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Atomist or holist? A diagnosis and vision for more productive interdisciplinary AI ethics dialogue
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Atomist or holist? A diagnosis and vision for more productive interdisciplinary AI ethics dialogue

Travis Greene, Amit DhurandharGalit Shmueli
Patterns, 卷.4(1), 100652
01/2023

摘要

DSML 1: Concept: Basic principles of a new data science output observed and reported Decision Sciences (all)
In response to growing recognition of the social impacts of new artificial intelligence (AI)-based technologies, major AI and machine learning (ML) conferences and journals now encourage or require papers to include ethics impact statements and undergo ethics reviews. This move has sparked heated debate concerning the role of ethics in AI research, at times devolving into name calling and threats of “cancellation.” We diagnose this conflict as one between “atomist” and “holist” ideologies. Among other things, atomists believe facts are and should be kept separate from values, while holists believe facts and values are and should be inextricable from one another. With the goal of reducing disciplinary polarization, we draw on numerous philosophical and historical sources to describe each ideology's core beliefs and assumptions. Finally, we call on atomists and holists within the ever-expanding data science community to exhibit greater empathy during ethical disagreements and propose four targeted strategies to ensure AI research benefits society.

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https://doi.org/10.1016/j.patter.2022.100652檢視
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