> It's so easy to blame this phenomenon on rose-tinted glasses and older people like us thinking all old things are better than modern, but when the world wasn't decided by "data scientists" and corporate committees, there was more variety, more volatility. Lower lows but higher highs as well.
There's a trend of thinking that our age is the most accepting and inclusive and the past was rigid and conformist but in many regards it's the opposite. Through all the metrics and quantification and SEO-like data analysis-based incentives and judgments we are being "snapped to grid". The risk averseness is growing. There's only a narrow path and people must tick many boxes or get disqualified.
Just as movie producers make the nth superhero movie and everything is a sequel of old IP, science is similarly turned into a formulaic churn.
Just think about how Peter Higgs said he couldn't fit the mold of today's academia and the pressure of producing a stream of consistent (and hence typically consistently mediocre - like the consistent taste of a BigMac) output.
The other day I watched this interview with a pioneer of artifical neural networks Warren McCulloch (https://www.youtube.com/watch?v=wawMjJUCMVw). I wonder if today we're letting such personalities thrive in academia. He was originally headed to the Christian ministry and learned a lot of theology then got drawn rather to math, and his pondering of abstractions, understanding, humans and theology moved him to study neurology and to use math to model logic expressed as neural networks. Nowadays, you must specialize early and grind for tests, no "forgiveness" if you go off-track, you must be single-mindedly focus on optimizing your path towards tenure for it to be realistic. Can't even get a PhD position without having published several of your original research papers beforehand.
While hiring committees say they reward well-roundedness and try to avoid a monoculture, what that becomes in practice is checking if your parents sent you to one of these trendy types of extracurriculars or foreign "volunteer" programs, and whether you later were engaged with some shortlist of trendy buzzword issues.
This breeds conformity, uniformity and bland predictability.
There's a trend of thinking that our age is the most accepting and inclusive and the past was rigid and conformist but in many regards it's the opposite. Through all the metrics and quantification and SEO-like data analysis-based incentives and judgments we are being "snapped to grid". The risk averseness is growing. There's only a narrow path and people must tick many boxes or get disqualified. Just as movie producers make the nth superhero movie and everything is a sequel of old IP, science is similarly turned into a formulaic churn.
Just think about how Peter Higgs said he couldn't fit the mold of today's academia and the pressure of producing a stream of consistent (and hence typically consistently mediocre - like the consistent taste of a BigMac) output.
The other day I watched this interview with a pioneer of artifical neural networks Warren McCulloch (https://www.youtube.com/watch?v=wawMjJUCMVw). I wonder if today we're letting such personalities thrive in academia. He was originally headed to the Christian ministry and learned a lot of theology then got drawn rather to math, and his pondering of abstractions, understanding, humans and theology moved him to study neurology and to use math to model logic expressed as neural networks. Nowadays, you must specialize early and grind for tests, no "forgiveness" if you go off-track, you must be single-mindedly focus on optimizing your path towards tenure for it to be realistic. Can't even get a PhD position without having published several of your original research papers beforehand. While hiring committees say they reward well-roundedness and try to avoid a monoculture, what that becomes in practice is checking if your parents sent you to one of these trendy types of extracurriculars or foreign "volunteer" programs, and whether you later were engaged with some shortlist of trendy buzzword issues.
This breeds conformity, uniformity and bland predictability.