Intuition and Algorithms: Dilemmas of Modern Cognition

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Intuition and Algorithms: Dilemmas of Modern Cognition

Introduction

Modern culture is a marketplace of validity claims where intuition has become a systemic force. It is no longer just a private hunch, but a mechanism filtering decisions in business, politics, and the judiciary. In a world dominated by algorithms, the so-called adaptive unconscious co-shapes the global flow of goods and life opportunities. This article analyzes the dilemma: should we trust lightning-fast judgments or cold data analytics? You will learn how "thinking without thinking" affects the authenticity of art, social justice, and the future of our relationship with AI technology.

The Getty Kouros: The Failure of Institutional Rationality

The case of the Getty Museum’s kouros sculpture illustrates the conflict between expertise and institutional rationality. While a laboratory spent 14 months confirming the object's authenticity through geological testing, experts felt an "affective inconsistency" in a fraction of a second. Their unconscious intuition—a condensed history of years of practice—accurately recognized a forgery that microscopes failed to see.

Today, AI and the global art market are marginalizing this "soft factor" in favor of quantitative metrics. In the US, AI is seen as a tool for democratization; in Europe, as a support for interpretation; and in Arab countries, as a tool for legitimizing political decisions. Ignoring expert intuition paves the way for

Frequently Asked Questions

How does intuition differ from popular psychology in the context of modern cognition?
The article defines intuition not as a private hunch, but as a systemic force and a condensed history of practice that actually filters business and political decisions.
Why has scientific research on the kouros from the Getty Museum proved insufficient?
Institutional rationality focused on laboratory analyses of dolomite, ignoring the affective signals of experts who, thanks to many years of practice, immediately sensed the inconsistency of the work.
How can AI amplify the so-called Harding bias?
If recruitment algorithms learn from historical data that favors a particular type of appearance, the machine petrifies these biases, giving them the appearance of an objective statistical pattern.
What are effective methods for eliminating bias in decision-making?
Structural thinking is key, as in the case of blind auditions in orchestras, where removing irrelevant features from the field of perception allows for a fair assessment of competence.
Does forcing rational justification for intuitive choices improve their accuracy?
Paradoxically, the so-called introspection paradox shows that verbal justification of preferences often sabotages the accuracy of judgment, as demonstrated by experiments with the evaluation of the quality of jams.

Related Questions

Tags: intuition algorithms thin slices of reality adaptive unconscious expert systems Harding's mistake artificial intelligence naturalization of inequality indirect discrimination Implicit Association Test aesthetic rationality financialization validation of works petrification of prejudices structural blindness