Ask HN: Is there really a need for this, or are we drinking the wrong kool-aid
Maybe I am an old fool, and like to romanticize things, but I cannot believe that we encourage people to become masters in a field or subfield, and then go and write marketing algorithms for Google.
Having a PhD should not be a requirement for MOST jobs in AI or ML or whatever. Most jobs are bordering on CRUD, and those that need some kind of thinking can be done by someone who has a 'lowly' masters degree.
I see this trend happening for three reasons:
1) To reduce competition in job applications; employers are inundated with thousands of resumes for one job.
2) Most employers are copying FAANG, pretending that their business problems require PhDs to solve them.
3) We have lost our understanding of what having a PhD means, i.e. for a college student who wants to decide between two paths, industry or academics, there is no difference anymore. That seems like a very dangerous trend to me because 1) we're wasting workers who could be productive and have no intention of being academics or teachers on PhDs, and 2) we're wasting PhDs on people who have no intention of staying in academics, research or teaching. Not saying that PhDs have a limited supply, but PhD programs certainly have limited slots.
Industry cannot be like academia because most employers do not have the time or resources to indulge years and years on research, and making sure that the problems that solved are truly sound, and not just sound enough to ship it. This kind of lazy academics in industry almost seems damaging and counterproductive to any field it touches.
Maybe I am wrong about this whole deal, and so I ask.
5 comments
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I myself is a PhD working in the industry. My day job is unrelated to my PhD training, but I still think my PhD is worth it. I want to be an entrepreneur eventually. PhD thought me how to pick up a new field quickly and how to self-study and research. These are important skills for entrepreneurship.
The real world isn't a place where we get to be prescriptive in terms of dictating what other people focus on. This isn't Plato's world, where occupations are chosen for us at birth, with no opportunity for deviation. Here sovereign individuals make their own choices and the outcomes are an emergent property of the interactions of those billions of individuals.
All of that said, I also posit that it is possible (in some fields, albeit not all) to do original research outside the halls of "The Academy", with or without a PhD, both in industry or as an independent researcher who isn't affiliated with industry or academia.
* the economics of staying in academia are just so amazingly awful, the decision to go into industry is a no-brainer for most anyone along the academic path -- grad student, postdoc, instructor, whatever -- who stops, looks around, and realizes (better late than never), that they'd like to actually make a decent income before they reach old age, maybe actually start a family, etc. Academia is effectively pushing talented people out, and industry will happily put their skills to use selling advertisements (instead of them researching cancer at a university or whatever).
* For ML/AI work, you need to have a strong quantitative skillset. Almost any graduate degree will provide a sufficient quantitative/statistical background (whether it's physics, sociology, whatever), hence employers find it a useful filter for such roles. If one only has a bachelor's the ML/AI market right now will be tougher but I wish those folks success.
Personally, as to whether someone should pursue grad school, regardless of future plans, my feeling it's usually a rip-off, but it depends on one's own situation.