I am a little curious that the "seven kinds of intelligence" (give or take a few, in recent years) notion has not been mentioned much, if at all, even if just for completeness.... Has that been discredited by some body of argument or consensus, that I missed somewhere along the line, in the last few years?
Particularly in many approaches to AI, which seem to view, almost a priori (I'll skip the italics and save them for emphasis) the approach of the day to be: work on (ostensibly) "component" features of intelligent agents as we conceive of them, or find them naturalistically.
Thus, (i) machine "visual" object recognition (wavelength band... up for grabs, perhaps, for some items might be better identified by switching up or down the E.M. scale and visual intelligence was one of the proposed seven kinds; (ii) mathematical intelligence or mathematical (dare I say it) intuition; (iii) facility with linguistic tasks, comprehension, multiple language acquisition -- another of the proposed seven; (i.v) manual dexterity and mechanical ability and motor skill (as in athletics, surgery, maybe sculpture, carpentry or whatever) -- another proposed form of intelligence, and so on. (Aside, interesting that these alleged components span the spectrum of difficulty... are, that is, problems from both easy and harder domains, as has been gradually -- sometimes unexpectedly -- revealed by the school of hard knocks, during the decades of AI engineering attempts.)
It seems that actors sympathetic to the top-down, "piecemeal" approach popular in much of the AI community would have jumped at this way of supplanting the ersatz "G" -- as it was called decades ago in early gropings in psychology and cogsci which sought a concept of IQ or living intelligence -- with, now, what many in cognitive science consider the more modern view and those in AI consider a more approachable engineering design strategy.
Any reason we aren't debating this more than we are? Or did I miss it in one of the posts, or bypass it inadvertently in my kindle app (where I read Bostrom's book)?
Bring these questions back up in later discussions!
This is part of a weekly reading group on Nick Bostrom's book, Superintelligence. For more information about the group, and an index of posts so far see the announcement post. For the schedule of future topics, see MIRI's reading guide.
Welcome. This week we finish chapter 2 with three more routes to superintelligence: enhancement of biological cognition, brain-computer interfaces, and well-organized networks of intelligent agents. This corresponds to the fourth section in the reading guide, Biological Cognition, BCIs, Organizations.
This post summarizes the section, and offers a few relevant notes, and ideas for further investigation. My own thoughts and questions for discussion are in the comments.
There is no need to proceed in order through this post, or to look at everything. Feel free to jump straight to the discussion. Where applicable and I remember, page numbers indicate the rough part of the chapter that is most related (not necessarily that the chapter is being cited for the specific claim).
Reading: “Biological Cognition” and the rest of Chapter 2 (p36-51)
Summary
Biological intelligence
Brain-computer interfaces
Networks and organizations
Summary
The book so far
Here's a recap of what we have seen so far, now at the end of Chapter 2:
Do you disagree with any of these points? Tell us about it in the comments.
Notes
Snake Oil Supplements? is a nice illustration of scientific evidence for different supplements, here filtered for those with purported mental effects, many of which relate to intelligence. I don't know how accurate it is, or where to find a summary of apparent effect sizes rather than evidence, which I think would be more interesting.
Ryan Carey and I talked to Gwern Branwen - an independent researcher with an interest in nootropics - about prospects for substantial intelligence amplification. I was most surprised that Gwern would not be surprised if creatine gave normal people an extra 3 IQ points.
And some more health-specific ones.
People have apparently been getting smarter by about 3 points per decade for much of the twentieth century, though this trend may be ending. Several explanations have been proposed. Namesake James Flynn has a TED talk on the phenomenon. It is strangely hard to find a good summary picture of these changes, but here's a table from Flynn's classic 1978 paper of measured increases at that point:
Here are changes in IQ test scores over time in a set of Polish teenagers, and a set of Norwegian military conscripts respectively:
This study uses 'Genome-wide Complex Trait Analysis' (GCTA) to estimate that about half of variation in fluid intelligence in adults is explained by common genetic variation (childhood intelligence may be less heritable). These studies use genetic data to predict 1% of variation in intelligence. This genome-wide association study (GWAS) allowed prediction of 2% of education and IQ. This study finds several common genetic variants associated with cognitive performance. Stephen Hsu very roughly estimates that you would need a million samples in order to characterize the relationship between intelligence and genetics. According to Robertson et al, even among students in the top 1% of quantitative ability, cognitive performance predicts differences in occupational outcomes later in life. The Social Science Genetics Association Consortium (SSGAC) lead research efforts on genetics of education and intelligence, and are also investigating the genetics of other 'social science traits' such as self-employment, happiness and fertility. Carl Shulman and Nick Bostrom provide some estimates for the feasibility and impact of genetic selection for intelligence, along with a discussion of reproductive technologies that might facilitate more extreme selection. Robert Sparrow writes about 'in vitro eugenics'. Stephen Hsu also had an interesting interview with Luke Muehlhauser about several of these topics, and summarizes research on genetics and intelligence in a Google Tech Talk.
For Parkinson's disease relief, allowing locked in patients to communicate, handwriting, and controlling robot arms.
Big ones I can think of include innovations in using text (writing, printing, digital text editing), communicating better in other ways (faster, further, more reliably), increasing population size (population growth, or connection between disjoint populations), systems for trade (e.g. currency, finance, different kinds of marketplace), innovations in business organization, improvements in governance, and forces leading to reduced conflict.
In-depth investigations
If you are particularly interested in these topics, and want to do further research, these are a few plausible directions, some inspired by Luke Muehlhauser's list, which contains many suggestions related to parts of Superintelligence. These projects could be attempted at various levels of depth.
How to proceed
This has been a collection of notes on the chapter. The most important part of the reading group though is discussion, which is in the comments section. I pose some questions for you there, and I invite you to add your own. Please remember that this group contains a variety of levels of expertise: if a line of discussion seems too basic or too incomprehensible, look around for one that suits you better!
Next week, we will talk about 'forms of superintelligence', in the sense of different dimensions in which general intelligence might be scaled up. To prepare, read Chapter 3, Forms of Superintelligence (p52-61). The discussion will go live at 6pm Pacific time next Monday 13 October. Sign up to be notified here.