Visioning Activity

Artificial Intelligence Roadmap

One cannot get through the day without some acknowledgment of Artificial Intelligence (AI), whether it’s something in the news or a direct interaction with an AI system. However, there is still much basic research to be done in the area.

In fall 2018, the Computing Community Consortium (CCC) initiated an effort to create a Roadmap for Artificial Intelligence, led by Yolanda Gil (University of Southern California and President-Elect of AAAI) and Bart Selman (Cornell University). The goal of the initiative was to identify challenges, opportunities, and pitfalls, and create a compelling report that will effectively inform future priorities—including future AI R&D Investments, as highlighted by National Science Foundation (NSF) Director France Cordova in her July 2018  monthly address. This effort is similar to one of the CCC’s first activities, the Robotics Roadmap, which helped to launch the National Robotics Initiative in 2011 and the subsequent 2016 Robotics Roadmap and NRI 2.0.

In order to obtain broad community input for the Roadmap, a series of three workshops were held in the Fall/Winter of 2018/2019. Feedback from the community was gathered at a Townhall at AAAI and via numerous other communication channels to different groups of stakeholders. The resulting AI Research Roadmap draft is now available for comments below.

AI Research Roadmap – Request for Comments

The Computing Community Consortium (CCC) requests comments by May 28, 2019 on a draft of A 20-Year Community Roadmap for AI Research in the US. Learn more about the roadmapping process below.

The 20-year AI Research Roadmap that was produced by this community effort includes the following specific recommendations:

I — Create and Operate a National AI Infrastructure to serve academia, industry, and government through four interlocking capabilities:

  1. Open AI platforms and resources: a vast interlinked distributed collection of “AI-ready” resources (curated high-quality datasets, software libraries, knowledge repositories, instrumented homes and hospitals, robotics environments, cloud-scale computing services, etc.) contributed by and available to the academic research community, as well as to industry and government. Recent major innovations from companies demonstrate that AI breakthroughs require large-scale hardware investments and open-source software infrastructures, both of which require substantial ongoing investments.
  2. Sustained community-driven AI challenges: organizational structures that coordinate the formulation of grand-challenge problems by AI and domain experts to drive research in key areas, building upon—and adding to—the shared resources in the Open AI Platforms and Facilities.
  3. National AI Research Centers: physical and virtual facilities that bring together Faculty Fellows from a range of academic institutions and Industry Fellows from industry and government in multi-year funded projects focused on pivotal areas of long-term AI research.
  4. Mission-Driven AI Laboratories: living laboratories that provide sustained infrastructure, facilities, and human resources to support the Open AI Platforms and the AI Challenges, and work closely with the National AI Research Centers to integrate results to address critical AI challenges in vertical sectors of public interest such as health, education, policy, ethics, and science.

II  — Re-conceptualize and Train an All-Encompassing AI Workforce, building upon the elements of the National AI Infrastructure listed above to create:

  1. Development of AI Curricula at All Levels: guidelines should be developed for curricula that encourage early and ongoing interest in and understanding of AI, beginning in K-12 and extending through graduate courses and professional programs
  2. Recruitment and Retention Programs for Advanced AI Degrees: including grants for talented students to obtain advanced graduate degrees, retention programs for doctoral-level researchers, and additional resources to support and enfranchise AI teaching faculty
  3. Engaging Underrepresented and Underprivileged Groups: programs to bring the best talent into the AI research effort.
  4. Incentivizing Emerging Interdisciplinary AI Areas: initiatives to encourage students and the research community to work in interdisciplinary AI studies—e.g., AI-related policy and law, AI safety engineering, as well as analysis of the impact of AI on society—will ensure a workforce and a research ecosystem that understands the full context for AI solutions.
  5. Training Highly Skilled AI Engineers and Technicians: to support and build upon the Open AI Platform to grow the AI pipeline through community colleges, workforce retraining programs, certificate programs, and online degrees.

III – Core Programs for AI Research. The new resources and initiatives outlined above cannot come at the expense of existing programs for funding theoretical and applied AI. These existing programs—which provide well-established, broad-based support for research progress, for training young researchers, for integrating AI research and education, and for nucleating novel interdisciplinary collaborations—are critical complements to the broader initiatives described in this Roadmap, and they too will require expanded support.

CCC would value your comments on this draft report, including the findings and recommendations. Please submit your comments here by May 28, 2019.

Here is a link to the whole report (117 pages).

Here are links to individual sections:

     Title Page, Executive Summary, and Table of Contents (7 pages)

  1. Introduction (5 pages)
  2. Major Societal Drivers for Future Artificial Intelligence Research (4 pages)
  3. Overview of Core Technical Areas of AI Research Roadmap: Workshop Reports (72 pages)

    1. Workshop I: A Research Roadmap for Integrated Intelligence (19 pages)
    2. Workshop II: A Research Roadmap for Meaningful Interaction (27 pages)
    3. Workshop III: A Research Roadmap for Self-Aware Learning (26 pages)
  4. Major Findings (4 pages)
  5. Recommendations (22 pages)
  6. Conclusions (1 page)
  7. Appendices (participants and contributors) (2 pages)

Workshops (invitation-only)

November 2018 – Integrated Intelligence
Co-Chairs: Marie desJardins (Simmons) and Ken Forbus (Northwestern University)

January 2019 – Interaction
Co-Chairs: Kathy McKeown (Columbia University) and Dan Weld (University of Washington)

January 2019 – Learning and Robotics
Co-Chair: Fei Fei Li (Stanford) and Tom Dietterich (Oregon State)

Townhall: A 20-year Roadmap for AI Research

On January 28th, roadmap chairs Yolanda Gil and Bart Selman, along with workshop chairs Marie deJardins, Ken Forbus, Kathy McKeown, Dan Weld, and Tom Dietterich, presented the discussions and findings of the workshops during a townhall meeting at AAAI-19. Watch the full video of the presentation and Q&A on the townhall webpage.

Report Timeline

May: Draft report released to the community and community feedback collected

June: Released to the community



Steering Committee

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Previous Similar Activities

Robotics Roadmap – In 2009, the CCC released A Roadmap for US Robotics, From Internet to Robotics (Robotics Roadmap). The Robotics Roadmap explored the capacity of robotics to act as a key economic enabler, specifically in the areas of manufacturing, healthcare, and in the service industry, 5, 10, and 15 years into the future and was influential in developing 2011’s National Robotics Initiative (NRI). An updated version of the Robotics Roadmap was released in November 2016 and it expands on the topics discussed in the 2009 roadmap as well as addressing the areas of public safety, earth science, and workforce development. You can read the full 2016 roadmap here.

Related Materials

NITRD Working Group – On June 27, 2018, OSTP and the newly formed Select Committee on AI approved the formation of a new NITRD AI R&D IWG.

National Artificial Intelligence Research And Development Strategic Plan– Published in October 2016