TL;DR: induced demand isn’t just for highways
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Re this from @thedansimonson, the phrase “information pollution” has been rattling around in my head a lot lately:
https://lingo.lol/@thedansimonson/113068984297050648AI-generated nonsense. Google results filling with content-farmed garbage (written by humans and by AI). Steve Bannon’s “flooding the zone with shit.” GIGO.
→ all “information pollution” -
Cave Cattumreplied to concept of a display name last edited by
@thedansimonson @inthehands But the problem there is conflating "generative AI" with all of machine learning, no? It is quite possible to build reliable (safety critical) software systems that solve hard problems using machine learning AND do not "hallucinate" anything. But there is no known way to do it cheaply.
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Re this from @thatandromeda, I also think that there’s •still• immense promise in automated driver assistance for accident prevention. For example, I’ve driven a couple of cars with radar cruise control that prevents rear-ending people at speed, and found it more helpful than not.
But that sort of thing doesn’t seem to be where the money is flowing.
Andromeda Yelton (@[email protected])
@[email protected] We used to have the same hope (plus an element of "some people cannot drive at all and this would open options"), but then my husband worked on self-driving vehicles and became an extreme self-driving vehicle hype pessimist... There ARE aspects of automation in this space that are super good (e.g. lane divergence alarms) but the lift from there to full self-driving is......big
ohai.social (ohai.social)
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@fgcallari @thedansimonson
There is indeed tremendous unexplored potential in that space. Classifier systems (ML or not) can outperform humans for some problems, and can give an expedited first step for others. When the model turns to human augmentation instead of human replacement, things get a lot more sensible. Maybe we’ll get there on the other side of this hype cycle. -
concept of a display namereplied to Cave Cattum last edited by
@fgcallari @inthehands yes. from a cost perspective, a lot of applications of older techniques are simply ignored. the problem space wasn't exhausted, but few were willing to invest in fully exploring it from a commercial perspective.
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@inthehands Public mass transit > self-driving cars any day
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@belehaa
I mean, yes, for sure, that’s my tune too.Also cars will be with us for a long time, and I’m all for reducing the harm they cause. If self-driving were a route to reducing the number of pedestrians and cyclists killed by cars (and thus making walking and biking more attractive), I’d be all on board.
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@inthehands Same! It just feels like a mighty big and as-yet-unsupported If
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Good point from @mkj here:
https://social.mkj.earth/@mkj/11306912875790975999 Percent Invisible did a good episode about this:
https://99percentinvisible.org/episode/children-of-the-magenta-automation-paradox-pt-1/
(As always, web text is a summary; full story is in the audio) -
@belehaa
Yes, per the rest of the thread, it’s very much a counterfactual right now, not a reality that’s just around the corner. -
Cave Cattumreplied to concept of a display name last edited by
@thedansimonson @inthehands sadly safety is not a "feature" amenable to scaling in a short VC-funded development cycle. Fundamentally, safety must be backed into the entire development culture, in an org willing to experiment (and lose money) until your safety-critical widgets are really ready. Where "readiness" is decided by a customer with the financial clout to shut you down if you get it wrong, or a government that'll jail you if you lie about performance.
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@fgcallari @thedansimonson
I never thought I’d miss the consumer-driven version of capitalism, but the investor-driven version sure makes it look good. -
@inthehands The whole LLM situation makes me flash back on the daily; I remember clearly what it looked and felt like siting in that software class in the early 90s, talking about expert systems vs neural networks.
The neural networks part shared the story of the tank spotting system that they trained to perfection till it consistently found the tanks. Till they “tried it in prod” and it turned out the training set tank photos were all on a cloudy day.
That data set was at least consistent.
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@donw
That story is such a classic example! -
@inthehands Some years back before I was thoroughly disillusioned I interviewed with an autonomous car company for doing my thing (analytics for insight, auditability, accountability), got to “interview an SVP” where I realized they were more paying heed to the idea they wanted this, rather than actually wanting it. Afterwards, I told the recruiter I didn’t think it’d be a good fit & the recruiter told me the role had been eliminated
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@inthehands @davidzipper I didn't realize this phenomenon had a name, and there must be a million examples now of highway expansions leading to more traffic. He says, as they tirelessly expand all the interstates that swing by here.
The LED example is excellent, though. It's recent, and it's probably relatable. Hands up if you got told off as a kid for leaving lightbulbs on. These days? Not at much. Plus, we've demonstrably made light pollution worse.
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@inthehands @thatandromeda oh, absolutely. I have Subaru EyeSight and it's really good. It reduces fatigue on long drives in ways standard cruise control can't, and keeps a reliable, safe distance.
Although, I've regularly driven the system in two cars, 4 years difference in age, and it's interesting how they've tuned it differently. Where I'm used to it doing one thing in one car, it's subtly different in the other. "Same" system. Doesn't bode well for complete automation.
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@inthehands with apologies for the quick double reply, I just got around to reading that link. Absolutely fascinating. Couldn't help think about accidents I'm vaguely aware of, and ones I happen to know in depth because I've studied them for work, etc.
Will share that with my colleagues.
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@tehstu
It’s a classic. I always keep coming back to it. Glad it’s found a new fan!