Dealing with "Deepfakes": How Synthetic Media Will Distort Reality, Corrupt Data, and Impact Forecasts

John Wood and Nada Sanders

Foresight: The International Journal of Applied Forecasting, 2020, issue 59, 32-37

Abstract: Preview and key points from the authors: Distorted data are nothing new. However, deepfake technology-the term is a combination of "deep learning" and "fake"- has created the ability to distort reality in new and alarming ways. This technology is capable of fabricating audio, video, and even text files that are almost indistinguishable from authentic documentation. Machine-learning capabilities are escalating the technology's sophistication, making deepfakes ever more realistic and increasingly resistant to detection. The implications for communication, data integrity, forecasting, and decision making are vast and unequivocally grim. Our best hope for dealing with deepfakes may lie with the creative problem solving of the data-science community, sponsored and supported by corporate leadership. Copyright International Institute of Forecasters, 2020

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:for:ijafaa:y:2020:i:59:p:32-37

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