Posts Tagged ‘Psychology’
“They will read many things without instruction and will therefore seem to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise.”*…
Socrates was worried about the impact of a new technology– writing– on effetive intelligence of its users. Similar concerns have surfaced with the rise of other new communications technologies: moveable-type printing, photography, radio, television, and the internet. As Erik Hoel reminds us, AI is next on that list…
Unfortunately, there’s a growing subfield of psychology research pointing to cognitive atrophy from too much AI usage.
Evidence includes a new paper published by a cohort of researchers at Microsoft (not exactly a group predisposed to finding evidence for brain drain). Yet they do indeed see the effect in the critical thinking of knowledge workers who make heavy use of AI in their workflows.
To measure this, the researchers at Microsoft needed a definition of critical thinking. They used one of the oldest and most storied in the academic literature: that of mid-20th century education researcher Benjamin Bloom (the very same Benjamin Bloom who popularized tutoring as the most effective method of education).
Bloom’s taxonomy of critical thinking makes a great deal of sense. Below, you can see how what we’d call “the creative act” occupies the top two entries of the pyramid of critical thinking, wherein creativity is a combination of the synthesis of new ideas and then evaluative refinement over them.
To see where AI usage shows up in Bloom’s hierarchy, researchers surveyed a group of 319 knowledge workers who had incorporated AI into their workflow. What makes this survey noteworthy is how in-depth it is. They didn’t just ask for opinions; instead they compiled ~1,000 real-world examples of tasks the workers complete with AI assistance, and then surveyed them specifically about those in all sorts of ways, including qualitative and quantitative judgements.
In general, they found that AI decreased the amount of effort spent on critical thinking when performing a task…
… While the researchers themselves don’t make the connection, their data fits the intuitive idea that positive use of AI tools is when they shift cognitive tasks upward in terms of their level of abstraction.
We can view this through the lens of one of the most cited papers in all psychology, “The Magical Number Seven, Plus or Minus Two,” which introduced the eponymous Miller’s law: that working memory in humans caps out at 7 (plus or minus 2) different things. But the critical insight from the author, psychologist George Miller, is that experts don’t really have greater working memory. They’re actually still stuck at ~7 things. Instead, their advantage is how they mentally “chunk” the problem up at a higher-level of abstraction than non-experts, so their 7 things are worth a lot more when in mental motion. The classic example is that poor Chess players think in terms of individual pieces and individual moves, but great Chess players think in terms of patterns of pieces, which are the “chunks” shifted around when playing.
I think the positive aspect for AI augmentation of human workflows can be framed in light of Miller’s law: AI usage is cognitively healthy when it allows humans to mentally “chunk” tasks at a higher level of abstraction.
But if that’s the clear upside, the downside is just as clear. As the Microsoft researchers themselves say…
While GenAI can improve worker efficiency, it can inhibit critical engagement with work and can potentially lead to long-term over-reliance on the tool and diminished skill for independent problem-solving.
This negative effect scaled with the worker’s trust in AI: the more they blindly trusted AI results, the more outsourcing of critical thinking they suffered. That’s bad news, especially if these systems ever do permanently solve their hallucination problem, since many users will be shifted into the “high trust” category by dint of sheer competence.
The study isn’t alone. There’s increasing evidence for the detrimental effects of cognitive offloading, like that creativity gets hindered when there’s reliance on AI usage, and that over-reliance on AI is greatest when outputs are difficult to evaluate. Humans are even willing to offload to AI the decision to kill, at least in mock studies on simulated drone warfare decisions. And again, it was participants less confident in their own judgments, and more trusting of the AI when it disagreed with them, who got brain drained the most…
… Admittedly, there’s not yet high-quality causal evidence for lasting brain drain from AI use. But so it goes with subjects of this nature. What makes these debates difficult is that we want mono-causal universality in order to make ironclad claims about technology’s effect on society. It would be a lot easier to point to the downsides of internet and social media use if it simply made everyone’s attention spans equally shorter and everyone’s mental health equally worse, but that obviously isn’t the case. E.g., long-form content, like blogs, have blossomed on the internet.
