I like this three-part decomposition: digital, physical, social. One thing that holds AI back in the social is a lack of embodied empathy and a lack of a "theory of mind." Part of my ability to predict your actions, understand your goals, and potentially collaborate or compete with you is a blend of my knowledge of the needs common to all humans and the specific needs or goals you are trying to satisfy in the current situation.
I think the digital/physical/social breakdown is useful for considerations of complexity and coordination. Unless we're just going to hand over all authority to robots, the objectives and machinations of humans will continue to loom large in attempts to improve or change.
Not too fond of the concluding line however - much too broad what is meant by 'genuine': "So I doubt that genuine artificial intelligence is close at hand." There are many kinds of intelligence, some have been achieved 'artificially' while many have not. Work is ongoing!
Although it is quite true that the human social realm is highly complex (and has been for a long time – recently finished the Payton and Mammitzch translation of Huizinga’s The Autumn of the Middle Ages which provides more than ample evidence should anyone doubt), that is not to say that human social institutions are particularly competent at the businesses they are ostensibly about and that absent certain sentimental attachments to the corrupt, random, and arbitrary, AI couldn’t readily replace a majority of humans in such enterprises as the courts, government bureaucracy, and the schools. And indeed each of these are lousy enough that there would be little lost in the unlikely event proved incapable of producing substantially better outcomes.
Dr. Kling mentions the human role in promoting motivation. While the research does demonstrate that certain techniques in the vein of self determination theory such as autonomy promotion can have demonstrably positive effects, these techniques are rarely taught in schools of education and few teachers have the wherewithal to practice them. Indeed observational studies find that the incidence of positive classroom environments in the US is rare. As most people are well aware:
AI on the other hand can execute motivational strategies consistently and competently:
“Yes, research indicates that AI can significantly boost student motivation, particularly when tools are designed to support autonomy, competence, and relatedness. A 2025 meta-analysis of 71 studies found that generative AI produces moderate positive effects on motivation and engagement, with the impact being stronger when students use AI consistently over time rather than in isolated instances.
The motivational benefits are driven by several key mechanisms:
Personalization and Autonomy: AI adapts to individual learning paces and interests, allowing students to direct their own learning paths, which fosters intrinsic motivation and reduces anxiety.
Immediate Feedback: Real-time, personalized feedback helps students understand their progress, enhancing their sense of competence and self-efficacy.
Engagement: Interactive features, such as adaptive gamification and conversational agents, make learning more enjoyable and sustain interest.“
Traditional teacher led classrooms perhaps are best understood through the lens of Clastres’ work on torture rituals in primitive cultures. Clastres views both torture rituals and public education as forms of coercion designed to maintain social order, but they operate differently:
Rites measure personal endurance and mark the body to prevent the rise of separate political power; they are an immediate, physical imposition of the group's will on the individual.
Schooling is a more abstract, systemic imposition where the "severity of the law" is taught intellectually, creating a population that cannot claim exemption from legal authority due to lack of knowledge. Whether the latter form of torture is more repulsive is a matter of debate one might suppose. At any rate, AI offers a measurable outcome oriented alternative amenable to scientific testing.
And similarly with the courts. Encouragingly, countries like Canada and Brazil have tested AI-assisted Online Dispute Resolution for simple civil claims and small money disputes, where algorithms may propose outcomes or mediate, though final binding judgments often still involve human elements or require party acceptance of AI proposals. Its hard to see how failure to achieve total replacement of judges by AIs in the next 5 to 10 years will be able to be attributable to anything other than sentimentality. It appears that support among the public would be widespread: https://www.pew.org/en/research-and-analysis/issue-briefs/2025/08/experience-with-state-courts-highlights-areas-for-improvement
Achieving supplantation progress in the simplest and easiest situations for AI, that is the rule and procedure bound administrative processes of government, are ironically the most difficult politically given the administrative state’s foundation in patronage and clientelism. The sinecures will be the hardest to abolish given the corrupt slugs we call a Congress.
Perhaps an ideological framework is needed to spur progress. Turning to Clastres again, perhaps Society against the State (https://theanarchistlibrary.org/library/pierre-clastres-society-against-the-state ) is a framework compatible with humanitiy’s innate psychological needs: autonomy, competence, and relatedness. When these needs are satisfied by social environments, people experience greater intrinsic motivation, well-being, and personal growth. AI may prove to be ideal tool to promote such social environments, because it decentralizes access to power thereby opens the door to progress. Clastres posited that “Knowledge is the ability to obtain, process and use information, so that it benefits you as an asset and not a liability.” AI ought be able to make this possible so that we are no longer trapped in the manifestation of Tom Clancy’s law of information: “ If you can control information, you can control people."
