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Advised by an Algorithm: Learning with Different Informational Resources

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  • Walter, Johannes
  • Biermann, Jan
  • Horton, John

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Suggested Citation

  • Walter, Johannes & Biermann, Jan & Horton, John, 2024. "Advised by an Algorithm: Learning with Different Informational Resources," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302407, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc24:302407
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    File URL: https://www.econstor.eu/bitstream/10419/302407/1/vfs-2024-pid-107662.pdf
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    References listed on IDEAS

    as
    1. Gijs Kuilen, 2009. "Subjective Probability Weighting and the Discovered Preference Hypothesis," Theory and Decision, Springer, vol. 67(1), pages 1-22, July.
    2. Balafoutas, Loukas & Kerschbamer, Rudolf, 2020. "Credence goods in the literature: What the past fifteen years have taught us about fraud, incentives, and the role of institutions," Journal of Behavioral and Experimental Finance, Elsevier, vol. 26(C).
    3. Yongping Bao & Ludwig Danwitz & Fabian Dvorak & Sebastian Fehrler & Lars Hornuf & Hsuan Yu Lin & Bettina von Helversen, 2022. "Similarity and Consistency in Algorithm-Guided Exploration," CESifo Working Paper Series 10188, CESifo.
    4. John D. Hey, 2018. "Does Repetition Improve Consistency?," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 2, pages 13-62, World Scientific Publishing Co. Pte. Ltd..
    5. Gijs Kuilen & Peter Wakker, 2006. "Learning in the Allais paradox," Journal of Risk and Uncertainty, Springer, vol. 33(3), pages 155-164, December.
    6. Rick Harbaugh & John W. Maxwell & Beatrice Roussillon, 2011. "Label Confusion: The Groucho Effect of Uncertain Standards," Management Science, INFORMS, vol. 57(9), pages 1512-1527, February.
    7. Fabrice Etilé & Sabrina Teyssier, 2016. "Signaling Corporate Social Responsibility: Third-Party Certification versus Brands," Scandinavian Journal of Economics, Wiley Blackwell, vol. 118(3), pages 397-432, July.
    8. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
    9. Andrew Prahl & Lyn Van Swol, 2017. "Understanding algorithm aversion: When is advice from automation discounted?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 691-702, September.
    10. Nikhil Agarwal & Alex Moehring & Pranav Rajpurkar & Tobias Salz, 2023. "Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology," NBER Working Papers 31422, National Bureau of Economic Research, Inc.
    11. Nicky Nicholls & Aylit Romm & Alexander Zimper, 2015. "The impact of statistical learning on violations of the sure-thing principle," Journal of Risk and Uncertainty, Springer, vol. 50(2), pages 97-115, April.
    12. Michael H. Birnbaum & Ulrich Schmidt, 2015. "The Impact of Learning by Thought on Violations of Independence and Coalescing," Decision Analysis, INFORMS, vol. 12(3), pages 144-152.
    13. Nicky Nicholls & Aylit Romm & Alexander Zimper, 2015. "Erratum to: The impact of statistical learning on violations of the sure-thing principle," Journal of Risk and Uncertainty, Springer, vol. 50(2), pages 117-117, April.
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    More about this item

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D79 - Microeconomics - - Analysis of Collective Decision-Making - - - Other
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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