Author Topic: Intelligence and Psychology, Artificial Intelligence  (Read 64166 times)

Body-by-Guinness

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The Genetic Interplay of Nature and Nurture
« Reply #200 on: January 30, 2024, 05:33:40 PM »
A take on the nature/nurture debate I have not seen before postulating that parents invest more nurturing in children displaying an education seeking nature, in other words meaning nature influences nurturing commitment, while nurturing resources impact a child’s nature. Bottom line: nurture has an impact on genetic nature, while genetic nature can incentivize (or not) nurturing investments. The take away is that the two are not ends of spectrums to be debated, but intertwined variables that impact the other.

Full disclosure, I gave the lay sections a quick read, and utterly scrolled past the formula laden sections, but nonetheless find myself intrigued by this new (to me at least) synthesis of the nature/nurture question, particularly in view of the dysfunctional wolves I was raised by.

Conclusion posted here:

To better understand the interplay between genetics and family resources for skill formation and its relevance for policy, we incorporated genetic endowments measured by an EA PGS into a dynamic model of skill formation. We modelled and estimated the joint evolution of skills and parental investments throughout early childhood (ages 0 to 7 years). We observed both child and parental genetic endowments, allowing us to estimate the independent effect of the child’s genes on skill formation and to estimate the importance of parental genes for child development. Furthermore, by incorporating (child- and parent-) genetics into a formal model, we were able to evaluate the mechanisms through which genes influence skill formation.

Using the model, we document the importance of both parental and child genes for child development. We show that the effect of genes increases over the child’s early life course and that a large fraction of these effects operate via parental investments. Genes directly influence the accumulation of skills; conditional on their current stock of skills and parental investments, genetics make some children better able to retain and acquire new skills (the direct effect). In addition, we show that genes indirectly influence investments as parents reinforce genetic differences by investing more in children with higher skills (the nurture of nature effect). We also find that parental genes matter, as parents with different genetic makeups invest differently in their children (the nature of nurture effect). The impact of genes on parental investments is especially significant as it implies an interplay between genetic and environmental effects. These findings illustrate that nature and nurture jointly influence children’s skill development, a finding that highlights the importance of integrating biological and social perspectives into a single framework.

We highlight the critical implications of our findings using two simulation counterfactu- als. In one counterfactual, we show that the association between genetics and skills is smaller in a world where parental investments are equalized across families. This finding shows that the existence of genetic effects is not at odds with the value of social policies in reducing inequality. The presence of genetic effects makes these policies even more relevant since genetic inequality increases inequality in parental investments. In another counterfactual, we demonstrate how it is possible to negate completely all genetic influences on skills with a change in how parental (or public) investments are allocated across children. This shows that skill disparities due to genetic differences may be mitigated via social behavior and social policy. In particular, whether parents (and schools) compensate for or reinforce initial disparities can significantly impact the relative importance of genetics in explaining inequal- ities in skill, and might explain why estimates of the importance of genes differ significantly across countries (Branigan, McCallum, and Freese, 2013).

A limitation of our work is that genetic endowments are measured using polygenic scores. It is possible for genes unrelated to educational attainment also to influence children’s skill formation. For example, genetic variation related to mental health and altruism may poten- tially be unrelated to education but might influence how parents interact with their children. If this is true, we are missing a critical genetic component by using a PGS for educational attainment. Another limitation of using polygenic scores is measurement error. Since poly- genic scores are measured with error, our estimates are lower bounds of the true genetic effects. An interesting extension of our work would be to use different methods, such as genome-based restricted maximum likelihood (GREML), to sidestep the measurement prob- lem and document whether different genetic variants are related to the various mechanisms we outline in Section 2.

