Carnegie Mellon University

The Future of Work Initiative

Machine Learning. Artificial Intelligence. Autonomous Vehicles.

University laboratories and corporate R&D centers are investing heavily in these disruptive technologies. The next generation of machines have the potential to transform our society, redefining the way human beings work, play, earn a living, and interact with the larger economy.

The Block Center's Future of Work Initiative at Carnegie Mellon University’s Heinz College is dedicated to rigorous scientific investigation of the impact of emerging technologies on workers at all skill levels, as well as the communities they inhabit.

The Future of Work Initiative charts the impact of disruptive innovation on the U.S. labor market, develops policy interventions that ensure the benefits of innovation are more widely shared, and leverages advanced technologies to address the social and economic needs of those being left behind as a result of technological change.

Faculty Leads

Linda Argote head shot

Linda Argote
Thomas Lord Professor of Organizational Behavior and Theory; Director, Center of Organizational Learning, Innovation and Knowledge
Lee Branstetter

Lee Branstetter
Professor of Economics And Public Policy

majd sakr head shot

Majd Sakr
Teaching Professor, Computer Science

Rahul Telang

Rahul Telang
Professor of Information Systems

In the News

Block Build Back Better grant awardee, Ashley Orr featured in Next Pittsburgh for her work to help workers gain tech jobs

Photo by Alexis Wary
Ashley Orr, Heinz College PhD candidate and Block Build Back Better grant awardee was featured in Next Pittsburgh for her "growth mindset training," in which individuals learn to adapt their skills to new tasks and overcome fears and challenges to become productive in new careers. 
Article by Joyce Gannon

Read the full article here

Work of Future of Work faculty leader, Lee Branstetter, cited in Economist - "A golden age for workers"

Image by Mikel Jaso
In the cited paper, Branstetter with CMU colleague Dean Alderucci had found that firms in the United States that used even basic AI had 25% faster emloyment growth and 40% faster revenue growth than their competitors that did not use AI.

Read the full article here
(Requires subscription to The Economist)

How AI Changes Work and What We Should Do About It
- Prof. Tom Mitchell

Can AI Make Education Great Again?
- Prof. Lee Branstetter


Jobs in an Appalachian Clean Energy Transition: A Regional Skills-Matching

A worker in a reflective vest and hard hat carries a solar panel

This project is developing an integrated research effort to characterize job opportunities in a regional transition to clean energy, with a focus on mapping the skill sets of today’s underemployed and vulnerable populations to employment opportunities in a decarbonizing regional economy. Focusing on ten counties in Southwestern Pennsylvania, the team will perform this mapping under scenarios that assume growth in different activities in a clean energy economy.

Faculty team:

Rick Stafford
Valerie Karplus





Developing Automation Policy to Ensure Worker Health and Safety in the Hospitality Sector

Two caterers prepare platters of food in industrial kitchen

This research team, based in the Human-Computer Interaction Institute, is continuing work to co-design automation implementation policies for workers and customers in the hospitality industry to ensure their health and safety. The work is carried out in cooperation with labor union UNITE HERE and the U.S. Occupational Safety and Health Administration (OSHA). [Read the full story.]

Faculty team:

Jodi Forlizzi
Sarah Fox
Chinmay Kulkarni



Using Patent DATA to Forecast Disruption

machine learning concept of code and computer hardware creating the outline of a human head

While advancements in artificial intelligence and robotics have the potential to spur growth and create new job categories that don’t even exist yet, the resulting automation of job tasks will likely have dramatic impacts on the current labor market—the real questions are where and to what extent those impacts will be felt. By applying machine learning to patent filing data, Professor Branstetter and the Future of Work Initiative are working with other CMU experts to map what jobs and industries are likely to see the most intense applications of artificial intelligence—and where policymakers need to focus their attention. [Read the full story.]

So far, the team has issued a report detailing which firms have filed for the most AI-related patents in the U.S., which patent subcategories have seen the most activity, and where geographically those patents are originating. [View the report.]


traffic streaks in a busy urban highway

Citizens with lower levels of education and skill often confront challenges when seeking employment. The jobs best suited for their skills may be geographically distant from their homes, and the existing public transportation system may not provide them with an easy way of commuting to those jobs. Effective cooperation between governments, regulatory authorities, and transportation networking companies could remove those barriers and make ridesharing systems available to disadvantaged citizens. 

To assess citizen response to a public ridesharing policy, the Future of Work Initiative is currently running field experiments in Pittsburgh and adjacent areas of Allegheny County.

Cognitive Tutors Make Gains in Education

female students working on notebook computers

Students learn in different ways and at different rates. Intelligent cognitive software “tutors,” which have been developed and successfully tested for Algebra I, can analyze student errors, learn what the student does not understand, and provide individualized practice problems and instruction to remedy that lack of understanding. If intelligent tutors could achieve that same effectiveness documented in Algebra I across other subjects, it could revolutionize the American workforce. 

