At the recent AGI workshop, Michael Anissimov concisely summarized one of the reasons to worry about AI: the greatest risk is that there won’t be small risks leading up to it.
Science and Technology
Book review: Evolution’s Rainbow: Diversity, Gender, and Sexuality in Nature and People by Joan Roughgarden
This book provides some good descriptions of sexual and gender diversity in nature and in a variety of human cultures, and makes a number of valid criticisms of biases against diversity in the scientific community and in society at large.
Many of her attempts to criticize sexual selection theory are plausible criticisms of beliefs that don’t have much connection to sexual selection theory (e.g. the belief that all sexually reproducing organisms fall into one of two gender stereotypes).
Her more direct attacks on the theory amount to claiming that “almost all diversity is good” and ignoring the arguments of sexual selection theorists who describe traits that appear to indicate reduced evolutionary fitness (see Geoffrey Miller’s book The Mating Mind). She practically defines genetic defects out of existence. She tries to imply that biologists agree on her criteria for a “genetic defect”, but her criteria require that a “trait be deleterious under all conditions” (I suspect most biologists would say “average” instead of “all”), and that it reduce fitness by at least 5 percent.
Her “alternative” theory, social selection, may have some value as a supplement to sexual selection theory, but I see no sign that it explains enough to replace sexual selection theory.
She sometimes talks as if she were trying to explain the evolution of homosexuality, but when doing so she is referring to bisexuality, and doesn’t attempt to explain why an animal would be exclusively homosexual.
Her obsession with discrediting sexual selection comes from an exaggerated fear that the theory implies that most diversity is bad. This misrepresents sexual selection theory (which only says that some diversity represents a mix of traits with different fitnesses). It’s also a symptom of her desire to treat natural as almost a synonym for good (she seems willing to hate diversity if it’s created via genetic engineering).
She tries to imply that a number of traits (e.g. transsexualism) are more common than would be the case if they significantly reduced reproductive fitness, but her reasoning seems to depend on the assumption that those traits can only be caused by one possible mutation. But if there are multiple places in the genome where a mutation could produce the same trait, there’s no obvious limit to how common a low-fitness trait could be.
Her policy recommendations are of very mixed quality. She wants the FDA to regulate surgical and behavioral therapies the way it regulates drugs, and claims that would stop doctors from “curing” nondiseases such as gender dysphoria. But she doesn’t explain why she expects the FDA to be more tolerant of diversity than doctors. Instead, why not let the patient decide as much as possible whether to consider something a disease?
This book is a colorful explanation of why we are less successful at finding happiness than we expect. It shows many similarities between mistakes we make in foreseeing how happy we will be and mistakes we make in perceiving the present or remembering the past. That makes it easy to see that those errors are natural results of shortcuts our minds take to minimize the amount of data that our imagination needs to process (e.g. filling in our imagination with guesses as our mind does with the blind spot in our eye).
One of the most important types of biases is what he calls presentism (a term he borrows from historians and extends to deal with forecasting). When we imagine the past or future, our minds often employ mental mechanisms that were originally adapted to perceive the present, and we retain biases to give more weight to immediate perceptions than to what we imagine. That leads to mistakes such as letting our opinions of how much food we should buy be overly influenced by how hungry we are now, or Wilbur Wright’s claim in 1901 that “Man will not fly for 50 years.”
This is more than just a book about happiness. It gives me a broad understanding of human biases that I hope to apply to other areas (e.g. it has given me some clues about how I might improve my approach to stock market speculation).
But it’s more likely that the book’s style will make you happy than that the knowledge in it will cause you to use the best evidence available (i.e. observations of what makes others happy) when choosing actions to make yourself happy. Instead, you will probably continue to overestimate your ability to predict what will make you happy and overestimate the uniqueness that you think makes the experience of others irrelevant to your own pursuit of happiness.
I highly recommend the book.
Some drawbacks:
His analysis of memetic pressures that cause false beliefs about happiness to propagate is unconvincing. He seems to want a very simple theory, but I doubt the result is powerful enough to explain the extent of the myths. A full explanation would probably require the same kind of detailed analysis of biases that the rest of the book contains.
