The Dotted Line World: Shadows, Subscriptions, Services

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My presentation to ETech 2009 that links the capabilities of ubiquitous computing and intersects it with service design to come up with a justification for creating subscription-based services out of (certain) everyday objects. Get a PDF at: http://www.orangecone.com/tm_etech_2009_0.1.pdf

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Mike Kuniavsky O’Reilly Emerging Technology Conference March 10, 2009 The dotted-line world shadows, services, subscriptions

Mike Kuniavsky [email_address]

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The software running much of our world today, from consumer apps to industrial infrastructures, is increasingly built on systems that learn and try to predict the future, our future. They’re increasingly sophisticated and profoundly different than technologies we’ve ever lived with before, and they're not particularly good in their predictions. This talk is about what we—the intended beneficiaries of these products and services—will do, and how our lives will change, as the algorithms that are supposed to understand us are on what is likely a slow learning curve.

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This talk explores the potential, and the challenge of designing predictive artificial intelligence-enabled, user experiences for the Internet of Things. The Internet of Things promises that by analyzing data from many IoT devices our experience of the world becomes better and more efficient. The environment predicts our behavior, anticipates problems, and intercepts them before they occur. However, we don’t have good examples for designing user experiences of predictive AI. This talk gives examples of several different systems, lists UX challenges to creating behavioral systems, and potential approaches to addressing those challenges.

The UX of Predictive AI in the IoT (Rosenfeld To Be Designed)

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One of the biggest challenges in designing novel connected hardware is knowing whether the final experience will be successful, and minimizing the investment in developing the wrong product. Building fully-functional hardware to evaluate an idea is a significant investment, and slow. We believe it’s possible to manage risk and still explore big, potentially transformative, ideas for products and services. Our approach looks at novel digital product systems (broadly in the Internet of Things, but not exclusively) with the explicit goal of building the minimum amount of technology as is necessary to answer questions about the value and impact of a new product or service.

Hardware without Hardware, minimal explorations of novel product ideas (O'Rei...

Hardware without Hardware, minimal explorations of novel product ideas (O'Rei...

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The software running much of our world today, from consumer apps to industrial infrastructures, is increasingly built on systems that learn and try to predict the future, our future. They’re increasingly sophisticated and profoundly different than technologies we’ve ever lived with before, and they're not particularly good in their predictions. This talk is about what we—the intended beneficiaries of these products and services—will do, and how our lives will change, as the algorithms that are supposed to understand us are on what is likely a slow learning curve.

Our Future in Algorithm Farming (Long Now Interval 5/17/16)

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This presentation identifies challenges to the user experience design of smart devices (such as the Nest Thermostat, the Amazon Echo, the Edyn water monitor, etc.) that use machine learning to anticipate the needs of people and environments and adapt in response, and point to some potential design patterns to help address those challenges. The Internet of Things promises that by analyzing data from many sensors over time our experience of the world becomes better and more efficient. Our environment can predict our behavior, anticipate problems and needs, and maximize the chances of a desirable end result. Though this notion of effortless automation is seductive (espresso machines that start just as you’re thinking it’s a good time for coffee; office lights that dim when it’s sunny and power is cheap), we don’t have good examples for designing user experiences of predictive systems. As a result, today it’s much easier to create such systems that are confusing, unpredictable and uncontrollable.

The UX of Predictive Behavior for the IoT (2016: O'Reilly Designing for the IOT)

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The UX of Predictive Behavior for the IoT (2016: O'Reilly Designing for the IOT)

New product ecosystem_2013_0.1

New product ecosystem_2013_0.1

New product ecosystem_2013_0.1

Picture a world where Amazon.com is a factory. Products are made as needed, based on direct input from users to designers and developers. Consumption directly drives production, and data informs design. If we weren't talking about physical products, this would sound a lot like Web/app interaction design, but the worlds of making atoms and bits are quickly colliding, and the implications are profound. By mapping what we have learned creating analytics-driven digital design to the physical world, we can change how everything is made, for the better.

