Title
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Author
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Year
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Privacy, Algorithms, and Artificial Intelligence
Many economists assume that consumers understand how their data will be used and do not consider how one consumer’s decision to share data affects others. Some artificial intelligence (AI) systems seem to have learned discriminatory behavior, and simplistic models do not address this.
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Catherine Tucker |
2019 |
The Impact of Machine Learning on Economics
Machine learning (ML) has begun to transform economics. ML systems can make it easy to classify large amounts of data. Empirical economists can use ML to develop new methodologies, ensure that others can reproduce their studies, and design more sophisticated studies.
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Susan Athey |
2019 |
Artificial Intelligence, Automation, and Work
Automation tends to displace human workers, reducing wages by reducing the demand for labor. But automation also increases productivity and creates new-labor intensive tasks. Several factors constrain the labor market’s capacity to adjust, especially if automation proceeds too quickly.
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Daron Acemoglu, Pascual Restrepo |
2019 |
Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass
Artificial intelligence (AI) systems often rely on human workers to classify content. The workers find tasks using on-demand labor platforms like Mechanical Turk, receiving low wages and no benefits; however, on-demand work platforms enable many disadvantaged workers to earn income.
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Mary L. Gray, Siddharth Suri |
2019 |
Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics
Artificial intelligence (AI) is advancing rapidly, but productivity growth has been falling for a decade, and real income has stagnated. The most plausible explanation is that it will take considerable time for AI-related technologies to be deployed throughout the economy.
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Erik Brynjolfsson, Chad Syverson, Daniel Rock |
2019 |
The Cambridge Handbook of Consumer Privacy
New data collection technologies raise privacy issues for consumers. Educational technologies and “smart cars” present new issues. Every aspect of life will be logged and analyzed. We must revisit basic ideas about democracy, the distribution of power in society, and bias.
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Evan Selinger, Jules Polonetsky, Omer Tene |
2018 |
Antisocial Media: How Facebook Disconnects Us and Undermines Democracy
Facebook and other tech firms have failed to filter out racism and other harmful ideas from the public sphere and encourage people to express themselves in shallow ways. The idea that the Internet would lead to more freedom and more competition was a myth.
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Siva Vaidhyanathan |
2018 |
Shifting Institutional Roles in Biomedical Innovation in a Learning Healthcare System
In future, health care outcomes will be guided by a learning healthcare system, which uses data from patients to evaluate treatments. Some data derived in clinical settings might be of low quality. The FDA now evaluates more treatments using data collected after the treatment begins to be used.
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Rebecca S. Eisenberg |
2018 |
Interventions Over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment
Machine learning is now being used in the criminal justice system. Because these systems focus on accuracy of prediction and ignore factors that drive crime, they can exacerbate problems of mass incarceration and inequality.
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Jonathan Zittrain, Chelsea Barabas, Joichi Ito, Karthik Dinakar, Madars Virza |
2018 |
Are Ideas Getting Harder to Find?
Economic growth arises when people create ideas. Evidence from a wide range of industries, products, and firms shows that while the number of researchers is increasing, their productivity is falling. Large increases in research will offset its declining productivity.
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Nicholas Bloom, Charles I. Jones, John Van Reenen, Michael Webb |
2018 |