Lastly, it is important to recognise that we only include individuals of European ancestry in our analysis. This opens the question whether our findings would extend to other ancestry groups. Unfortunately, this is not something we can test. This is a major issue in the literature since the majority of polygenic scores are constructed from GWAS’ performed in Europeans, and their transferability to other populations is dependent on many factors (see Martin et al. (2017) for a discussion of the transferability issues of GWAS results, and Mostafavi et al. (2020) for an empirical comparison of PGS’ across ethnic groups). This also illustrates a problem of inequity in research, where the only individuals being studied are those of European ancestry. This opens the possibility that other ancestry groups will not benefit from the advances in genetics research (see the discussion in Martin et al., 2019). While the key insights from our research apply to all ancestry groups, we cannot test for any differences in the role of genetics across groups until we have solved the transferability issue. We hope future work will address these issues and lead to a more inclusive research agenda.

https://docs.iza.org/dp13780.pdf

Crafty_Dog

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Re: Intelligence and Psychology, Artificial Intelligence
« Reply #201 on: February 01, 2024, 04:15:41 AM »
See Matt Ridley's "Nature via Nurture".  It has had quite the influence on me.

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Gemini's racial marxism
« Reply #204 on: February 22, 2024, 05:58:36 AM »


Body-by-Guinness

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AI Offers Better Customer Service and Outcomes?
« Reply #206 on: February 28, 2024, 09:40:21 AM »

Body-by-Guinness

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AI: The Future of Censorship
« Reply #207 on: February 28, 2024, 08:53:25 PM »
AI already has been shown to embrace the woke sensibilities of its programmers; what happens when it’s applied to Lenny Bruce, one of the examples explored here:

https://time.com/6835213/the-future-of-censorship-is-ai-generated/

Body-by-Guinness

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Can AIs Libel?
« Reply #208 on: February 29, 2024, 07:44:56 PM »
AI makes up a series of supposed Matt Tabbi “inaccuracies” for pieces he never wrote published in periodicals he’s not submitted to:

https://www.racket.news/p/i-wrote-what-googles-ai-powered-libel

Body-by-Guinness

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Can AI Infringe on Copyright?
« Reply #209 on: February 29, 2024, 08:19:12 PM »

Body-by-Guinness

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Yet Another AI Reveals the Biases of its Programmers
« Reply #210 on: March 02, 2024, 12:29:40 PM »
ChatGPT demonstrates its the language equivalent of GoogleAI’s images.

https://link.springer.com/content/pdf/10.1007/s11127-023-01097-2.pdf

Crafty_Dog

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Killer AI Robots
« Reply #213 on: March 08, 2024, 04:11:40 AM »

Crafty_Dog

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A FB post
« Reply #214 on: March 11, 2024, 02:23:50 PM »

AI will tailor itself to classes of users:

1. Minimal thinking, high entertainment, low initiative. Probably the most addictive algorithms and making up the majority. AI does the thinking for a consumer heavy model.

2. Enhanced search returns, variations of basic question formats offering a larger array of possibilities. AI as a basic partnership model.

3. Information gap anticipation, analytical depth (analysis, synthesis, deductive, inductive), identifying hypothesis, alerting of new, relevant information or data summaries based on specific and diverse ‘signal strength’ of user trends. AI as a research catalyst.
Population statistics show the majority are sensors, feelers, and judgers (i.e Myers-Briggs) therefore the cost-effective AI market to focus on (1) above; those that are more investigative, innovative or productivity driven vs consumption driven will be more ‘expensive’ as a minority (3) above, requiring higher costs to participate & employ.

AI will simply ‘become’ us across different tiers

Crafty_Dog

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EU law tightens up AI uses
« Reply #215 on: March 13, 2024, 01:06:11 PM »

Crafty_Dog

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Ted Cruz & Phil Gramm: First, do no harm
« Reply #216 on: March 26, 2024, 05:44:52 PM »
Biden Wants to Put AI on a Leash
Bill Clinton’s regulators, by contrast, produced prosperity by encouraging freedom on the internet.
By Ted Cruz and Phil Gramm
March 25, 2024 4:22 pm ET

The arrival of a new productive technology doesn’t guarantee prosperity. Prosperity requires a system, governed by the rule of law, in which economic actors can freely implement a productive idea and compete for customers and investors. The internet is the best recent example of this. The Clinton administration took a hands-off approach to regulating the early internet. In so doing it unleashed extraordinary economic growth and prosperity. The Biden administration, by contrast, is impeding innovation in artificial intelligence with aggressive regulation. This could deny America global leadership in AI and the prosperity that leadership would bring.