Bringing together technology experts in the education domain, quantitative social scientists, and behavioral economists, this project seeks to develop strategies to incentivize Pennsylvania school districts to experiment with and adopt these potentially game-changing technologies.

the economic consequences of ai and robotics

AI concept with woman

While much of the discourse surrounding machine learning and automation pertains to disrupting employment, these advancements also have the capacity to reskill and re-employ displaced employees. To this end, Professor Tom Mitchell aims to dispel common misconceptions about the future of work by recharacterizing the nature of work itself as a bundle of tasks. By reframing work in this way, employers and policymakers can more holistically approach the impact of automation on job design, compensation and organization.

This project has resulted in a report for the National Academy of Science, currently being updated and built upon, as well as a paper on the Economic Consequences of Artificial Intelligence and Robotics.

Diversity and Inclusion in Open-Source Software Development

Open source diversity and inclusion

The gender gap in technology is widening. In 1985, 37% of computer science Bachelor's degree recipients were women. However, by 2017, this percentage dropped to just 19%. Although women make up about 57% of the U.S. workforce, they only hold about 26% of professional computing occupations. In particular, only 6% of the computing workforce is comprised of Asian women, while African American women and Hispanic women only make up 3% and 2% of this workforce, respectively. 

As many fields become increasingly digitized, the open-source software development ecosystem has become an important means of demonstrating technical competence while pursuing career opportunities. However, women's participation in this ecosystem is relatively low. To this end, we aim to develop novel socio-technical interventions to support women's participation in open-source endeavors to close both the gender and skill gaps in the computing industry.

This project has received  follow-on funding from the National Science Foundation and the Sloan Foundation. [Hear more from Laura Dabbish.]

Affiliated Faculty:
- Laura Dabbish, Associate Professor, Human-Computer Interaction Institute
- James Herbsleb, Professor, Institute for Software Research

Job creation in the autonomous trucking industry


Autonomous vehicles are poised to significantly disrupt the professional driving industry, particularly in the long-haul trucking sector. While this automation is likely to focus more on specific tasks in the freight transport process, rather than on the complete automation of entire jobs, there is still much to discover in the areas of which tasks are most technologically feasible to automate, which new tasks might be created as a result of automation, and which technologies will most safely and reliably support this automation.

Through collaboration with economists and industry professionals, we intend to characterize the future of trucking. In particular, this team is investigating how these changes will provide human operators with new tasks and, by extension, create new jobs while reducing the labor costs and environmental footprint associated with freight transport.

This project has resulted in a paper, published in Nature: Humanities and Social Sciences Communications, and was covered by Bloomberg News.

Affiliated Faculty:
- Alexander Davis, Assistant Professor of Engineering and Public Policy
- Parth Vaishnav, Assistant Research Professor of Engineering and Public Policy
Venkat Viswanathan, Assistant Professor of Mechanical Engineering

Gigs, risks and skills in the Digital Economy

Construction worker looks into distance

The gig economy has become a major aspect of the labor landscape and has disrupted numerous markets, from transportation to healthcare to meal delivery. While the income derived from emergent online labor markets often varies significantly, decreased job security and higher unemployment rates have nonetheless drawn workers to gig platforms. 

We are examining the ways in which temporary work markets, such as gig platforms, could be leveraged to provide skills training for blue-collar workers. This research aims to inform the kinds of policies and institutions that can support income risk mitigation for employees, as well as assess the effect of numerous factors, such as training, pay level, income uncertainty and job risk, on employee productivity, career paths and well-being.

This project has received additional follow-on funding from the Sloan Foundation.

Affiliated Faculty:
- Geoffrey Parker, Professor of Engineering, Dartmouth College
Erina Ytsma, Assistant Professor of Accounting

Better Videos for Better Education


While video content has been a central component of both online and in-class learning for decades, few existing studies have characterized what exactly makes instructional videos an effective pedagogical tool or how to finetune this content to better address discrepancies in student backgrounds and learning styles. 

We are addressing this gap in the literature by analyzing how both the content and associated pedagogy of educational videos contribute to student achievement. This research will use tri-dimensional mapping between features of educational videos, students' characteristics and attained performance gains in order to understand how technological changes in the educational market can positively impact student outcomes.

Affiliated Faculty:
- Pedro Ferreira, Associate Professor of Information Systems
Michael D. Smith, Professor Of Information Technology And Marketing

Entrepreneurship and the Platform Economy


Economic uncertainty can be a strong deterrent from the development of new business ventures. As the platform economy, or gig economy, has provided an alternative to the standard 40-hour workweek, gig labor could potentially provide workers with the flexibility and income stability necessary to promote entrepreneurial activity. 

We are investigating whether platform-based jobs can incentivize and support entrepreneurship by providing nascent business owners with an additional source of income. In addition to characterizing the size and scope of the platform economy, this research group is evaluating the impact of gig employment on both income volatility and entrepreneurial activity. These insights could inform the development of policy to support entrepreneurship and protect gig workers.

Affiliated Faculty:
- Matthew Denes, Assistant Professor of Finance
Spyridon Lagaras, Assistant Professor of Finance, University of Pittsburgh

Margarita Tsoutsoura, Associate Professor of Finance and John and Dyan Smith Professor of Management and Family Business, Cornell University