Beyond Bias and Compliance: Towards Individual Agency and Plurality of Ethics in AI
Megan is the CEO and co-founder of daios, a deep tech AI ethics startup, and a background in the philosophy and methodology of science. Tom is a Postdoctoral Fellow at Cornell Tech’s Digital Life Initiative, has a Ph.D. in Machine Ethics and Epistemology from the University of California, Berkeley, and leads AI Ethics research at daios
Overview: The fixation on bias and compliance within the AI ethics market leaves out actual ethics: leveraging moral principles to decide how to act. This paper examines the current AI ethics solutions and proposes an alternative method focused on ground truth for machines: data labeling. The paper builds a foundation for how machines understand reality, unlocking the means to integrate freedom of individual expression within AI systems.
The hype around AI has greatly increased with the emergence of large language models (LLMs) such as ChatGPT, Stable Diffusion, Midjourney, etc. More people can understand and experience AI as a technology, but trust in AI still needs to be higher.
