Michio Kaku on the Evolution of Intelligence

Michio Kaku on the Evolution of Intelligence
Big Think
Mar 25, 2014

04:00 By monkeying with just one gene [ASPM], you can double the size of the brain case and the brain itself.
In the future, we may use gene therapy to begin the process of making–perhaps–a chimpanzee intelligent.
We know the genes that would increase the size of the brain.
We’ve isolated now the genes that give us manual dexterity.

ASPM (abnormal spindle‐like microcephaly‐associated)

related:
https://franzcalvo.wordpress.com/2014/07/14/language-gene-has-a-partner

Is human intelligence still evolving?

How smart is smart?
Is human intelligence still evolving?
EMBO reports (2009)  10 (11),  1198-1201
Philip Hunter
http://embor.embopress.org/content/10/11/1198

The development of higher cognitive functions in Homo sapiens—commonly and perhaps wrongly described as intelligence …

Bob Sternberg, for instance, a psychologist from Tufts University (Medford, MA, USA) and a pioneer of human intelligence research, believes that intelligence is an adaptive trait, but not a quantity that can be measured by standard intelligence quotient (IQ) tests. Instead, he has defined human intelligence as “a mental activity directed toward purposive adaptation to, selection, and shaping of real‐world environments relevant to one’s life” (Sternberg, 1985). However, there is a caveat to this so‐called ‘triarchic’ theory: its human devisers are not objective bystanders. “Higher levels of intelligence as we conceive of it can be and [have] been adaptive,” Sternberg said. “I say ‘as we conceive of it’ because the concept [of intelligence] is in large part a human invention of successful people to explain their own success.”

“For a neuroscientist, any aspect of ‘intelligent behaviour’ involves many different processes—attention, motivation, arousal, motor skills, perception, memory.
To lump all these together into one ‘crystallized intelligence’ makes no biological sense

A 2006 study from the University of Chicago (IL, USA) suggested that two genes, microcephalin and ASPM (abnormal spindle‐like microcephaly‐associated), which are thought to regulate brain size, have been under strong selective pressure since humans left Africa (Evans et al, 2005). However, the team, led by Bruce Lahn, do not claim that these genes are associated with cognitive functions, and others have suggested that they might have undergone selection to cope with the decreasing amounts of good daylight as humans migrated northwards through Europe, Asia and possibly North America. “There is now nice evidence of selection over recent time for genes that promote large brains at high latitudes, such as Bruce Lahn’s work,” Robin Dunbar agreed. “But this is almost certainly due to the need for a larger visual area at high latitudes [where light levels are lower], not for greater intelligence, although this is as yet unpublished data.”

However, human brains have actually decreased by about 10% in volume during the past 30,000 years[1]; the rapid evolution of new cognitive functions—language in particular—might therefore have resulted from structural rather than volume changes.

One explanation for this reverse trend in human brain size is that brains come with metabolic costs attached—the brain consumes about 20% of the basal calories used by our bodies each day—and human evolution might have reached a point where increased metabolic demand outweighed the benefits of greater brain volume. Instead, selective pressures might have begun to favour genes that conferred greater processing efficiency and improved coordination between functional units.

“We should be more concerned with what is likely a distinctively human quality—wisdom—the skill in how to use our intelligence in a way that promotes a common good, over the long term as well as the short term, through the infusion of positive ethical values.”

reference:
[1]
average brain volume of 1274 cm3 for men, and 1131 cm3 for women
Neanderthals: 1,500–1,800 cm3
http://en.wikipedia.org/wiki/Brain_size

Any sufficiently advanced technology is …

Clarke’s three laws
http://en.wikipedia.org/wiki/Clarke’s_three_laws

Any sufficiently advanced technology is indistinguishable from magic.

Arthur C. Clarke

related:
Revisiting The Tenure Of Supreme Court Justice Louis Brandeis, The ‘Jewish Jefferson’
June 7, 2016·
http://www.npr.org/2016/06/07/481076322/revisiting-the-tenure-of-supreme-court-justice-louis-brandeis-the-jewish-jeffers
He didn’t realize that television was one way – it kind of broadcast to you in your home. It was very new when he was on the Supreme Court.
And he was afraid that the government could monitor you in your living room through your television.

Resource leveling

Resource leveling
http://en.wikipedia.org/wiki/Resource_leveling

Microsoft Project

Set task priorities for resource leveling
Applies To: Project Professional 2013, Project 2013 Standard
https://support.office.com/en-US/article/Set-task-priorities-for-resource-leveling-CA3442BC-8DFB-4C08-ABA8-4ADB5B9FBC32

Distribute project work evenly (level resource assignments)
Applies To: Project 2010, Project 2010 Standard
https://support.office.com/en-US/article/Distribute-project-work-evenly-level-resource-assignments-59EE715D-4446-42C9-8756-4EA2A5A7E4A0

Resource Leveling dialog box
Applies To: Project 2007 Standard
https://support.office.com/en-US/article/Resource-Leveling-dialog-box-05A2EDCA-82FB-440B-AC77-9CEF80C353B0

Automation bias

Complacency and bias in human use of automation: an attentional integration.
Hum Factors. 2010 Jun;52(3):381-410.
Parasuraman R, Manzey DH.
http://www.ncbi.nlm.nih.gov/pubmed/21077562

http://hfs.sagepub.com/content/52/3/381.abstract

OBJECTIVE:
Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation.

BACKGROUND:
Automation-related complacency and automation bias have typically been considered separately and independently.

METHODS:
Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved.

RESULTS:
Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator’s attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency.

CONCLUSION:
Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics.

APPLICATION:
The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.