People are often reluctant to incorporate information produced by algorithms into their decisions, a phenomenon called ``algorithm aversion''. This paper shows how algorithm aversion arises when the choice to follow an algorithm conveys information about a human's ability. I develop a model in which workers make forecasts of an uncertain outcome based on their own private information and an algorithm's signal. Low-skill workers receive worse information than the algorithm and hence should always follow the algorithm's signal, while high-skill workers receive better information than the algorithm and should sometimes override it. However, due to reputational concerns, low-skill workers inefficiently override the algorithm to increase the likelihood they are perceived as high-skill. The model provides a fully rational microfoundation for algorithm aversion that aligns with the broad concern that AI systems will displace many types of workers.

What will likely be the effect of the emergence of ChatGPT and other forms of artificial intelligence (AI) on the skill premium? To address this question, we develop a nested constant elasticity of substitution production function that distinguishes between industrial robots and AI. Industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers.

By Peter Dizikes This is part 3 of a three-part series examining the effects of robots and automation on employment, based on new research from economist and Institute Professor Daron Acemoglu. Modern technology affects different workers in different ways. In some white-collar jobs -- designer, engineer -- people become more productive with sophisticated software at their side. In other cases, forms of automation, from robots to phone-answering systems, have simply replaced factory workers, receptionists, and many other kinds of employees. Now a new study co-authored by an MIT economist suggests automation has a bigger impact on the labor market and income inequality than previous research would indicate -- and identifies the year 1987 as a key inflection point in this process, the moment when jobs lost to automation stopped being replaced by an equal number of similar workplace opportunities.

This is part 3 of a three-part series examining the effects of robots and automation on employment, based on new research from economist and Institute Professor Daron Acemoglu. Modern technology affects different workers in different ways. In some white-collar jobs -- designer, engineer -- people become more productive with sophisticated software at their side. In other cases, forms of automation, from robots to phone-answering systems, have simply replaced factory workers, receptionists, and many other kinds of employees. Now a new study co-authored by an MIT economist suggests automation has a bigger impact on the labor market and income inequality than previous research would indicate -- and identifies the year 1987 as a key inflection point in this process, the moment when jobs lost to automation stopped being replaced by an equal number of similar workplace opportunities.

New AI and robotics technologies are increasingly automating work tasks. How much of a threat does automation pose to workers? A new study by one of us (James Bessen), along with Maarten Goos, Anna Salomons, and Wiljan van den Berge, provides the first large-scale quantitative evidence of how automation affects individual workers, using government data from 2000-2016 for 36,000 firms in the Netherlands, covering about 5 million workers each year. We found that automation does indeed affect many workers. Each year, about 9% of the workers in the sample are employed at firms that make major investments in automation.

Automation in the workplace has been one of the looming existential threats to American workers for years now. And with each new study published, the fear of robots, machines, and artificial intelligence coming to take our jobs ticks higher. But a new report from McKinsey finds that the future of work and automation isn't quite the zero-sum game when it comes to jobs as some perceive. Right now, 51% of job activities could be automated with "currently demonstrated" technology, the McKinsey report says. The distinction is noteworthy: McKinsey isn't saying half of all jobs can be automated with existing technology, but rather job tasks.