ΑΙhub.org
 

One Hundred Year Study on Artificial Intelligence (AI100) – a panel discussion at #IJCAI-PRICAI 2020


by
21 January 2021



share this:
IJCAI-PRICAI2020 LOGO

One of the panel discussions at IJCAI-PRICAI 2020 focussed on the One Hundred Year Study on Artificial Intelligence (AI100). The mission of AI100 is to launch a study every five years, over the course of a century, to better track and anticipate how artificial intelligence propagates through society, and how it shapes different aspects of our lives. This IJCAI session brought together some of the people involved in the AI100 initiative to discuss their efforts and the direction of the project.

Taking part in the panel discussion were:

  • Mary L Gray (Microsoft Research & Harvard University)
  • Peter Stone (University of Texas at Austin)
  • David Robinson (Cornell University)
  • Johannes Himmelreich (Syracuse University)
  • Thomas Arnold (Tufts University)
  • Russ Altman (Stanford University)

The goals of the AI100 are “to support a longitudinal study of AI advances on people and society, centering on periodic studies of developments, trends, futures, and potential disruptions associated with the developments in machine intelligence, and formulating assessments, recommendations and guidance on proactive efforts”.

Working on the AI100 project are a standing committee and a study panel. The first study panel report, released in 2016, can be read in full here. This reports provide insights from people who work closely in the field, in part to counter the external perceptions and the hype which surround AI, and to accurately portray what is going on in the field. The intended audience for this report is broad, ranging from AI researchers to the general public, from industry to policy makers.

The second study panel report, expected in late 2021, is now underway. It will be based, in part, on two study-workshops commissioned by the AI100 standing committee, one entitled “Coding Caring” and the other “Prediction in Practice”.

In the first part of the session, the panellists discussed their experiences from the two study workshops. These study groups brought together a whole range of stakeholders, including academics (from different disciplines), start-ups, care-givers, and other practitioners. They also brought in people who had created high-stakes AI applications and found out what it was like to maintain and integrate AI applications as part of a larger system. Their aim was to address conceptual, ethical and political issues via a multidisciplinary approach. Balancing the needs of systems users, customers, start-ups and the public sector is a fiendishly difficult challenge, but one that it is necessary to address.

In the second part of the session, we heard views on the value of the AI100 initiative. AI100 allows a periodic, longitudinal view of how AI is viewed by society, and aims to report realistic hopes and concerns. AI has progressed to the point where we need to be having conversations with practitioners about the implications of deploying AI systems in settings such as care and law. AI researchers should be aware of how their work impacts society.

Find out more about the next report here.



tags:


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.




            AIhub is supported by:



Related posts :



Better images of AI on book covers

  25 Nov 2025
We share insights from Chrissi Nerantzi on the decisions behind the cover of the open-sourced book ‘Learning with AI’, and reflect on the significance of book covers.

What is AI poisoning? A computer scientist explains

  24 Nov 2025
Poisoning is a growing problem in the world of AI – in particular, for large language models.

New AI technique sounding out audio deepfakes

  21 Nov 2025
Researchers discover a smarter way to detect audio deepfakes that is more accurate and adaptable to keep pace with evolving threats.

Learning robust controllers that work across many partially observable environments

  20 Nov 2025
Exploring designing controllers that perform reliably even when the environment may not be precisely known.

ACM SIGAI Autonomous Agents Award 2026 open for nominations

  19 Nov 2025
Nominations are solicited for the 2026 ACM SIGAI Autonomous Agents Research Award.

Interview with Mario Mirabile: trust in multi-agent systems

  18 Nov 2025
We meet ECAI Doctoral Consortium participant, Mario, to find out more about his research.

Review of “Exploring metaphors of AI: visualisations, narratives and perception”

and   17 Nov 2025
A curated research session at the Hype Studies Conference, “(Don’t) Believe the Hype?!” 10-12 September 2025, Barcelona.

Designing value-aligned autonomous vehicles: from moral dilemmas to conflict-sensitive design

  13 Nov 2025
Autonomous systems increasingly face value-laden choices. This blog post introduces the idea of designing “conflict-sensitive” autonomous traffic agents that explicitly recognise, reason about, and act upon competing ethical, legal, and social values.



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence