Should Computers Be Easy To Use? Questioning the Doctrine of Simplicity in User Interface Design

Abstract

That computers should be easy to learn and use is a rarely-questioned tenet of user interface design. But what do we gain from prioritising usability and learnability, and what do we lose? I explore how simplicity is not an inevitable truth of user interface design, but rather contingent on a series of events in the evolution of software. Not only does a rigid adherence to this doctrine place an artificial ceiling on the power and flexibility of software, but it is also culturally relative, privileging certain information cultures over others. I propose that for feature-rich software, negotiated complexity is a better target than simplicity, and we must revisit the ill-regarded relationship between learning, documentation, and software. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models; HCI theory, concepts and models; Interaction design theory, concepts and paradigms; • Social and professional topics → Cultural characteristics; History of computing; Computing education; Computing and business.

"It's like a rubber duck that talks back": Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study

“…For streamlining workflows: Previous research has noted the challenges of cross-application workflows, particularly when using feature-rich software termed praxisware [57]. Participants described a desire to integrate generative AI within the feature-rich applications they already use, rather than a separate experience which requires context switching between generative AI and application.…”

Will Code Remain a Relevant User Interface for End-User Programming with Generative AI Models?

“…A wide variety of AI approaches to facilitate learning for EUPs have been previously explored, from suggesting relevant tutorials [51,122], to proactive suggestions for improving the likelihood of EUPs to write test cases to improve the robustness of their programs [120], and overcoming conceptual learning barriers [41]. However, a key challenge remains in adapting tutorials and learning materials to an individual's problem context (what exactly are they trying to solve), their existing knowledge, and their learning style [14,91]. Studies of spreadsheet learning show that learning from colleagues or "hallway experts" is common because it is an ideal learning situation: the colleague understands the user's problem context and can tailor an explanation precisely to the learner's needs [92].…”

“…However, a lot of EUP is not like this, where instead the objective is to develop ad-hoc data processing or cleaning scripts which are used exactly once for a specific transformation and then discarded. In such one-off automations a lot of interesting enduser programming behaviour is observed, such as accepting errors or brittleness in the program, and transforming the data through a patchwork of manual and automated steps [81,91]. Generative AI technologies are capable of transforming, cleaning, and augmenting data directly, which would eliminate the need for writing a reusable script for one-off automations entirely [38,115].…”

“…Awareness of the possible. The fourth reason that learning and using a formal system is still useful is the "awareness of the possible" [91]; experience with a formal system gives users a thought language within which to define problems and envision potential solutions. Knowing that something can be automated is as important as knowing how to automate it; a user with a powerful generative AI that can automate some task is still at a disadvantage if they do not conceive of that task as something which can be automated.…”

“…In 2005, Scaffidi et al estimated the number of end-user programmers using US labour statistics and extrapolating from the number of spreadsheet users [97]. This methodology works for as long as EUP activity is strongly associated with particular applications (such as spreadsheets), but the generative shift will enable EUP activities across many more applications and platforms, facilitating the breakdown of application boundaries [77] and mitigating the pains of transitioning between tools in the "toolbelt" style of computing [91,107].…”