The Clinton administration established a Global Information Infrastructure framework in 1997 defining the government’s role in the internet’s development with a concise statement of principles: “address the world’s newest technologies with our Nation’s oldest values . . . First, do no harm.” The administration embraced the principle that “the private sector should lead [and] the Internet should develop as a market driven arena, not a regulated industry.” The Clinton regulators also established the principle that “government should avoid undue restrictions on electronic commerce, . . . refrain from imposing new and unnecessary regulations, bureaucratic procedures or new taxes and tariffs.”

That regulatory framework faithfully fleshed out the provisions of the bipartisan 1996 Telecommunications Act and provided the economic environment that made it possible for America to dominate the information age, enrich our lives, create millions of jobs, and generate enormous wealth for retirement savers.

The Biden administration is doing the opposite. It has committed to “govern the development and use of AI.” In one of the longer executive orders in American history, President Biden imposed a top-down, command-and-control regulatory approach requiring AI models to undergo extensive “impact assessments” that mirror the infamously burdensome National Environmental Policy Act reviews, which are impeding semiconductor investment in the U.S. And government controls are permanent, “including post-deployment performance monitoring.”

Under Mr. Biden’s executive order, AI development must “be consistent with my administration’s dedication to advancing equity and civil rights” and “built through collective bargains on the views of workers, labor unions, educators and employers.” Mr. Biden’s separate AI Bill of Rights claims to advance “racial equity and support for underserved communities.” AI must also be used to “improve environmental and social outcomes,” to “mitigate climate change risk,” and to facilitate “building an equitable clean energy economy.”

Education Secretary Miguel Cardona, who as Connecticut schools commissioner said “we need teachers behind this wave of our curriculum becoming more woke,” now wants to impose “guardrails” on AI to protect against “bias and stereotyping through technology.” The Commerce Department has appointed a “senior adviser for algorithmic justice,” while the Justice Department, Federal Trade Commission, Consumer Financial Protection Bureau and the Equal Employment Opportunity Commission have issued a joint statement asserting legal authority to root out racism in computing.

FTC Chairwoman Lina Khan has launched several AI-related inquiries, claiming that because AI “may be fed information riddled with errors and bias, these technologies risk automating discrimination—unfairly locking out people from jobs, housing and key services.”

Regulating AI to prevent discrimination is akin to the FTC’s regulating a cellphone’s design to enforce the do-not-call registry. There is virtually no limit to the scope of such authority. Under what constitutional authority would Congress even legislate in the area of noncommercial speech? How could the FTC regulate in this area with no legislative authority? But in the entire Biden administration, noted for governing through regulatory edict, no agency has been less constrained by law than the FTC.

Others demanding control over AI’s development include the progressives who attended Sen. Chuck Schumer’s recent AI “Insight Forums.” Janet Murguía, president of UnidosUS—the activist group formerly known as the National Council of La Raza—demanded “a strong voice in how—or even whether” AI models “will be built and used.” Elizabeth Shuler, president of the AFL-CIO, demanded a role for “unions across the entire innovation process.” Randi Weingarten, president of the American Federation of Teachers, said, “AI is a game changer, but teachers and other workers need to be coaches in the game.”

Particularly painful is Mr. Biden’s use of the Defense Production Act of 1950 to force companies to share proprietary data regarding AI models with the Commerce Department. That a law passed during the Korean War and designed for temporary national security emergencies could be used to intervene permanently in AI development is a frightening precedent. It begs for legislative and judicial correction.

What’s clear is that the Biden regulatory policy on AI has little to do with AI and everything to do with special-interest rent-seeking. The Biden AI regulatory demands and Mr. Schumer’s AI forum look more like a mafia shakedown than the prelude to legitimate legislation and regulatory policy for a powerful new technology.

Some established AI companies no doubt welcome the payment of such tribute as a way to keep out competition. But consumers, workers and investors would bear the cost along with thousands of smaller AI companies that would face unnecessary barriers to innovation.

