Defining AI in Policy versus Practice

TL;DR

This paper explores the differing definitions of AI used by researchers and policymakers, highlighting how these differences impact regulation and ethical considerations of current and future AI technologies.

Contribution

It provides an empirical survey of expert and policy-maker views on AI definitions, revealing a gap that affects regulation and ethical focus.

Findings

Researchers focus on technical functionality in definitions.

Policy-makers emphasize human-like thinking and behavior.

Current definitions may overlook pressing issues with existing AI systems.

Abstract

Recent concern about harms of information technologies motivate consideration of regulatory action to forestall or constrain certain developments in the field of artificial intelligence (AI). However, definitional ambiguity hampers the possibility of conversation about this urgent topic of public concern. Legal and regulatory interventions require agreed-upon definitions, but consensus around a definition of AI has been elusive, especially in policy conversations. With an eye towards practical working definitions and a broader understanding of positions on these issues, we survey experts and review published policy documents to examine researcher and policy-maker conceptions of AI. We find that while AI researchers favor definitions of AI that emphasize technical functionality, policy-makers instead use definitions that compare systems to human thinking and behavior. We point out that definitions adhering closely to the functionality of AI systems are more inclusive of technologies in use today, whereas definitions that emphasize human-like capabilities are most applicable to hypothetical future technologies. As a result of this gap, ethical and regulatory efforts may overemphasize concern about future technologies at the expense of pressing issues with existing deployed technologies.