Should one wave through the autonomous vehicle? Should one refer to the LLM as "you"? My parent's pool tech used to refer to the vacuum as "he," so they named it "Bruce" in his honor. Like those who rejected Darwin, I think we overstate the difference between the human mind and this technology. Individual humans are no great shakes in any of these "worlds." The AI node counts are getting into the same ballpark as our neuron counts, and it can program itself (with a little help) a lot faster than we can. The AI is "spotting" different patterns entirely than we do... "Any sufficiently advanced technology is like magic" -- Arthur C. Clarke.
I think you're on to something but this short essay does need to go deeper. For instance, if the digital can concoct the fundamentals for a vaccine, then it can theoretically impact the physical world. Will it take physical assistance? Yes, until sophisticated robots are run by AI. Will it take social compliance/endorsement? Yes. Humans will need to cooperated. Willingly or otherwise. And with that, I'm treading on the whole alignment conversation. How can AI and humans align? The big question.
There is a fundamental flaw in this piece. It is focused on solving problems in the social and physical world such as cancer, education reform, and ever-evolving cyber security. But the concluding paragraphs include, "We decide what to believe by deciding who to believe." This may indeed be critical to how we acquire knowledge but it is not how we create new knowledge and capabilities. That often comes from ignoring much of what others believe.
Beyond that, even though AI tends to believe what others believe, it nonetheless has immense capabilities to draw from disparate sources in novel ways to come up with new alternatives. We don't know how well it will do at addressing social and physical problems on its own or with some assistance but I wouldn't discount the possibility. It's usefulness as a tool to speed human progress on these issues already has many clear examples.
"That Terminator is out there, it can't be bargained with, it can't be reasoned with, it doesn't feel pity or remorse or fear, and it absolutely will not stop… EVER, until you are dead!"
Modeling the interaction of light and matter in the physical world is difficult because light and matter are both complex phenomena and interaction between the two can be radically more complex. With enough resources you can measure how light scatters from a particular instance of matter. You can then feed that result into your model for a given case. But how well will that measurement work for a different case that you want to model? Your next case might differ in a dozen ways including wavelength, polarization, angle of incidence, angle of exitance, complex incidence of refraction, orientation and shape of scratches, scale, amount and shape of surface contaminants, temperature, partial coherence, and combinations of matter. Before training your a generally intelligent model of light-matter interaction you would need to conduct countless measurements and organize those measurements into a systematic library of scattering data.
But once you had such a model, you could model how drones see, thus increasing their accuracy and value.
Modeling the social realm seems impossible in comparison. Perhaps someone can sketch out what it would take?
In a physical model, the data is mostly or all somewhat objective. Social data is messier and far more subjective but it is still data on which to make decisions. AI decisions using this data will be less accurate but so are human decisions using this data.
Welcome to the party. Until AI enters the realm of the physical world (e.g. autonomous robots), then most of the chatter and valuations are overrated hype and not nearly as disruptive as tech bros would like us to believe.
Economics is driven by expectations, but nobody knows what all the possibilities are or what their respective probabilities are. FOMO (fear of missing out) enters in the generation of scenarios and their probability, e.g., "if we don't do X and they do Y, which is almost certain, we will go bankrupt." Fallible humans may give that scenario more probability than a perfectly rational creature would.
Wow - I’d never thought of looking at it this way before!
If you build it they will come…except when everyone builds it at the same time and then capacity far outpaces demand. That’s the point where expectations meet reality in a not so good way.
Expectations eventually meet reality. Some times it's not pretty. Some times people learn from it. And some times, "Real [fill in the blank] has never been tried."
I like this three-part decomposition: digital, physical, social. One thing that holds AI back in the social is a lack of embodied empathy and a lack of a "theory of mind." Part of my ability to predict your actions, understand your goals, and potentially collaborate or compete with you is a blend of my knowledge of the needs common to all humans and the specific needs or goals you are trying to satisfy in the current situation.
I think the digital/physical/social breakdown is useful for considerations of complexity and coordination. Unless we're just going to hand over all authority to robots, the objectives and machinations of humans will continue to loom large in attempts to improve or change.
