Licklider in the making.
“This essay will explore some of the possibilities to rethink how humans and ‘intelligent’ machines interact today. The focus is on practical application – how can technology that exists today be leveraged creatively to make applications that are vastly more powerful and useful?”
Jessy Lin a.k.a. /jessylin | @realJessyLin ★
Ethics and Tech, a much debated combination.
“Beyond simply understanding the ethical issues that technology may raise, using technology responsibly requires organizations to apply a consistent method for identifying ethical courses of action.”
Catherine Bannister, Brenna Sniderman and Natasha Buckley ~ Deloitte Insights ★
Taking the human perspective in all technology achievements.
“Our people-centered design principles support the goal of providing and informing with data to allow people more opportunities in their work. In our experience, there are three key principles organizations need to hold up as pillars for any AI implementation: transparency, explainability, and reversibility. (…) There are three methods that companies can take to put these principles into action in their AI projects. These methods aim to reduce the risk of introducing poorly tuned AI systems and inaccurate or biased decision-making in pilots and implementations.”
David A. Bray et al. ~ MIT Sloan Management Review ★
Abstraction going meta.
“Meta-designing in this sense could be the next grand frontier of design practice, imbued with a strategic sense for humanism and intellectualism, which are necessary elements if we are to make design thinking + customer experience + user experience into more than a checklist of ingredients for a successful business. What will you do to advance this approach? It’s admittedly aspirational and fuzzy to tackle, but that doesn’t mean it’s not feasible or valuable.”
Uday Gajendar ~ ACM Interactions Volume XXVI.4 ★ courtesy of @riander
Always keep your principles.
“Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether these principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principles for ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice. On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts.”
Luciano Floridi and Josh Cowls ~ Harvard Data Science Review Issue 1 ★
Mentals models for all objects, even smart onces.
“Users of Siri, Alexa, and Google Assistant conceptualize them in one of 3 ways: an interface, a personal assistant, or a brain. Frequent users are less likely to push the interaction limits of these AI systems than new users.”
Raluca Budiu a.k.a. /ralucabudiu | @rbudiu ~ Nielsen Norman Group ★
Structure as the backbone of all conversations.
“Design practices that build bridges between user needs and technology requirements to meet business goals are crucial to making this vision a reality. Information architects, content strategists, developers, and experience designers all have a role to play in designing and delivering effective structured content solutions. Practitioners from across the design community have shared a wealth of resources in recent years on creating content systems that work for humans and algorithms alike.”
Andy Fitzgerald a.k.a. /andyfitzgerald | @andybywire ~ A List Apart ★
UX still remains relevant for any type of technology.
“If you are a designer looking to pave ways into the Blockchain technology and applications, it is never late to start. From my personal experience I would suggest to kick start your learning by getting acquainted with the three core components the technology is composed of being: distributed ledger technology (DLT), decentralized (or better, distributed) networks, and public-key cryptography.”
Jo Mercieca a.k.a. /jomercieca ~ Medium ★
Machines have feelings too.
“The IoT network can range from a smart home thermostat to medical devices that send patient data from an ambulance to the emergency room to a tractor gathering crop yield data from different areas of the field, and so much more. IoT products are in their infancy—well, maybe the toddler stage—and spreading in different industries (for example, UX will play a huge role in smart factories of the new Industry 4.0) And, as mentioned, UX is not limited to the outside of the device; it is in all areas of the device. Let’s make it count.”
Kianosh Pourian a.k.a. /kianoshpourian | @kianoshp ~ The Magazine of the User Experience Professionals Association ★
Deep understanding through some deep human learning.
“(…) UX designers and researchers need to be the co-creators of intelligent solutions to make sure AI technology works for people and society. More than ever, we must consider the capabilities and roles of human versus machine. When should machines make decisions and take action, and when should they augment or support people making decisions? How will these AI solutions make people feel? Do people feel like the solution is trustable, easy, and fun, or do they feel frustrated or even potentially endangered? UX professionals must act to learn, share, collaborate, and participate in cognitive technology research and development both at a strategic level and as a part of the product development process. We should also get involved in governance. We encourage UX professionals to join us and continue this dialog so that we can help create a better world.”
Cindy Lu a.k.a. and Alice Preston ~ UXPA magazine ★
Take it away!
“In this Insight Report, we’ll look at the factors which make UX for IoT particularly challenging. We’ll discuss how technical architecture and business models shape UX, and how IoT blurs the line between product and service experiences. We’ll look at the need to give users transparency around how complex systems work and share data, in particular in relation to GDPR. And we’ll set out the challenges of designing distributed user experiences across multiple UIs, and show how some companies are tackling the challenges of designing for both hardware and software in parallel.”