But it’s also foolish to therefore dismiss the concern about shorter attention spans, because people will literally describe their own attention spans as shortening! They’ll write personal essays about it, or ask for help with dealing with it, or casually describe it as a generational issue, and the effect continues to be found in academic research.
With that caveat in mind, there’s now enough suggestive evidence from self-reports and workflow analysis to take “brAIn drAIn” seriously as a societal downside to the technology (adding to the list of other issues like AI slop and existential risk).
Similarly to how people use the internet in healthy and unhealthy ways, I think we should expect differential effects. For skilled knowledge workers with strong confidence in their own abilities, AI will be a tool to chunk up cognitively-demanding tasks at a higher level of abstraction in accordance with Miller’s law. For others… it’ll be a crutch.
So then what’s the take-away?
For one, I think we should be cautious about AI exposure in children. E.g., there is evidence from another paper in the brain-drain research subfield wherein it was younger AI users who showed the most dependency, and the younger cohort also didn’t match the critical thinking skills of older, more skeptical, AI users. As a young user put it:
It’s great to have all this information at my fingertips, but I sometimes worry that I’m not really learning or retaining anything. I rely so much on AI that I don’t think I’d know how to solve certain problems without it.
What a lovely new concern for parents we’ve invented!
Already nowadays, parents have to weather internal debates and worries about exposure to short-form video content platforms like TikTok. Of course, certain parents hand their kids an iPad essentially the day they’re born. But culturally this raises eyebrows, the same way handing out junk food at every meal does. Parents are a judgy bunch, which is often for the good, as it makes them cautious instead of waiting for some finalized scientific answer. While there’s still ongoing academic debate about the psychological effects of early smartphone usage, in general the results are visceral and obvious enough in real life for parents to make conservative decisions about prohibition, agonizing over when to introduce phones, the kind of phone, how to not overexpose their child to social media or addictive video games, etc.
Similarly, parents (and schools) will need to be careful about whether kids (and students) rely too much on AI early on. I personally am not worried about a graduate student using ChatGPT to code up eye-catching figures to show off their gathered data. There, the graduate student is using the technology appropriately to create a scientific paper via manipulating more abstract mental chunks (trust me, you don’t get into science to plod through the annoying intricacies of Matplotlib). I am, however, very worried about a 7th grader using AI to do their homework, and then, furthermore, coming to it with questions they should be thinking through themselves, because inevitably those questions are going to be about more and more minor things. People already worry enough about a generation of “iPad kids.” I don’t think we want to worry about a generation of brain-drained “meat puppets” next.
For individuals themselves, the main actionable thing to do about brain drain is to internalize a rule-of-thumb the academic literature already shows: Skepticism of AI capabilities—independent of if that skepticism is warranted or not!—makes for healthier AI usage.
In other words, pro-human bias and AI distrust are cognitively beneficial.
It’s said that first we shape our tools, then they shape us. Well, meet the new boss, same as the old boss… Just as, both as individuals and societies, we’ve had to learn our way into effective use of new technologes before, so we will with AI.
The enhancement and atrophy of human cognition go hand in hand: “brAIn drAIn,” from @erikphoel.
Pair with a broad and thoughtful view from Robin Sloan: “Is It OK?“
* “For this invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them. You have invented an elixir not of memory, but of reminding; and you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise.” – Socrates, in Plato’s dialogue Phaedrus 14, 274c-275b
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As we think about thinking, we might send carefully-considered birthday greetings to Alfred North Whitehead; he was born on this date in 1861. Whitehead began his career as a mathematician and logician, perhaps most famously co-authoring (with his former student, Bertrand Russell), the three-volume Principia Mathematica (1910–13), one of the twentieth century’s most important works in mathematical logic.
But in the late teens and early 20s, Whitehead shifted his focus to philosophy, the central result of which was a new field called process philosophy, which has found application in a wide variety of disciplines (e.g., ecology, theology, education, physics, biology, economics, and psychology).
