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The AI Mirror: Reclaiming our Humanity in an Age of Machine Thinking

Published:27 July 2022Publication History

ABSTRACT

The new interdisciplinary field of AI ethics has revealed the extent to which AI systems tend to reflect back and amplify human vices: our unfair biases and discriminatory behaviours, our penchant for consuming and spreading misinformation, and our tendency to pursue narrow gains while losing sight of the bigger picture. While this is true, the mirror metaphor conveys the misleading and dangerous impression that AI merely captures and replicates our humanity in software. Yet we all know that a mirror does not capture the embodied human presence. Glass mirrors erase and occlude much of our material and conscious reality. Mirror images convey no smell, no depth, no softness, no fear, no hope, no imagination. What does the AI mirror occlude? In this talk I explore the dimensions of our humanity that AI's transformation of the socioeconomic and moral order makes it harder for us to see in ourselves and in one another, and why our futures depend upon bringing these vital aspects of our humanity back into view.

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  1. The AI Mirror: Reclaiming our Humanity in an Age of Machine Thinking

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      • Published in

        cover image ACM Conferences
        AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
        July 2022
        939 pages
        ISBN:9781450392471
        DOI:10.1145/3514094

        Copyright © 2022 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 27 July 2022

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        Overall Acceptance Rate61of162submissions,38%
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