UI/UX Articles and Interesting Tidbits of the Week
February//23//2024
Here are some interesting finds on UI/UX of the week!
1.
Jobs to be Done Framework in Research. Very interesting article from the dScout blog (People Nerds) and author Nikki Anderson-Stanier on the Jobs to be Done framework, and how it permeates research studies. It’s an article which provides some recommendations on how to include this framework on a research endeavor, providing some forewarning on leveraging it appropriately and avoiding tilting the study in a certain direction in order to inform a particular type of perspective/bias (in other words, learn from the customer, don’t expect the customer to do the work for you). Highlight of the article includes:
“Understanding how to conduct a JTBD study properly and making it actionable can take quite a lot of time. These studies require a good deal of prep work, especially if everyone is new to the approach. Much of that can be trying to break down misconceptions or how jobs are “supposed to work.” So, when stakeholders come to me wanting to conduct JTBD, I always try to understand what they’re trying to look for. If it is for pain points and unmet needs, I typically recommend generative 1x1 interviews focusing on uncovering this information. If it is about understanding processes, I recommend a journey mapping or mental model interview.”
2.
Pendo and a Case Study focused on ADP, AI and Jobs. Very brief article from the Pendo blog, focused on ADP Assist, an AI powered feature (or product), that ADP has set in motion. The article claims this feature/product “…is designed to give customers proactive insights and recommendations regarding every stage of the employee lifecycle…”. Based on the additional details that the article provides, this solution doesn’t necessarily bode well in terms of pertinence, but when it comes to AI and its ability to pattern recognition in hiring and parsing through resumes, that is unquestionable. For better and for worse. Particularly for specific cases such as Designers, whose baseline of relevance is not solely a resume, but more importantly a portfolio. Highlight of the article includes:
“Lariviere also pointed to AI’s untapped potential for expediting and optimizing the hiring process. “If you think about hiring and applying for a new job, it’s a process that could really use some [artificial] intelligence to influence the process.” It’s now possible, she explained, for AI to deeply analyze the characteristics of an applicant’s resume. AI can not only gain a clear understanding of the skills an individual has, but even infer and suggest roles that the individual may be better suited for. In other words, AI for ADP is a tool to unlock the means to get the right people in the right roles and make getting a job faster and easier.”
3.
Adobe’s Approach to Generative AI in Digital Documents. Worth reading through this article from the Adobe blog, regarding the company’s stance on AI and Digital Documents. The article highlights Liquid Mode, their reading experience especially carved for reading documents in mobile devices and also how they’re establishing trust, by relying on a series of principles when it comes to leveraging AI ethically. Informative reading. Highlight of the article includes:
“Liquid Mode — Adobe’s breakthrough reading experience that delivers an easier way to read documents on mobile — is powered by proprietary AI models that offer a deep understanding of PDF structure and content. Liquid Mode turns static information into dynamic data, automatically reflowing PDF documents to make them more readable and accessible on any sized screen. On the 30th anniversary of Adobe Acrobat and PDF, Liquid Mode achieved a major milestone, with customers using the feature to read more than 1 billion files on mobile devices. The technology has revolutionized reading experiences for individuals of all abilities and was recognized as one of Time Magazine’s 2023’s Best Inventions.”
