[ccppurcell]

Can you give an analogous example for data science? I confess ignorance here, and always took the term at face value. Is the issue that "data science" tries to be agnostic about the source of the data? (I'm not claiming that that is true, just guessing)

[bsoles]

Sure. There are many examples of data scientists attempting to use complex Machine Learning and Deep Learning models to predict machine (bearings, gears, etc.) failures from vibration data, where a simple Fourier Transform (FFT) provides a lot more insight and predictive powers about the same problem.

However, spectrum analysis is not something that data scientists learn at school, yet every mechanical/electronics engineer working in the field knows about it. So, without an expertise in a particular field, data scientists often reach for a big hammer, when more specialized tools exist and are known to the experts in the field.

[randcraw]

Another classic example is data scientists trying to model biological processes (or answer questions about processes while ignorant of which components regulate others). Systems biology has a long history of largely clueless attempts to predict outcomes from complex processes that no one understands well enough to model usefully. The biologists know this but the data scientists do not.

[mythical_39]

huh. I'm a professional data scientist, and my masters was in signal processing. In one class the final exam required us to transcribe fourier transforms of speech into the actual words. In another the final exam required us to perform 2d FFTs in our head.

Please be careful about generalizing.

I agree that many 'data science' programs don't teach these skills, and you certainly have evidence behind your assertation.

[Nevermark]

I don’t think anyone is making the claim that data science has no merit, or data scientists are universally ignorant of anything.

Simply that some data scientists, formally trained or titled by themselves or others, have been known to apply their skills to data without having special knowledge regarding the data.

It is a bit of a cliche in some of our experiences. The consulting company that analyzes data for a decision paralyzed organization, that seeks outside guidance in lieu of getting better leadership, is something I see.

That is a real phenomenon, and despite good intentions, can have all the effectiveness of reading tea leaves.

Because there is always data to be scienced. Competently or not.

[bsoles]

> ... my masters was in signal processing

But, you are making my point for me here. Most data scientists don't get masters in signal processing. You are also acknowledging that gaining expertise in a particular field was worth pursuing.

[Grosvenor]

It's much worse than that. If you dare to ask that a team speak with the problem owners - mechanics, managers, etc, you will get booted right quick.

Since the 2010's data science has gone from scientific based curiosity in solving problems to pure technicians work. There's a set of algorithms they follow, no exceptions allowed. Kaggle is a horrible anti-pattern.

NB: I am a data scientist.

[IOT_Apprentice]

Yet I suspect that mechanical engineers are not writing software for companies in the large. There are software developers doing so.

I suspect that they should be consulted by data science folks as domain experts.

That said won’t AI replace both? ;)

[layer8]

Likewise, UX designers should consult HCI experts.

[doctorpangloss]

i confess, i've read both of your comments on this - your analogy and a deeper explanation of the analogy - and i still have no idea what you are saying. i'm not stupid. so first, my feedback here is, it sounds like you are an educator or in an education-adjacent role, and you should focus on making more sense haha. like lay out your beefs clearly, it sounds like you have a beef with interdisciplinary work, specifically between some STEM departments and especially with humanities and STEM departments, which is subjective. you don't have to be objective about everything. you can just say, "i don't like this design thinking thing because i don't like the people involved" or whatever. but i don't know! i cannot figure out what you are saying.

it sounds like your point is: "some ways of solving problems are superior to others." i've heard this take a million times. one perspective i'll offer to you is, math is not the only way to solve problems. it's not even the best way in many cases. not everything can be solved by defining a narrow goal, and then having a dispute about the methods, and then picking some objective method and then applying it very optimally, or whatever. this is also on you, as an educator, to understand! i could give a bajillion specific examples.

but first, you have to concede: an analogy nobody understands is bad, and you have to own that, and two, it's not really clear, what exactly is your dispute with Design Thinking? it doesn't have anything to do with user interfaces... so why the hell are you talking about it? why "Design Thinking people"? What is your beef here?

[rrm1977]

Me too don't understand the analogy between design thinking and data science. Both are too different. But even if I am a designer and teach design, I don't think there superiority here. it is how to benefit from each approach to achieve in intended goal.

[bsoles]

As many other people on HN, I am an advocate for software engineers and I think it is important that software engineers themselves develop expertise and become owners in their particular fields of application, their processes, etc.

Attempts to undermine their role and turn developers into simple cogs in the machine rub me the wrong way.

I perceive (you might disagree) that Design Thinking, Agile, Scrum, and similar things as attempt for designers, PMs, etc. to insert themselves into the process, not as equal partners, but as people with elevated privileges over software developers.

I don't necessarily disagree with the idea and ideals of Design Thinking. I disagree with the practitioners and their perception of themselves as something special over software developer.

I also think that my original analogy at the top is perfectly understood by a lot of people here as much as I understand the type of people on HN.

[doctorpangloss]

having a specific negative experience can be interesting, why don't you talk about that instead? generally, having been both the "design thinker" and the thinkee, in both the formal big corporate setting you are lamenting and in a less formal research environment, my and my colleagues experiences have been unequivocally positive. nobody is thinking about things in terms of, "perception of themselves as something special over software developer." that may be a problem unrelated to "design thinking," i can see how any creative thinking exercise can test people's interpersonal relationships differently than say, telling Claude what to do.

[rrm1977]

it is normal to see people advocate their favourite tool or process. However, I always tell my design students to be critical and strategic when choosing their tools.

[rawgabbit]

I believe he is trying to articulate the failings of e.g., JFK's Whiz Kids who were experts of statistical analysis and tried to use that knowledge to domains they knew little about. In a nutshell, these experts tend to deep dive on parts of the problem where data was available and ignore the parts of the problem that is not quantified. Which is usually a huge mistake.

[runlaszlorun]

Sorry... OT... But I'm dying to know how you use FFT for machine failures. Is it just a matter of looking for unwelcome vibrations? Or more?