Not too fond of the concluding line however - much too broad what is meant by 'genuine': "So I doubt that genuine artificial intelligence is close at hand." There are many kinds of intelligence, some have been achieved 'artificially' while many have not. Work is ongoing!
Although it is quite true that the human social realm is highly complex (and has been for a long time – recently finished the Payton and Mammitzch translation of Huizinga’s The Autumn of the Middle Ages which provides more than ample evidence should anyone doubt), that is not to say that human social institutions are particularly competent at the businesses they are ostensibly about and that absent certain sentimental attachments to the corrupt, random, and arbitrary, AI couldn’t readily replace a majority of humans in such enterprises as the courts, government bureaucracy, and the schools. And indeed each of these are lousy enough that there would be little lost in the unlikely event proved incapable of producing substantially better outcomes.
Dr. Kling mentions the human role in promoting motivation. While the research does demonstrate that certain techniques in the vein of self determination theory such as autonomy promotion can have demonstrably positive effects, these techniques are rarely taught in schools of education and few teachers have the wherewithal to practice them. Indeed observational studies find that the incidence of positive classroom environments in the US is rare. As most people are well aware:
https://www.pewresearch.org/short-reads/2024/04/04/about-half-of-americans-say-public-k-12-education-is-going-in-the-wrong-direction/
AI on the other hand can execute motivational strategies consistently and competently:
“Yes, research indicates that AI can significantly boost student motivation, particularly when tools are designed to support autonomy, competence, and relatedness. A 2025 meta-analysis of 71 studies found that generative AI produces moderate positive effects on motivation and engagement, with the impact being stronger when students use AI consistently over time rather than in isolated instances.
The motivational benefits are driven by several key mechanisms:
Personalization and Autonomy: AI adapts to individual learning paces and interests, allowing students to direct their own learning paths, which fosters intrinsic motivation and reduces anxiety.
Immediate Feedback: Real-time, personalized feedback helps students understand their progress, enhancing their sense of competence and self-efficacy.
Engagement: Interactive features, such as adaptive gamification and conversational agents, make learning more enjoyable and sustain interest.“
Traditional teacher led classrooms perhaps are best understood through the lens of Clastres’ work on torture rituals in primitive cultures. Clastres views both torture rituals and public education as forms of coercion designed to maintain social order, but they operate differently:
Rites measure personal endurance and mark the body to prevent the rise of separate political power; they are an immediate, physical imposition of the group's will on the individual.
Schooling is a more abstract, systemic imposition where the "severity of the law" is taught intellectually, creating a population that cannot claim exemption from legal authority due to lack of knowledge. Whether the latter form of torture is more repulsive is a matter of debate one might suppose. At any rate, AI offers a measurable outcome oriented alternative amenable to scientific testing.
And similarly with the courts. Encouragingly, countries like Canada and Brazil have tested AI-assisted Online Dispute Resolution for simple civil claims and small money disputes, where algorithms may propose outcomes or mediate, though final binding judgments often still involve human elements or require party acceptance of AI proposals. Its hard to see how failure to achieve total replacement of judges by AIs in the next 5 to 10 years will be able to be attributable to anything other than sentimentality. It appears that support among the public would be widespread: https://www.pew.org/en/research-and-analysis/issue-briefs/2025/08/experience-with-state-courts-highlights-areas-for-improvement
Achieving supplantation progress in the simplest and easiest situations for AI, that is the rule and procedure bound administrative processes of government, are ironically the most difficult politically given the administrative state’s foundation in patronage and clientelism. The sinecures will be the hardest to abolish given the corrupt slugs we call a Congress.
Perhaps an ideological framework is needed to spur progress. Turning to Clastres again, perhaps Society against the State (https://theanarchistlibrary.org/library/pierre-clastres-society-against-the-state ) is a framework compatible with humanitiy’s innate psychological needs: autonomy, competence, and relatedness. When these needs are satisfied by social environments, people experience greater intrinsic motivation, well-being, and personal growth. AI may prove to be ideal tool to promote such social environments, because it decentralizes access to power thereby opens the door to progress. Clastres posited that “Knowledge is the ability to obtain, process and use information, so that it benefits you as an asset and not a liability.” AI ought be able to make this possible so that we are no longer trapped in the manifestation of Tom Clancy’s law of information: “ If you can control information, you can control people."
