At last month’s EDUCAUSE Learning Initiative (ELI) Annual Meeting, I had the opportunity to hear Dr. Satya Nitta, Global Head and Program Director of Cognitive Science and Education Technology at IBM Research, speak twice on IBM's Watson AI system. My first opportunity was in a session sponsored by the Leading Academic Transformation (LAT) group, which was set up as a more informal Q&A session that I helped to facilitate; the second was Dr. Nitta’s morning keynote.
What struck me was how varied these two engagements were, and how much different the takeaways likely were depending upon which session people attended.
In essence, this isn't really a tale of two AIs, but rather, a different telling of one AI.
A Deep Dive into AI
The LAT session was designed to provide a more in-depth look at one of the keynote topics. In an ideal world, it would have taken place after Dr. Nitta's keynote, but logistically, it needed to be scheduled beforehand. My co-facilitator, Thomas Cavanagh, and I had a chance to speak with Dr. Nitta on the phone prior to the conference and had agreed on a format for the group session.
Dr. Nitta suggested some pre-reading suggested for folks who were interested (Dawn of the Age of Cognitive Assistants or Chatbots in Education and Limitations of AI). At the session, we made sure we had reasonably well-balanced tables and then did a round of three exercises to get attendees to think about AI in higher education: the promise of AI, the pitfalls of AI, and some possible campus applications. After each set of conversations, we asked that each table share their perspectives on one of the aforementioned topics, with Dr. Nitta responding to them in turn.
If you were in that session, you likely left it with an impression of an AI expert who understands the very sophisticated challenges and the very real limitations of AI — along with a powerful sense that humans need to stay involved in any high stakes decisions or recommendations that AIs might make. Overall, it was a very invigorating and thoughtful conversation.
An Uncertain Future
The next day kicked off with Dr. Nitta’s keynote, which was directed toward all ELI attendees. Like most keynotes, he spoke for quite a while from a prepared presentation about the power of AI in education. Unfortunately, this presentation lacked any of the nuanced discussion a number of us had already heard in the LAT session, and it sparked comments on the backchannel like these:
@calimorrison Watson concerns: if admins don't appreciate need for human relationships in affective domains of learning, we lose. #eli2017
— Kristen Eshleman (@kreshleman) February 14, 2017
Just listened to a computer make its own argument for why it is the best tutor. #future #eli2017 #elearning #education
— Katrina Wehr (@katrinamwehr) February 14, 2017
OH GOD NOW WE'RE ON TO WATSON AND SESAME WORKSHOP AND IS NOTHING SACRED #eli2017 "It will be friends with children"
— Lee Skallerup (@readywriting) February 14, 2017
It was as if the talk had been authored by someone with a completely different perspective on AI. Whereas our LAT conversation included some specific references to the idea of the AI serving as an advisor to the expert (i.e. AI providing information to advisors that could be used with students), the keynote lacked any of that. From the LAT session, you got a sense that there is a place for AI in education, but one that requires thought and continuous human presence. Conversely, if you had only attended the keynote, you got a sense of AI as a definitive replacement for human interaction. If you went to both, you were probably confused. (I know I was.)
So how do I reconcile this? Well, honestly, I can't. These were two vastly different conversations with the same person about the same AI. True, the venue and structural difference of the two could perhaps explain some of the disparity, but that feels like shaky reasoning at best. It’s difficult to say why Dr. Nitta had approached the keynote in this way, especially when presenting to an audience of teaching and learning professionals. After all, aren’t we the educators, designers and technologists who could one day be upstaged by an intelligent machine?
The keynote wasn’t presented as a far off, futuristic view — the examples Dr. Nitta provided were happening right now. These two competing visions of AI in higher education need to be discussed now, before the decisions get made for us. The LAT session brought some important perspective and in-depth conversation around the issue, and I think this is one of the valuable assets LAT brings to the broader teaching and learning community within higher education. I hope that more of these facilitated group-expert discussions can be planned for future conferences so we can continue to grapple with these issues together.
"2011-04-23_00104" flickr photo by I am I.A.M.
https://flickr.com/photos/ianalexandermartin/5655639052 shared under a Creative Commons (BY-NC-ND) license
Kyle Johnson is Dean for Information Technology & Services and Director of Emerging Learning Technology for Chaminade University.