AI for Good: Fallacies and Controversies

In this chapter, the speaker discusses fallacies related to AI risks, including bias against automation, overlook of gains, and negative impacts on vulnerable populations. They argue that technology can be a democratizer and equalizer, providing more access and scale. The chapter concludes by suggesting a regulatory approach that recognizes the potential for both good and bad uses of data.

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