Monitoring Misuse for Accountable Artificial Intelligence as a Service. AI is increasingly being offered u0027as a serviceu0027 (AIaaS). This entails service providers offering customers access to prebuilt AI models and services, for tasks such as object recognition, text translation, texttovoice conversion, and facial recognition, to name a few. The offerings enable customers to easily integrate a range of powerful AIdriven capabilities into their applications. Customers access these models through the provideru0027s APIs, sending particular data to which models are applied, the results of which returned. However, there are many situations in which the use of AI can be problematic. AIaaS services typically represent generic functionality, available u0027at a clicku0027. Providers may therefore, for reasons of reputation or responsibility, seek to ensure that the AIaaS services they offer are being used by customers for u0027appropriateu0027 purposes. This paper introduces and explores the concept whereby AIaaS providers uncover situations of possible service misuse by their customers. Illustrated through topical examples, we consider the technical usage patterns that could signal situations warranting scrutiny, and raise some of the legal and technical challenges of monitoring for misuse. In all, by introducing this concept, we indicate a potential area for further inquiry from a range of perspectives.

Defining AI in Policy versus Practice 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 agreedupon 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 policymaker conceptions of AI. We find that while AI researchers favor definitions of AI that emphasize technical functionality, policymakers 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 humanlike 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.