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.
Highlights
WHAT IS THE GOAL OF AI RESEARCH? EMULATION OR APPLICATIONG OALS of artificial intelligence (AI) research were proposed at least 60 years ago, when early conferences brought together those who believed in pursuing Alan Turing’s question “can machines think?” [64]
The emulation goal is to understand human perceptual, cognitive, and motor abilities to build computers that perform tasks as well as or better than humans. This goal includes the aspiration for humanoid robots, natural language and image understanding, commonsense reasoning, and artificial general intelligence (AGI)
The desire to make commercially successful products and services means that human–computer interaction (HCI) methods, such as design thinking, observation of users, usability testing, market research, and continuous monitoring of usage, are frequent processes employed by the application goal community
Summary
G OALS of artificial intelligence (AI) research were proposed at least 60 years ago, when early conferences brought together those who believed in pursuing Alan Turing’s question “can machines think?” [64]. IBM’s researcher who built Deep Blue, Feng-Hsiung Hsu, makes an explicit statement that the brute-force hardware solution did not use AI methods [22] Another example is that AI-guided knowledgebased expert systems failed, but carefully engineered rulebased systems with human-curated rule sets succeeded in many business applications [28]. It summarizes the application goal of developing widely used products and services by using AI methods, which ensure human control.
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