Professor & Canada Research Chair in Innovative Learning and Technology at Royal Roads University

Bots, AI, & Education update #1

Posted on March 21st, by George Veletsianos in teacherbots. 2 comments

A rough set of notes from today that focus on teacherbots and artificial intelligence in education

  • Bots in education bring together many technologies & ideas including, but not limited to artificial intelligence, data analytics, speech-recognition technologies, personalized learning, algorithms, recommendation engines, learning design, and human-computer interaction.
    • They seek to serve many roles (content curation, advising, assessment, etc)
  • Many note the potential that exists in developing better algorithms for personalized learning. Such algos are endemic in the design of AI and bots
    • Concerns: Black box algorithms, data do not fully capture learning & may lead to biased outcomes & processes
  • Downes sees the crux of the matter as What AI can currently do vs. What AI will be able to do
    • This is an issue with every new technology and the promises of its creators
    • Anticipated future impact features prominently in claims surrounding impact of tech in edu
  • Maha Bali argues that AI work misunderstands what teachers do in the classroom
    • Yet, in a number of projects we see classroom observations as being used to inform the design of AI systems
  • “AI can free time for teachers to do X” is an oft-repeated claim of AI/bot proponents. This claim often notes that AI will free teachers from mundane tasks and enable them to focus on those that matter. We see this in Jill Watson, in talks from IBM regarding Watson applications to education, but also in earlier attempts to integrate AI, bots, and pedagogical agents in education (e.g., 1960s, 1980s). Donald Clark reiterates this when he argues that teachers should “welcome something that takes away all the admin and pain.” See update* below.
  • Another oft-repeated claim is that AI & bots will work with teachers, not replace them
  • At times this argument is convincing. At other times, it seems dubious (e.g., when made in instances where proponents ask readers/audience to imagine a future where every child could have instant access to [insert amazing instructor here])
  • Predictions regarding the impact of bots and AI abound (of course). There’s too many to list here, but here’s one example
  • Why a robot-filled education future may not be as scary as you think” argues that concerns around robots in education are to be expected. The article claims that people are “hard-wired” to perceive “newness as danger” as it seeks to explain away concerns by noting that education, broadly speaking, avoids change. There’s no recognition anywhere in the article that (a) education is, and has always been, in a constant state of change, and (b) edtech has always been an optimistic endeavour, so much so that its blind orthodoxy has been detrimental to its goal of improving education.



From Meet the mind-reading robo tutor in the sky:

And underpaid, time-stressed teachers don’t necessarily have the time to personalize every lesson or drill deep into what each child is struggling with.

Enter the omniscient, cloud-based robo tutor.

“We think of it like a robot tutor in the sky that can semi-read your mind and figure out what your strengths and weaknesses are, down to the percentile,” says Jose Ferreira, the founder and CEO of ed-tech company¬†Knewton.”

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