that space—what if we replaced some of those with devices? What if we replaced some of those things with sensors and actuators? What happens to the service in that situation? That's how we're trying to envision an entire ecosystem without actually having any of the pieces of it in place. There's this slippery slope between service design and UX design. I think UX design is more digital, and service design allows itself to include things like a poster that's on a wall in a lobby, or a little card that gets mailed to people, or a human being that they can talk to, and what does that human being say and under what circumstances do they say it. Service design takes a slightly broader view, whereas UX design is still—and I think usefully—focused largely on the digital aspect of it. Pattern matching and predictive analytics I'm interested in, broadly speaking, predictive analytics—I should say, machine learning, statistical modeling, but specifically in predictive statistical modeling, predictive machine learning. I think that really that is the new superpower. That is literally looking into the future with some degree of confidence. In a place where you would never normally be able to look into the future, like identifying how often I pick up my cup of coffee. My cup of coffee would never have been able to tell me that before. Now it can. Again, to some degree, and that's really interesting. That's really a different relationship. That's to me a big shift in our relationship to our everyday objects and their relationship to how they can—as per my earlier point—how they can make our lives better. That's why I'm really interested in the predictive stuff right now. We as humans have no idea how limited our sensors are, our own personal ability to sense the world. We're really good at pattern matching in certain ways, and we're really not very good in many other ways, and we've never really had a very good way to compensate for that. Now, to some extent, we do, and that's really interesting.

The O'Reilly Radar Podcast: The Internet of Things ecosystem, predictive machine learning superpowers, and deep-seated love for appliances and furniture.O'Reilly's Mary Treseler chats with Mike Kuniavsky, a principal scientist in the Innovation Services Group at PARC. Kuniavsky talks about designing for the Internet of Things ecosystem and why the most interesting thing about the IoT isn't the "things" but the sensors. He also talks about his deep-seated love for appliances and furniture, and how intelligence will affect those industries.Here are some highlights from their conversation: Wearables as a class is really weird. It describes where the thing is, not what it is. It's like referring to kitchenables. 'Oh, I'm making a kitchenable.' What does that mean? What does it do for you? There's this slippery slope between service design and UX design. I think UX design is more digital and service design allows itself to include things like a poster that's on a wall in a lobby, or a little card that gets mailed to people, or a human being that they can talk to. ... Service design takes a slightly broader view, whereas UX design is — and I think usefully — still focused largely on the digital aspect of it. I have a deep, long-seated love for appliances and for furniture because they are the tools of our everyday lives, and if anything becomes the content of this new Internet of Things thing first, it's them. What's interesting to me is that they have an already existing set of affordances, which means people know what to do with them and how to do it. They have a set of expectations, and how this set of things can now utilize this amazing set of sensing and actuation and meaning-making and statistical analysis technologies that are available up in the cloud, to do the things that they have always done, but do it better. I'm really interested in how intelligence affects the appliance industry. There are ways to spin the IoT as an Orwellian cyberpunk anti-future, things that spy on you from every corner. They will do that, but I'm not that interested in that aspect of it. I think, actually, that humans are pretty good at negotiating their technologies, even though it sometimes takes a while. The thing that is happening right now is that by connecting all of these different sensing devices, you turn that sensor input from this very simple gas gauge-like thing that might be useful to somebody in one situation, to a sequence of knowledge that can be modeled and can be much more broadly useful, especially when you have many, many different sources of information that are coming together. That, to me, is a tectonic shift because now you can essentially reason on a giant quantity of information, but the end points that are collecting this information or acting on it can be incredibly small and thin. You get the full power of these enormous artificial intelligence systems, machine learning systems, but without any of the computational overhead or cost, locally. That is really powerful. Every single little thing becomes as powerful as the most powerful computer on earth, and can then anticipate, compensate, and work together with other things in ways that were inconceivable before this shift. What I'm interested in, broadly speaking, is predictive analytics — I should say, machine learning, statistical modeling, but specifically in predictive statistical modeling, predictive machine learning. I think, really, that is the new super power. Subscribe to the O'Reilly Radar Podcast: Stitcher, TuneIn, iTunes, SoundCloud, RSS

