edu@2035: Big Shifts are Coming!

I’m attending the ICDE World Conference on Online Learning 2017 in Toronto, Canada and blogging the sessions I’m attending.

This session is presented by Richard N. Katz, Contact North Research Associate

Prediction is Hard

It’s hard, but increasingly essential. Read Richard’s full paper on this topic online here.

It’s difficult to do forward thinking without using the past as a frame of reference.

He shared a cool serious of pictures from Jean Marc-Cote from 1899 predicting 2000 paired with how that has turned out now. Interesting how many early ideas still required human intervention with the technology.

We’ve all seen examples of famous people, CEOs, saying things that were wrong. My favorite: Bill Gates in 2004, within “two years from now, spam will be solved.” Oh if only!

Past vs. Future

Will we be pushed by our past memories, or pulled by our future dreams? – Rev. Jesse Jackson

Richard suggests we can gain more by reading science fiction than by looking backwards.

He quoted Thomas Friedman:

Finally, we’re going through a change in the “climate” of technology and work. We’re moving into a world where computers and algorithms can analyze (reveal previously hidden patterns); optimize (tell a plane which altitude to fly each mile to get the best fuel efficiency); prophesize (tell you when your elevator will break or what your customer is likely to buy); customize (tailor any product or service for you alone); and digitize and automatize more and more products and services. Any company that doesn’t deploy all six elements will struggle, and this is changing every job and industry.

Richard replaced “company” in the last sentence with post-secondary institution. To what extent do we think we are employing these six strategies, then to what extent do we think we will struggle?

Algorithms

  • What we read on social media is a product of algorithms
  • What we see and do on the web is a product of algorithms
  • Algorithms help gadgets do all kinds of cool things
  • Artificial intelligence is built on algorithms

Teaching Changes

Consider the Jetsons image:

The robot teacher?

vs. the Jean Marc-Cote from 1899:

The technology enabled classroom

We do still have the teacher!

Some Scenarios to Visualize the Future

Nice collection of videos: one that has a smartphone falling down and smashing a campus; one where Disney and Pixar decide to improve the production quality of Open University courses; another with people talking about the human impact of the campus residential experience.

See the image on page 12 of his paper – where technology giants are attacking academe with faculty using pens, books, and ink to defend.

Invent our Future?

What are our choices? Do we avoid the topic? do we have paralysis by analysis? Do we choose mindful incrementalism? Or do we invent a new future? What would it take to do that? To construct scenarios, develop models, identify risks, extract themes, and iterate that over and over. These are behaviors that academe knows how to do.

The Future is Now

  • Algorithms helping us with everything; 80% of the top 100 companies will have cognitive intelligence and/or artificial intelligence in their products
  • Chatbots: Jill Watson, Woebot, Eno, Abie, HealthJoy, Poncho, Melody, LARA
  • Explosion in R&D investments
  • The technology giants are “all in” on artificial intelligence: Google assistant, home, allo, messenger, watson health, echo, alexa, siri, cortana
  • Jill Watson – a way to provide faster answers and feedback to students: read more about the experiment and experience here
  • Pew Research Center referenced – thinking about code-dependent: pros and cons of algorithms – the need grows for algorithmic literacy, transparency and oversight
  • Knowledge is on networks now

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