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Content-first for a better user experience

The content experience as a result of content design.

“​This is a people problem. We have all the tools we need. Too many, in fact. Go back to pencil and paper. Sticky notes and whiteboards. Don’t wait for the perfect time or the perfect project. They won’t happen. Figure out what you can do tomorrow – or today – to start the shift to a content-first process. Don’t wait to be asked. No one is going to ask you to do this. Make it happen. When you do, everyone is happy.”

Carrie Hane a.k.a. /carriehane | @carriehd ~ Tanzen

A new model for the design thinking process

Design thinking process in many variations.

“​One way to frame the relationship between these two is that design properties describe the foundational structures on which design principles are hung. Or to use an analogy, properties are the basic rules of chess (how the board is set up, how the pieces move, etc.), and principles are the various strategies, play styles, and schools of thought.”

Yosef Shuman a.k.a. /yosefshuman | @aleafinwater ~ YosefsHuman.com courtesy of @peterboersma

Global Information Design: A New Framework for Understanding Data Visualization

Now wondering how the underlying data sets are represented.

“​Information designers and dataviz practitioners today face a daily challenge: what technique, method, software, or code library to use for their next project. Practitioners look both forward and backward, trying to keep up with the latest software tools and at the same time find more examples from the past — “classic” examples that can teach us something today.”

Paul Kahn a.k.a. /paulkahn | @pauldavidkahn ~ Medium

A Design Thinking Mindset for Data Science

Thinking from a human perspective for data scientists.

“Data science has received recent attention in the technical research and business strategy since; however, there is an opportunity for increased research and improvements on the data science research process itself. Through the research methods described in this paper, we believe there is potential for the application of design thinking to the data science process in an effort to formalize and improve the research project process. Thus, this paper will focus on three core areas of such theory. The first is a background of the data science research process and an identification of the common pitfalls data scientists face. The second is an explanation of how design thinking principles can be applied to data science. The third is a proposed new process for data science research projects based on the aforementioned findings. The paper will conclude with an analysis of implications for both data science individuals and teams and suggestions for future research to validate the proposed framework.”

Rachel Woods ~ Towards Data Science

Simultaneous triangulation: Mixing user research & data science methods

Using DataSci (quant) to get meaning out of UsrRes (qual).

“Simultaneous triangulation is an incredibly powerful tool to generate comprehensive and verified findings. If you only use one method, you could end up with blindspots. If you employ methods sequentially rather than simultaneously, you could run into unexplainable contradictions, like we did at first. The solution is simultaneous triangulation. Next time you have a complex research question, consider using the three-step process to mitigate blindspots and turn discrepancies in learning opportunities.”

Colette Kolenda and Kristie Savage ~ Spotify Design

Rise of the meta-designer

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

A unified framework of five principles for AI in society

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

An interdiscipline emerges: Pathways to Systemic Design

From system design, to systematic design and systemic design.

“In this theme issue of She Ji, we present work from the Sixth Relating Systems Thinking and Design Symposium (RSD6) in Oslo. The emerging field of systemic design has expanded to engage with increasingly important societal issues ranging from housing and quality of life in cities, to foreign policy, immigration, and cultural development, as well as our environments and ecologies. (…) The guest-editors have co-edited a number of works in the past. We normally agree enough to co-create a shared vision for the overall thrust of the publication. But this time, we found ourselves in fruitful argument about the issues of interest or concern posed by nearly every article, which demonstrates the compelling discursive value of the ideas. The viewpoint articles in particular raised a number of micro-arguments between us. Our discussion follows, revealing the distinctions arising from each of these thoughtful essays.”

Birger Sevaldson and Peter Jones ~ She Ji: The Journal of Design, Economics, and Innovation Volume 5, Issue 2

Teach Slower to Teach Better

But what’s the speed of learning and how to speed it up?

