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Goodbye, data science

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Re: Goodbye, data science

#331

Post by PragmaticPulp »

nostrademons wrote: post #182
scottLobster wrote: post #156

Earlier quoted context omitted.

Not to get too off topic, but as a 35 year old engineer it seems the world in general has far fewer consequences than I was raised to expect. Everything from businesses with bullshit ideas flourishing at a loss, to January 6 even being possible (politics aside I expected the Capitol Police to crack a lot more skulls than they did once people started smashing windows), to the whole FTX situation and the tepid response…

Parenting & the public education system is a very artificially constructed bubble designed to reinforce and reward "good" behavior, where "good" is usually defined as "that which makes life easier for my caregivers". That gives kids a falsely inflated sense of how much everything matters: your caregivers want you to mind your behavior, because then they don't have to, even if you would've been perfectly fine playing…

This is the kind of mindset that felt obvious to me when I was young and resented anyone else trying to influence what I chose to do for myself.

But after growing up and having kids of my own as well as watching others' kids grow up with varying degrees of parental involvement, I have a whole new appreciation for adult caregivers who get involved and help shape healthy behaviors and habits in kids.

> your caregivers want you to mind your behavior, because then they don't have to, even if you would've been perfectly fine playing with mud or swearing in school or watching TV all day.

You've got it backwards. The easy way of caregiving is to just not care. Let kids watch TV all day, swear in inappropriate social situations, and whatever else they feel like doing. You don't have to get involved if you just don't care what they're doing.

But anyone who has worked with kids in an education setting can tell you that this doesn't actually produce good outcomes for the kids. There are occasional exception stories where students with minimal parental involvement lean heavily into becoming successful in life, but the more common outcome is that hands-off or absentee parenting styles lead to poor outcomes for the children, including social and personal issues. It's not just about getting good grades just because. It's about learning how to operate and function within a civilized society, as well as how to balance your own emotions, impulses, desires, and other behaviors they need to learn as they grow up.

Re: Goodbye, data science

#332

Post by Radim »

Foobar8568 wrote: post #145
CapmCrackaWaka wrote: post #120

Earlier quoted context omitted.

> 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.

With a handle like Foobar8568, why not be more specific? It sounds like you might have a good story.

Re: Goodbye, data science

#333

Post by icedchai »

quickthrower2 wrote: post #203
pessimizer wrote: post #174

Earlier quoted context omitted.

> For establishing competence, you still have to dig in to see what caused the slowness. Not as management. You just have to see that other people's similar sites are not slow with the same resources, therefore it is possible for your site not to be slow. You don't have to know why you're failing to know that the totality of the people you hired were not as good as the people those others hired. This is of course bar…

Software Engineering is one of the few knowledge working areas where you can actually test the result in various ways as a layman. You can flush the toilet before paying the plumber to a large extent and hire another counter-team called QA. QA themselves are tested by future production bugs. In other disciplines it is way more fuzzy. If you are in the conclusion business and there isn’t a clear path to test your conc…

Unfortunately, I haven't worked at a company with dedicated QA in the past 5+ years, maybe longer. QA is often seen as a side job for engineers and product teams.

Re: Goodbye, data science

#334

Post by Jensson »

cjglo wrote: post #104
whatever1 wrote: post #55

Earlier quoted context omitted.

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.

Could be wrong here, but in physics and most natural sciences, you don’t throw away your model if you have one experiment against it. Usually isn’t it looking for an experiment that proves it and is repeatable? If I discover a new element in one experiment, the results are published. After publication, many labs will try to repeat and its not taken away if one can’t do it. Only if all can’t and it casts doubt on whet…

Scientific method? Models are disproved, not proved. Do data scientists not know about science? People usually understand how science works here on HN, but not in this thread.

Example of a test that invalidated our old theory of gravity and validated Einsteins claims:

https://en.wikipedia.org/wiki/Eddington_experiment

This is how science is done. But apparently not data science.

