Design critique, properly done the best feedback loop.
“Giving each other helpful feedback is one of the most important parts of being a team. But many teams struggle to give each other feedback in productive ways. Thankfully, the design community has been absolutely obsessed with how to give each other feedback since the start of time.”
Braden Kowitz a.k.a. /kowitz | @kowitz ~ Range ★
Digital infiltrating in every aspect of live, and changing it.
“Industry after industry has reinvented itself in response to upstart challengers and shifting consumer expectations that are the hallmarks of this new era. The same is true in healthcare, where we have weathered the introduction of the electronic medical records, patient portals and now interoperability. But to date our industry’s digital transformation has been guided largely by government regulation – leaving the design of the future of healthcare to be driven by policy makers and executed largely by IT departments. Meanwhile, most other industries have turned to a different guru for inspiration and guidance: the consumer. Northwell Health has undertaken a cultural transformation grounded in patient and family centered care. In this narrative, we explore our digital patient experience (dPx) journey and lessons learned. Every person, every role, every moment matters.”
Emily Kagan Trenchard, Laura Semlies, and Sven Gierlinger ~ PXJ Issue 2 ★
But are you measuring what you want to measure?
“We take a comprehensive journey into the world of UX metrics, exploring both behavioural and attitudinal measurements, before highlighting our own single score program for user experience.”
Christopher Ratcliff and Kuldeep Kelkar ~ userzoom ★
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 ★
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
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 ★
The big four going UCD and tech.
“Artificial intelligence technology can result in artificial stupidity if it’s poorly designed, implemented, or adapted. What’s crucial? Ensuring it’s designed to help humans think better.”
Jim Guszcza ~ Deloitte Insights ★
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 ★
Looks like a kind of universal design principle.
“Because when you strip away all the styles, all the mark-up, all the cool features from a website or app — what’s left? People. And honestly, the more I learn about digital accessibility, the more I realize it’s not about the code at all.”
Carie Fisher ~ A List Apart ★
All manifestations of design are relevant for start-ups, scale-ups and f*ck-ups.
“Start-ups and innovation environments represent exciting, challenging and relatively-uncharted terrain for service design. Despite the fact that we as service designers are barely visible in the start-up world, and mostly unmentioned in their literature, my own experience as a service designer working with start-ups and innovation programmes has proven to me that we can add significant value in these settings. In this article, I’ll look at hurdles to address and overcome in terms of mindset, and suggest some practical ways service designers can address this opportunity.”
Jesse Grimes a.k.a. /jessegrimes ~ Kolmiot Service Design ★
Designing a healthy experience.
“As UX researchers and designers working in healthcare, it’s our job to advocate for the user. Involving nurses in innovation and research is critical in advancing the digitization of healthcare. As you plan research and design, consider the varied ages and tech approaches of clinicians and beware of the complex ecosystem in which your designs will live. Given the growth of voice interfaces, telemedicine, AR/VR, etc, we are witnessing a wave of new technology in healthcare and with it comes an equally large learning curve.”
Eliana Stein and Barbara Gulten ~ UX Booth ★
Digital and experience transformations, in every domain you can imagine.
“Industry after industry has reinvented itself in response to upstart challengers and shifting consumer expectations that are the hallmarks of this new era. The same is true in healthcare, where we have weathered the introduction of the electronic medical records, patient portals and now interoperability. But to date our industry’s digital transformation has been guided largely by government regulation – leaving the design of the future of healthcare to be driven by policy makers and executed largely by IT departments. Meanwhile, most other industries have turned to a different guru for inspiration and guidance: the consumer. Northwell Health has undertaken a cultural transformation grounded in patient and family centered care. In this narrative, we explore our digital patient experience journey and lessons learned. Every person, every role, every moment matters.”
Emily Kagan Trenchard, Laura Semlies, and Sven Gierlinger ~ Patient Experience Journal ★
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 ★
Application onboarding versus organisation onboarding. Just a matter of principles.
“As a UX designer and marketer in the tech industry, I have been onboarded for a number of software and design projects. During these onboarding processes, I have noticed that software, apps, and user flows are not always conveyed in a simple, readily-comprehensible manner. As software and apps become more complex, the ability to define and explain technical concepts in simple terms has become an increasingly valuable skill for project leaders. In noticing this, an adherence to universal design principles would improve accessibility for all who take part in the onboarding process.”
Nicholas Farmen a.k.a. @FarmenNicholas ~ UXbooth
Global and local vars, lots of them.
“UX research pulls many terms, methods, and conventions from other fields. Selecting a method is an important first choice in measuring the user experience. But an important next step is understanding the variables you’ll have to deal with when designing a study or drawing conclusions. Variables are things that change. Variables can be controlled and measured.”
Jeff Sauro a.k.a. /jeffsauro | @MeasuringU ~ MeasuringU ★
Life is full of connections, to be made and to be found.
“At the Ulm School of Design (1953-1968), there was a promising approach to teaching visual as well as verbal communication. Although it took place in separate departments, this pioneering approach attempted to integrate form and content, theory and practice. From the school’s inception, the Information Department was established alongside the Departments of Visual Communication, Product Design and Building: writing was considered a discipline on a par with two- and three-dimensional design. While the Department of Visual Communication flourished, however, the Information Department languished, not least as a result of the school’s policy and staff conflicts. A closer look at the HfG’s history nevertheless reveals the Information Department’s overall importance to the school’s self-conception and attitude. Beyond its relevance for design history, this might also contribute to the discussion of a greater emphasis on verbal and writing competence in present day design education.”
David Oswald and Christiane Wachsmann ~ A/I/S/Design ★
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
Just a matter of abstraction and focus.
“In this article, we explore how UX writing compares to content strategy. Since many are confused a bit about how UX writing fits in with content strategy, we compare the two fields and see how your business can use both of them to build an online presence and improve customer experience with digital products.”
Bridgette Hernandez ~ UXPA Magazine ★
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 ★
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 ★