Claire Rowland a.k.a. /clairerowland | @clurr ~ IoT.uk ★
All technology gets a business application, one way or another.
“Although we are now relatively more familiar with augmented reality (AR) and virtual reality (VR), it is still quite a challenge to understand how to design effective brand experiences with them. You don’t want to invest in technology for it only to be a gimmick that does not significantly bolster your branding activities. And yet, there is the pressure to not get left behind while everyone else seems to be using cutting edge technology. Most major brands today—The New York Times and Mercedes, as two examples—have used augmented reality and virtual reality experiences to engage customers. How can your brand leverage AR/VR for best results?”
Babar Suleman a.k.a. /babarsuleman | @B_Su ~ Boxes and Arrows ★
Design for trust is the best design principle for IoT.
“The internet of things requires a different, expanded kind of design. It’s all about paying attention to several principles (and thousands of trifles).”
Dieter Petereit a.k.a. @dpetereit ~ noupe ★
Some deep thinking going on here. Be aware of the algo’s.
“This paper explores pragmatic approaches that might be employed to document the behavior of large, complex socio-technical systems (often today shorthanded as ‘algorithms’) that centrally involve some mixture of personalization, opaque rules, and machine learning components. Thinking rooted in traditional archival methodology (…) has been a total failure for many reasons, and we must address this problem. (…) It may well be that we see the emergence of a new group of creators of documentation, perhaps predominantly social scientists and humanists, taking the front lines in dealing with the Age of Algorithms, with their materials then destined for our memory organizations to be cared for into the future.”
Clifford Lynch ~ First Monday (22.12) ★
Digital designers really need to understand the underlying technologies. As always.
“Designers will need to ramp up on new design skills to make a smooth career transition to the design of immersive experiences when the inevitable wave of new VR and AR design projects hits the pipeline.”
Pabini Gabriel-Petit a.k.a. /pabini | @pabini ~ UXmatters ★
Giving consent respects humanity.
“Having strong, clear apparency to real semantic and pragmatic transparency as a backbone to meaningful consent will also help clarify risks within the data flows of large-scale, heterogeneous IoT infrastructures, from homes to cities to national infrastructure. Overall, by improving apparency to s/p transparency, we make meaningful consent possible. When meaningful consent becomes part of a system, entirely new kinds of services may be imagined that create value based on visible, shareable data. We can also make services more resilient. To get there, we need the design acumen of HCI researchers and UX practitioners to help design, deliver, and evaluate apparency interactions at IoT scale.”
M.C. Schraefer et al. ~ Interaction magazine Volume XXIV.6 ★
UX designers have to become computational thinkers as well.
“UX designers have years of experience in creating the best design elements, and most of the time the results of which carries a UX designer to be largely positive in terms of increased interaction and achieving the bottom line. However, there is a gap between the positive change brought by UX designers and what should be the utopian final script interaction. The results may be better, but the UX design in this world cannot guarantee that every user will like everything on the website or application. There will always be some people who adore in other parts of the conversion path with a focus on UX. The main reason for this is not enough customization in the UX design to optimize the interests of each user separately. Each user is different and needs a different treatment. UX design works on a global level but there is still a gap and potential that can be achieved and brands help to invest more in significant UX design.”
Melissa Crooks a.k.a. /msmelissacrooks ~ home toys ★
If you can scale, you can deliver at any level of abstraction.
“HCI has had a massive impact on the world through streamlining and enabling millions of interfaces on billions of devices. As we face the potential of a tenfold increase in the number of devices and their complexity, it is worth asking about the relationship between HCI and scale. Do the tools and research methods we currently deploy scale to the millions of future interfaces and systems, used by billions of people, across multiple contexts? In this article we outline how we see the challenge of scale. By scale we mean how technology is used in large networks of interconnected systems, with billions of users, across diverse contexts. How can we understand and design for this complex of interconnected uses? Put simply, does HCI scale?”
Barry Brown, Susanne Bødker, and Kristina Höök ~ Interactions XXIV.5 ★
New technology waves are ahead of us.
“Machine learning is the science of helping computers discover patterns and relationships in data instead of being manually programmed. It’s a powerful tool for creating personalized and dynamic experiences, and it’s already driving everything from Netflix recommendations to autonomous cars. But as more and more experiences are built with ML, it’s clear that UXers still have a lot to learn about how to make users feel in control of the technology, and not the other way round.”
Jess Holbrook a.k.a. /jessholbrook courtesy of O’Reilly Design ★
AI is eating the HCI world.
“There has been a revolution, but it snuck up on us so gradually that you’d be forgiven if you missed it. It’s called artificial intelligence, and it will have a profound impact on how we design digital products in the near future.”
Lars Holmquist ~ Interactions XXIV.4 ★