Re: Goodbye, data science

#335

Post by in9 »

tomrod wrote: post #154
fnands wrote: post #110

Tangentially, I also think the term data scientist has been so abused as to almost be meaningless at this point. When I was applying for jobs it could range from anything from "knows how to use MS Excel" to "Can train large language models at scale". Personally I went for ML Engineering. My company at some point hired people as data scientists (some of my more senior colleagues still have the title, despite doing the…

Agreed. I've run a "data science consultancy" in some form or fashion for three years now. When people say "data science" they mean one of three things: (1) MLE (2) Data Management (3) Data Analysis or Business Intelligence (applications of the same skillsets). (1) has a lot of ongoing innovation, be it in MLOps, autoML, mapping frontier ML to business cases, etc. Innovation is expensive if the investment strategy is…

wow. How you phrase the work and client expectations make seem like working for you is a breath of fresh air in the DS world. Let me know if you ever need a contractor, or let me know how to reach you with a resume :D

Re: Goodbye, data science

#336

Post by icelancer »

PragmaticPulp wrote: post #196
scottLobster wrote: post #156

Earlier quoted context omitted.

Not to get too off topic, but as a 35 year old engineer it seems the world in general has far fewer consequences than I was raised to expect. Everything from businesses with bullshit ideas flourishing at a loss, to January 6 even being possible (politics aside I expected the Capitol Police to crack a lot more skulls than they did once people started smashing windows), to the whole FTX situation and the tepid response…

Consequences often catch up slowly. It took years for Elizabeth Holmes to be sentenced because it takes time to collect evidence, build an airtight case, and give people their due process. As I get older, I'm actually noticing more and more consequences catching up with people, albeit slowly. The people I knew who drank heavily through their 20s and 30s are in much worse shape than basically anyone who made an effort…

I think both you and the GP are correct. I do think that consequences are being detached from actions, at least in the last decade of free money and rapid growth. But I also agree with you on the slow burning nature of small bad decisions made many times over years on end.

With the economy contracting and inflation skyrocketing, consequences should be back in fashion relatively soon. We're already seeing it in mass layoffs and other areas of business.

Re: Goodbye, data science

#337

Post by [deleted] »

brosciencecode wrote: post #229

> 23 year-old data scientists should probably not work in start-ups, frankly; they should be working at companies that have actual capacity to on-board and delegate work to data folks fresh out of college. If a 23 year old manages to get a data science job at a startup, and then actually delivers the results that the start-up expected of them, the learning experience there is infinitely more valuable than going to Go…

[deleted]

Re: Goodbye, data science

#338

Post by zmmmmm »

Feels like data science outside of deep learning is slowly edging towards the trough of disillusionment. Time to rebrand your CVs folks in line with the new hype, while waiting it out to get to the plateau of productivity ...

Re: Goodbye, data science

#339

Post by arcturus17 »

salty_biscuits wrote: post #314

See a lot of pessimism here, and heard a lot of the same stuff by grumpy engineers over my career "nobody knows how to do statistics properly", "scientists are bad at coding" and "managers don't care about quality and rigour". I'm old enough to say it all pre-dates data science as a term. It all comes across as a conspiracy like everyone is bad on purpose. There is a null hypothesis here, that the average person in r…

> there is an implied intentionality that I don't agree with. We are all just plodding along, doing our best with limited information and skills.

Never got the feeling the author blamed the data scientists (he was one himself), but rather management, and not their bad intentions but their incompetence.

Re: Goodbye, data science

#340

Post by r-zip »

zmmmmm wrote: post #338

Feels like data science outside of deep learning is slowly edging towards the trough of disillusionment. Time to rebrand your CVs folks in line with the new hype, while waiting it out to get to the plateau of productivity ...

The funny thing is that it shouldn't be. There is plenty of potential, but all sorts of (mostly non-technical) factors are getting in the way.
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