Artificial intelligence: who owns the future? - ethical.net
Whether consciously or not, AI manufacturers have decided to prioritise plausibility over accuracy. It means AI systems are impressive, but in a world plagued by conspiracy and disinformation this decision only deepens the problem.
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Information literacy and chatbots as search • Buttondown
If someone uses an LLM as a replacement for search, and the output they get is correct, this is just by chance. Furthermore, a system that is right 95% of the time is arguably more dangerous tthan one that is right 50% of the time. People will be more likely to trust the output, and likely less able to fact check the 5%.
Report: Thinking about using AI? - Green Web Foundation
A solid detailed in-depth report.
The sheer amount of resources needed to support the current and forecast demand from AI is colossal and unprecedented.
A short note on AI – Me, Robin
I hope to make something that could only exist because I made it. Something that is the one thing that it is. Not an average sentence. Not a visual approximation of other people’s work. Not a stolen concept that boils lakes and uses more electricity than anything in my household.
Why “AI” projects fail
“AI” is heralded (by those who claim it to replace workers as well as those that argue for it as a mere tool) as a thing to drop into your workflows to create whatever gains promised. It’s magic in the literal sense. You learn a few spells/prompts and your problems go poof. But that was already bullshit when we talked about introducing other digital tools into our workflows.
And we’ve been doing this for decades now, with every new technology we spend a lot of money to get a lot of bloody noses for way too little outcome. Because we keep not looking at actual, real problems in front of us – that the people affected by them probably can tell you at least a significant part of the solution to. No we want a magic tool to make the problem disappear. Which is a significantly different thing than solving it.
Does AI benefit the world? – Chelsea Troy
Our ethical struggle with generative models derives in part from the fact that we…sort of can’t have them ethically, right now, to be honest. We have known how to build models like this for a long time, but we did not have the necessary volume of parseable data available until recently—and even then, to get it, companies have to plunder the internet. Sitting around and waiting for consent from all the parties that wrote on the internet over the past thirty years probably didn’t even cross Sam Altman’s mind.
On the environmental front, fans of generative model technology insist that eventually we’ll possess sufficiently efficient compute power to train and run these models without the massive carbon footprint. That is not the case at the moment, and we don’t have a concrete timeline for it. Again, wait around for a thing we don’t have yet doesn’t appeal to investors or executives.
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I listened to a day of talks on AI at UX Brighton, and I came away disappointed by what wasn’t mentioned.