Summary of Sources on AI and Automation

Introduction

This summary provides an overview of several sources that discuss the impact of artificial intelligence (AI) and automation on various aspects of society. The sources include academic papers and articles from reputable institutions such as MIT and Boston University. The topics covered in these sources range from the influence of AI on economic inequality to the effects of automation on workers. The information presented in this summary aims to provide a comprehensive understanding of the current state of AI and automation research.

"AI-tocracy" by Beraja, Kao, Yang, and Yuchtman (2022)

This working paper by Beraja, Kao, Yang, and Yuchtman explores the concept of an "AI-tocracy," referring to a society where power and influence are concentrated among those who control AI technologies. The authors argue that AI has the potential to exacerbate existing inequalities and create a new form of social hierarchy. They discuss the implications of this AI-driven power structure and propose policy interventions to mitigate its negative effects. The paper was published in 2022 and can be accessed here.

"Data-intensive Innovation and the State: Evidence from AI Firms in China" by Beraja, Yang, and Yuchtman (2022)

In this working paper, Beraja, Yang, and Yuchtman examine the relationship between data-intensive innovation and the role of the state, focusing on AI firms in China. The authors analyze the impact of government policies and regulations on the development and success of AI companies. They provide empirical evidence to support their findings and discuss the implications for other countries seeking to foster innovation in the AI sector. The paper was published in 2022 and can be accessed here.

"Automation Reaction – What Happens to Workers at Firms that Automate?" by Bessen, Goos, Salomons, and Van den Berge (2019)

Bessen, Goos, Salomons, and Van den Berge investigate the consequences of automation on workers in this research paper. They examine the employment and wage effects of automation at firms that adopt new technologies. The authors find that while automation leads to job displacement in the short term, it also creates new job opportunities in the long run. They discuss the importance of worker retraining and policy interventions to support workers affected by automation. The paper was published in 2019 and can be accessed here.

"Machine Learning, Explained" by Brown (2021)

This article by Brown provides a comprehensive explanation of machine learning, a subset of AI. The author breaks down the concepts and techniques used in machine learning and discusses its applications in various industries. The article aims to demystify machine learning and make it accessible to a wider audience. It was published by MIT Sloan in 2021 and can be accessed here.

Overall, these sources contribute to our understanding of the impact of AI and automation on society. They highlight the potential benefits and challenges associated with these technologies and provide insights into policy interventions and strategies to navigate the changing landscape of work and power dynamics.

Published on October 15, 2022

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