Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.


AI for Good: Maximizing the economic and societal benefits of AI

May 3rd, 2017 / in Announcements, research horizons, Research News, robotics / by Helen Wright

Contributions to the following blog were made by former CCC Chair Greg Hager and Tom Kalil, former Deputy Director for Technology and Innovation in the Office of Science and Technology Policy.  

It is clear that Artificial Intelligence is having an impact on society and will continue to do so in the foreseeable future, in ways we cannot even imagine today. Through its AI and Robotics Task Force, the Computing Community Consortium (CCC) seeks to articulate the unique research challenges and under-recognized opportunities in AI. This includes a recent addition to the website entitled “AI for Good: Maximizing the economic and societal benefits of AI” authored by Tom Kalil, former Deputy Director for Technology and Innovation in the Office of Science and Technology Policy. Kalil discusses the building blocks of a strategy to maximize the economic and societal benefits of AI, with a focus on identifying and pursuing compelling, ambitious and achievable goals.

Kalil first outlines an overarching strategy for the responsible and beneficial development of AI that comprises six components:

  • Advancing the state-of-the-art of the technology through basic and applied research;
  • Understanding and pro-actively addressing risks and ethical dimensions (e.g. AI safety, AI and cybersecurity, transparency and fairness of algorithmic decision-making);
  • Expanding the workforce needed to both develop and use AI;
  • Supporting activities such as scenario planning, given the inherent uncertainty of future impacts of AI, especially over the medium and long-term;
  • Engaging the public and other key stakeholders in meaningful discussions and collaborations; and
  • Identifying mechanisms to advance the economic and societal benefits of AI.

To drive this strategy, Kalil proposes an actionable, challenge-based strategy for advancing AI which must provide answers to the following three questions:

  • What is the challenge and how should success be measured?
  • What are actions that could be taken to make these challenges achievable?
  • Who are the actors who can enable progress?

A sampling of the challenges he puts forward include:

  • AI and Workforce: Increase the wages of non-college educated workers (or unemployed/under-employed veteran’s) by $10,000 in 6 months or less, by enabling them to master a skill that is a ticket to a middle class job.
  • AI and Infrastructure: Increase the capacity of America’s roadways by 50% while reducing the number of accidents and injuries due to traffic accidents.
  • AI and Healthcare: Reduce error rates in medical diagnostics by 80 percent.
  • AI and Education: Develop intelligent toys that increase the school readiness (e.g. executive function, vocabulary size) of children from low-income families.
  • AI and Energy: Significantly increase the energy efficiency of residential and commercial buildings and industrial systems.
  • AI and Aging: Increase the capacity of senior citizens to live independently in “smart” homes by at least 5 years.

He notes that for many AI applications, market forces will be sufficient to drive the development, validation and deployment of the technology. For those that are not an alternative is to identify concrete, mutually reinforcing, and high-impact public and private actions. A collaboration between different sectors and actors (e.g. companies, foundations and philanthropists, non-profits) and public outreach is needed in order to enable progress and advance AI for Good.

To learn more, please see the report here.

AI for Good: Maximizing the economic and societal benefits of AI