Stanford University


Effects of AI, Data-Driven Decision Making and Management Practices on Inequality and Firm Performance


Erik Brynjolfsson
John Van Reenen
Kristina McElheran


Accelerating advances in information technology capabilities and machine learning applications have led to burgeoning interest and concern with what this means for the future of production and work in the US economy. With permission of the US Census, the investigators now have an opportunity to include a set of new questions relating to machine learning and artificial intelligence, further details of data-driven decision making, and new dimensions of the management practices governing how work is organized in an increasingly digital age. By including a new wave of questions concerning “core” management and organizational practices (relating to the distribution of power within the enterprise), the investigators can collect longitudinal/panel data on these practices. This will make possible deeper and more rigorous analyses of the causal relationships among technology, management practices, corporate performance, inequality, growth and other metrics of interest.

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Stanford University