Letting the administration seize control over AI and subject it to the demands of its privileged political constituencies wouldn’t eliminate bias, stereotyping or the spreading of falsehoods and racism, all of which predate AI and sadly will likely be with us until Jesus comes back. Mr. Biden’s policies will, however, impede AI development, drive up the costs of the benefits it brings, and diminish America’s global AI pre-eminence.

Mr. Cruz is ranking Republican on the Senate Commerce Committee. Mr. Gramm, a former chairman of the Senate Banking Committee, is a visiting scholar at the American Enterprise Institute.


Crafty_Dog

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Body-by-Guinness

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AI Learns to Lie
« Reply #221 on: May 13, 2024, 04:28:12 PM »
Given the penchant of so many to vigorously grasp whatever twaddle the MSM vends, the thought of AI embracing convenient fictions does more than give pause:

https://www.businessinsider.com/ai-deceives-humans-2024-5


Body-by-Guinness

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Open AI For the Internet Win?
« Reply #223 on: May 14, 2024, 02:02:22 PM »
I trust this isn’t a scam; it appears ChatGPT4o is capable of making human-like inferences and carry on a free ranging conversation:

https://x.com/heybarsee/status/1790080494261944609?s=61
« Last Edit: May 14, 2024, 02:09:49 PM by Body-by-Guinness »

Body-by-Guinness

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12 Wicked Cool Thing GPT-4o Can D
« Reply #224 on: May 15, 2024, 05:17:35 PM »
More new AI capabilities emerging:

https://x.com/rowancheung/status/1790783202639978593?s=61

The inflection and extrapolations are astounding.

Hmm, mebbe I gotta see if it can peruse an extensive number of thread topics and then suggest which one a given post should land in….

Crafty_Dog

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Re: Intelligence and Psychology, Artificial Intelligence
« Reply #225 on: May 19, 2024, 04:00:24 AM »
Well the latent wit in some of the Subject headings may confuse e.g. The Cognitive Dissonance of His Glibness for Baraq Obama :-D

Body-by-Guinness

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Re: Intelligence and Psychology, Artificial Intelligence
« Reply #226 on: May 21, 2024, 06:45:21 AM »
Well the latent wit in some of the Subject headings may confuse e.g. The Cognitive Dissonance of His Glibness for Baraq Obama :-D

I'm trying to teach GPT4.o. So far it's been ... interesting. It can whip out a graphic off a verbal description that hits close to the mark, but is unable to access web pages, hence my effort to get it to catalog topics here and hence help my neurodiverse brain from running off the rails seeking this topic or that has yet to bear fruit. It's the end of the semester and I have a large RFP running full bore that I want to complete in advance of retirement, but once I have some time on my hands I'm going to attempt to drop every list topic into 4.0 and see if "she" can keep 'em straight for me.

Body-by-Guinness

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The Neural Basis of Consciousness
« Reply #227 on: May 22, 2024, 09:25:28 PM »
This will be interesting to watch: once they ID a quantifiable basis/theory of consciousness, confirm it by applying it to other organisms to see if it fits, and then perhaps applying that theory to silicon to see if consciousness can be created … that’ll be a huge sea change:

Scientists Are Working Towards a Unified Theory of Consciousness
Singularity Hub / by Shelly Fan / May 20, 2024 at 1:54 PM
The origin of consciousness has teased the minds of philosophers and scientists for centuries. In the last decade, neuroscientists have begun to piece together its neural underpinnings—that is, how the brain, through its intricate connections, transforms electrical signaling between neurons into consciousness.

Yet the field is fragmented, an international team of neuroscientists recently wrote in a new paper in Neuron. Many theories of consciousness contradict each other, with different ideas about where and how consciousness emerges in the brain.

Some theories are even duking it out in a mano-a-mano test by imaging the brains of volunteers as they perform different tasks in clinical test centers across the globe.

But unlocking the neural basis of consciousness doesn’t have to be confrontational. Rather, theories can be integrated, wrote the authors, who were part of the Human Brain Project—a massive European endeavor to map and understand the brain—and specialize in decoding brain signals related to consciousness.

