References:
- Download the transcript for this TREATs talk here.
- “Artificial Intelligence Triggers Fast, Lifesaving Care for Covid-19 Patients.”Epic.
- Bertrand, Marianne, and Sendhil Mullainathan. Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination, 2003.
- Bond, Robert M., et al. “A 61-Million-Person Experiment in Social Influence and Political Mobilization.”Nature, vol. 489, no. 7415, 2012, pp. 295–298.
- Goel, Vindu. “As Data Overflows Online, Researchers Grapple with Ethics.”The New York Times, 13 Aug. 2014.
- Kramer, Adam D., et al. “Experimental Evidence of Massive-Scale Emotional Contagion through Social Networks.”Proceedings of the National Academy of Sciences, vol. 111, no. 24, 2014, pp. 8788–8790.
- Liu, Xiaoxuan, et al. “A Comparison of Deep Learning Performance against Health-Care Professionals in Detecting Diseases from Medical Imaging: A Systematic Review and Meta-Analysis.”The Lancet Digital Health, vol. 1, no. 6, 2019.
- Lum, Kristian, and William Isaac. “To Predict and Serve?”Significance, vol. 13, no. 5, 2016, pp. 14–19.
- Markoff, John. “Social Networks Can Affect Voter Turnout, Study Says.”The New York Times, 12 Sept. 2012.
- Miller, Claire Cain. “Can an Algorithm Hire Better than a Human?”The New York Times, 25 June 2015.
- Singh, Karandeep, et al. “Evaluating a Widely Implemented Proprietary Deterioration Index Model among Hospitalized Patients with COVID-19.”Annals of the American Thoracic Society, vol. 18, no. 7, 2021, pp. 1129–1137.
- Tomašev, Nenad, et al. “A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury.”Nature, vol. 572, no. 7767, 2019, pp. 116–119.
- Z, Obermeyer, et al. “Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations.”Yearbook of Paediatric Endocrinology, 2020.