Position: AI for Just Work: Constructing Diverse Imaginations of AI beyond "Replacing Humans''

Weina Jin, Nicholas Vincent, Ghassan Hamarneh

TL;DR: The current AI community is dominated by a homogeneous vision of AI, which underlying assumptions may not be as ethical as we assume. We call for diversified collective imaginations of AI that synergize both ethical values and AI development.

Abstract: The AI community usually focuses on "how" to develop AI techniques, but lacks thorough open discussions on "why" we develop AI. Lacking critical reflections on the general visions and purposes of AI may make the community vulnerable to manipulation. In this position paper, we explore the "why" question of AI. We denote answers to the "why" question the imaginations of AI, which depict our general visions, frames, and mindsets for the prospects of AI. We identify that the prevailing vision in the AI community is largely a monoculture that emphasizes objectives such as replacing humans and improving productivity. Our critical examination of this mainstream imagination highlights its underpinning and potentially unjust assumptions. We then call to diversify our collective imaginations of AI, embedding ethical assumptions from the outset in the imaginations of AI. To facilitate the community's pursuit of diverse imaginations, we demonstrate one process for constructing a new imagination of "AI for just work," and showcase its application in the medical image synthesis task to make it more ethical. We hope this work will help the AI community to open dialogues with civil society on the visions and purposes of AI, and inspire more technical works and advocacy in pursuit of diverse and ethical imaginations to restore the value of AI for the public good.

Primary Area: Social, Ethical, and Environmental Impacts

Keywords: AI Ethics, AI Research Priorities, Imagination, Machine Learning

Submission Number: 7