We envision an economy where dramatic advances in automation and computation go hand in hand with improved outcomes and economic security for workers. Our work includes technology development, organizational research and professional training to identify how workers and firms can thrive in a dynamic technological environment. The Initiative builds on the research findings and intellectual community of the Work of the Future Task Force.
Task Force websiteTechnology development: when engineers develop a new software tool or piece of equipment, they could make decisions that have downstream consequences for workers. For example, how much skill it requires to program a machine might affect the types of workers that can interact with the technology – and the wages they can demand. How can engineering research incorporate worker context and worker consequences into the technology development process?
Organizational practices: employers make management decisions, including technology adoption decisions, that affect the skills needed, the quality of the jobs they provide, and their competitiveness in the marketplace. Different organizations may organize work differently and even approach the same technology differently, leading to divergent worker outcomes. Research on how organizational practices shape job quality, and how technology affects workers, can inform engineering and management practice.
Innovation in training: firms consistently report difficulty recruiting and retaining workers with the right skills to compete. One challenge is how workers whose jobs are affected by technological change can continue to improve their skills to thrive in new technological environments. When firms adopt new technologies, there is frequently a new demand for training so employees can adapt to new tools and practices. When new technologies demand workers to develop new skills, what are the most effective ways to help workers learn and adapt?
Seed Fund to broaden the research community focused on automation and worker success
Employer program to grow industry and government partnerships
Policy white paper series translating research for government officials and the public
The steering committee includes MIT faculty Julie Shah (Aeronautics and Astronautics), David Autor (Economics), John Hart (Mechanical Engineering), and Erin Kelly (Work and Organization Studies).
Ben Armstrong (Industrial Performance Center) is the executive director.
Robot Adoption in Manufacturing: research from robotics engineers and social scientists shows that robot adoption in manufacturing is rare. But when firms adopt robots, it can be beneficial for worker productivity and job quality. In multidisciplinary research drawing on data from technology providers as well as manufacturers, we are exploring the obstacles facing robot investment in American factories with a particular focus on informing technology development and organizational decision-making.
Responsible AI: as firms develop artificially intelligent algorithms to automate decision-making or inform resource allocation, there are risks that AI — even if developed with the best intentions — could have unforeseen consequences for workers and communities. Drawing on lessons from philosophers and an ethics curriculum deployed in MIT classrooms, we are working with practitioners to introduce a structured process for mitigating the risks — and enhancing the benefits — of AI in the wild.
Automation in Healthcare: healthcare organizations are deploying new automation technologies to improve the productivity of back-office operations and enhance the quality of clinical practices. We are studying how these technologies are integrated into healthcare practices with a focus on the potential consequences of technological change for healthcare workers and patients.