He leaves the impression that he thinks he’s explained most of the problems with achieving happiness, when he probably hasn’t done that (it’s unlikely any single book could).
He presents lots of experimental results, but he doesn’t present the kind of evidence needed to prove that presentism is a consistent problem across a wide range of domains.
He fails to indicate how well he follows his own advice. For instance, does he have any evidence that writing a book like this makes the author happy?
Book Review: The Labyrinth of Time: Introducing the Universe by Michael Lockwood
This book provides a great overview of the more interesting parts of modern physics, with some emphasis on time and the philosophy of time.
It is less clearly focused on time than the cover suggests. If you want a deep and narrow focus on time, Huw Price’s book Time’s Arrow is more appropriate and provocative.
Labyrinth of Time explains many things better than other physics books do.
For instance, the standard description of the twin paradox suggests that acceleration is responsible for the differences in how each twin ages. Lockwood refutes that with a nifty diagram of a cylindrical space-time where unaccelerated twins age differently on world-lines of different lengths.
The book provides good explanations of why the alleged paradoxes of time travel aren’t sufficient to imply that time travel is impossible.
Lockwood does a relatively good job of arguing in favor of the Everett (many world) interpretation of quantum mechanics, but that section requires enough experience with the subject that many laymen will have trouble following it.
The speculations he reports about how time might mean before the Planck time are really strange.
Book Review: Kanzi: The Ape at the Brink of the Human Mind by Sue Savage-Rumbaugh
This book makes plausible claims that some bonobos have learned to handle language in a way that is approximately as sophisticated as that of a two year old human. But their anecdotal evidence is somewhat hard to evaluate, and they didn’t quite convince me that they were careful enough to rule out the possibility that their biases caused them to overestimate the sophistication of Kanzi’s understanding.
The book is a bit long-winded about research that Savage-Rumbaugh did before working with Kanzi, and I was a bit disappointed that the book didn’t provide more of the anecdote about Kanzi that made the book worth reading. But those anecdotes convinced me that much more is going on than some authors such as Pinker had led me to believe. I still hope for better evidence that will help clarify how much bonobos can understand. But that will be hard, and I don’t know how it should be done.
Book Review: One of Us : Conjoined Twins and the Future of Normal by Alice Domurat Dreger
This book raises questions about peoples’ reactions to conjoined twins that may have important implications for many other unusual traits. It eloquently questions common assumptions about the desire to seem normal. It has led me to wonder about the extent to which healthcare is used to make people more normal at the cost of making them less healthy.
The book presents strong evidence that conjoined twins who remain conjoined are at least as well off as those who are separated, and some evidence that separations reduce the twins’ life expectancy, possibly by a significant amount.
Remarkably, of the twins who remained conjoined to adulthood, only one pair requested separation (they didn’t survive it), and among those whose refused separation are a number whose twin had just died (which meant that separation appeared to offer the only chance for the remaining twin to survive).
This doesn’t mean conjoined twins are better off that way (those who have been separated seem equally satisfied with their status), but it strongly suggests that decisions to perform separations are motivated by something other than concern over the twins wellbeing. And it suggests that people who claim things like “The proposed operation would give these children’s bodies the integrity that nature denied them” are imposing their values on others in ways which would be considered unacceptable if the victims had a little political power.
The book reports a fair number of statements by doctors (and occasionally parents) which suggest they consider a normal appearance worth risking health to achieve. The book also theorizes that having a normal child is an important enough part of parents’ identity to override their interest in their children’s’ wellbeing. The book also reports some indications that surgeons are biased toward surgery for unusual problems by the fame if can bring them.
Unfortunately, there isn’t as much evidence as there ought to be about the health effects of separations. The book claims (plausibly, but without supporting references), that “most medicine is not yet evidence-based”, with most surgical decisions being based on storytelling rather than careful studies.