Should one wave through the autonomous vehicle? Should one refer to the LLM as "you"? My parent's pool tech used to refer to the vacuum as "he," so they named it "Bruce" in his honor. Like those who rejected Darwin, I think we overstate the difference between the human mind and this technology. Individual humans are no great shakes in any of these "worlds." The AI node counts are getting into the same ballpark as our neuron counts, and it can program itself (with a little help) a lot faster than we can. The AI is "spotting" different patterns entirely than we do... "Any sufficiently advanced technology is like magic" -- Arthur C. Clarke.
"... is indistinguishable from magic."
from his 1962 book "Profiles of the Future"
I think you're on to something but this short essay does need to go deeper. For instance, if the digital can concoct the fundamentals for a vaccine, then it can theoretically impact the physical world. Will it take physical assistance? Yes, until sophisticated robots are run by AI. Will it take social compliance/endorsement? Yes. Humans will need to cooperated. Willingly or otherwise. And with that, I'm treading on the whole alignment conversation. How can AI and humans align? The big question.
There is a fundamental flaw in this piece. It is focused on solving problems in the social and physical world such as cancer, education reform, and ever-evolving cyber security. But the concluding paragraphs include, "We decide what to believe by deciding who to believe." This may indeed be critical to how we acquire knowledge but it is not how we create new knowledge and capabilities. That often comes from ignoring much of what others believe.
Beyond that, even though AI tends to believe what others believe, it nonetheless has immense capabilities to draw from disparate sources in novel ways to come up with new alternatives. We don't know how well it will do at addressing social and physical problems on its own or with some assistance but I wouldn't discount the possibility. It's usefulness as a tool to speed human progress on these issues already has many clear examples.
Perhaps we need to examine the highest realm, which is the spiritual realm.
I think, therefore I am was popularized but not owned by Descartes.
The Jewish tradition would say that thought is a passageway to the spiritual.
I am is a spiritual statement of my existence. Existence itself belongs to the spiritual realm.
Just beyond the pale of our brave new world a gathering darkness haunts our fevered hopes.
Not yet!
https://youtu.be/xcPeTeTBqHE?is=WZ5p13qF3jBRc3sy
"That Terminator is out there, it can't be bargained with, it can't be reasoned with, it doesn't feel pity or remorse or fear, and it absolutely will not stop… EVER, until you are dead!"
What you wrote is stated simply and elegantly. And becomes obvious: the mark of brilliance.
Modeling the interaction of light and matter in the physical world is difficult because light and matter are both complex phenomena and interaction between the two can be radically more complex. With enough resources you can measure how light scatters from a particular instance of matter. You can then feed that result into your model for a given case. But how well will that measurement work for a different case that you want to model? Your next case might differ in a dozen ways including wavelength, polarization, angle of incidence, angle of exitance, complex incidence of refraction, orientation and shape of scratches, scale, amount and shape of surface contaminants, temperature, partial coherence, and combinations of matter. Before training your a generally intelligent model of light-matter interaction you would need to conduct countless measurements and organize those measurements into a systematic library of scattering data.
But once you had such a model, you could model how drones see, thus increasing their accuracy and value.
Modeling the social realm seems impossible in comparison. Perhaps someone can sketch out what it would take?
In a physical model, the data is mostly or all somewhat objective. Social data is messier and far more subjective but it is still data on which to make decisions. AI decisions using this data will be less accurate but so are human decisions using this data.
Longer? No. Less is more.
As the late Howard Pattee wrote, "No amount of semiotic information, thought, or discourse alone can cause the body to move. It takes some physics."
The first function of language was to cause actions, not to make statements.
Welcome to the party. Until AI enters the realm of the physical world (e.g. autonomous robots), then most of the chatter and valuations are overrated hype and not nearly as disruptive as tech bros would like us to believe.
So, are all of the capital investments to build out more and more data centers mostly driven by the FOMO or the economics? We shall see in due course.
Economics is driven by expectations, but nobody knows what all the possibilities are or what their respective probabilities are. FOMO (fear of missing out) enters in the generation of scenarios and their probability, e.g., "if we don't do X and they do Y, which is almost certain, we will go bankrupt." Fallible humans may give that scenario more probability than a perfectly rational creature would.
Wow - I’d never thought of looking at it this way before!
If you build it they will come…except when everyone builds it at the same time and then capacity far outpaces demand. That’s the point where expectations meet reality in a not so good way.
Expectations eventually meet reality. Some times it's not pretty. Some times people learn from it. And some times, "Real [fill in the blank] has never been tried."