MIT FutureTech are hiring for four postdoc positions. Applications close the 3rd of January 2024.

We also have open roles for operations and project management, junior research scientists and research assistants. 

Please apply or share as relevant.

Why apply or share?

• Our work to understand progress in computing and artificial intelligence, and its implications, is highly relevant to understanding and mitigating the risks of AI. This write-up provides a good overview of some of our interests and areas of focus. 
• We are one of Open Philanthropy's 10 largest Global Catastrophic Risk, and AI Governance grantees. 
• These roles are a good fit for people interested in impact in AI Governance via these aptitudes: research, macrostrategy, distillation and/or policy development and communication. 

Job Description

Dr. Neil Thompson, Director of MIT FutureTech, seeks to hire Postdoctoral Associates for the following research projects:

• AI scaling and its impacts on what can be automated

The ever-growing AI models being released by OpenAI and its other competitors are a natural consequence of AI scaling laws, which characterize a potential roadmap for the path of growth in AI capabilities as a function of the dedicated data and computational resources (see https://ide.mit.edu/insights/whats-next-ai-scaling-and-its-implications/). In this work, we will map the economic consequences of these scaling laws, in particular the capabilities and skills that these models will acquire and the automation consequences (e.g. in robotics).

• AI bottlenecks

Computer scientists and economists disagree profoundly about the extent to which AI may lead to the acceleration of growth in aggregate productivity and in consumer welfare across advanced economies. On the one hand, computer scientists point to the rapid improvements in the performance of AI systems captured, for instance, by the scaling laws that have governed these improvements over the past decades. On the other hand, economists emphasize the presence of bottlenecks, such as production complementarities with other scarce factors, that may diminish productivity gains. In this work, we will empirically explore which of these bottlenecks do, or do not, have the potential to slow the pace of automation or stymie its benefits.

• Analyzing AI job automation at the process level

Current analyses of job automation focus on task level feasibility.  But such analyses ignore the interdependencies between tasks. If a task is a bottleneck in a production process, then automating it can increase productivity across many workers. Conversely, automating some others tasks may provide almost no benefit.  In this joint work with Martin Fleming (former IBM chief economist) and Christophe Combemale (CMU professor) we explore how automation is occurring in the context of business processes and how this changes conclusions about the Future of Work.

• Estimating the productivity effects of IT improvement

Measuring the effects of IT on firm performance can substantially understate the real effect of IT (“You can see the computer age everywhere but in the productivity statistics” -Solow). We believe that this is in large part due to poor measures of quality of IT inputs: when researchers measure IT inputs using spending without properly accounting for changes in IT performance) and when important categories of improvement are missing (algorithm improvement). We are seeking an IO economist with an interest in using Census data (or similar) and FutureTech’s detailed data sets on IT progress to re-estimate these effects. The postdoc may also apply some of our new research on the potential of quantum computing for firms

In addition to researching these issues, the post-doc will be expected to become a team leader, supervising and mentoring younger students.

Qualifications

• PhD or equivalent[1] in economics or related field
• Demonstrated expertise in computing / AI
• Interest in working in an interdisciplinary lab with computer scientists and engineers
• Strong data analysis skills, including statistical / econometric training
• Proficiency with a modern programming language[2], e.g. Python, R
• Solid English communication skills (verbal and written)
• Desire and skill (e.g. organizational abilities) to work in teams

The post-doc’s primary appointment would be at the MIT Sloan School of Management, and would have a secondary appointment at the MIT Computer Science and Artificial Intelligence Lab.

Salary

$70,000 per year, plus benefits.

To apply

By January 3^rd  2024, send an email to Dr. Neil Thompson (neil_t@mit.edu) with the following materials:

• CV
• Job market paper (or other sample of previous research)
• Sample of code
• Cover letter discussing the applicant’s experience and which research projects would be of interest

Selected candidates will be first interviewed in January via zoom.

About MIT FutureTech

Led by Dr. Neil Thompson, MIT FutureTech is an interdisciplinary group of computer scientists, engineers, and economists who study the foundations of progress in computing and Artificial Intelligence: the trends, implications, opportunities and risks.

Our work is supported by grants from Open Philanthropy, the National Science Foundation, Microsoft, Accenture, IBM, the MIT-Air Force AI accelerator, and the MIT Lincoln Laboratory.

The following are examples of our recent work:

• How industry is dominating AI research
• The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not)
• A workshop on AI scaling and its implications for AI development, automation, and more
• The Great Inflection? A Debate About AI and Explosive Growth
• There’s plenty of room at the Top: What will drive computer performance after Moore’s law?
• Deep Learning's Diminishing Returns: The Cost of Improvement is Becoming Unsustainable
• America’s lead in advanced computing is almost gone
• The Decline of Computers as a General Purpose Technology: Why Deep Learning and the End of Moore’s Law are Fragmenting Computing
• How Fast Do Algorithms Improve?

About Dr. Neil Thompson, the Director of MIT FutureTech - futuretech.mit.edu/team/neil-thompson

Dr. Thompson is the Director of MIT FutureTech. Prior to starting FutureTech, Dr. Thompson was a professor of Innovation and Strategy at the MIT Sloan School of Management.  His PhD is in Business & Public Policy from Berkeley.  He also holds Master’s degrees in: Computer Science (Berkeley), Economics (London School of Economics), and Statistics (Berkeley).  Prior to joining academia, Dr. Thompson was a management consultant with Bain & Company, and worked for the Canadian Government and the United Nations.

About the MIT Initiative on the Digital Economy (IDE) - ide.mit.edu

The MIT Initiative on the Digital Economy is a team of internationally recognized thought leaders and researchers examining how people and businesses work, interact, and prosper in a time of rapid digital transformation.  It is housed at the MIT Sloan School of Management.

About the MIT Computer Science and Artificial Intelligence Lab (CSAIL) - www.csail.mit.edu

CSAIL is one of the world’s top research centers for computer science and artificial intelligence (currently ranked #1).  It has hosted 9 Turing awards winners (the “Nobel Prize of Computing”) and has pioneered many of the technologies that underpin computing.