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Der vorhersagbare Mensch

Chancen und Risiken der KI-basierten Prädiktion von kognitiven Fähigkeiten, Persönlichkeitsmerkmalen und psychischen Erkrankungen

The predictable human

Possibilities and risks of AI-based prediction of cognitive abilities, personality traits and mental illnesses

Zusammenfassung

Neue Ansätze der Nutzung künstlicher Intelligenz (KI) zur Analyse von Daten aus der Neurobildgebung, aber auch passiv gesammelter Daten von sog. „Wearables“ wie Smartphones oder Smartwatches sowie Daten, die sich aus Social-Media- und anderen Online-Aktivitäten extrahieren lassen, ermöglichen es bereits heute, kognitive Fähigkeiten, Persönlichkeitsmerkmale und psychische Erkrankungen vorherzusagen sowie akute mentale Zustände offenzulegen. In diesem Beitrag erläutern wir die Hintergründe der aktuellen Entwicklung, leuchten ihre Möglichkeiten und Grenzen aus und gehen auf ethische und gesellschaftliche Aspekte ein, die sich aus der Nutzung ergeben.

Abstract

New approaches to the use of artificial intelligence (AI) to analyze data from neuroimaging but also passively collected data from so-called wearables, such as smartphones or smartwatches, as well as data that can be extracted from social media and other online activities, already make it possible to predict cognitive abilities, personality traits, and mental illnesses, as well as to reveal acute mental states. In this article, we explain the methodological concepts behind these current developments, illuminate the possibilities and limitations, and address ethical and social aspects arising from the use.

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Correspondence to Simon B. Eickhoff.

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Interessenkonflikt

S.B. Eickhoff und B. Heinrichs geben an, dass kein Interessenkonflikt besteht.

Für diesen Beitrag wurden von den Autoren keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien.

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Cite this article

Eickhoff, S.B., Heinrichs, B. Der vorhersagbare Mensch. Nervenarzt 92, 1140–1148 (2021). https://doi.org/10.1007/s00115-021-01197-8

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Schlüsselwörter

  • Maschinelles Lernen
  • Präzisionsmedizin
  • Vorhersage
  • Ethik
  • Biomarker

Keywords

  • Machine learning
  • Precision medicine
  • Prediction
  • Ethics
  • Biomarker