The book raises some important questions about cases where doctors think the only way to save one twin is to kill the other. The author points out some strong similarities between the medical killing that is done in some of these cases and a hypothetical case where a heart is taken from a live singleton (i.e. not conjoined) donor to save another (which all would agree is wrong). One difference that she fails to consider is that if you consider the heart property, it looks like jointly owned property in one case and individually owned property in the other, and we should expect some differences to result from that (although doctors may still be more willing to kill one twin than that perspective would justify).
One interesting example that the book provides of medicalizing a difference is the attempt to get doctors to recognize Drapetomania, a “disease” which causes slaves to run away.
How widespread is the practice of impairing health to make people more normal? Surgeries on intersex children probably create modest health risks. Commonly used medicines to deal with ordinary colds suppress annoying symptoms that are tools the body uses to fight the disease, and tend to make the disease last longer (see the book Why We Get Sick : The New Science of Darwinian Medicine by Randolph Nesse). A child with 3 arms makes doctors want to chop it off, presumably at some risk.
Are these part of a wider pattern that would help explain why increased healthcare spending doesn’t seem to make us healthier?
On a loosely related note, I just ran across an unsettling complaint that Prozac seems to help too many people:
“There’s nobody nonsyndromal. You can give Prozac to anyone you want.”
Which is anathema to what medical science is supposed to be about. “We try to convince people there’s some specificity to what we do,” says Millman. “But this is embarrassing.”
Is this an indication that people don’t want drugs to do anything other than treat abnormal conditions (i.e. that they consider it wrong to improve on normal conditions)? Or does it reflect concern that there will be less demand for doctors’ skills if no diagnosis is relevant to the decision to use it? (This seems less likely given that they can still play a role in monitoring side effects).
I was inspired to read this book by a brief comment from Robin Zebrowski at the recent Human Enhancement Conference.
The conference on Human Enhancement Technologies and Human Rights this past weekend had many boring parts and a few interesting tidbits.
Many of the speakers were left-wing ideologues who seemed to be directing their speeches only to others from the same small set of left-wing academics. There were fewer libertarians at the conference than I expected, but still enough that it was strange how much of a disconnect there was between the ideology shown in the speeches and the ideology I knew from elsewhere that many people held but were being quiet about.
There was plenty of concern about whether increased control over one’s body would decrease diversity, but I heard little that enlightened me on that subject. There have clearly been many technologies that increased diversity, such as tattoos. There are some that have decreased diversity because there is a substantial consensus about what’s best (e.g. eyesight – it’s unclear why we should be concerned about a shortage of people who can’t see well enough to drive). Then there are a few traits such as degree of autism where there’s some uncertainty whether reduced diversity would be good. There are some pontificators (I didn’t hear anyone this focused at the conference) who think they know better than the masses what the right amount of diversity is, and that their opinions should be imposed on the masses. But the evidence for the pontificators’ expertise and the masses propensity to make mistakes is generally underwhelming, so I can’t find much reason to be as concerned about the effects of enhancement technology as I am about the desire to impose expert opinion on those who don’t want it.
Hank Greely pointed out that the letter of the law authorizes the FDA to regulate anything that could be considered a body enhancement, including clothing. So only the FDA’s interest in obeying the spirit of the law will deter them from regulating external enhancements.
One amusing report of unwanted side effects of an enhancement technology is the increase in sexually transmitted diseases in seniors following the introduction of Viagra.
Aubrey de Grey made an interesting argument that the most effective approach to convincing people to support a cure for aging is to persuade them that they are being logically inconsistent when they fail to do so. He has a point, but it’s weaker than he thinks. He gave several examples of problems that were allegedly solved by persuading society to be more logically consistent, but I generally doubt that’s what happened. One example was tolerance of homosexuality. I see few signs that logical arguments had much effect on that. I think the biggest change came from peer pressure, which became increasingly popular as gays became able to migrate to places where there were enough gays to safely start exerting peer pressure. Another factor was the shift away from the belief that the main purpose of sex should be reproduction. That initially happened due to changing circumstances (reduced reliance on children to support elderly parents). I’d say that has generally produced beliefs that are more inconsistent as people abandon the least convenient symptoms of the belief (e.g. contraception) but are much slower to abandon symptoms that are remote from their experience. I think similar theories could be made about some other examples he gave (slavery becoming more expensive to enforce when railroads made it easier for slaves to escape to a non-slave state).