Not all authors agree on the specific brain mechanisms that allow us to perceive the outer world and construct an inner world of “self.” But by collaborating, they merged their ideas, showing that different theories aren’t necessarily mutually incompatible—in fact, they could be consolidated into a general framework of consciousness and even inspire new ideas that help unravel one of the brain’s greatest mysteries.

If successful, the joint mission could extend beyond our own noggins. Brain organoids, or “mini-brains,” that roughly mimic early human development are becoming increasingly sophisticated, spurring ethical concerns about their potential for developing self-awareness (to be clear, there aren’t any signs). Meanwhile, similar questions have been raised about AI. A general theory of consciousness, based on the human mind, could potentially help us evaluate these artificial constructs.

“Is it realistic to reconcile theories, or even aspire to a unified theory of consciousness?” the authors asked. “We take the standpoint that the existence of multiple theories is a sign of healthiness in this nascent field…such that multiple theories can simultaneously contribute to our understanding.”

Lost in Translation

I’m conscious. You are too. We see, smell, hear, and feel. We have an internal world that tells us what we’re experiencing. But the lines get blurry for people in different stages of coma or for those locked-in—they can still perceive their surroundings but can’t physically respond. We lose consciousness in sleep every night and during anesthesia. Yet, somehow, we regain consciousness. How?

With extensive imaging of the brain, neuroscientists today agree that consciousness emerges from the brain’s wiring and activity. But multiple theories argue about how electrical signals in the brain produce rich and intimate experiences of our lives.

Part of the problem, wrote the authors, is that there isn’t a clear definition of “consciousness.” In this paper, they separated the term into two experiences: one outer, one inner. The outer experience, called phenomenal consciousness, is when we immediately realize what we’re experiencing—for example, seeing a total solar eclipse or the northern lights.

The inner experience is a bit like a “gut feeling” in that it helps to form expectations and types of memory, so that tapping into it lets us plan behaviors and actions.

Both are aspects of consciousnesses, but the difference is hardly delineated in previous work. It makes comparing theories difficult, wrote the authors, but that’s what they set out to do.

Meet the Contenders

Using their “two experience” framework, they examined five prominent consciousness theories.

The first, the global neuronal workspace theory, pictures the brain as a city of sorts. Each local brain region “hub” dynamically interacts with a “global workspace,” which integrates and broadcasts information to other hubs for further processing—allowing information to reach the consciousness level. In other words, we only perceive something when all pieces of sensory information—sight, hearing, touch, taste—are woven into a temporary neural sketchpad. According to this theory, the seat of consciousness is in the frontal parts of the brain.

The second, integrated information theory, takes a more globalist view. The idea is that consciousness stems from a series of cause-effect reactions from the brain’s networks. With the right neural architecture, connections, and network complexity, consciousness naturally emerges. The theory suggests the back of the brain sparks consciousness.

Then there’s dendritic integration theory, the coolest new kid in town. Unlike previous ideas, this theory waved the front or back of the brain goodbye and instead zoomed in on single neurons in the cortex, the outermost part of the brain and a hub for higher cognitive functions such as reasoning and planning.

The cortex has extensive connections to other parts of the brain—for example, those that encode memories and emotions. One type of neuron, deep inside the cortex, especially stands out. Physically, these neurons resemble trees with extensive “roots” and “branches.” The roots connect to other parts of the brain, whereas the upper branches help calculate errors in the neuron’s computing. In turn, these upper branches generate an error signal that corrects mistakes through multiple rounds of learning.

The two compartments, while physically connected, go about their own business—turning a single neuron into multiple computers. Here’s the crux: There’s a theoretical “gate” between the upper and lower neural “offices” for each neuron. During consciousness, the gate opens, allowing information to flow between the cortex and other brain regions. In dreamless sleep and other unconscious states, the gate closes.

Like a light switch, this theory suggests that consciousness is supported by flicking individual neuron gates on or off on a grand scale.

The last two theories propose that recurrent processing in the brain—that is, it learns from previous experiences—is essential for consciousness. Instead of “experiencing” the world, the brain builds an internal simulation that constantly predicts the “here and now” to control what we perceive.

A Unified Theory?

