Psychology professor at University of New Mexico. BA Columbia, PhD Stanford. Works on evolutionary psychology, Effective Altruism, AI alignment, X risk. Worked on neural networks, genetic algorithms, evolutionary robotics, &  autonomous agents back in the 90s.

Wiki Contributions


Gordon - I was also puzzled by the initial downvotes. But they happened so quickly that I figured the downvoters hadn't actually read or digested my essay. Disappointing that this happens on LessWrong, but here we are.

Max - I think your observations are right. The 'normies', once they understand AI extinction risk, tend to have much clearer, more decisive, more negative moral reactions to AI than many EAs, rationalists, and technophiles tend to have. (We've been conditioned by our EA/Rat subcultures to think we need to 'play nice' with the AI industry, no matter how sociopathic it proves to be.)

Whether a moral anti-AI backlash can actually slow AI progress is the Big Question. I think so, but my epistemic confidence on this issue is pretty wide.  As an evolutionary psychologist, my inclination is to expect that human instincts for morally stigmatizing behaviors, traits, and people perceived as 'evil' have evolved to be very effective in reducing those behaviors, suppressing those traits, and ostracizing those people. But whether those instincts can be organized at a global scale, across billions of people, is the open question. 

Of course, we don't need billions to become anti-AI activists. We only need a few million of the most influential, committed people to raise the alarm -- and that would already vastly out-number the people working in the AI industry or actively supporting its hubris.

Maybe. But at the moment, the US is really the only significant actor in the AGI development space. Other nations are reacting in various ways, ranging from curious concern to geopolitical horror. But if we want to minimize risk of a nation-state AI arms races, the burden is on the US companies to Just Stop Unilaterally Driving The Arms Race.

I'm predicting that an anti-AI backlash is likely, given human moral psychology and the likely applications of AI over the next few years.

In further essays I'm working on, I'll probably end up arguing that an anti-AI backlash may be a good strategy for reducing AI extinction risk -- probably much faster, more effective, and more globally applicable than any formal regulatory regime or AI safety tactics that the AI industry is willing to adopt.

Well, the AI industry and the pro-AI accelerationists believe that there is an 'immense upside of AGI', but that is a highly speculative, faith-based claim, IMHO. (The case for narrow AI having clear upsides is much stronger, I think.)

It's worth noting that almost every R&D field that has been morally stigmatized -- such as intelligence research, evolutionary psychology, and behavior genetics -- also offered huge and transformative upsides to society, when the field first developed. Until they got crushed by political demonization, and their potential was strangled in the cradle, so to speak.

The public perception of likely relative costs vs. benefits is part of the moral stigmatization process. If AI gets stigmatized, the public will not believe that AGI has 'immense upside'. And they might be right.

I don't think so. My friend Peter Todd's email addresses typically include his middle initial 'm'.


mwatkins - thanks for a fascinating, detailed post. 

This is all very weird and concerning. As it happens, my best friend since grad school is Peter Todd, professor of cognitive science, psychology, & informatics at Indiana University. We used to publish a fair amount on neural networks and genetic algorithms back in the 90s.

That's somewhat helpful. 

I think we're coming at this issue from different angles -- I'm taking a very evolutionary-functional view focused on what selection pressures shape psychological adaptations, what environmental information those adaptations need to track (e.g. snake! or pathogen!), what they need to represent about the world (e.g. imminent danger of death from threat X!), and what behaviors they need to trigger (e.g. run away!). 

From that evolutionary-functional view, the 'high-level cognitive properties' of 'fitness affordances' are the main things that matter to evolved agents, and the lower-level details of what genes are involved, what specific neural circuits are needed, or what specific sensory inputs are relevant, just don't matter very much -- as long as there's some way for evolution to shape the relevant psychological adaptations. 

And the fact that animals do reliably evolve to track the key fitness affordances in their environments (e.g. predators, prey, mates, offspring, kin, herds, dangers) suggests that the specifics of neurogenetic development don't in fact impose much of a constraint on psychological evolution. 

It seems like you're coming at the issue from more of a mechanistic, bottom-up perspective that focuses on the mapping from genes to neural circuits. Which is fine, and can be helpful. But I would just be very wary about using neurogenetic arguments to make overly strong claims about what evolution can or can't do in terms of crafting complex psychological adaptations.

If we're dead-serious about infohazards, we can't just be thinking in terms of 'information that might accidentally become known to others through naive LessWrong newbies sharing it on Twitter'. 

Rather, we need to be thinking in terms of 'how could we actually prevent the military intelligence analysts of rival superpowers from being able to access this information'?

My personal hunch is that there are very few ways we could set up sites, security protocols, and vetting methods that would be sufficient to prevent access by a determined government. Which would mean, in practice, that we'd be sharing our infohazards only with the most intelligent, capable, and dangerous agents and organizations out there.

Which is not to say we shouldn't try to be very cautious about this issue. Just that we shouldn't be naive about what the American NSA, Russian GRU, or Chinese MSS would be capable of.

If we're nowhere close to solving alignment well enough that even a coarse-grained description of actual human values is relevant yet, then I don't understand why anyone is advocating further AI research at this point. 

Also, 'avoiding deceptive alignment' doesn't really mean anything if we don't have a relatively rich and detailed description of what 'authentic alignment' with human values would look like. 

I'm truly puzzled by the resistance that the AI alignment community has against learning a bit more about the human values we're allegedly aligning with. 

Load More