Authors:
- Martin Blapp, blappm@student.ethz.ch
- Doruk Çetin, dcetin@student.ethz.ch
- Bernhard Kratzwald, bkratzwald@ethz.ch
Description:
Unlike human decision-makers, algorithmic decision-making models fail to consider the broader (social) context of their decisions and may ignore some of the important nuances involved. Can we take advantage of both of these decision-making paradigms, i.e., human insight/judgment and automated data-driven decisions?
References:
- Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer. Madras et al., 2018
- Enhancing the Accuracy and Fairness of Human Decision Making. Valera et al., 2018
- Disparate Interactions: An Algorithm-in-the-Loop Analysis of Fairness in Risk Assessments. Green and Chen, 2019