All the theories have extensive experiments to back up their claims. So, who’s right? To the authors, the key is to consider consciousness not as a singular concept, but as a “ladder” of sorts. The brain functions at multiple levels: cells, local networks, brain regions, and finally, the whole brain.

When examining theories of consciousness, it also makes sense to delineate between different levels. For example, the dendritic integration theory—which considers neurons and their connections—is on the level of single cells and how they contribute to consciousness. It makes the theory “neutral,” in that it can easily fit into ideas at a larger scale—those that mostly rely on neural network connections or across larger brain regions.

Although it’s seemingly difficult to reconcile various ideas about consciousness, two principles tie them together, wrote the team. One is that consciousness requires feedback, within local neural circuits and throughout the brain. The other is integration, in that any feedback signals need to be readily incorporated back into neural circuits, so they can change their outputs. Finally, all authors agree that local, short connections are vital but not enough. Long distance connections from the cortex to deeper brain areas are required for consciousness.

So, is an integrated theory of consciousness possible? The authors are optimistic. By defining multiple aspects of consciousness—immediate responses versus internal thoughts—it’ll be clearer how to explore and compare results from different experiments. For now, the global neuronal workspace theory mostly focuses on the “inner experience” that leads to consciousness, whereas others try to tackle the “outer experience”—what we immediately experience.

For the theories to merge, the latter groups will have to explain how consciousness is used for attention and planning, which are hallmarks for immediate responses. But fundamentally, wrote the authors, they are all based on different aspects of neuronal connections near and far. With more empirical experiments, and as increasingly more sophisticated brain atlases come online, they’ll move the field forward.

Hopefully, the authors write, “an integrated theory of consciousness…may come within reach within the next years or decades.”

https://singularityhub.com/2024/05/20/scientists-are-working-towards-a-unified-theory-of-consciousness/


Crafty_Dog

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Re: Intelligence and Psychology, Artificial Intelligence
« Reply #228 on: May 23, 2024, 02:41:58 PM »
That was super interesting for me.

Konrad Lorenz's "Behind the Mirror" has been of deep influence to me in this regard:

https://en.wikipedia.org/wiki/Behind_the_Mirror

Behind the Mirror

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Behind the Mirror

Cover of the first edition
Author   Konrad Lorenz
Original title   Die Rückseite des Spiegels
Country   Austria
Language   German
Published   1973
Media type   Print (hardcover)
Pages   261

Behind the Mirror: A Search for a Natural History of Human Knowledge (German: Die Rückseite des Spiegels, Versuch einer Naturgeschichte menschlichen Erkennens) is a 1973 book by the ethologist Konrad Lorenz.[1] Lorenz shows the essentials of a lifetime's work and summarizes it into his very own philosophy: evolution is the process of growing perception of the outer world by living nature itself. Stepping from simple to higher organized organisms he shows how they benefit from information processing. The methods mirrored by organs have been created in the course of evolution as the natural history of this organism. Lorenz uses the mirror as a simplified model of our brain reflecting the part of information from the outside world it is able to "see". The backside of the mirror was created by evolution to gather as much information as needed to better survive. The book gives a hypothesis how consciousness was "invented" by evolution.

One of the key positions of the book included the criticism of Immanuel Kant, arguing that the philosopher failed to realize that knowledge, as mirrored by the human mind is the product of evolutionary adaptations.[2]

Kant has maintained that our consciousness[3] or our description and judgments about the world could never mirror the world as it really is so we can not simply take in the raw data that the world provides nor impose our forms on the world.[4] Lorenz disputed this, saying it is inconceivable that - through chance mutations and selective retention - the world fashioned an instrument of cognition that grossly misleads man about such world. He said that we can determine the reliability of the mirror by looking behind it.[2]

Summary
Lorenz summarizes his life's work into his own philosophy: Evolution is the process of growing perception of the outer world by living nature itself. Stepping from simple to higher organized organisms, Lorenz shows how they gain and benefit from information. The methods mirrored by organs have been created in the course of evolution as the natural history of this organism.

