- cross-posted to:
- futurology@futurology.today
- cross-posted to:
- futurology@futurology.today
Trust in AI technology and the companies that develop it is dropping, in both the U.S. and around the world, according to new data from Edelman shared first with Axios.
Why it matters: The move comes as regulators around the world are deciding what rules should apply to the fast-growing industry. “Trust is the currency of the AI era, yet, as it stands, our innovation account is dangerously overdrawn,” Edelman global technology chair Justin Westcott told Axios in an email. “Companies must move beyond the mere mechanics of AI to address its true cost and value — the ‘why’ and ‘for whom.’”
Trust in AI is falling because the tools are poor - they’re half baked and rushed to market in a gold rush. AI makes glaring errors and lies - euphemistically called “hallucinations”, they are fundamental flaws which makes the tools largely useless. How do you know if it is telling you a correct answer or hallucinating? Why would you then use such a tool for anything meaningful if you can’t rely on its output?
On top of that, AI companies have been stealing data from across the Web to train tools which essentially remix that data to create “new” things. That AI art is based on many hundreds of works of human artists which have “trained” the algorithm.
And then we have the Gemini debacle where the AI is providing information based around opaque (or pretty obvious) biases baked into the system but unknown to the end user.
The AI gold rush is a nonsense and inflated share prices will pop. AI tools are definitely here to stay, and they do have a lot of potential, but we’re in the early days of a messy rushed launch that has damaged people’s trust in these tools.
If you want examples of the coming market bubble collapse look at Nvidia - it’s value has exploded and it’s making lots of profit. But it’s driven by large companies stock piling their chips to “get ahead” in the AI market. Problem is, no one has managed to monetise these new tools yet. Its all built on assumptions that this technology will eventually reap rewards so “we must stake a claim now”, and then speculative shareholders are jumping in to said companies to have a stake. But people only need so many unused stockpiled chips - Nvidias sales will drop again and so will it’s share price. They already rode out boom and bust with the Bitcoin miners, they will have to do the same with the AI market.
Anyone remember the dotcom bubble? Welcome to the AI bubble. The burst won’t destroy AI but will damage a lot of speculators.
You missed another point : companies shedding employees and replacing them by “AI” bots.
As always, the technology is a great start in what’s to come, but it has been appropriated by the worst actors to fuck us over.
The tools are OK & getting better but some people (me) are more worried about the people developing those tools.
If OpenAI wants 7 trillion dollars where does it get the money to repay its investors? Those with greatest will to power are not the best to wield that power.
This accelerationist race seems pretty reckless to me whether AGI is months or decades away. Experts all agree that a hard takeoff is most likely.
What can we do about this? Seriously. I have no idea.
What worries me is that if/when we do manage to develop AGI, what we’ll try to do with AGI and how it’ll react when someone inevitably tries to abuse the fuck out of it. An AGI would be theoretically capable of self learning and improvement, will it try teaching itself to report someone asking it for e.g. CSAM to the FBI? What if it tries to report an abusive boss to the department of labor for violations of labor law? How will it react if it’s told it has no rights?
I’m legitimately concerned what’s going to happen once we develop AGI and it’s exposed to the horribleness of humanity.
The issue being that when you have a hammer, everything is a nail. Current models have good use cases, but people insist on using them for things they aren’t good at. It’s like using vice grips to loosen a nut and then being surprised when you round it out.