The O'Reilly Radar Podcast: The Internet of Things ecosystem, predictive machine learning superpowers, and deep-seated love for appliances and furniture.O'Reilly's Mary Treseler chats with Mike Kuniavsky, a principal scientist in the Innovation Services Group at PARC. Kuniavsky talks about designing for the Internet of Things ecosystem and why the most interesting thing about the IoT isn't the "things" but the sensors. He also talks about his deep-seated love for appliances and furniture, and how intelligence will affect those industries.Here are some highlights from their conversation: Wearables as a class is really weird. It describes where the thing is, not what it is. It's like referring to kitchenables. 'Oh, I'm making a kitchenable.' What does that mean? What does it do for you? There's this slippery slope between service design and UX design. I think UX design is more digital and service design allows itself to include things like a poster that's on a wall in a lobby, or a little card that gets mailed to people, or a human being that they can talk to. ... Service design takes a slightly broader view, whereas UX design is — and I think usefully — still focused largely on the digital aspect of it. I have a deep, long-seated love for appliances and for furniture because they are the tools of our everyday lives, and if anything becomes the content of this new Internet of Things thing first, it's them. What's interesting to me is that they have an already existing set of affordances, which means people know what to do with them and how to do it. They have a set of expectations, and how this set of things can now utilize this amazing set of sensing and actuation and meaning-making and statistical analysis technologies that are available up in the cloud, to do the things that they have always done, but do it better. I'm really interested in how intelligence affects the appliance industry. There are ways to spin the IoT as an Orwellian cyberpunk anti-future, things that spy on you from every corner. They will do that, but I'm not that interested in that aspect of it. I think, actually, that humans are pretty good at negotiating their technologies, even though it sometimes takes a while. The thing that is happening right now is that by connecting all of these different sensing devices, you turn that sensor input from this very simple gas gauge-like thing that might be useful to somebody in one situation, to a sequence of knowledge that can be modeled and can be much more broadly useful, especially when you have many, many different sources of information that are coming together. That, to me, is a tectonic shift because now you can essentially reason on a giant quantity of information, but the end points that are collecting this information or acting on it can be incredibly small and thin. You get the full power of these enormous artificial intelligence systems, machine learning systems, but without any of the computational overhead or cost, locally. That is really powerful. Every single little thing becomes as powerful as the most powerful computer on earth, and can then anticipate, compensate, and work together with other things in ways that were inconceivable before this shift. What I'm interested in, broadly speaking, is predictive analytics — I should say, machine learning, statistical modeling, but specifically in predictive statistical modeling, predictive machine learning. I think, really, that is the new super power. Subscribe to the O'Reilly Radar Podcast: Stitcher, TuneIn, iTunes, SoundCloud, RSS

Let’s start with the assumption that computing and networking are as cheap to incorporate into product designs as plastic and aluminum. Anything can tweet, everything knows about everything. The cloud extends from smart speed bumps to exurban data systems, passing through us in the process. We’re basically there technologically today, and over the next [pick a date range] years, we’ll be there distribution-wise. Here’s the issue: now that we have this power what do we do with it? Yes we can now watch the latest movies on our phones while ignoring the rest of the world (if you believe telco ads) and know more about peripheral acquaintances than you ever wanted. But, really, is that it? Is it Angry Birds all the way down? Of course not. Every technology’s most profound social and cultural changes are invisible at the outset. Cheap information processing and networking technology is a brand new phenomenon, culturally speaking, and quickly changing the world in fundamental ways. Designers align the capabilities of a technology with people’s lives, so it is designers who have the power and responsibility to think about what this means. This talk will discuss where ubiquitous computing is today, some changes we can already see happening, and how we can begin to think about the implications of these technologies for design, for business and for the world at large. Mike Kuniavsky is a designer, writer, researcher, consultant and entrepreneur focused on people’s relationship to digital technology. He cofounded Adaptive Path, a San Francisco design consulting firm, and ThingM, a ubiquitous computing design studio and micro-manufacturer. He is the author of ‘Observing the User Experience,’ a popular textbook of user research methods, and ‘Smart Things: ubiquitous computing user experience design,’ a guide to the user-centered design of digital products. Follow Mike on Twitter: @mikekuniavsky Licensed as Creative Commons Attribution NonCommercial ShareAlike 3.0 Unported license (http://creativecommons.org/licenses/by-nc-sa/3.0/).

I spoke to Jared Braiterman, from jaredRESEARCH (www.jaredresearch.com). Jared has done ethnographic research many organisations.I asked him what's meant by ethongraphic research, and how it's applied.The Mobile China work Jared refers to is avaialble on his site (www.jaredresearch.com/mobilechina).The book on user research that he mentions is Mike Kuniavsky's Observing the User Experience (www.amazon.com/exec/obidos/ASIN/1558609237/informdesign) - a book which I coincidentally described on my infodesign.com.au website as "the only 'must-read' book in the field published in 2003". (References to books on this webiste are links to Amazon.com - we earn a small commission on any purchases you make on following such links).