By Dee Smith
The extraordinary arrogance displayed by AI specialists convinced that they are “creating” super-intelligence, or even creating God, is stunning. Given that human perception and understanding are too frail and incomplete to comprehend the insuperable complexity of the real world, or even of ourselves, the claim that we can make machines into super intelligences that transcend anything comprehensible to humans shows an astonishing hubris. If we cannot even realistically determine how human or animal minds operate, how could we have any basis of making such claims about AIs?
Nonetheless, in part because our understanding of intelligence, consciousness, and the world itself is so lacking, there may well be aspects of machine intelligence that can become very dangerous indeed, even if machines do not experience anything like the consciousness and awareness that animals—including humans—possess.
An AI may not require human-type consciousness, or even what we think of as awareness, to manifest agency and intentionality, and to act on those.
That may seem like a contradiction in terms, but it may just be that we don’t have the understanding and lexicon to grasp and express what is going on. There may be a different “package” or mix of elements in AIs than there is in humans or animals: a mix that can produce qualities that seem paradoxical to us.
We may well be anthropomorphizing: assigning human characteristics to AIs that are utterly non-human and don’t think or behave like humans (despite being “trained” on a substantial part of human knowledge). In looking for human-type consciousness or intelligence, we may have our eye on the wrong ball.
Are we asking the wrong questions?
As Gertrude Stein memorably said: “When you get there, there isn’t any there there.” But what could that mean in the context of AI?
In the final analysis, yet again, we just don’t know.
We have, however, for decades studied elements about complex systems that are relevant to all of this. (The study of complexity is one of the great triumphs of 20th century science— and was enabled by earlier digital computers.) Put basically, order and structure emerge spontaneously and often unexpectedly from complex systems. Consider how organized a hurricane is, although it starts out as only water vapor, wind, and heat from sunlight and water. Or look at the beautiful structures that emerge in a cup of coffee when you pour cream into it.
This characteristic of emergent properties innately becoming orders of magnitude more complex is another element that should give us pause. What is emerging or will emerge unexpectedly within complex AI systems? We don’t know, although we see some alarming indicators, as noted earlier.
One danger is even that AIs could lead to a dumbed-down, binary perceptual world that is devoid of certain kinds of awareness and thought, but that is nevertheless relentlessly driven by the pursuit by the AIs of programmed or ultimately machine-derived goals. Suppose, for example, that humans program an AI with explicit and non-cancellable instructions to ensure that nothing further damages Earth’s biosphere, and the AI determines that humans are the reason the biosphere is being damaged. Then, with impeccable logic, the AI decides that humans must be eliminated in order to fulfill its programming. Now, that is a relatively straightforward example with relatively simple fail-safes. But can we think of, forecast, and guard against all the permutations of all the programs in all the AIs, including programs they may generate themselves? The answer is no.
Clearly, AI has benefits. For example, recent AI redesigns of aircraft wings, in particular in Germany and China, seem to provide significantly more efficiency. AIs can, though statistical means, solve mathematics problems, and devise winning gaming strategies never before seen (such as in chess). AI is good at organizing and summarizing information, another statistical, calculational task. But you have to check the output for errors and hallucinations every time. For example, recent private research showed that the best AI model that was tested scored 82.4% accuracy on financial spreadsheets. This means that one number in about every six is wrong. Would any manager put up with that level of inaccuracy from a human analyst?
The only sane thing to do would be to slow all of this way down, or even bring it essentially to a halt, at least until we can figure out more about what it really represents. And we may never figure that out: the problem of consciousness is so intractable that we may not be equipped with the means to ever understand it.
But humans, with their competitive natures and competitive national and commercial structures—and their strange predilection to act against their own interests to satisfy psychological and financial needs—seem extremely unlikely to slow down. Even if it is banned, countries will continue to develop AI in secret based on their fear that an adversary nation is also developing it in secret.
Tragically, AI may turn out to be a perfect exemplar of the Great Filter—and possibly in the not-too-distant future.
What happens would seem ultimately to depend on the maturity of the human race, and on luck: two constantly recurring, and terrifyingly thin, threads to hang our future on.
AI is by no means the only part of the Great Filter story, just my entry point. More soon!