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Goodbye, data science

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Re: Goodbye, data science

#141

Post by vsareto »

jimbokun wrote: post #112
vsareto wrote: post #94

Earlier quoted context omitted.

That's the same for many tech jobs. Competence is often only a local thing, subject to politics, reputation, and appearances. There's also no ground truth because the ground changes so fast. No one knows if the technologies mentioned in the OP will be popular 5-10 years from now.

But if the page loads slowly or the UI is unresponsive, people notice. The output of Data Science is harder for non-specialists to evaluate.

For establishing competence, you still have to dig in to see what caused the slowness. A regular user can't tell you that.

Re: Goodbye, data science

#142

Post by lajosbacs »

agomez314 wrote: post #10

"Managers will say they want to make data-driven decisions, but they really want decision-driven data" Ooofff. This is too true. How often is the case that data is collected to test hypotheses vs confirming priors?

This especially sucks if you are the middle manager. You know that what you are asked to do is a complete BS but you have to somehow communicate it to you underlings (who see through the BS) without using sarcasm or snarky remarks.

Re: Goodbye, data science

#143

Post by bradlys »

Davertron wrote: post #36
boringg wrote: post #28

Earlier quoted context omitted.

To counter your professor opinion. The amount of extra time available as a student that I had to pursue things of interest was in the negative. All academic time was spent getting course content accomplished. I am a naturally curious individual but time limitations prevent further exploration in most circumstances. Additionally there is a relevancy factor weighed on top of it. If something looks curious I have to pre…

Well good luck then, in my experience the most free time I've ever had in my life was during college. I squandered massive amounts of that time doing things completely unrelated to education, and I definitely don't regret doing that. College isn't just about book learning after all. But still, BY FAR, college is the time of my life when I had the most free time to do whatever I wanted.

Sounds like you weren’t in a competitive program that constantly tried to get people to drop from college altogether.

I was. Didn’t have anywhere near the free time and the lack of stress I do post-college. Helps that I also make a good chunk of change rather than living off a relatively small stipend in one of the most expensive cities in the world.

Re: Goodbye, data science

#144

Post by fn-mote »

dclowd9901 wrote: post #85
Davertron wrote: post #36

Earlier quoted context omitted.

Well good luck then, in my experience the most free time I've ever had in my life was during college. I squandered massive amounts of that time doing things completely unrelated to education, and I definitely don't regret doing that. College isn't just about book learning after all. But still, BY FAR, college is the time of my life when I had the most free time to do whatever I wanted.

That’s impressive. Between work (30 hours a week) and classes (full time credit load), I’ve never had less free time than when I was in college. And I’m speaking now as someone with 2 young kids and a full time job. Something tells me your experience is not commensurate with the standard college experience. Perhaps you didn’t have a full time job or only took part time credits?

> Something tells me your experience is not commensurate with the standard college experience.

I know very few university students with significant work commitments.

In the US, the stereotypical college student is not also holding down any kind of job. Maybe 5-7 hours of "work study" (light work running the reference desk at the library or working in the dining hall).

Frankly, I doubt the majority could do learn a lot and also work a significant number of job hours.

At a community college, it would be very different - most students also holding down jobs, I would guess. At a flagship state university, I would be very suprised.

Evidence in [1]... about 30% of full time students are working 20+ hours/week. Also apparently I was wrong about the low hours being typical; less than 10% are working but [1] https://nces.ed.gov/programs/coe/pdf/coe_ssa.pdf

Re: Goodbye, data science

#145

Post by Foobar8568 »

CapmCrackaWaka wrote: post #120
Radim wrote: post #114

Earlier quoted context omitted.

> clients will come back to us saying "XYZ says they can get better performance" Oh yes, good old marketing. Along with buying off "Industry Awards" – hey, we're objectively the "Best cybersecurity company of 2022!" With a matching "platinum/gold badge" to go on our website! Or buying a place in the "10 Best Products for X" and "Independent X-vs-Y Comparison", another classic. Because it works. Are your customers not…

> Are your customers not sophisticated? Are they unable (or unwilling) to follow up on defects and outright lies? You would probably be depressed if you knew who our customers were, and how technologically unsophisticated they are.

I manage at a client an application which is the actual leader (most top right and by far) in Gartner magic quadrant for its category, and for years, I have never seen a product this bad, where the implementors and supports are clueless of their own product. And obviously it's buggy as hell.

Lies and deceptions.

Re: Goodbye, data science

#146

Post by yamtaddle »

agomez314 wrote: post #10

"Managers will say they want to make data-driven decisions, but they really want decision-driven data" Ooofff. This is too true. How often is the case that data is collected to test hypotheses vs confirming priors?

