Among the many recent controversies around AI, there is the claim that to solve a longstanding mathematical problem, OpenAI stole the work of the New York University mathematician Tristan Buckmaster and a colleague, Levent Alpöge, who also is a researcher for Anthropic. I have no ability to assess the validity of the claim, but as I understand it, the argument is that OpenAI had access to work done by Buckmaster and Alpöge. It then built on this work to quickly rush ahead and find a solution, which also had a $1 million prize attached to it.
Insofar as that accurately describes what OpenAI did, this seems like it would be equivalent to having a professor doing a seminar for colleagues and then having one of the attendees do a few additions and claim the work as their own. This would not be viewed as very collegial behavior in a normal academic department.
I’m not sure what claim a professor would have against a colleague under such circumstances. I suppose if their work was properly cited, there would not be a claim of plagiarism. (OpenAI’s work did not directly cite the work of Buckmaster and Alpöge, from my understanding.) I suppose there could be a basis for disputing rights to the million-dollar prize. But the problem seems much greater.
If AI can effectively steal the work of others, and claim it as its own, then it undermines the practice of openness in science that has allowed for enormous progress for centuries. This practice depended on norms, whereby scientists would properly credit the work of their peers.
In the seminar scenario I described, if one of the attendees listened to the presentation and realized the one or two additional steps needed to get over the goal line, they would be expected to raise the issue with the presenter. Assuming the additions were correct, the presenter would finish the paper, acknowledging the contribution or possibly adding the attendee as a co-author, if their contribution was sufficiently important.
But that relies on norms. If the owner of the AI doesn’t share those norms and can freely scrape scientific work wherever it finds it, and then take credit for the product, it will threaten the longstanding practice of openness in science. With the risk of having years of work stolen without getting any credit, researchers will likely keep their work closely held until they have a finished paper.1 They would only share it with a small group of trusted colleagues. Posting a working paper, or having an open seminar, would put control over their work at risk.
However, it is important to recognize the villain in this story. It is Sam Altman and his company, not the AI. Altman and the company are the ones responsible for what their AI does. If it did something they disapprove of, it is their responsibility to correct it. However adept AI may become, it is not the active player; it is the individual or company that set it in motion.
This issue applies more generally. There has been a social media mini firestorm over Texas Attorney General and Republican Senate candidate Ken Paxton using AI to have his opponent, James Talarico, making a series of outlandish statements that he never said. Much of the outrage seems to be over Paxton using AI, rather than the fact that he is lying about what Talarico said.
The issue here is that Paxton is defaming Talarico; the AI is secondary. The AI presumably makes the defamation more effective, but if Paxton were an exceptionally gifted mimic, he could likely also trick some people into believing that he was speaking in Talarico’s voice when making outlandish assertions. If that were the case, it would be every bit as bad as using AI to accomplish the job.
There were also the claims that the girls’ school in Iran, which was destroyed by the US military on the first day of the war, killing 120 children, was selected as a target by AI. That may be the case, but the important point was that the military did not have a system in place to properly review targets. It doesn’t matter whether or not an AI system identified the target. The problem was that there was no system that ensured the places designated were proper military targets.
It is important to keep our eyes on the ball. The bad actors are those who do bad things with AI, not the AI. This is like the husband who gets drunk and beats his wife and then says the whiskey did it. No one should ever accept that story. In the same vein, if a theft of mathematical work did occur, it was Sam Altman who did it and it was Ken Paxton who libeled his political opponent. The AI is beside the point.
Of course he did, that doesn't mean AI is a worthwhile product. It is just a means for rich to steal your life.
Your problem is with capitalism, not AI.
Blaming a field of machine learning because some rich assholes are exploiting it demonstrates a failure to diagnose the issue.
AI isn't building data centers, a human being made that decision.
That's the core problem. The wealthy capitalists both own and drive the development of ML right now. I agree that machine learning algorithms (AI) in a vacuum aren't inherently a problem, but that's just a hypothetical position versus the material reality we all face every day.
Maybe we'll get global Socialism or Communism someday, but trying to convince people that AI is fundamentally good underneath it all is putting the cart before the horse; AI as it stands is a symbol of Capitalism and the problems it embodies.
Worry about the nuances of AI after you've dealt with the rot.
I know and agree.
I'm only saying that promoting that symbol is damaging in other ways, such as to the sciences.
Some people may be expressing an opinion with that type of nuance (and I do agree with it) but, what appears to be the large majority of social media users on this topic don't make that distinction and those people attack the sciences/non-LLM uses of the technology.
Yes, overuse of local water and power supplies is damaging, the replacement of workers is causing all kinds of economic issues, the ability for AI to enable mass surveilance and authoritarians is an urgent problem that needs to be addressed AND ALSO the people trying to fight against it are causing collateral damage to other important aspects of society, an example being that it's making ML/AI a less popular major which will result in less researchers/slower advancement.
It's important to point out that there have been several advances in AI that have significantly reduced the computation requirements. So, whatever the demand for AI will ultimately be, it will require an order of magnitude less datacenters because of this kind of research.
The source of the problems here are the people making the decision to deploy the technology in this way and their outsized influence on the government that should be regulating their actions.
AI is just the current topic. Outsourcing was another huge topic in the Clinton era. After that we had the post-crash bailout and the mass acquisition of housing by large capital funds in order to control the rental/real estate markets.
All of these things caused massive economic issues for the vast majority of people and were entirely done because the people that benefitted were able to influence the government and prevent their regulation.
This isn't an AI problem. It's a power, influence and corruption problem. AI's destructive deployment is just the current symptom.