Moravec’s view is that the robots will eventually suc-ceed us—that humans clearly face extinction.

by far the most illuminating to me is the idea that mental causation works from virtual futures towards the past 00:33:17 whereas physical causation works from the past towards the future and these two streams of causation sort of overlap in the present

there's this broader issue of of being able to get inside other people's heads as we're driving down the road all the time we're looking at other 00:48:05 people and because we have very advanced theories of mind

in my view the biggest the most dangerous phenomenon on the human on our planet is uh human stupidity it's not artificial intelligence

Remember ChatGPT? It is going to do to the white collar world what robotics and offshoring did to blue collar America. So maybe this isn't the best time to be abandoning the Humanities to focus on vocational training?

A.G.I.-ism distracts from finding better ways to augment intelligence.

the writings of the Spanish physician JuanHuarte, who in the late sixteenth century published a widely translated studyon the nature of human intelligence. In the course of his investigations, Huartecame to wonder at the fact that the word for “intelligence,” ingenio, seems tohave the same Latin root as various words meaning “engender” or “generate.”

In this paper, we propose and analyse a potential power triangle between three kinds of mutuallydependent, mutually threatening and co-evolving cognitive systems—the human being, the socialsystem and the emerging synthetic intelligence. The question we address is what configuration betweenthese powers would enable humans to start governing the global socio-econo-political system

Thompson’s point is that “artificial intelligence” — defined as machines that can think on their own just like or better than humans — is not yet (and may never be) as powerful as “intelligence amplification,” the symbiotic smarts that occur when human cognition is augmented by a close interaction with computers.

With approximately half of variance in cognitive task performance having non-g sources of variance, we believe that other traits may be important in explaining cognitive performance of both non-Western and Western groups.

Although we believe that this study establishes the presence of g in data from these non-Western cultures, this study says nothing about the relative level of general cognitive ability in various societies, nor can it be used to make cross-cultural comparisons. For this purpose, one must establish measurement invariance of a test across different cultural groups (e.g., Holding et al., 2018) to ensure that test items and tasks function in a similar way for each group.

Two peer reviewers raised the possibility that developmental differences across age groups could be a confounding variable because a g factor may be weaker in children than adults.

some of these data sets were collected by individuals who are skeptical of the existence or primacy of g in general or in non-Western cultures (e.g., Hashmi et al., 2010; Hashmi, Tirmizi, Shah, & Khan, 2011; O’Donnell et al., 2012; Pitchford & Outhwaite, 2016; Stemler et al., 2009; Sternberg et al., 2001, 2002). One would think that these investigators would be most likely to include variables in their data sets that would form an additional factor. Yet, with only three ambiguous exceptions (Grigorenko et al., 2006; Gurven et al., 2017), these researchers’ data still produced g.

The mean sample size of the remaining data sets was 539.6 (SD = 1,574.5). The large standard deviation in relationship to the mean is indicative of the noticeably positively skewed distribution of sample sizes, a finding supported by the much smaller median of 170 and skewness value of 6.297. There were 16,559 females (33.1%), 25,431 males (48.6%), and 10,350 individuals whose gender was unreported (19.8%). The majority of samples—62 of 97 samples (63.9%)—consisted entirely or predominantly of individuals below 18. Most of the remaining samples contained entirely or predominantly adults (32 data sets, 33.0%), and the remaining 3 datasets (3.1%) had an unknown age range or an unknown mix of adults and children). The samples span nearly the entire range of life span development, from age 2 to elderly individuals.

Alternatively, one could postulate that a general cognitive ability is a Western trait but not a universal trait among humans, but this would require an evolutionary model where this general ability evolved several times independently throughout the mammalian clade, including separately in the ancestors of Europeans after they migrated out of Africa and separated from other human groups. Such a model requires (a) a great deal of convergent evolution to occur across species occupying widely divergent environmental niches and (b) an incredibly rapid development of a general cognitive ability while the ancestors of Europeans were under extremely strong selection pressures that other humans did not experience (but other mammal species or their ancestors would have experienced at other times). We find the more parsimonious model of an evolutionary origin of the general cognitive ability in the early stages of mammalian development to be the more plausible one, and thus we believe that it is reasonable to expect a general cognitive ability to be a universal human trait.

Investigating cultural beliefs about intelligence may be mildly interesting from an anthropological perspective, but it sheds little light on the nature of intelligence. One undiscussed methodological problem in many studies of cultural perspectives on intelligence is the reliance on surveys of laymen to determine what people in a given culture believe about intelligence. This methodology says little about the actual nature of intelligence.

Panga Munthu test of intelligence

Berry (1986)

We believe that members of the public likely learn some inaccurate information about intelligence in their psychology courses. The good news about this implication is that reducing the public’s mistaken beliefs about intelligence will not take a massive public education campaign or public relations blitz. Instead, improving the public’s understanding about intelligence starts in psychology’s own backyard with improving the content of undergraduate courses and textbooks.

This means that it is actually easier to measure intelligence than many other psychological constructs. Indeed, some individuals trying to measure other constructs have inadvertently created intelligence tests

many psychologists simply accept an operational definition of intelligence by spelling out the procedures they use to measure it. . . . Thus, by selecting items for an intelligence test, a psychologist is saying in a direct way, “This is what I mean by intelligence.” A test that measures memory, reasoning, and verbal fluency offers a very different definition of intelligence than one that measures strength of grip, shoe size, hunting skills, or the person’s best Candy Crush mobile game score. (p. 290)

Minnesota Transracial Adoption Study

the Stanford-Binet intelligence test

Some readers will also be surprised to find that The Bell Curve is not as controversial as its reputation would lead one to believe (and most of the book is not about race at all).

Gardner’s multiple intelligences

Most frequently this appeared in the form of a tacit acknowledgment that IQ test scores correlate with academic success, followed by a quick denial that the scores are important for anything else in life

this study highlights the mismatch between scholarly consensus on intelligence and the beliefs of the general public

Judged solely by the number of factually inaccurate statements, the textbooks we examined were mostly accurate.

We found that 79.3% of textbooks contained inaccurate statements and 79.3% had logical fallacies in their sections about intelligence.

Gottfredson’s (1997a) mainstream statement on intelligence

CTP synthesizes critical reflection with technology production as a way of highlighting and altering unconsciously-held assumptions that are hindering progress in a technical field.

And its very likely that IA is a much easier road to the achievement of superhumanity than pure AI. In humans, the hardest development problems have already been solved. Building up from within ourselves ought to be easier than figuring out what we really are and then building machines that are all of that.

"... groups of individuals doing things collectively that seem intelligent.” [41]