I've found this to be the rule, not the exception. Pointing out extremely-obvious (to me? Maybe I'm just unusually good at it? I don't even have much formal science training, and hell, barely any math training by the standards of HN folks, though) damning errors in experimental construction that should invalidate the whole thing won't earn you any friends, even if you do it before the work is undertaken, and even if you're telling the person who's claiming to want good data and useful results. Everyone seems to just want a veneer of science to what they're doing, not actually good efforts at it. As long as you have a paper-thin layer of justification that falls apart if anyone looks at it long enough, that's considered good enough and people will sit around in meetings nodding along.

Of course, in many situations the business totally lacks what it needs to correctly do the "data-driven" stuff they want to, and it'd take a good deal of up-front effort by competent people to get it, amounting to entire new projects or deep modification of existing projects.

So, given the choice between: going without that stuff and acknowledging that a lot of what they're doing is guesswork and gut decision making, or simply arbitrary; putting a smaller but still-large amount of work into finding out what they can glean from what's available; spending the time and money to collect what they need, the right way, to do the data-driven decision making they claim to want to do; and insisting they're doing things "data driven" but having all their data hopelessly ruined by e.g. selection bias and comically-bad experimental construction that can't possibly be yielding reliable results, so they can cheap out and get no actual "data-driven" benefits aside from falsely claiming that's what they're doing—they tend to go with that last option, nearly every time!

Re: Goodbye, data science

#147

Post by ifyoubuildit »

fn-mote wrote: post #130
lotsofpulp wrote: post #117

Earlier quoted context omitted.

I have only heard “show me the data” when someone wants someone else to support a claim. I do not see why this would necessarily be a bad thing.

It's BS because the people asking for the data do not have the sophistication to actually do a reasonable _analysis_ of the data. Or criticize an existing analysis. Unfortunately, as many posters here are pointing out, there's plenty of ways to do a correct-looking analysis of the data to get evidence to support your agenda. Maybe your agenda is right and maybe it's not, but I'd love to hear a story of someone standi…

So whats the alternative? "Just trust me"?

Re: Goodbye, data science

#148

Post by lifeisstillgood »

mschuster91 wrote: post #47
jmhammond wrote: post #13

> But there’s also a part of me that’s just like, how can you not be curious? How can you write Python for 5 years of your life and never look at a bit of source code and try to understand how it works, why it was designed a certain way, and why a particular file in the repo is there? How can you fit a dozen regressions and not try to understand where those coefficients come from and the linear algebra behind it? I d…

Not everyone is wired that way. Personally, I have taken apart and reassembled most of the tech stuff I have at home simply because it interests me how things work (and broke and repaired a non-negligible amount of them in the process, to add), I've dabbled in repairing cars, gas boilers, do my own electricity work... but in my social circle, I'm pretty much the only one. And as I grew older, managed to land myself a…

Hear hear

Re: Goodbye, data science

#149

Post by 2devnull »

samvher wrote: post #129
2devnull wrote: post #108

Earlier quoted context omitted.

This gave me a chuckle. If you read the feature article you understand that this is also because management wants “decision driven data.” They have an idea and use ds to provide charts and tables to support their idea. The harder the idea is to support, the greater value data science is able to provide. I guess data science is inferior to research in this way. People care about research methods, rigor, etc… Maybe dat…

I did read the article - some of the problems with judgements of work quality also come up with (hypothetical) well-intentioned truth-seeking non-political long-term-optimizing managers who just don't happen to be stats experts.

Sorry, wasn’t trying to imply you didn’t and I fully agree. Even managers that know stats can be busy or but into hype about ml or other shiny new things that they don’t have time or resources to deconstruct. This is another big problem with data science, “black box” systems and cargo cults. It’s easy to think “LLMs will change the world! We should use them, the competition will.”

Re: Goodbye, data science

#150

Post by md224 »

whatever1 wrote: post #55
lagt_t wrote: post #54

Earlier quoted context omitted.

You don't look at single outcomes with statistics.

See? “Better luck next time”. Not being mean to you, just showing how typically the goal posts are moved. To give you an example from physics, if you find just one experiment that goes against your model, you immediately invalidate the model. You don’t just make grand claims that the model in general works.

> if you find just one experiment that goes against your model, you immediately invalidate the model

Pierre Duhem would like to have a word with you:

https://plato.stanford.edu/entries/scientific-underdetermina...

> Holist underdetermination ensures, Duhem argues, that there cannot be any such thing as a “crucial experiment”: a single experiment whose outcome is predicted differently by two competing theories and which therefore serves to definitively confirm one and refute the other.

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