Design Lessons From AI’s Two Grand Goals: Human Emulation and Useful Applications

Abstract

Researchers' goals shape the questions they raise, collaborators they choose, methods they use, and outcomes of their work. This article offers a fresh vision of artificial intelligence (AI) research by suggesting a simplification to two goals: 1) emulation to understand human abilities to build systems that perform tasks as well as or better than humans and 2) application of AI methods to build widely used products and services. Researchers and developers for each goal can fruitfully work along their desired paths, but this article is intended to limit the problems that arise when assumptions from one goal are used to drive work on the other goal. For example, autonomous humanoid robots are prominent with emulation researchers, but application developers avoid them, in favor of tool-like appliances or teleoperated devices for widely used commercial products and services. This article covers four such mismatches in goals that affect AI-guided application development: 1) intelligent agent or powerful tool; 2) simulated teammate or teleoperated device; 3) autonomous system or supervisory control; and 4) humanoid robot or mechanoid appliance. This article clarifies these mismatches to facilitate the discovery of workable compromise designs that will accelerate human-centered AI applications research. A greater emphasis on human-centered AI could reduce AI's existential threats and increase benefits for users and society, such as in business, education, healthcare, environmental preservation, and community safety.

Bridging the Gap Between Ethics and Practice

“…User experience design promotes improved interfaces, which guide users to ensure that they understand how decisions are made and have recourse when they wish to challenge the decision. These traditional humancomputer interaction methods and guidelines [104,100] are being updated by leading corporations and researchers to meet the needs of HCAI [102,103].…”

“…These guidelines build on a long history of user interface design [104,100] and newer research on designing interfaces for HCAI systems [29,4,103]. However, guidelines have to be taught to user interface designers, programmers, AI engineers, product managers, and policy makers, whose practices gain strength if there are organizational mechanisms for ensuring enforcement, granting exemptions, and making enhancements.…”

“…), natural language processing and translation, bipedal robots, emotionally responsive human faces, and game playing (checkers, chess, go). In contrast, HCAI focuses on amplifying, augmenting, and enhancing human performance [103] in ways that make systems reliable, safe, and trustworthy [102]. These systems also support human self-efficacy, encourage creativity, clarify responsibility, and facilitate social participation.…”

Human- versus Artificial Intelligence

“…However, no matter how intelligent and autonomous AI agents become in certain respects, at least for the foreseeable future, they probably will remain unconscious machines or special-purpose devices that support humans in specific, complex tasks. As digital machines they are equipped with a completely different operating system (digital vs biological) and with correspondingly different cognitive qualities and abilities than biological creatures, like humans and other animals ( Moravec, 1988 ; Klein et al, 2004 ; Korteling et al, 2018a ; Shneiderman, 2020a ). In general, digital reasoning- and problem-solving agents only compare very superficially to their biological counterparts, (e.g.…”

Human-Centered Artificial Intelligence: Three Fresh Ideas

“…While there is an understandable attraction for some researchers and designers to make computers that are intelligent, autonomous, and human-like, that desire should be balanced by appreciating that many users want to be in control of technologies that support their abilities, raise their self-efficacy, respect their responsibility, and enable their creativity. Shneiderman (2020b) describes four such design tradeoffs that challenge designers of HCAI applications, and offers combined designs that bring the best of both ( Figure 6): Figure 6. Four issues raised by the Emulation and Application Goals, which lead to combined designs that balance intelligent, autonomous, and human-like qualities with an appreciation that many users want to be in control of technologies that support their self-efficacy, responsibility, and creativity…”