In the book, Lorenz uses the mirror as a simple model of the human brain that reflects the part of the stream of information from the outside world it is able to "see". He argued that merely looking outward into the mirror ignores the fact that the mirror has a non-reflecting side, which is also a part and parcel of reality.[5] The backside of the mirror was created by evolution to gather as much information as needed to better survive. The picture in the mirror is what we see within our mind. Within our cultural evolution we have extended this picture in the mirror by inventing instruments that transform the most needed of the invisible to something visible.

The back side of the mirror is acting for itself as it processes the incoming information to improve speed and effectiveness. By that human inventions like logical conclusions are always in danger to be manipulated by these hardwired prejudices in our brain. The book gives a hypothesis how consciousness was invented by evolution.

Main topics

Fulguratio, the flash of lightning, denotes the act of creation of a totally new talent of a system, created by the combination of two other systems with talents much less than those of the new system. The book shows the "invention" of a feedback loop by this process.

Imprinting, is the phase-sensitive learning of an individual that is not reversible. It's a static program run only once.

Habituation is the learning method to distinguish important information from unimportant by analysing its frequency of occurrence and its impact.

Conditioning by reinforcement, occurs when an event following a response causes an increase in the probability of that response occurring in the future. The ability to do this kind of learning is hardwired in our brain and is based on the principle of causality. The discovery of causality (which is a substantial element of science and Buddhism) was a major step of evolution in analysing the outer world.

Pattern matching is the abstraction of different appearances into the identification of being one object and is available only in highly organized creatures

Exploratory behaviour is the urge of the highest developed creatures on earth to go on with learning after maturity and leads to self-exploration which is the base for consciousness.

=======================

https://www.britannica.com/biography/Konrad-Lorenz

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Konrad Lorenz
Konrad Lorenz
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Born: Nov. 7, 1903, Vienna, Austria
Died: Feb. 27, 1989, Altenburg (aged 85)
Awards And Honors: Nobel Prize (1973)
Subjects Of Study: aggressive behaviour animal behaviour evolution imprinting
Konrad Lorenz (born Nov. 7, 1903, Vienna, Austria—died Feb. 27, 1989, Altenburg) was an Austrian zoologist and the founder of modern ethology, the study of animal behaviour by means of comparative zoological methods. His ideas contributed to an understanding of how behavioral patterns may be traced to an evolutionary past, and he was also known for his work on the roots of aggression. He shared the Nobel Prize for Physiology or Medicine in 1973 with the animal behaviourists Karl von Frisch and Nikolaas Tinbergen.

Lorenz was the son of an orthopedic surgeon. He showed an interest in animals at an early age, and he kept animals of various species—fish, birds, monkeys, dogs, cats, and rabbits—many of which he brought home from his boyhood excursions. While still young, he provided nursing care for sick animals from the nearby Schönbrunner Zoo. He also kept detailed records of bird behaviour in the form of diaries.

Mushrooms growing in forest. (vegetable; fungus; mushroom; macrofungi; epigeous)
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In 1922, after graduating from secondary school, he followed his father’s wishes that he study medicine and spent two semesters at Columbia University, in New York City. He then returned to Vienna to study.

During his medical studies Lorenz continued to make detailed observations of animal behaviour; a diary about a jackdaw that he kept was published in 1927 in the prestigious Journal für Ornithologie. He received an M.D. degree at the University of Vienna in 1928 and was awarded a Ph.D. in zoology in 1933. Encouraged by the positive response to his scientific work, Lorenz established colonies of birds, such as the jackdaw and greylag goose, published a series of research papers on his observations of them, and soon gained an international reputation.

In 1935 Lorenz described learning behaviour in young ducklings and goslings. He observed that at a certain critical stage soon after hatching, they learn to follow real or foster parents. The process, which is called imprinting, involves visual and auditory stimuli from the parent object; these elicit a following response in the young that affects their subsequent adult behaviour. Lorenz demonstrated the phenomenon by appearing before newly hatched mallard ducklings and imitating a mother duck’s quacking sounds, upon which the young birds regarded him as their mother and followed him accordingly.