Book Review: Race, Evolution, and Behavior: A Life History Perspective by J. Philippe Rushton
Rushton has a plausible theory that some human populations are more k-selected than others. He presents lots of marginal-quality evidence, but that’s no substitute for what he should be able to show if his theory is true.
Much of the book is devoted to evidence about IQs and brain sizes, but he fails to provide much of an argument for his belief that k-selected humans ought to have higher intelligence. It’s easy to imagine that it might work that way. But I can come up with an alternative based on the sexual selection theory in Geoffrey Miller’s book The Mating Mind that seems about as plausible: r-selected humans have more of their reproductive fitness determined by success at competition for mates (as opposed to k-selected humans for whom child support has a higher contribution to reproductive fitness). Since The Mating Mind presents a strong argument that human intelligence evolved largely due to such competition for mates, it is easy to imagine that r-selected humans had stronger selection for the kind of social intelligence needed to compete for mates. Note that this theory suggests the intelligence of k-selected humans might be easier to measure via standardized tests than that of r-selected humans.
Rushton’s analysis of the genetic aspects of IQ makes the usual mistake of failing to do much to control for the effects of motivation on IQ scores (see pages 249-251 of Judith Rich Harris’s book The Nurture Assumption for evidence that this matters for Rushton’s goals).
He also devotes a good deal of space to evidence such as crime rates where it’s very hard to distinguish genetic from cultural differences, and there’s no reason to think he has succeeded in controlling for culture here.
Rushton mentions a number of other traits that are more directly connected to degree of k-selection and less likely to be culturally biased. It’s disappointing that he provides little evidence of the quality of the data he uses. The twinning data seem most interesting to me, as the high twin rates of the supposedly r-selected population follow quite clearly from his theory, it’s hard to come up with alternative theories that would explain such twinning rates, and the numbers he gives look surprisingly different from random noise. But Rushton says so little about these data that I can’t have much confidence that they come from representative samples of people. (He failed to detect problems with the widely used UN data on African AIDS rates, which have recently been shown to have been strongly biased by poor sampling methods, so it’s easy to imagine that he uses equally flawed data for more obscure differences). (Aside – the book’s index is poor enough that page 214, which is where he lists most of his references for the twinning data, is not listed under the entry for twins/twinning).
Rushton occasionally produces some interesting but irrelevant tidbits, such as that Darwin “affirmed human unity” by ending the debate over whether all humanity had a common origin, or that there’s evidence that “introverts are more punctual, absent less often, and stay longer at a job”.
Edward M. Miller has a theory that is similar to but slightly more convincing than Rushton’s in a paper titled Paternal Provisioning versus Mate Seeking in Human Populations.
A recent report says that switching from a meat-heavy diet to a vegetarian diet is as valuable for reducing greenhouse-gas emissions as switching to driving the right car. And that if you eat fish, switching from large fish to things like sardines and anchovies makes a big difference.
I’m unsure whether to believe the magnitudes of the differences, but the general idea appears right.
I went to an interesting talk Wednesday by the CTO of D-Wave. He indicated that their quantum computing hardware is working well enough that their biggest problems are understanding how to use them and explaining that to potential customers.
This implies that they are much further advanced than the impressions I’ve gotten from sources unconnected with D-Wave suggest is plausible. D-Wave is being sufficiently secretive that I can’t put too much confidence in what they imply, but the degree of secrecy doesn’t seem unusual, and I don’t see any major reasons to doubt them other than the fact that they’re way ahead of what I gather many experts in the field think is possible. Steve Jurvetson’s investment in D-Wave several years ago is grounds for taking them fairly seriously.
The implications if this is real are concentrated in a few special applications (quantum computing sounds even more special purpose than I had previously realized), but for molecular modelling (and fields that depend on it such as drug discovery) it means some really important changes. Modelling that previously required enormous amounts of cpu power and expertise to produce imperfect approximations will apparently now require little more than the time and expertise needed to program a quantum computer (plus whatever exorbitant fees D-Wave charges).