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

大数据 人工智能 数据科学 计算机科学 人口 预测分析 多样性(控制论) 任务(项目管理) 分析 机器学习 工程类 数据挖掘 社会学 人口学 系统工程
作者
Giuseppe Riva,Brenda K. Wiederhold,Sauro Succi
出处
期刊:Cyberpsychology, Behavior, and Social Networking [Mary Ann Liebert]
卷期号:25 (3): 169-173 被引量:9
标识
DOI:10.1089/cyber.2022.0035
摘要

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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