Jun 18, 2024 02:27 PM
(This post was last modified: Jun 18, 2024 02:48 PM by C C.)
https://aeon.co/essays/why-intelligence-...e-beholder
EXCERPT: . . . But despite facilitating the global reach of our species, intelligence remains notoriously slippery to define. When pressed, scholars often point to more tractable mental skills such as abstraction, problem-solving, efficiency, learning, planning, social cognition and adaptability – even numeracy or the ability to recognise oneself in a mirror – although they quibble over which ones most demonstrate intelligent behaviour.
This plurality is precisely what we should anticipate: intelligence is not and never has been a single entity. Instead, it is a hominin-shaped heuristic, a way for us to easily perceive valued characteristics in other people. Like beauty, it lies in the eye of the beholder...
The natural world overflows with animals that see, hear, smell and feel in very different ways than we do, along with living in conditions that would crush, freeze, dissolve or cook us alive. There are also a multitude of smaller and single-celled organisms thriving in ways that don’t easily fit into our scale of reality, not to mention the kingdoms of plants and fungi out there. Every species alive today can be considered our equal in the success game, by the simple virtue of continued existence. Physically speaking, humans are a middling mammal with an odd hair pattern, a badly evolved back, and a mouth that no longer fits all our adult teeth. All of which is why we really like brains.
[...] Among living animals, Homo sapiens has the highest encephalisation quotient, meaning that our brains are much bigger than expected for our body size. This plays to our vanity, but some of the smartest creatures out there have brains quite unlike ours – cuttlefish, for example, rely on neurons in their arms for complex problem-solving. African grey parrots have the smarts of a human child, but much smaller brains than might be expected. Shrews, on the other hand, have some of the highest neuronal densities among mammals but, ironically, they aren’t terribly shrewd. Tiny-brained digger wasps use tools, and monarch butterflies perform continent-spanning annual migrations. Large brains are important for human intelligence, but life finds other ways to succeed.
Adding to the mire, intelligent behaviour in people is not always the result of conscious choice or rational strategy, but can arise from autonomic processes. The cognitive bubbling up of hunches, intuitions and gut feelings can often be credited to ‘lower-order’ systems such as the sympathetic nervous system or the amygdala, or manifest as subliminal or subconscious conditioned responses to environmental cues.
In some contexts, the brain itself has been suggested as a poor candidate for the locus of intelligence. Supporters of swarm or collective intelligence tell us that the problem of problem-solving can be shared among a host of similar entities, as in a shoal of fish or a surge of grasshoppers. Ants build boats, bridges and metropolises with populations in the millions, and yet their individual cerebral horsepower doesn’t amount to much. The boundaries of an interacting group – the nest, the shoal, the rational mind, the nation-state – all can be argued as the scale at which true intelligence arises.
Paradoxically, we value intelligence as a marker of individual success, yet it exists both as a collective of our own neurons, and an aggregate of collective behaviour. To paraphrase Inigo Montoya, we keep using this word, but perhaps it does not mean what we think it means.
If we are going to continue talking about intelligence, we need to at least make sure we’re talking about the same thing. Our starting point is (we hope) uncontroversial: intelligence is a label that humans use to help dissect the world. The label’s existence does not automatically mean that there is a single, true thing to which it corresponds...
[...] Humanity’s relationship to AI is characterised by similar cycles of underestimation and surprise, followed by exploration, understanding and explanation, and a subsequent downgrading of our belief that intelligence is currently at play. Current large language models (LLMs) such as ChatGPT converse in sentences that are almost indistinguishable from those of another person ... However, the brittleness and uncertain mechanisms of these programs have led to doubt about whether this is ‘true’ artificial intelligence ... Once again, human minds are the shibboleth in the shadows: if a computer exhibits one trait of human intelligence, but not the others, it slips in our estimation of true smarts.
This is sometimes called the ‘AI effect’, explained by the computer scientist Larry Tesler as our tendency to believe that ‘Intelligence is whatever machines haven’t done yet.’ Now that it is possible for machines to beat human chess grandmasters, the game is no longer widely seen as a marker of ‘true’ intelligence. In areas of medicine where AI diagnoses are more reliable than those of doctors, diagnosing those diseases will similarly be considered unintelligent, mere rote computing. [...] Once we can reliably predict its success, it is no longer surprising, and the machine’s intelligence is relegated as merely mechanistic. The goalposts move of their own accord.