“There is urgency in coming to see the world as a web of interrelated processes of which we are integral parts, so that all of our choices and actions have consequences for the world around us.”
“What’s in a name?”*…
… maybe, Roger’s Bacon suggests, more than we typically think…
An aptronym is when a person has a name that is uniquely suited to its owner. Some examples:
- Usain Bolt, the fastest human ever
- Mark De Man, Belgian football defender
- William Headline, Washington Bureau Chief for CNN
- Marijuana Pepsi Vandyck, American education professional with a dissertation on uncommon African-American names in the classroom
- William Wordsworth, poet
- Philander Rodman, father of basketball player Dennis Rodman, who fathered 26 children by 16 mothers
- Sue Yoo, attorney
And of course there are also inaptronyms:
- Rob Banks, a British police officer
- Don Black, white supremacist
- Robin Mahfood, President and CEO of Food for the Poor
- I.C. Notting, an ophthalmologist at Leiden University
Maybe this is all coincidence, or maybe it’s nominative determinism, the hypothesis that people tend to gravitate towards areas of work that fit their names (an idea captured in the ancient Roman proverb “nomen est omen” meaning “the name is the sign”). Psychologist Lawrence Casler proposed three possible explanations for nominative determinism: one’s self-image and self-expectation being internally influenced by one’s name; the name acting as a social stimulus, creating expectations in others that are then communicated to the individual; and genetics—attributes suited to a particular career being passed down the generations alongside the appropriate occupational surname.
But does nominative determinism actually exist—are people with occupation-related names over-represented in those occupations?…
[RB considers the evidence… then ponders a more fundamental issue: “the virtually universal practice of assigning a permanent name at birth”…]
… When naming conventions are created by governments and for governments, they favor legibility and as a consequence, individuality and stability of identity. In my brief heretical statement, I suggested that our modern naming conventions have caused a species-wide shift towards a more narcissistic and egotistical mode of being. Maybe this goes too far (or not far enough…), but the more general idea is that personal nomenclature is never value neutral and never without cultural and psychological ramifications. In other words, we shouldn’t be surprised that our culture has become sterile, stagnant, and individualistic to a fault when those values are embedded in the way we name ourselves.
The global hegemony of governmentally-developed naming systems has crippled our imagination by removing alternative models of nomenclature…
[He considers alternatives with examples from New Guinean and Native American cultures…]
… Naming systems are reflections of a culture’s values, but, as I’ve argued, it’s a two-way street—the way we name ourselves reinforces these values and frames how we think about ourselves and the world around us. When legibility, individuality, and stability of identity are the master values of our personal nomenclature, of course we will look for legible, de-personalized solutions (e.g. technology, laws, governmental programs) to society’s ills (environmental degradation, social isolation and loss of community, mental health and addiction, to name just a few). These solutions are only partial and always will be because they don’t get to the root of the problem: ourselves—who we are as people, what we value, and how we think. There is no shortcut to profound personal change, but a first step in the right direction might make all the difference—if we want to be the kind of people who value community and the natural world and who believe that people can grow and then perhaps we should name ourselves in a way that inspires us to be those kind of people…
A provocative challenge to the way we name ourselves: “Nomen est Omen,” from @RogersBacon1.
* Shakespeare, Romeo and Juliet
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As we dig into denotation, we might note that today is a red-letter day for another of the descriptors of our idenitities, one with increasing importance (at least unless we use trustworthy password managers or come up with a better system): it’s Change Your Password Day.
“The world of reality has its limits; the world of imagination is boundless”*…
Still, it’s useful to know the difference… and as Yasemin Saplakoglu explains, that’s a complex process– one that science takes very seriously…
As I sit at my desk typing up this newsletter, I can see a plant to my left, a water bottle to my right and a gorilla sitting across from me. The plant and bottle are real, but the gorilla is a product of my mind — and I intuitively know that this is true. That’s because my brain, like most people’s, has the ability to distinguish reality from imagination. If it didn’t, or if I had a condition that disrupts this distinction, I’d constantly see gorillas and elephants where they don’t exist.
