Not my exact field, but I keep track of the research for potential applications.
The general vibe is that there are potentially large welfare gains to be achieved if algorithms, ML or statistical methods are integrated into human decision making in principled way. People have innate tendency treat noise as a signal. That does not mean that the dangers mentioned in the article are not real [2].
We should be very aware of them in their current forms and prevent repeating them.
The general vibe is that there are potentially large welfare gains to be achieved if algorithms, ML or statistical methods are integrated into human decision making in principled way. People have innate tendency treat noise as a signal. That does not mean that the dangers mentioned in the article are not real [2]. We should be very aware of them in their current forms and prevent repeating them.
Few of my favorite papers:
1. Human Decisions and Machine Predictions The Quarterly Journal of Economics, Volume 133, Issue 1, 1 February 2018, Pages 237–293, https://doi.org/10.1093/qje/qjx032 https://www.nber.org/papers/w23180
2. Dissecting Racial Bias in an Algorithm that Guides Health Decisions for 70 Million People (2019) https://dl.acm.org/citation.cfm?doid=3287560.3287593
3. Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability https://arxiv.org/abs/1809.04578
4. Direct Uncertainty Prediction for Medical Second Opinions https://arxiv.org/abs/1807.01771