The economics of Machine Learning: a microeconomic model of customer-firm interaction

Artificial Intelligence (AI) and Machine Learning (ML) are disruptive technologies expected, in the years to come, to be applied to a variety of products and services from several industries. Because of their tight bond with data, AI and ML will result in a change in customers-firm interplay, making necessary to address the economic impact of these technologies, so that policymakers can act to protect the customer's interest, especially in terms of data sharing. This thesis is an attempt to create a microeconomic model of customer-firm interaction, with the firm offering a product featuring Machine Learning properties and the customer sharing data and personal information, an essential ingredient in the creation of value from smart algorithms. The customer-firm interaction is therefore modeled to take place in two interconnected markets: one for the product and the other for the customer data. The firm is assumed to be a monopolist first and a social optimizer later, so that the comparison clarifies which solution (under which conditions) is to be preferred from a consumer perspective.