Imagination is sometimes described as perception in reverse. When we look at an object, electromagnetic waves enter the eyes, where they are translated into neural signals that are then sent to the visual cortex at the back of the brain. This process generates an image: “plant.” With imagination, we start with what we want to see, and the brain’s memory and semantic centers send signals to the same brain region: “gorilla.”
In both cases, the visual cortex is activated. Recalling memories can also activate some of the same regions. Yet the brain can clearly distinguish between imagination, perception and memory in most cases (though it is still possible to get confused). How does it keep everything straight?
By probing the differences between these processes, neuroscientists are untangling how the human brain creates our experience. They’re finding that even our perception of reality is in many ways imagined. “Underneath our skull, everything is made up,” Lars Muckli, a professor of visual and cognitive neurosciences at the University of Glasgow, told me. “We entirely construct the world in its richness and detail and color and sound and content and excitement. … It is created by our neurons.”
To distinguish reality and imagination, the brain might have some kind of “reality threshold,” according to one theory. Researchers recently tested this by asking people to imagine specific images against a backdrop — and then secretly projected faint outlines of those images there. Participants typically recognized when they saw a real projection versus their imagined one, and those who rated images as more vivid were also more likely to identify them as real. The study suggested that when processing images, the brain might make a judgment on reality based on signal strength. If the signal is weak, the brain takes it for imagination. If it’s strong, the brain deems it real. “The brain has this really careful balancing act that it has to perform,” Thomas Naselaris, a neuroscientist at the University of Minnesota, told me. “In some sense it is going to interpret mental imagery as literally as it does visual imagery.”
Although recalling memories is a creative and imaginative process, it activates the visual cortex as if we were seeing. “It started to raise the question of whether a memory representation is actually different from a perceptual representation at all,” Sam Ling, a neuroscientist at Boston University, told me. A recent study looked to identify how memories and perceptions are constructed differently at the neurobiological level. When we perceive something, visual cues undergo layers of processing in the visual cortex that increase in complexity. Neurons in earlier parts of this process fire more precisely than those that get involved later. In the study, researchers found that during memory recall, neurons fired in a much blurrier way through all the layers. That might explain why our memories aren’t often as crisp as what we’re seeing in front of us…
“How Do Brains Tell Reality From Imagination?” from @yaseminsaplakoglu.bsky.social in @quantamagazine.bsky.social.
* Jean-Jacques Rousseau
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As we parse perception, we might send mindful birthday greetings to a man whose work figures into the history of science’s struggle on this issue, Franz Brentano; he was born on this date in 1838. A philosopher and psychologist, his 1874 Psychology from an Empirical Standpoint, considered his magnum opus and is credited with having reintroduced the medieval scholastic concept of intentionality into contemporary philosophy and psychology.
Brentano also studied perception, with conclusions that prefigure the discussion above…
He is also well known for claiming that Wahrnehmung ist Falschnehmung (‘perception is misconception’) that is to say perception is erroneous. In fact he maintained that external, sensory perception could not tell us anything about the de facto existence of the perceived world, which could simply be illusion. However, we can be absolutely sure of our internal perception. When I hear a tone, I cannot be completely sure that there is a tone in the real world, but I am absolutely certain that I do hear. This awareness, of the fact that I hear, is called internal perception. External perception, sensory perception, can only yield hypotheses about the perceived world, but not truth. Hence he and many of his pupils (in particular Carl Stumpf and Edmund Husserl) thought that the natural sciences could only yield hypotheses and never universal, absolute truths as in pure logic or mathematics.
However, in a reprinting of his Psychologie vom Empirischen Standpunkte (Psychology from an Empirical Standpoint), he recanted this previous view. He attempted to do so without reworking the previous arguments within that work, but it has been said that he was wholly unsuccessful. The new view states that when we hear a sound, we hear something from the external world; there are no physical phenomena of internal perception… – source
“A different language is a different vision of life”*…
Damián Blasi delves into historic and current efforts to catalog the planet’s 7,000-plus languages…
As a scientist who has researched language diversity for a decade and a half, I recently joined a team to work on a task that even some linguists think is “ultimately unobtainable”: helping catalog and count the world’s complex and ever-changing languages. I am part of an international team of experts assembled by UNESCO to create a World Atlas of Languages. This catalog will hopefully generate updated estimates of the number of active languages and information on how these languages are being used.
