(Part 1 is written elsewhere, I’ll add a link here to it later)
I finished the book by Joseph Aoun a little while ago, and I’ve been sitting on my notes letting them stir. I think i have a fairly safe conclusion for its second half. That said, I would expect those with an understanding and empathetic relationship with their CS students and their families will have been at the cusp of some similar conclusions drawn by Aoun in Robot Proof in 2017.
The second half received more anecdotes, with example student requirement scenarios (inc those switching jobs regularly as job role dynamics change, and entrepreneurs looking to capture innovation opportunities) and example personality profiles that would fit a new definition of the life long learning applicant.
A discourse of operational procedure and revenue generation strategy, familiar to university as an institution for profit, runs through that latter half. I guess I should have anticipated this. The constraints (or institutional targeting) of the recommendations and sources of evidence were culturally-specific to the US and supported the arguments and strategies, as indeed are Aoun’s experience. With all that said, these are the key take home points of the later chapters:
- Life long learning (LLL) and the Intraprenuer are going to be key to future businesses.
- Networks and friendships that will have led to business opportunities will link back to the Bachelor days, rather than LLL courses or boot camps.
- This indicates modularisation (in particular in short segments) and custom design of course content will be key aspects of that educational demand.
- LLL requests to specialise will be regular, with individuals returning to specialist via LLL study approx every 5 years.
- Teachers will be required to think of themselves more as as content learners and deliverers, rather than consistent pursuers of a single topic focus.
- There maybe a requirement for more teaching staff to deliver specialised (cut down and tailored) modules.
The future Aoun envisions is a volatile market of industries led by consumer demand for more customisation, personalisation and individualism. That doesn’t yet address the education industry specifically; however, that follows suit as per the recommendations above. By consumer demand for personalisation, requirements on companies will be volatile following ever more closely to trends. The human roles will adjust about as quickly as hummingbird switches to a new nectar, and retraining on company time or own time will be the decider. Part of this consumer feed solution is internal opportunity finding of new products/services and new features for existing products to serve the changing needs. Though, I don’t recall Aoun mentioning, the self-disruption (as in the innovation term) to put one’s own business out of business before another business does, seems apt thinking here.
With those regular changes in businesses, the requirements for retraining are paramount to continue innovating or be taken over. Hence the time pressure on student and, by extension, teacher rises. The course design changes therefore follow to feed (fulfil) those needs.
I suppose there should be something said about AI in this review about the book caption with the title “Higher Education in the Age of AI”, but there isn’t a lot more to include. In my interpretation, Aoun relates AI to improved service personalisation and its impacts on industry and thus education. Humanics is the name for fostering new students to be prepared for the challenges with AIs. Both introduced an insightful perspective for me to work through over the chapters. One might go further to discuss the impact of evidence-based decision making on education, or incremental improvement of courses, or new measures for evaluating content and delivery. Current and future online educational services are mentioned in passing, such as MOOCs. I sense that favour lies in the combination of the hybrid delivery techniques, but that may be my own biased interpretation. Another adjacent topic is taking knowledge or proven hypotheses from data platforms such as YouTube or other online educationally focused sites, to factor human cognition and attention into content and delivery design; an idea executed by YCombinator. These topics could but don’t seem to factor into the future put forward.
The main reason, I believe, for the more limited view of AI’s impact is perhaps two fold. “We climb as high as we can see; then from that viewpoint we can see further”. The second is perhaps more realistic. Frankly, its quite hard to imagine concrete scenarios where an actual artificially intelligent entity exists. Up until now, a lot of the talk of AI is an impressive curve fitting model, which is clever but nothing more than data fitting. Those things we already experience everyday. The ways in which a sentient artificial intelligence will, with its capabilities to learn and overpower, compete with us humans to effect and affect our lives and our societies is particularly hard to fathom and foresee. This is a story that remains untold and ready for future historians to write.
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