“Over the last decade, as a rejection to a tired model of higher education, new educational programs and structures have emerged. Many of these are in the fields of design, digital product development, and programming. The new models of education take many forms. Some are short day-long or week-long workshops. Some are meetups and brownbags. Some are online, some offline, and some hybrid. What connects many of these models is their immediate vocational emphasis. The majority intend to train practitioners, not academics. The focus is on preparing people to do design and get jobs. (…) We need educational innovation, but not at the expense of quality. Students need the space to develop problem solving strategies. Speed is not in our favor here. Let’s all slow down.”

Jon Kolko a.k.a /jkolko | @jkolko ~ modernist studio

Creative next: AI, automation, and the practice of user experience design

Become more strategic, ‘creative’ and human, as we always should have been.

“The word automation conjures an image of a factory full of robots, a modern marvel symbolizing both technological progress and the regression of working-class opportunities and lifestyles. But our notion of automation generally remains ossified in this physical, machine-replaces-labor frame. We don’t think of automation in the realm of knowledge work beyond the most mundane and mindlessly repeatable tasks. But automation, powered by machine-learning advances in artificial intelligence (AI), is coming. It’s actually already been here for decades, going back to relatively primitive software innovations that eluded our ability to connect the dots back to industrial robotics before it. Perhaps surprisingly, modern AI automation has been making original art for years and has collaborated with a human team on an original painting that sold at Christie’s for $432,500. Beyond art making, AI automation can also write procedural content such as stock blurbs and minor league sports stories.”

Dirk Knemeyer a.k.a. /knemeyer | @dknemeyer and Jonathan Follett a.k.a. /jonfollett | @jonfollett ~ ACM Interactions (XXVI.3)

Ethics of identity in the time of big data

Never could have preducted that ethics was so closely connected to technology. I’m not a futurist.

“Compartmentalizing our distinct personal identities is increasingly difficult in big data reality. Pictures of the person we were on past vacations resurface in employers’ Google searches; LinkedIn which exhibits our income level is increasingly used as a dating web site. Whether on vacation, at work, or seeking romance, our digital selves stream together. One result is that a perennial ethical question about personal identity has spilled out of philosophy departments and into the real world. Ought we possess one, unified identity that coherently integrates the various aspects of our lives, or, incarnate deeply distinct selves suited to different occasions and contexts? At bottom, are we one, or many? The question is not only palpable today, but also urgent because if a decision is not made by us, the forces of big data and surveillance capitalism will make it for us by compelling unity. Speaking in favor of the big data tendency, Facebook’s Mark Zuckerberg promotes the ethics of an integrated identity, a single version of selfhood maintained across diverse contexts and human relationships. This essay goes in the other direction by sketching two ethical frameworks arranged to defend our compartmentalized identities, which amounts to promoting the dis-integration of our selves. One framework connects with natural law, the other with language, and both aim to create a sense of selfhood that breaks away from its own past, and from the unifying powers of big data technology.”

James Brusseau ~ First Monday (Volume 24 Issue 5)

The map is not the territory: Empathy in design

The analogy of map and territory has its limits.

“If you ask a user experience person—academic or practitioner—whether empathy is important to design, it’s hard to imagine anything other than a resounding ‘Yes!’ Indeed, statements like the one above seem to imply that empathy is a silver bullet that will transform design and lead to innovation. Before empathy was a buzzword, many of us would still have said that helping product teams develop empathy for their users was a core function of user experience research. After all, what else could it mean to study another’s experience and share those insights with others? As often happens in business, though, once a concept like empathy catches on, it’s treated like a fresh discovery. The groundswell is then translated into a small number of new techniques that instantiate the concept concretely. As these techniques become codified, too often reification takes over and their artifacts, or deliverables, seem to substitute for the more abstract virtue they supposedly represent. We act as though the map is the territory.”

David Siegel and Susan Dray ~ ACM Interactions (XXVI.2)

Researcher introspection for experience-driven design research

Like with second order cybernetics, the role of the researcher in the researched system is essential.