Typically, when I present research, one of my gimmicks is to begin with a rough estimate of the number of natural languages in use today: between 7,000 and 8,000. My point is to communicate that there are many languages and, therefore, an incredible diversity of ways humans think, reason, and feel. But pinpointing a more precise number opens the door to all sorts of problems.
For example, the Central African Republic hosts about 70 languages. The speakers of many of these languages live deep within roadless rainforests in villages that are very difficult for government representatives and other researchers to access. It’s hard to fathom how resource-intensive it would be to form an accurate linguistic picture of this country alone.
Of course, our project is far from the first to attempt to categorize and quantify languages. Many groups and individuals have done this in the past and continue to do so.
My task set me on a path to understanding the history and craft of counting languages. While I expected to read a dull sequence of estimates, I instead found a riveting tale involving Christian missionaries, post-war idealists, a colonialist opium agent, and more. I also gained even more appreciation for the potentially impossible task of counting languages…
A fascinating read: “Tackling the Impossibility—and Necessity—of Counting the World’s Languages,” from @blasi_lang and @WennerGrenOrg.
Apposite: “Disappearing languages“
* Federico Fellini
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As we total up tongues, we might spare a thought for Søren Kierkegaard; he died on this date in 1855. a Danish theologian, philosopher, poet, social critic, and religious author widely considered to be the first Christian existentialist philosopher, he wrote critical texts on organized religion, Christianity, morality, ethics, psychology, and the philosophy of religion, all displaying a fondness for metaphor, irony, and parables. Among his major works: Either/Or, Fear and Trembling, and The Sickness unto Death. It may come as no surprise that he was a major influence on Dostoevsky.
Kierkegaard wrote in Danish and the reception of his work was initially limited to Scandinavia, but by the turn of the 20th century his writings were translated into French, German, and other major European languages. By the mid-20th century, his thought exerted a substantial influence on philosophy, theology, and Western culture in general.
“I fear the day when the technology overlaps with our humanity. The world will only have a generation of idiots.”*…
Alva Noë on the importance of humans hanging on to their humanity– for all the promise and dangers of AI, computers plainly can’t think. To think is to resist – something no machine does:
Computers don’t actually do anything. They don’t write, or play; they don’t even compute. Which doesn’t mean we can’t play with computers, or use them to invent, or make, or problem-solve. The new AI is unexpectedly reshaping ways of working and making, in the arts and sciences, in industry, and in warfare. We need to come to terms with the transformative promise and dangers of this new tech. But it ought to be possible to do so without succumbing to bogus claims about machine minds.
What could ever lead us to take seriously the thought that these devices of our own invention might actually understand, and think, and feel, or that, if not now, then later, they might one day come to open their artificial eyes thus finally to behold a shiny world of their very own? One source might simply be the sense that, now unleashed, AI is beyond our control. Fast, microscopic, distributed and astronomically complex, it is hard to understand this tech, and it is tempting to imagine that it has power over us.
But this is nothing new. The story of technology – from prehistory to now – has always been that of the ways we are entrained by the tools and systems that we ourselves have made. Think of the pathways we make by walking. To every tool there is a corresponding habit, that is, an automatised way of acting and being. From the humble pencil to the printing press to the internet, our human agency is enacted in part by the creation of social and technological landscapes that in turn transform what we can do, and so seem, or threaten, to govern and control us.
Yet it is one thing to appreciate the ways we make and remake ourselves through the cultural transformation of our worlds via tool use and technology, and another to mystify dumb matter put to work by us. If there is intelligence in the vicinity of pencils, shoes, cigarette lighters, maps or calculators, it is the intelligence of their users and inventors. The digital is no different.
