A Future with Artificial Intelligence — Research Roundup January 2018


*The Research Roundup is a semi-regular list of outside research we have found interesting and think is worth sharing. The views and conclusions of the papers’ authors do not necessarily reflect the opinions of anyone affiliated with TPI.*

This month, TPI is gearing up for our next event, “Terminator or the Jetsons? The Economics and Policy Implications of Artificial Intelligence,” on Thursday, February 22, 2018 – register today! In that spirit, this edition of Research Roundup includes pieces on the current and potential implications of artificial intelligence (AI) for the economy, public safety, and daily interactions. Authors Daron Acemoglu and Pascual Restrepo focus their attention on the effects of automation and artificial intelligence on the workplace, particularly on the demand for labor and wages. They find a tradeoff, of sorts: a decrease in the demand for labor for automated tasks and a corresponding increase in productivity in those tasks. Certain limitations, however, will complicate any transition towards AI in the workplace. Click through for a more detailed description of this work and others discussing a future with AI.


Artificial Intelligence, Automation, and Work

Discussion of: Artificial Intelligence and the Future of Growth

Privacy and Integrity Considerations in Hyperconnected Autonomous Vehicles

Punishing Robots: Issues in the Economics of Tort Liability and Innovation in Artificial Intelligence


Descriptions of papers below are edited abstracts from authors


Artificial Intelligence, Automation, and Work
Daron Acemoglu & Pascual Restrepo

The authors lay out a task-based framework within which they analyze the implications of automation and AI on the demand for labor, wages, and employment. The framework emphasizes the displacement effect created when machines and AI assume responsibility for tasks that human labor used to perform. The authors note, however, that the net employment effect of this displacement is not necessarily negative. Most immediately, it tends to reduce the demand for labor and wages. But this reduction is counteracted by increased productivity, which increases the demand for labor in other, non-automated, tasks. In turn, this productivity effect leads to additional capital accumulation and the deepening of automation (improvements of existing machinery), both of which further increase the demand for labor.

The authors also note a powerful countervailing force against automation, the creation of new labor-intensive tasks. Such tasks reinstate labor in new activities and tend to increase the labor share, balancing out the impact of automation Finally, the authors’ framework highlights the constraints that make it difficult for the economy to adjust to automation and temper any gains in productivity. In particular, a mismatch between the skills required to leverage new technologies and a high rate of change and innovation in automation technologies, which makes it difficult for the labor force to keep up.


Discussion of: Artificial Intelligence and the Future of Growth, by Philippe Aghion, Benjamin Jones, and Charles E. Jones^
Patrick Francois
Political Economy is important for two reasons. One, if the scientists’ predictions pan out, we are on the cusp of a world where humans will be largely redundant as an economic input. How we manage the relationship between the haves (who own the key inputs) and the have-nots (who only own labor) is going to be a key aspect of societal health. Successful ones will be inclusive in the sense of sharing rents owned by the haves with the have-nots. This is quite obvious. Less obviously, managing the relationship between high-level human decision-making and our machine servants will involve humans at many levels, no matter how productive machines become. So, even in the instance where machines become better at doing all human production, there will still be work for humans in what could be broadly referred to as the political realm.

^The Abstract of the piece to which Francois refers, Aghion, Jones, and  Jones, published in NBER Working Paper Series January 2017, is available below.

This paper examines the potential impact of artificial intelligence (AI) on economic growth. The authors model AI as the latest form of automation, a broader process dating back more than 200 years. Electricity, internal combustion engines, and semiconductors facilitated automation in the last century, but AI now seems poised to automate many tasks once thought to be out of reach, from driving cars to making medical recommendations and beyond. How will this affect economic growth and the division of income between labor and capital? What about the potential emergence of “singularities” and “superintelligence,” concepts that animate many discussions in the machine intelligence community? How will the linkages between AI and growth be mediated by firm-level considerations, including organization and market structure? The goal throughout is to refine a set of critical questions about AI and economic growth and to contribute to shaping an agenda for the field.


Privacy and Integrity Considerations in Hyperconnected Autonomous Vehicles
Stamatis Karnouskos & Florian Kerschbaum
Rapid advances in technology are evident in the emergence of cyber-physical systems that pertain to several domains of our society. In transportation, we see the emergence of self-driving vehicles that utilize a multitude of sensors and intelligent learning techniques to navigate autonomously. Such vehicles are complex mobile cyber-physical systems and, due to their sensor and intrinsic intelligence, are able to collect, analyze, and capitalize upon an unprecedented amount of fine-grained data and collaborate in real time with multiple stakeholders. Although such rich data can play a key role in data-driven economies of scale, they raise questions with respect to privacy- and integrity-dependent scenarios. In this work, the feasibility of ensuring integrity and safety while preserving privacy in the emerging hyperconnected vehicle scenarios is discussed. An exemplary case study on real-time vehicle interactions pertaining to map updates exemplifies the combination of privacy-enhancing technologies and integrity-protecting mechanisms.


Punishing Robots: Issues in the Economics of Tort Liability and Innovation in Artificial Intelligence
Alberto Galasso & Hong Luo
A tort is an action that causes harm or loss, resulting in legal liability for the person who commits the act. The role of the tort system is to deter people from injuring others and to compensate those who are injured. Two important classes of tort law are product liability law that protects customers from defective or dangerous products, and medical malpractice law that governs professional negligence by physicians. Tort suits often make the headlines because of their large damages awards. For example, General Motors recently paid about $2.5 billion in penalties and settlements in a case involving faulty ignition switches linked to 124 deaths. Rapid advancements in the field of artificial intelligence and robotics have led to lively debates over the application of tort law to these technologies, several of which are discussed in this piece.