Author Topic: Intelligence and Psychology, Artificial Intelligence  (Read 61073 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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