But there is another origin of our impulse to concede mind to devices of our own invention, and this is what I focus on here: the tendency of some scientists to take for granted what can only be described as a wildly simplistic picture of human and animal cognitive life. They rely unchecked on one-sided, indeed, milquetoast conceptions of human activity, skill and cognitive accomplishment. The surreptitious substitution (to use a phrase of Edmund Husserl’s) of this thin gruel version of the mind at work – a substitution that I hope to convince you traces back to Alan Turing and the very origins of AI – is the decisive move in the conjuring trick.
What scientists seem to have forgotten is that the human animal is a creature of disturbance. Or as the mid-20th-century philosopher of biology Hans Jonas wrote: ‘Irritability is the germ, and as it were the atom, of having a world…’ With us there is always, so to speak, a pebble in the shoe. And this is what moves us, turns us, orients us to reorient ourselves, to do things differently, so that we might carry on. It is irritation and disorientation that is the source of our concern. In the absence of disturbance, there is nothing: no language, no games, no goals, no tasks, no world, no care, and so, yes, no consciousness…
[Starting with Turing, Noë considers the relative roles of humans and technology across a number of spheres, including music…]
… The piano was invented, to be sure, but not by you or me. We encounter it. It pre-exists us and solicits our submission. To learn to play is to be altered, made to adapt one’s posture, hands, fingers, legs and feet to the piano’s mechanical requirements. Under the regime of the piano keyboard, it is demanded that we ourselves become player pianos, that is to say, extensions of the machine itself.
But we can’t. And we won’t. To learn to play, to take on the machine, for us, is to struggle. It is hard to master the instrument’s demands.
And this fact – the difficulty we encounter in the face of the keyboard’s insistence – is productive. We make art out of it. It stops us being player pianos, but it is exactly what is required if we are to become piano players.
For it is the player’s fraught relation to the machine, and to the history and tradition that the machine imposes, that supplies the raw material of musical invention. Music and play happen in that entanglement. To master the piano, as only a person can, is not just to conform to the machine’s demands. It is, rather, to push back, to say no, to rage against the machine. And so, for example, we slap and bang and shout out. In this way, the piano becomes not merely a vehicle of habit and control – a mechanism – but rather an opportunity for action and expression.
And, as with the piano, so with the whole of human cultural life. We live in the entanglement between government and resistance. We fight back…
… The telling fact: computers are used to play our games; they are engineered to make moves in the spaces opened up by our concerns. They don’t have concerns of their own, and they make no new games. They invent no new language.
The British philosopher R G Collingwood noticed that the painter doesn’t invent painting, and the musician doesn’t invent the musical culture in which they find themselves. And for Collingwood this served to show that no person is fully autonomous, a God-like fount of creativity; we are always to some degree recyclers and samplers and, at our best, participants in something larger than ourselves.
But this should not be taken to show that we become what we are (painters, musicians, speakers) by doing what, for example, LLMs do – i.e., merely by getting trained up on large data sets. Humans aren’t trained up. We have experience. We learn. And for us, learning a language, for example, isn’t learning to generate ‘the next token’. It’s learning to work, play, eat, love, flirt, dance, fight, pray, manipulate, negotiate, pretend, invent and think. And crucially, we don’t merely incorporate what we learn and carry on; we always resist. Our values are always problematic. We are not merely word-generators. We are makers of meaning.
We can’t help doing this; no computer can do this…
Eminently worth reading in full: “Rage against the machine,” from @alvanoe in @aeonmag.
For more, see Noë’s The Entanglement: How Art and Philosophy Make Us What We Are.
* Albert Einstein
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As we resolve to wrestle, we might recall that it was on this date in 1969 that UCLA professor Leonard Kleinrock (aided by his student assistant Charley Kline) created the first networked computer-to-computer connection (with SRI programmer Bill Duvall in Palo Alto), via which they sent the first networked computer-to-computer communication)… or at least part of it. Duvall’s machine crashed partway through the transmission, meaning the only letters received from the attempted “login” were “lo.” The next month two more nodes were added (UCSB and the University of Utah) and the network was dubbed ARPANET.
Still, “lo”– perhaps an appropriate way to announce what would grow up to be the internet.
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