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Panels

Panels

The Coming of Age of AIED: Perspectives from Inside and Outside the Community

Wednesday July 27

The AIED community has researched the application of AI in educational settings for more than forty years. Today, many AIED successes have been commercialised – such that, around the world, there are as many as thirty multi-million-dollar-funded AIED corporations, and a market expected to be worth $6 billion within two years. At the same time, AIED has been criticised for perpetuating poor pedagogic practices, datafication, and introducing classroom surveillance. The commercialisation and critique of AIED presents the AIED academic community with a conundrum. Does it carry on regardless, continue its traditional focus, researching AI applications to support students, in ever more fine detail? Or does it seek a new role? Should the AIED community reposition itself, building on past successes but opening new avenues of research and innovation that address pedagogy, cognition, ethics, human rights, and social justice? These questions will be the subject of debate in this unique series of panel discussions, entitled: The Coming of Age of AIED: Perspectives from Inside and Outside the Community.

Panel 1: The Coming of Age of AIED: Perspectives from inside the AIED community (panellists to be announced)

Panel 2: The Coming of Age of AIED: Perspectives from outside the AIED community (panellists to be announced)


The explainability of AIED

Wednesday July 27

The so-called AI revolution poses a host of ethical dilemmas, which represent significant roadblocks to reaping the potential of the new technologies now being developed. Many of these dilemmas created by AI are not new—they are shared with bioscience, health, and other fields where ethical thinking has closely followed the development of new tools and practices. One ethical dimension, however, is new with AI, namely explicability. All agree that explainable AI (xAI) is an aim to strive towards. However, in the nascent field of AIED development we should try to be more concrete in defining our aims, unless we want to be stuck with mainly technical solutions that leave out the social and societal aspects of technologies. AI needs to be intelligible, and AI needs to be accountable. For education, this opens up an unprecedented space of engagement. We need research into the technologies supporting AI systems; we also need continuous education and training in how to interact with AI systems across the many domains in which AI tools will change the way we work and live. In this session we will discuss xAI in the education context and explore different aspects of AI explicability from an educational perspective and see what need to be addressed in the years to come. We have gathered panellists from different fields of expertise, technical AI as well as ethics, governance, and pedagogy.

Panel 3: The Explainability of AIED (panellists to be announced)