“We challenge the unquestioning pursuit of the appearance of objectivity and ingrained designer-user dualism in human-centred design research and propose a resurrection of introspection as a valid approach to investigating subjective experiences. Through comparing epistemic perspectives and reviewing the histories of introspection in several disciplines, we liberate the research field of experience-driven design from a long-lasting doubt about and the disguised and unsystematic use of this method. To establish a foundation for the further development of introspective methods, we focus on its most controversial type (i.e. researcher introspection) and discuss its strengths and weaknesses, preconditions of use, diverse ways to practise for different suitable experience-driven design research purposes, and useful techniques and tools.”

Haian Xue and Pieter M.A.Desmet ~ Design Studies Volume 63

The vandalisation of UX

How the semantics of UX change all the time.

“If anything, the T in T-shape isn’t a deep dive into a specific UX sub discipline, and its not to stay within the confines of either research or design. The skill you most want to T shape is the ability transfer the principles of good design across these factors. This is why the broad UX lens is perfectly positioned to engage the ambiguity that comes with design. After all, why put a cap on your abilities? We all have a ceiling but don’t put one there yourself.”

Max Taylor ~ Medium courtesy of @thebrainlady

Taxonomy (the secret ingredient of great content) and how it is linked to business strategy

Taxos for business as well.

“While I haven’t shared all the strategic reasoning behind the website taxonomy, I hope this post explains the approach well enough to solicit feedback. Is it perfect? I don’t know! We will come to know only after the website is launched, feedback is collected from the target audience, and website traffic is tracked over a period of time. That’s when I am going to update this post.”

The Verditer

Agile research

Agile eats research, design and evaluation for (fast food) breakfast.

“In this paper we ask: “How might we take the ideas, the methods and the underlying philosophy behind agile software development and explore applying them in the context of doing research — even research that does not involve software development?” We look at some examples of agile research methods and think about how they might inspire the design of even better methods. We also try to address some potential criticisms of an approach that aims to minimize a need for Big Design Up Front by developing tighter iteration cycles, coupled with reflection and learning as part of a process for doing research.”

Michael Twidale and Preben Hansen ~ FirstMonday 24.1

Improving onboarding with employee experience journey mapping: A fresh take on a traditional UX technique

EX, the experience we all forgot.

“We present a creative method for applying the UX technique of journey mapping to improve the onboarding experience of new employees in any organization. Journey mapping is a well-known design research tool used to gain insight into how a user experiences a service, process, or product, with the goal of making informed improvements to deliver a better experience for future users. We argue that journey mapping can also be used to improve the internal process of onboarding new employees and improve the experience for future new hires, which is important because positive onboarding experiences are linked to increased productivity and greater employee retention. We share how other organizations can use journey mapping to improve the onboarding process utilizing our employee experience journey mapping project toolkit designed to help guide similar projects, complete with shareable templates. In addition, we share the methods used at our library, as well as our findings, recommendations, and lessons learned.”

Hannah McKelvey and Jacqueline L. Frank ~ Weave 1.9

Blockchain UX: Challenges, principles and heuristics

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

Reading in a post-textual era

Only reading sharps the mind.

“This paper analyses major social shifts in reading by comparing publishing statistics with results of empirical research on reading. As media statistics suggest, the last five decades have seen two shifts: from textual to visual media, and with the advent of digital screens also from long-form to short-form texts. This was accompanied by new media-adequate reading modes: while long-form content invokes immersed and/or deep reading, we predominantly skim online social media. Empirical research on reading indicates that the reading substrate plays an important role in reading processes. For example, comprehension suffers when complex texts are read from screens. This paper argues that media and reading trends in recent decades indicate broader social and cultural changes in which long-form deep reading traditionally associated with the printed book will be marginalised by prevailing media trends and the reading modes they inspire. As these trends persist, it may be necessary to find new approaches to vocabulary and knowledge building.”

Miha Kovač and Adriaan van der Weel ~ First Monday 23.10