4.5 Article

Zero Sales Resistance: The Dark Side of Big Data and Artificial Intelligence

Journal

CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING
Volume 25, Issue 3, Pages 169-173

Publisher

MARY ANN LIEBERT, INC
DOI: 10.1089/cyber.2022.0035

Keywords

artificial intelligence; big data; AI; causal explanation; predictive analytics; bayesian predictions

Funding

  1. European Research Council under the Horizon 2020 Programme [739964]

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Big data and artificial intelligence have a significant impact on science and society, but presenting them as a universal solution ignores the importance of explanation in understanding complex systems.
Big data (BD) is the hue and cry of modern science and society. The impact of such data deluge is huge and far reaching for both science and society. Moreover, given the effort required for collecting and analyzing these data, artificial intelligence (AI) has replaced the human mind in accomplishing the enormous task of deriving insight out of the information. In this article, we analyze the role of BD and AI in steering the world population toward the state of Zero Sales Resistance (ZSR): the inability to exert critical judgment over the most seductive aspects of the aforementioned data deluge. Moreover, we discuss the alarming consequences of presenting the merging of BD and AI as a universal panacea even if, to date, they have proven far more efficient for predicting human decisions and behaviors (predictive analytics) than for solving the most critical problems in science and society. Why? Our answer is simple. The causal structures associated with such challenges command a detailed understanding of the underlying mechanisms (causal explanation), typically acting nonlinearly and on a broad range of scales in space and time. In contrast, personality and behavior can be predicted with no need of a microscopic theory and understanding of the brain-mind system (empirical prediction). This is a direct consequence of the fact that our mind, at least for the intuitive level, uses the same prediction techniques applied by AI (bayesian predictions based on our experience). However, prediction is not explanation, and without joining them it will be impossible to achieve a major advance in our understanding of complex systems.

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