Economic history suggests big changes are plausible.
Sure, but it is hard to predict what changes are going to happen and when.
In particular, major economic changes are typically precipitated by technological breakthroughs. It doesn't seem that we can predict these breakthroughs looking at the economy, since the causal relationship is mostly the other way.
AI progress is ongoing.
Ok.
AI progress is hard to predict, but AI experts tend to expect human-level AI in mid-century.
But AI experts have a notoriously poor track record at predicting human-level AI.
Several plausible paths lead to superintelligence: brain emulations, AI, human cognitive enhancement, brain-computer interfaces, and organizations.
Organizations probably can't become much more "superintelligent" than they already are. Human cognitive enhancement, brain-computer interfaces, etc. also have limits.
Most of these probably lead to machine superintelligence ultimately.
Only digital intelligences (brain emulations and AIs) seem to have a realistic chance of becoming significantly more intelligent than anything that exists now, and even this is dubious.
That there are several paths suggests we are likely to get there.
There aren't really many paths, and they are not independent.
Do you think AI experts deserve their notoriety at predicting? The several public predictions that I know of prior to 1980 were indeed early (i.e. we have passed the time they predicted) but [Michie's survey] covers about ten times as many people and suggests that in the 70s, most CS researchers thought human-level AI would not arrive by 2014.
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.