Machine Learning and Artificial Intelligence in Strategy Research

Abstract

The introduction and spread of artificial intelligence and machine learning has made possible the mass-automation of many aspects of management. Yet the implications of this change for both firms and individuals are only now beginning to be explored in strategic management and related research. In particular, several important issues relating to the interface between humans and artificial intelligence are beginning to manifest, including the role of complementarities between existing human capital and the machine learning/artificial intelligence technologies, the role of artificial intelligence relative to human judgement, and if and how this role varies across contexts. In this symposium, we bring together a collection of four papers that attempt to address some of these issues. Together, these complementary presentations will shed new light on some of the core issues that firms are likely to face as machine learning and artificial intelligence become increasingly important. Different Strokes for Different Folks: Complementarities between Human Capital and Machine Learning Presenter: Prithwiraj Choudhury; Harvard U. Presenter: Evan Penniman Starr; U. of Maryland, College Park Machine Intelligence vs. Human Judgement in New Venture Finance Presenter: Christian Catalini; MIT Sloan School of Management Presenter: Ramana Nanda; Harvard U. Presenter: Chris Foster; Harvard Business School Using Artificial Neural Networks to Predict Firm Growth: Insights from a Prediction Exercise Presenter: Natarajan Balasubramanian; Syracuse U. Presenter: Akshay Anjani; Syracuse U. Presenter: Mohan Chilukuri; Syracuse U. Go West, Young Firm: The Value of Entrepreneurial Migration for Startups and Founders Presenter: Jorge Guzman; MIT Sloan School of Management