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.

中文翻译：

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零销售阻力：大数据和人工智能的阴暗面

大数据（BD）是现代科学和社会的主题。这种数据泛滥的影响对科学和社会来说都是巨大而深远的。此外，鉴于收集和分析这些数据所需的努力，人工智能 (AI) 已经取代了人类思维，完成了从信息中获得洞察力的巨大任务。在本文中，我们分析了 BD 和 AI 在引导世界人口走向零销售阻力状态中的作用(ZSR)：无法对上述数据泛滥中最具诱惑力的方面做出批判性判断。此外，我们还讨论了将 BD 和 AI 合并作为万能灵丹妙药的惊人后果，即使迄今为止，它们在预测人类决策和行为（预测分析）方面比在解决科学中最关键的问题方面更有效。和社会。为什么？我们的答案很简单。与这些挑战相关的因果结构需要对潜在机制（因果解释）的详细理解，通常是非线性的，并且在空间和时间的广泛范围内起作用。相比之下，无需微观理论和对大脑-心智系统的理解（经验预测）就可以预测人格和行为。这是我们的大脑（至少在直觉层面上）使用人工智能应用的相同预测技术（基于我们经验的贝叶斯预测）这一事实的直接结果。然而，预测不是解释，如果不加入它们，就不可能在我们对复杂系统的理解方面取得重大进展。