Artikel

Risks of observable and unobservable biases in artificial intelligence predicting consumer choice

Companies are increasingly adopting Artificial Intelligence (AI) today. Recently however debates started over the risk of human cognitive biases being replicated (and scaled) by AI. Research on biases in AI predicting consumer choice is incipient and focuses on observable biases. We provide a short synthesis of cognitive biases and their potential risk of being replicated in AI-based choice prediction. We also discuss for the first time the risk of unobservable biases, which affect choice indirectly, through other biases. We exemplify this by looking at looking at three prevalent, most frequently investigated biases in consumer behaviour: extremeness aversion, regret aversion and cognitive regulatory focus (prevention- versus promotion-focus). Based on a sample of 1747 respondents, through partial least squares structural equation modelling and significance testing, we show that regret aversion (unobservable bias) significantly reduces extremeness aversion (observable bias) and mediates the influence of cognitive regulatory focus (unobservable bias).

Sprache
Englisch

Erschienen in
Journal: Amfiteatru Economic Journal ; ISSN: 2247-9104 ; Volume: 23 ; Year: 2021 ; Issue: 56 ; Pages: 102-119

Klassifikation
Wirtschaft
Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making‡
Information, Knowledge, and Uncertainty: General
Microeconomic Behavior: Underlying Principles
Thema
cognitive bias
artificial intelligence
choice prediction
consumer choice behaviour
regret aversion
extremeness aversion
regulatory focus

Ereignis
Geistige Schöpfung
(wer)
Teleaba, Florian
Popescu, Sorin
Olaru, Marieta
Pitic, Diana
Ereignis
Veröffentlichung
(wer)
The Bucharest University of Economic Studies
(wo)
Bucharest
(wann)
2021

DOI
doi:10.24818/EA/2021/56/102
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Teleaba, Florian
  • Popescu, Sorin
  • Olaru, Marieta
  • Pitic, Diana
  • The Bucharest University of Economic Studies

Entstanden

  • 2021

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