Single-metric versions of intelligence are going the way of the dinosaur. In practical contexts, it's much better to test for a bunch of specific skills and aptitudes and to create a predictive model of success at the desired task.
I thought that this had become a fairly dominant view, over 20 years ago. See this PDF: http://www.learner.org/courses/learningclassroom/support/04_mult_intel.pdf
I first read the book in the early nineties, though Howard Gardner had published the first edition in 1982. I was at first a bit extra skeptical that it would be based too much on some form of "political correctness", but I found the concepts to be very compelling.
Most of the discussion I heard in subsequent years, occasionally by psychology professor and grad student friends, continued to be positive.
I might say that I had no ulterior motive in trying to find reasons to agree with the book, since I always score in the genius range myself on standardized, traditional-style IQ tests.
So, it does seem to me that intelligence is a vector, not a scalar, if we have to call it by one noun.
As to Katja's follow-up question, does it matter for Bostrom's arguments? Not really, as long as one is clear (which it is from the contexts of his remarks) which kind(s) of intelligence he is referring to.
I think there is a more serious vacuum in our understanding, than whether intelligence is a single property, or comes in several irreducibly different (possibly context-dependent) forms, and that is this : with respect to the sorts of intelligence we usually default to conversing about (like the sort that helps a reader understand Bostrom's book, an explanation of special relativity, or RNA interference in molecular biology), do we even know what we think we know about what that is.
I would have to explain the idea of this purported "vacuum" in understanding at significant length; it is a set of new ideas that stuck me, together, as a set of related insights. I am working on a paper explaining the new perspective I think I have found, and why it might open up some new important questions and strategies for AGI.
When it is finished and clear enough to be useful, I will make it available by PDF or on a blog.
(Too lengthy to put in one post here, so I will put the link up. If these ideas pan out, they may suggest some reconceptualizations with nontrivial consequences, and be informative in a scalable sense -- which is what one in this area of research would hope for.)
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.