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HENNESSY: When you think back about giving tenure to somebody, you ask
two questions. One, are they clearly already a leader in the field or well on their
way to becoming a leader in their field? And two, is their reputation as a leader in
the field the most important thing to them in their career? Because if it is, they’re
going to want to maintain a sustained record of contribution over time. And I
think that model has worked out well.
But it’s different for STEM people, for example, than for historians. Most
historians write their great work when they’re in their 50s and 60s, not when
they’re in their 30s or 40s. Most STEM people, on the other hand, do their great
work in their 20s, 30s, and early 40s. In the university there are lots of mechanisms
that encourage you to keep your skills up to date, like sabbaticals and research
grants. I think companies are now seriously realizing that they need to do more
of those things. The place you really can see this is in the machine learning
explosion. We haven’t yet educated many students in this new technology, so
we’ve had to build up opportunities for people to move into this field. At Stanford,
many years ago, we thought of part-time education as primarily focused on
getting people master’s degrees. Today, it’s a certificate — three courses in machine
learning, three courses in cybersecurity and blockchain — that can allow people
to upskill themselves broadly across the field. And I think we’re going to have to
continue to do that. The AI revolution’s going to force us to.
S+B: Do you teach?
HENNESSY: I do. I’m teaching a freshman seminar. It’s called “Great Discoveries
and Inventions in Computing.” It’s sort of a survey of all the interesting things
that have happened in the computing field over time, from hardware to software,
and I’ve got 16 bright-eyed, bushy-tailed students. +