A. Cai, I. Arawjo, E. L. Glassman
arXiv:2402.07350
Originally submitted 12 Feb 24
The vast majority of discourse around AI development assumes that subservient, "moral" models aligned with "human values" are universally beneficial -- in short, that good AI is sycophantic AI. We explore the shadow of the sycophantic paradigm, a design space we term antagonistic AI: AI systems that are disagreeable, rude, interrupting, confrontational, challenging, etc. -- embedding opposite behaviors or values. Far from being "bad" or "immoral," we consider whether antagonistic AI systems may sometimes have benefits to users, such as forcing users to confront their assumptions, build resilience, or develop healthier relational boundaries. Drawing from formative explorations and a speculative design workshop where participants designed fictional AI technologies that employ antagonism, we lay out a design space for antagonistic AI, articulating potential benefits, design techniques, and methods of embedding antagonistic elements into user experience. Finally, we discuss the many ethical challenges of this space and identify three dimensions for the responsible design of antagonistic AI -- consent, context, and framing.
Here is my summary:
This article proposes a thought-provoking concept: designing AI systems that intentionally challenge and disagree with users. It argues against the dominant view of AI as subservient and aligned with human values, instead exploring the potential benefits of "antagonistic AI" in stimulating critical thinking and challenging assumptions. While acknowledging the ethical concerns and proposing responsible design principles, the article could benefit from a deeper discussion of potential harms, concrete examples of how such AI might function, and how it would be received by users. Overall, "Antagonistic AI" is a valuable contribution that prompts further exploration and discussion on the responsible development and societal implications of such AI systems.
