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 ★