Issues

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.

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.

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.

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.

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.

Prediction, Judgment, and Complexity: A Theory of Decision Making and Artificial Intelligence

Artificial intelligence (AI) raises the possibility that machines will substitute for humans. AI improves the accuracy of predictions, but when a prediction cannot be made with absolute certainty, judgment is needed to choose the best course of action. Judgment can sometimes be automated.

Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security

"Deep fake" technology makes it possible to create audio and video files of real people saying and doing things they never said or did. These technologies create policy and legal problems. Possible responses include technological solutions, criminal and civil liability, and regulation.

The Auditing Imperative for Automated Hiring

Automated hiring systems are not well understood. Hiring platforms can use proxies for gender and race to facilitate and conceal discrimination. Antidiscrimination law is not designed to address these new issues.

Artificial Intelligence, Machine Learning, and Bias in Finance: Toward Responsible Innovation

Financial technology firms (fintech) using big data and machine learning have revived old debates regarding regulation of the financial services industry. State consumer protection laws should apply to these firms to protect consumers from predatory lending practices.

Afrofuturism, Critical Race Theory, and Policing in the Year 2044

In the future, more than half of the population of the United States will be people of color. Afrofuturists foresee a world in which egalitarian policies and technology reduce crime and bias in criminal justice.