Mobile intelligence goalposts are not unique to animals and AI, and we expect they have been around as long as there have been humans... (MORE - missing details)
EXCERPT: . . . But despite facilitating the global reach of our species, intelligence remains notoriously slippery to define. When pressed, scholars often point to more tractable mental skills such as abstraction, problem-solving, efficiency, learning, planning, social cognition and adaptability – even numeracy or the ability to recognise oneself in a mirror – although they quibble over which ones most demonstrate intelligent behaviour.
This plurality is precisely what we should anticipate: intelligence is not and never has been a single entity. Instead, it is a hominin-shaped heuristic, a way for us to easily perceive valued characteristics in other people. Like beauty, it lies in the eye of the beholder...
The natural world overflows with animals that see, hear, smell and feel in very different ways than we do, along with living in conditions that would crush, freeze, dissolve or cook us alive. There are also a multitude of smaller and single-celled organisms thriving in ways that don’t easily fit into our scale of reality, not to mention the kingdoms of plants and fungi out there. Every species alive today can be considered our equal in the success game, by the simple virtue of continued existence. Physically speaking, humans are a middling mammal with an odd hair pattern, a badly evolved back, and a mouth that no longer fits all our adult teeth. All of which is why we really like brains.
[...] Among living animals, Homo sapiens has the highest encephalisation quotient, meaning that our brains are much bigger than expected for our body size. This plays to our vanity, but some of the smartest creatures out there have brains quite unlike ours – cuttlefish, for example, rely on neurons in their arms for complex problem-solving. African grey parrots have the smarts of a human child, but much smaller brains than might be expected. Shrews, on the other hand, have some of the highest neuronal densities among mammals but, ironically, they aren’t terribly shrewd. Tiny-brained digger wasps use tools, and monarch butterflies perform continent-spanning annual migrations. Large brains are important for human intelligence, but life finds other ways to succeed.
Adding to the mire, intelligent behaviour in people is not always the result of conscious choice or rational strategy, but can arise from autonomic processes. The cognitive bubbling up of hunches, intuitions and gut feelings can often be credited to ‘lower-order’ systems such as the sympathetic nervous system or the amygdala, or manifest as subliminal or subconscious conditioned responses to environmental cues.
In some contexts, the brain itself has been suggested as a poor candidate for the locus of intelligence. Supporters of swarm or collective intelligence tell us that the problem of problem-solving can be shared among a host of similar entities, as in a shoal of fish or a surge of grasshoppers. Ants build boats, bridges and metropolises with populations in the millions, and yet their individual cerebral horsepower doesn’t amount to much. The boundaries of an interacting group – the nest, the shoal, the rational mind, the nation-state – all can be argued as the scale at which true intelligence arises.
Paradoxically, we value intelligence as a marker of individual success, yet it exists both as a collective of our own neurons, and an aggregate of collective behaviour. To paraphrase Inigo Montoya, we keep using this word, but perhaps it does not mean what we think it means.
If we are going to continue talking about intelligence, we need to at least make sure we’re talking about the same thing. Our starting point is (we hope) uncontroversial: intelligence is a label that humans use to help dissect the world. The label’s existence does not automatically mean that there is a single, true thing to which it corresponds...
[...] Humanity’s relationship to AI is characterised by similar cycles of underestimation and surprise, followed by exploration, understanding and explanation, and a subsequent downgrading of our belief that intelligence is currently at play. Current large language models (LLMs) such as ChatGPT converse in sentences that are almost indistinguishable from those of another person ... However, the brittleness and uncertain mechanisms of these programs have led to doubt about whether this is ‘true’ artificial intelligence ... Once again, human minds are the shibboleth in the shadows: if a computer exhibits one trait of human intelligence, but not the others, it slips in our estimation of true smarts.
This is sometimes called the ‘AI effect’, explained by the computer scientist Larry Tesler as our tendency to believe that ‘Intelligence is whatever machines haven’t done yet.’ Now that it is possible for machines to beat human chess grandmasters, the game is no longer widely seen as a marker of ‘true’ intelligence. In areas of medicine where AI diagnoses are more reliable than those of doctors, diagnosing those diseases will similarly be considered unintelligent, mere rote computing. [...] Once we can reliably predict its success, it is no longer surprising, and the machine’s intelligence is relegated as merely mechanistic. The goalposts move of their own accord.
Mobile intelligence goalposts are not unique to animals and AI, and we expect they have been around as long as there have been humans... (MORE - missing details)
