Most things to do with Green Energy. Don’t get me wrong, I think solar panels or wind turbines are great. I just think that most of the reported figures are technically correct but chosen to give a misleadingly positive impression of the gains.
Relevant smbc: https://www.smbc-comics.com/comic/capacity
I think they don’t matter with outrage, because outrage explodes in ways that are hard to predict. I mean, I can see the problem with the ad now that it has been pointed out to me. After reading about it repeatedly, I now find it bad and ridiculous and what were they thinking? But at a first look, as a test audience I would have probably rated it as “meh, ok”.
AKA “shit, looks like now we need to re-hire some of those engineers”
TBH those same colleagues were probably just copy/pasting code from the first google result or stackoverflow answer, so arguably AI did make them more productive at what they do
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About 20 new cases of gender violence arrive every day, each requiring investigation. Providing police protection for every victim would be impossible given staff sizes and budgets.
I think machine-learning is not the key part, the quote above is. All these 20 people a day come to the police for protection, a very small minority of them might be just paranoid, but I’m sure that most of them had some bad shit done to them by their partner already and (in an ideal world) would all deserve some protection. The algorithm’s “success” in defined in the article as reducing probability of repeat attacks, especially the ones eventually leading to death.
The police are trying to focus on the ones who are deemed to be the most at risk. A well-trained algorithm can help reduce the risk vs the judgement of the possibly overworked or inexperienced human handling the complaint? I’ll take that. But people are going to die anyway. Just, hopefully, a bit less of them and I don’t think it’s fair to say that it’s the machine’s fault when they do.
I have to admit It was a solid idea, though. Dick pics should be one of the best training sets you can find on the internet and you can assume that the most prolific senders are the ones with the lowest chance of having an STI (or any real-life sexual activity).
it’s just a convenience, not a magic wand. Sure relying on AI blindly and exclusively is a horrible idea (that lots of people peddle and quite a few suckers buy), but there’s room for a supervised and careful use of AI, same as we started using google instead of manpages and (grudgingly, for the older of us) tolerated the addition of syntax highlighting and even some code completion to all but the most basic text editors.
“Spectacular custom built oceanback, home, impressive land views & only a 5 minutes swim to the beach!”
we are doing this, now?
Just wanted to point out that the Pinterest examples are conflating two distinct issues: low-quality results polluting our searches (in that they are visibly AI-generated) and images that are not “true” but very convincing,
The first one (search results quality) should theoretically be Google’s main job, except that they’ve never been great at it with images. Better quality results should get closer to the top as the algorithm and some manual editing do their job; crappy images (including bad AI ones) should move towards the bottom.
The latter issue (“reality” of the result) is the one I find more concerning. As AI-generated results get better and harder to tell from reality, how would we know that the search results for anything isn’t a convincing spoof just coughed up by an AI? But I’m not sure this is a search-engine or even an Internet-specific issue. The internet is clearly more efficient in spreading information quickly, but any video seen on TV or image quoted in a scientific article has to be viewed much more skeptically now.
I’m not sure we, as a society, are ready to trust ML models to do things that might affect lives. This is true for self-driving cars and I expect it to be even more true for medicine. In particular, we can’t accept ML failures, even when they get to a point where they are statistically less likely than human errors.
I don’t know if this is currently true or not, so please don’t shoot me for this specific example, but IF we were to have reliable stats that everything else being equal, self-driving cars cause less accidents than humans, a machine error will always be weird and alien and harder for us to justify than a human one.
“He was drinking too much because his partner left him”, “she was suffering from a health condition and had an episode while driving”… we have the illusion that we understand humans and (to an extent) that this understanding helps us predict who we can trust not to drive us to our death or not to misdiagnose some STI and have our genitals wither. But machines? Even if they were 20% more reliable than humans, how would we know which ones we can trust?