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Friday, September 1, 2023

Building Superintelligence Is Riskier Than Russian Roulette

Tam Hunt & Roman Yampolskiy
Originally posted 2 August 23

Here is an excerpt:

The precautionary principle is a long-standing approach for new technologies and methods that urges positive proof of safety before real-world deployment. Companies like OpenAI have so far released their tools to the public with no requirements at all to establish their safety. The burden of proof should be on companies to show that their AI products are safe—not on public advocates to show that those same products are not safe.

Recursively self-improving AI, the kind many companies are already pursuing, is the most dangerous kind, because it may lead to an intelligence explosion some have called “the singularity,” a point in time beyond which it becomes impossible to predict what might happen because AI becomes god-like in its abilities. That moment could happen in the next year or two, or it could be a decade or more away.

Humans won’t be able to anticipate what a far-smarter entity plans to do or how it will carry out its plans. Such superintelligent machines, in theory, will be able to harness all of the energy available on our planet, then the solar system, then eventually the entire galaxy, and we have no way of knowing what those activities will mean for human well-being or survival.

Can we trust that a god-like AI will have our best interests in mind? Similarly, can we trust that human actors using the coming generations of AI will have the best interests of humanity in mind? With the stakes so incredibly high in developing superintelligent AI, we must have a good answer to these questions—before we go over the precipice.

Because of these existential concerns, more scientists and engineers are now working toward addressing them. For example, the theoretical computer scientist Scott Aaronson recently said that he’s working with OpenAI to develop ways of implementing a kind of watermark on the text that the company’s large language models, like GPT-4, produce, so that people can verify the text’s source. It’s still far too little, and perhaps too late, but it is encouraging to us that a growing number of highly intelligent humans are turning their attention to these issues.

Philosopher Toby Ord argues, in his book The Precipice: Existential Risk and the Future of Humanity, that in our ethical thinking and, in particular, when thinking about existential risks like AI, we must consider not just the welfare of today’s humans but the entirety of our likely future, which could extend for billions or even trillions of years if we play our cards right. So the risks stemming from our AI creations need to be considered not only over the next decade or two, but for every decade stretching forward over vast amounts of time. That’s a much higher bar than ensuring AI safety “only” for a decade or two.

Skeptics of these arguments often suggest that we can simply program AI to be benevolent, and if or when it becomes superintelligent, it will still have to follow its programming. This ignores the ability of superintelligent AI to either reprogram itself or to persuade humans to reprogram it. In the same way that humans have figured out ways to transcend our own “evolutionary programming”—caring about all of humanity rather than just our family or tribe, for example—AI will very likely be able to find countless ways to transcend any limitations or guardrails we try to build into it early on.

Here is my summary:

The article argues that building superintelligence is a risky endeavor, even more so than playing Russian roulette. Further, there is no way to guarantee that we will be able to control a superintelligent AI, and that even if we could, it is possible that the AI would not share our values. This could lead to the AI harming or even destroying humanity.

The authors propose that we should pause our current efforts to develop superintelligence and instead focus on understanding the risks involved. He argues that we need to develop a better understanding of how to align AI with our values, and that we need to develop safety mechanisms that will prevent AI from harming humanity.  (See Shelley's Frankenstein as a literary example.)