Communications of the ACM

across these domains, as do the opportunities for transforming people’s lives and the challenges posed in each domain. Moreover, the challenges so identified ranged across the full spectrum of computer science, from hardware to human-computer interaction. For instance, improvements in safe, reliable hardware were determined to be essential for progress in transportation and home-service robots. Autonomous transportation, which the report projects, may “soon be commonplace,” is among today’s most visible AI applications; in addition to changing individuals’ driving needs, it is expected to affect transportation infrastructure, urban organization, and jobs. Experience with home-service robots illustrates the key role of hardware. Although robotic vacuum cleaners have been in home use for years, technical constraints and the high cost of reliable mechanical devices has limited commercial opportunities to narrowly defined applications; the report projects they will do so for the foreseeable future. For healthcare, the challenges so highlighted include developing mechanisms for sharing data, removing policy, regulatory, and commercial obstacles, and enhancing the ability of systems to work naturally with care providers, patients, and patients’ families. The report also identifies capabilities for fluent interactions and effective partnering with people as key to achieving the promise of AI technologies for enhancing education. Major challenges toward realizing the potential of AI to address the needs of low-resource communities include design of methods to cooperate with agencies and organizations working in those communities and the development of trust of AI technologies by these groups and by the communities they serve. Such challenges also arise in public safety and security. In the domain of employment and the workplace, while noting that AI-capable systems will replace people in some kinds of jobs, the report also predicts AI capabilities are more likely to change jobs by replacing tasks than by eliminating jobs. It highlights the role of social and political decisions in approaching a range of societal challenges that will arise as work evolves in response to AI technologies and argues these challenges should be addressed immediately.

2017 International Joint Conferences on Artificial Intelligence, the study panel identified the main messages of the report, to appear as callouts in the margins of the report.

The Report

The report aims to address multiple audiences, ranging from general public to AI researchers and practitioners, and thus to be both accessible and provide depth. As a result, it has a three-part hierarchical structure: executive summary, more expansive five-page overview summarizing the core of the report, and a core with further details. The core examines eight “domains” of typical urban settings on which AI is likely to have impact over the coming years: transportation, home and service robots, healthcare, education, public safety and security, low-resource communities, employment and workplace, and entertainment. The authors deliberately did not give much weight to positions they considered excessively optimistic or pessimistic, despite the prevalence of such positions in the popular press, as they intended the report to provide a sober assessment by the people at the heart of technological developments in AI.

For each domain the study panel investigated, the report looks back to 2000 to summarize the AI-enabled changes that have already occurred and then project forward through 2030. It identifies the availability of large amounts of data, including speech and geospatial data, as well as cloud computing resources and progress in hardware technology for sensing and perception, as contributing to recent advances in AI research and to the success of deployed AI-enabled systems. Advances in machine learning, fueled in part by these resources, as well as by development of “deep” artificial neural nets, have played a key role in enabling these achievements. The goal of the study panel’s forward-looking assessment, which we summarize briefly, was to call attention to the opportunities the study panel anticipated for AI technologies to improve societal conditions, lower the barriers to realizing this potential, and address the realistic risks it likewise anticipated in applying AI technologies in the domains it studied.