Comment by lukifer
6 hours ago
Bear in mind, the same moral hazard of "high horse", "grift", etc, exists in the other direction. Ed Zitron, for instance, is likely correct about the financial bubble of the AI firms; and yet he seems frequently out of his depth on understanding the technology, and has a long history of predicting dead-ends in capabilities, which didn't occur [0].
But I feel no need to dismiss him as a "grifter", for a simple reason: as much as there are perverse incentives in our attention economy (audience capture in particular), the most effective grifters are the ones who believe what they are saying. Grifters who are knowingly dishonest are less persuasive. Far more pernicious is the confabulation of self-deception: cherry-picking evidence to support your narrative, while dismissing evidence which would contradict it.
It is entirely fair to call this out when it occurs among "doomers", and it would be naive to think it doesn't. But the same forces are at work amongst the skeptics as well. And maybe it's my own subjective bias, or algo-filtered information ecology, but I see far more dismissal of risk/doom by skeptics, accusations of delusion or cynical bias (ad hominem in the formal sense), than I've seen the other direction. I see very little refutation of the arguments ("here's why instrumental convergence can't overtake a human-provided goal"), and much more character attack ("they're in the pockets of Big AI, it's a marketing ploy to make the models look more impressive than they are").
I consider Zitron to be part of it all, not a counter example.
He’s built an audience and gained fame through his writings where he gathers people who think they know better than the unwashed masses. Once that becomes your bread and butter, it becomes hard not to believe what you’ve been preaching. People will come to deeply believe that which brings them fame and fortune.
I don’t think your grifter purity test is therefore all that useful. It actually doesn’t matter in the end if the person believes it or not, the end effect is the same.
> I see very little refutation of the arguments ("here's why instrumental convergence can't overtake a human-provided goal"), and much more character attack ("they're in the pockets of Big AI, it's a marketing ploy to make the models look more impressive than they are").
Hard disagree. There has been much refutation and quality analysis at every point. The AI safety people pull back to arguments about character as their defense.
The AI 2027 site for example drew numerous high quality refutations. Many people’s analyses showed in the first week that the mathematical model was useless as changing the supposed inputs resulted in the same outcome. All of these criticisms were met with a flood of attacks based on reputation, claiming that we should defer to Scott Alexander and other writers of the AI 2027 article due to their stats and reputation.
Meanwhile, defenses like yours that try to reduce the critics to ad hominem attackers continue to open the door to actual grifters coming in and extracting money and fame from the AI safety community. The otherwise completely inexplicable link between AI safety communities and Slutcon or the use of AI safety group buildings to host orgies (I can’t believe I’m writing this) is the current example of this. When it keeps happening over and over, some self-awareness is needed. I can’t buy the endless defenses that we must ignore or even defend all of these things that are happening that are clearly insane to anyone who hasn’t become trapped in the groupthink defenses of the core parts of these communities.
At some point the routine of “Tut tut, you are not allowed to make that criticism bruise as hominem!” becomes a smokescreen that the grifters are weaponizing to get their defenders mobilized. Some times, the person’s actions and reputation do need to be taken into account.
> There has been much refutation and quality analysis at every point.
I am curious about this. Any high quality refutations that directly engage with the arguments and the findings of published safety papers?
> Many people’s analyses showed in the first week that the mathematical model
Even if the model is faulty it just changes the timeline, no? (they predicted the OpenAI outbreak will happen in January 2027 fwiw, so they don't seem too far off)
> Slutcon or the use of AI safety group buildings to host orgies
I mean it's a bit weird, sure, but so what? What exactly is bothering you about these orgies?