Dynamic Contracting with a Forthcoming Technology of Automation

This paper investigates the microfundation of the high-skill jobs’ automation in a continuoustime agency framework. In this model, a project is either driven by the agent’s unobservable effort or by a forthcoming technology of automation that arises randomly and that can substitute to the agent. We derive an optimal contract that secures the principal-agent relationship at early-stage and then eases the automation through punishment when the technology becomes available. As a consequence, only the automation of successful agents is postponed as the instantaneous termination of the contract would be too costly. Our model predicts that the less successful agents are the first to be substituted by the technology and also that the agent’s lump-sum bonuses decrease after the technological advent. ∗I am indebted to my advisor Stéphane Villeneuve for his inestimable guidance. I would like to thank Sebastian Gryglewicz, Alexander Guembel, Sébastien Pouget, Sebastian Pfeil and Florian Hoffman for useful discussions and valuable comments. I am grateful to the participants of the TSE/TSM Ph.D. finance workshop (TSE, may 2018), the PhD Lunch Seminars Rotterdam (EUR, November 2018), and the 1 LUMS / TSM / WHU Doctoral Workshop (Toulouse, march 2019) where this paper was presented. All remaining errors and insufficiencies are mine. Address correspondence to Vincent TENA, TSM Doctoral Programme, 2 rue du doyen Gabriel Marty, J301, 31042 Toulouse – France; Phone Number: +33 (0)5 61 63 38 62; e-mail: vincent.tena@tsm-education.fr The recent advancements in artificial intelligence and robotics are tremendous, and their impacts on society is a key theme of several books (Brynjolfsson and Mcafee, 2016 or Ford, 2016 among others). Their authors predict in-depth changes in the economy and the emergence of numerous solutions to replace workers on a wide range of activities. The novelty is that high-skill individuals are more and more prone to be automated. According to a recent study by McKinsey, the current state of technology enables the automation of a large part of activity exerted by “even those in the highest-paid occupations (for example, financial planners, physicians, and senior executives)”. For Acemoglu and Restrepo (2018a), “the automation of the complex tasks in which high-skill workers specialize [. ] is on its way to becoming a potent force in the US labor market”. Several striking illustrations of this phenomenon have been offered recently. One of them concerned BlackRock, currently the world’s largest asset manager, when its CEO decided in 2017 to “change its ecosystem”. As a result, 13 % of the portfolio managers were dismissed and replaced by stock picking algorithms. Another example concerns Deep Knowledge Ventures (DKV), an Hong-Kong based venture capital firm. Since 2014, it holds in its board of directors an algorithm named Vital that makes investment recommendations based on big data and that also votes on every investment decision as any other of the five human board members. According to a Harvard Business Review article, “the potential of AI in decision-making will grow steadily”, leading to more automation of management activities in the future. Our paper investigates the microfundation of the automation of high-skill jobs, a phenomenon mainly studied in the literature at a macro-level in labor-economics papers such as Acemoglu and Restrepo (2018a) or Arntz, Gregory, and Zierahn (2019). In order to do so, we focus mainly of firm subject to moral hazard, a very expensive financial friction, as Chui, Manyika, and Miremadi (2015) https://www.nytimes. com/2017/03/28/business/dealbook/blackrock-actively-managed-fundscomputer-models.html https://www.bbc. com/news/technology-27426942 https://www.hbrfrance. fr/chroniques-experts/2019/01/23992-ce-que-lintelligence-artificielle-vachanger-dans-la-fonction-de-manager/