The online interactive magazine of the Association for the Advancement of Artificial Intelligence

By Kevin Crowston

AI technologies are characterized by high levels of autonomy and the ability to learn and interact with other systems, including humans. While these systems do not possess generalized intelligence, they are increasingly capable of performing tasks that have traditionally been the sole purview of humans. These abilities enable them to perform work with often greater speed, less cost and sometimes more accuracy than humans. The speed at which AI is developing has led many to rhetoricize the relation between AI-enabled systems and work to be a story of replacement: in the future, many people will be put out of work by automation. But this perspective is too simplistic: tasks that can be automated rarely stand in isolation and are defined by context. In other words,  the deployment of AI technologies in the future will likely require humans to collaborate with AI systems, and this realization highlights the need for more sustained research on how to design such systems.

Recently, a set of scholars came together for a workshop at the AAAI Fall Symposium Series to discuss the connection between AI and work from a variety of different perspectives. The workshop was sponsored by the National Science Foundation (NSF) funded Research Coordination Network on Work in the Age of Intelligent Machines ( The workshop featured a number of participant talks that addressed general changes in labor markets as well as specific changes in job design; the role of labour unions in designing technology, training and job transitions; and designs for systems that couple the labour of humans and artificial intelligence in different ways.

A final talk addressed the use of AI to promote just and sustainable work, drawing from knowledge about communities of artisans as well as knowledge about computer-supported cooperative work. This talk and the others led to discussion around redesigning work and rethinking incomes with bold ideas to improve the lives of workers and provide more interesting jobs with more meaning, purpose and dignity. A goal could be living wages for people to do things they love, for example, in the arts.

At the heart of the symposium were small group discussions in which teams of interdisciplinary researchers discuss the design of research to answer the following four questions:

  1. How do we design effective human-AI teaming?
  2. What does participatory design look like for AI in the context of work?
  3. What training do people need to be able to work successfully with smarter systems?
  4. How will AI, algorithms and/or robots influence the work practice in creative industries, e.g. art, entertainment or literature?

These discussions were aimed at identifying generative research gaps that could lead to submission of proposals to NSF and other agencies interested in funding research about the potentially transformative potential of AI on human work. An NSF program manager in attendance discussed specific funding opportunities related to the NSF’s Future of Work at the Human-Technology Frontier program.

The symposium was organized by Kevin Crowston (Syracuse University), Ingrid Erickson (Syracuse University), Larry Medsker (George Washington University) and Jeffrey V. Nickerson (Stevens Institute). Further information on the content of the workshop can be found at