In 1936 the German Society for Animal Psychology was founded. The following year Lorenz became coeditor in chief of the new Zeitschrift für Tierpsychologie, which became a leading journal for ethology. Also in 1937, he was appointed lecturer in comparative anatomy and animal psychology at the University of Vienna. From 1940 to 1942 he was professor and head of the department of general psychology at the Albertus University at Königsberg, Germany (now Kaliningrad, Russia).


From 1942 to 1944 he served as a physician in the German army and was captured as a prisoner of war in the Soviet Union. He was returned to Austria in 1948 and headed the Institute of Comparative Ethology at Altenberg from 1949 to 1951. In 1950 he established a comparative ethology department in the Max Planck Institute of Buldern, Westphalia, becoming codirector of the Institute in 1954. From 1961 to 1973 he served as director of the Max Planck Institute for Behaviour Physiology, in Seewiesen. In 1973 Lorenz, together with Frisch and Tinbergen, was awarded the Nobel Prize for Physiology or Medicine for their discoveries concerning animal behavioral patterns. In the same year, Lorenz became director of the department of animal sociology at the Institute for Comparative Ethology of the Austrian Academy of Sciences in Altenberg.

Lorenz’s early scientific contributions dealt with the nature of instinctive behavioral acts, particularly how such acts come about and the source of nervous energy for their performance. He also investigated how behaviour may result from two or more basic drives that are activated simultaneously in an animal. Working with Nikolaas Tinbergen of the Netherlands, Lorenz showed that different forms of behaviour are harmonized in a single action sequence.

Lorenz’s concepts advanced the modern scientific understanding of how behavioral patterns evolve in a species, particularly with respect to the role played by ecological factors and the adaptive value of behaviour for species survival. He proposed that animal species are genetically constructed so as to learn specific kinds of information that are important for the survival of the species. His ideas have also cast light on how behavioral patterns develop and mature during the life of an individual organism.

In the latter part of his career, Lorenz applied his ideas to the behaviour of humans as members of a social species, an application with controversial philosophical and sociological implications. In a popular book, Das sogenannte Böse (1963; On Aggression), he argued that fighting and warlike behaviour in man have an inborn basis but can be environmentally modified by the proper understanding and provision for the basic instinctual needs of human beings. Fighting in lower animals has a positive survival function, he observed, such as the dispersion of competitors and the maintenance of territory. Warlike tendencies in humans may likewise be ritualized into socially useful behaviour patterns. In another work, Die Rückseite des Spiegels: Versuch einer Naturgeschichte menschlichen Erkennens (1973; Behind the Mirror: A Search for a Natural History of Human Knowledge), Lorenz examined the nature of human thought and intelligence and attributed the problems of modern civilization largely to the limitations his study revealed.

Crafty_Dog

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Re: Intelligence and Psychology, Artificial Intelligence
« Reply #229 on: May 23, 2024, 02:47:47 PM »
Am I correct to assess that this passage is quite congurent with Lorenz's work?

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With extensive imaging of the brain, neuroscientists today agree that consciousness emerges from the brain’s wiring and activity. But multiple theories argue about how electrical signals in the brain produce rich and intimate experiences of our lives.

Part of the problem, wrote the authors, is that there isn’t a clear definition of “consciousness.” In this paper, they separated the term into two experiences: one outer, one inner. The outer experience, called phenomenal consciousness, is when we immediately realize what we’re experiencing—for example, seeing a total solar eclipse or the northern lights.

The inner experience is a bit like a “gut feeling” in that it helps to form expectations and types of memory, so that tapping into it lets us plan behaviors and actions.

Both are aspects of consciousnesses, but the difference is hardly delineated in previous work. It makes comparing theories difficult, wrote the authors, but that’s what they set out to do.

Meet the Contenders

Using their “two experience” framework, they examined five prominent consciousness theories.

The first, the global neuronal workspace theory, pictures the brain as a city of sorts. Each local brain region “hub” dynamically interacts with a “global workspace,” which integrates and broadcasts information to other hubs for further processing—allowing information to reach the consciousness level. In other words, we only perceive something when all pieces of sensory information—sight, hearing, touch, taste—are woven into a temporary neural sketchpad. According to this theory, the seat of consciousness is in the frontal parts of the brain.