How Web Design will reinvent manufacturing

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Video: youtube.com/watch?v=eN05B7dDsFY Picture a world where Amazon.com is a factory. Products are made in small quantities, as needed, based on direct input from users to designers and developers. Consumption directly drives product creation, and data informs design. Consumer products are made locally, with local materials and workers, while at the same time using design and engineering talent from anywhere on earth. It simultaneously looks exactly like our world, but is totally different. It’s almost here, and you know more about it than anyone else.

Designers and-geeks 2012-presentation_0.2

Designers and-geeks 2012-presentation_0.2

Designers and-geeks 2012-presentation_0.2

(SEE SLIDE NOTES FOR COMPLETE TRANSCRIPT) Imagine a world 8 years from now where instead of a warehouse, Amazon is a factory. Products are made in small quantities, as needed, based on direct input from users to designers and developers. In this world design directly drives product creation, and data informs design. Consumer products are made locally, with local materials and workers, while at the same time being able to use design and engineering talent from anywhere on earth. It simultaneously looks exactly like our world, but is totally different.

The New Product Development Ecosystem

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(look at slide notes for full talk transcript) Imagine a world 8 years from now where instead of a warehouse, Amazon is a factory, where products are made in small quantities based on direct input from users to designers. In this world design directly drives product creation, and where data informs design. (special thanks to Joel Truher for many of the ideas and Alex Chaffee for the Amazon example)

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(FULL TRANSCRIPT IN SLIDE NOTES) The technologies underlying most current Internet of Things visions are not particularly revolutionary. That of course doesn't mean that the visions are not compelling, just that the challenges in creating these visions have little to do with building new technologies. The challenge is to identify what people want and need, and how -- or if -- automatic identification, distributed processing, and pervasive networking can help address those needs and desires. We need to think about how we’re going to create the Google of Things, the Facebook of Things, the Foursquare of Things, the PayPal of Things, the Farmville of Things. It's not about the infrastructure, it's about the applications, and the applications are about people.

The Internet of People: Integrating IoT Technologies is Not a Technical Probl...

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(Look at slide notes for full transcript) How can digital hardware startups be more like Github and less like General Motors? The pieces that fell together to create the ecosystem of tools and business models that lead to the creation of Eric Ries' Lean Startup model for online products are now falling into place in the hardware sector. We're about to see an explosion of hardware startups based on the same ideas. Technological, social and financial changes are coming together to allow entrepreneurs to rapidly iterate new digital devices focused on customer needs. These core elements create a new way to conceptualize the development of digital hardware products. This talk will examine the components that are creating this change and suggest some directions we can expect things to go, and how we can take advantage of it.

Lean hardware startups: elements of a ubiquitous computing innovation ecosystem

Lean hardware startups: elements of a ubiquitous computing innovation ecosystem

Lean hardware startups: elements of a ubiquitous computing innovation ecosystem

Products are Services, how ubiquitous computing changes design

Products are Services, how ubiquitous computing changes design

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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.

Unintended Consequences: design [in|for|and] the age of ubiquitous computing

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In this workshop Mike Kuniavsky, author of "Smart Things: ubiquitous computing user experience design" introduces concepts of user experience design for the post-PC/post-phone world. How do you design experiences that transcend a single device, or even a family of devices? How do you create experiences that exist simultaneously in your hand and in the cloud? Using plentiful examples drawn from cutting edge products and the history of technology, the workshop describes underlying trends, shows the latest developments and asks broader questions. This presentation introduces fundamental concepts of ubiquitous computing user experience design and specific techniques for designing services and interfaces. Topics include: - Design for multiple scales - Design for services used by multiple devices - Rethinking everyday objects and experiences - Understanding use context

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Get notes and the full transcript here: http://orangecone.com/archives/2011/05/somatic_data_pe.html Augmented reality is the extension of our senses into the realm of information shadows where physical objects have data representations that can be manipulated digitally as we manipulate objects physically. To me this goes further than putting a layer of information over the world, like a veil. It’s about enhancing the direct experience of the world, not to replace it, and to do it in a way that’s not about being completely in the background, like ambient data weather, or about taking over our attention. I’m advocating a change in language away from “augmented reality” to something that’s more representative of the whole experience of data in the environment. I’m calling it “Somatic Data Perception.”

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