The relative influence of advice from human experts and statistical methods on forecast adjustments

By D. Onkal, Paul Goodwin, Mary E. Thomson, Sinan Gönül, Andrew C. Pollock. 2009

300 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Management Science and Operations Research

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Citations in the corpus

Manipulating and Measuring Model Interpretability (2018, background): “[83] Dilek Önkal, Paul Goodwin, Mary Thomson, and Sinan Gönül.”
'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions (2018, background): “Various research suggests that users—again, primarily experts— may in certain cases systematically over-rely on the outputs of intelligent systems [26, 19], while in others they may systematically distrust systems, despite reassurances as to their accuracy [57, 24].”
A systematic review of algorithm aversion in augmented decision making (2019, background): “…literature, such as the tendency for humans to seek a social or parasocial relationship with the source of advice (Alexander, Blinder, & Zak, 2018; Önkal, Goodwin, Thomson, Gonul, & Pollock, 2009; Prahl & Van Swol, 2017), the persistent belief that human error is random and repairable whereas…”
Understanding the Effect of Accuracy on Trust in Machine Learning Models (2019, background): “The relationship between interpretability and trust has been discussed in several recent papers [16, 22, 25].”
Task-Dependent Algorithm Aversion (2019, background): “Önkal et al. (2009) found that participants relied less on advice from an algorithm than from a human when forecasting stock prices.”
Resistance to Medical Artificial Intelligence (2019, unknown): “…Shah, Mullainathan, and Kleinberg, 2019) , lose confidence in statistical models more quickly than in humans after seeing both make the same mistake (Dietvorst et al. 2014), and place greater weight on the same advice given by human experts versus by statistical models ( € Onkal et al. 2009).”
Forecasting: theory and practice (2020, methodology): “Individuals appear to prefer forecasts from humans over those from statistical algorithms even when those forecasts are identical (Önkal et al., 2009).”
Human Decision Making with Machine Assistance (2019, background): “An experiment comparing the influence of (alleged) human with "statistical" advice found that the latter has a substantially smaller effect on people’s choices [52].”