How does the author compare AI to earlier tech shocks like the web and MOOCs?

The author argues that while the Internet, big data, and MOOCs promised major disruption, they ultimately left the core pedagogical experience—courses taught by professors in classrooms to groups of students—largely untouched. AI is different because it is not merely expanding the space where humans express creativity (as the web did) but expanding creativity itself. The author calls this layer deeper than previous shocks.

What evidence does the author cite that earlier tech disruptions had limited impact on higher education?

The web brought digital content and free access to knowledge but did not sideline universities; the core classroom remains offline. Big data led to new crossover programs (like data science majors) but did not replace group-based teaching structures or deliver the promised individualized learning paths at scale. MOOCs platforms (Coursera, Udemy, edX, Khan Academy) still exist but serve different student segments rather than displacing traditional higher education institutions.

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Higher ed faces AI shock deeper than the web, says academic

Hacker News8h ago4 min read

Key takeaway

A business school leader who witnessed three previous technology shocks to higher education argues that AI represents a fundamentally deeper disruption than the Internet, big data, or MOOCs. While those earlier technologies left the core classroom experience surprisingly stable—transforming operations and spawning new programs rather than replacing traditional teaching—AI may prove different because it expands human creativity itself. The author, who led digital transformation at emlyon business school starting in 2014, suggests the field should prepare for more substantial institutional change than previous disruptions required.

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3 Key Points

What happened
A business school professor who lived through three prior tech disruptions—the Internet, big data, and MOOCs—argues that AI is fundamentally different because it expands human creativity itself, not just the platforms where creativity happens. The author, drawing on experience at emlyon business school from 2014 onward, compares AI to the web as a historical frame of reference for understanding its impact on universities.
Why it matters
Unlike the web and MOOCs, which left the core classroom experience largely untouched despite grand promises, AI appears set for a deeper transformation. The author identifies AI as profound (frontier AI systems now meet or exceed human baselines on growing numbers of benchmarked cognitive tasks), broad (usage is widespread across education, workplaces, government, science, and culture), systemic (creating or intensifying environmental, geopolitical and societal imbalances), and rapid (significant development in less than four years since ChatGPT's November 2022 release). For higher education institutions, this suggests the need for more fundamental adaptation than previous shocks required.
What to watch
The author poses whether AI will follow the web's pattern—transformative at the societal level but with weaker-than-expected impact on the core teaching and learning experience—or whether it will prove fundamentally different. The comparison rests on recognizing that AI, unlike the web, does not merely expand the space for human expression but expands the capacity for creativity itself.

FAQ

How does the author compare AI to earlier tech shocks like the web and MOOCs?: The author argues that while the Internet, big data, and MOOCs promised major disruption, they ultimately left the core pedagogical experience—courses taught by professors in classrooms to groups of students—largely untouched. AI is different because it is not merely expanding the space where humans express creativity (as the web did) but expanding creativity itself. The author calls this layer deeper than previous shocks.
What evidence does the author cite that earlier tech disruptions had limited impact on higher education?: The web brought digital content and free access to knowledge but did not sideline universities; the core classroom remains offline. Big data led to new crossover programs (like data science majors) but did not replace group-based teaching structures or deliver the promised individualized learning paths at scale. MOOCs platforms (Coursera, Udemy, edX, Khan Academy) still exist but serve different student segments rather than displacing traditional higher education institutions.

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