Ideally, I'd like to save the world. One way to do that involves contributing academic research, which raises the question of what's the most effective way of doing that.

The traditional wisdom says if you want to do research, you should get a job in a university. But for the most part the system seems to be set up so that you first spend a long time working for someone else and research their ideas, after which you can lead your own group, but then most of your time will be spent on applying for grants and other administrative trivia rather than actually researching the interesting stuff. Also, in Finland at least, all professors need to also spend time doing teaching, so that's another time sink.

I suspect I would have more time to actually dedicate on research, and I could get doing it quicker, if I took a part-time job and did the research in my spare time. E.g. the recommended rates for a freelance journalist in Finland would allow me to spend a week each month doing work and three weeks doing research, of course assuming that I can pull off the freelance journalism part.

What (dis)advantages does this have compared to the traditional model?

Some advantages:

• Can spend more time on actual research.
• A lot more freedom with regard to what kind of research one can pursue.
• Cleaner mental separation between money-earning job and research time (less frustration about "I could be doing research now, instead of spending time on this stupid administrative thing").
• Easier to take time off from research if feeling stressed out.

Some disadvantages:

• Harder to network effectively.
• Need to get around journal paywalls somehow.
• Journals might be biased against freelance researchers.
• Easier to take time off from research if feeling lazy.
• Harder to combat akrasia.
• It might actually be better to spend some time doing research under others before doing it on your own.

EDIT: Note that while I certainly do appreciate comments specific to my situation, I posted this over at LW and not Discussion because I was hoping the discussion would also be useful for others who might be considering an academic path. So feel free to also provide commentary that's US-specific, say.

What are the plausible scientific limits of molecular nanotechnology?

Richard Jones, author of Soft Machines has written an interesting critique of the room-temperature molecular nanomachinery propounded by Drexler:

Rupturing The Nanotech Rapture

If biology can produce a sophisticated nanotechnology based on soft materials like proteins and lipids, singularitarian thinking goes, then how much more powerful our synthetic nanotechnology would be if we could use strong, stiff materials, like diamond. And if biology can produce working motors and assemblers using just the random selections of Darwinian evolution, how much more powerful the devices could be if they were rationally designed using all the insights we've learned from macroscopic engineering.

But that reasoning fails to take into account the physical environment in which cell biology takes place, which has nothing in common with the macroscopic world of bridges, engines, and transmissions. In the domain of the cell, water behaves like thick molasses, not the free-flowing liquid that we are familiar with. This is a world dominated by the fluctuations of constant Brownian motion, in which components are ceaselessly bombarded by fast-moving water molecules and flex and stretch randomly. The van der Waals force, which attracts molecules to one another, dominates, causing things in close proximity to stick together. Clingiest of all are protein molecules, whose stickiness underlies a number of undesirable phenomena, such as the rejection of medical implants. What's to protect a nanobot assailed by particles glomming onto its surface and clogging up its gears?

The watery nanoscale environment of cell biology seems so hostile to engineering that the fact that biology works at all is almost hard to believe. But biology does work--and very well at that. The lack of rigidity, excessive stickiness, and constant random motion may seem like huge obstacles to be worked around, but biology is aided by its own design principles, which have evolved over billions of years to exploit those characteristics. That brutal combination of strong surface forces and random Brownian motion in fact propels the self-assembly of sophisticated structures, such as the sculpting of intricately folded protein molecules. The cellular environment that at first seems annoying--filled with squishy objects and the chaotic banging around of particles--is essential in the operation of molecular motors, where a change in a protein molecule's shape provides the power stroke to convert chemical energy to mechanical energy.

In the end, rather than ratifying the ”hard” nanomachine paradigm, cellular biology casts doubt on it. But even if that mechanical-engineering approach were to work in the body, there are several issues that, in my view, have been seriously underestimated by its proponents.

...

Put all these complications together and what they suggest, to me, is that the range of environments in which rigid nanomachines could operate, if they operate at all, would be quite limited. If, for example, such devices can function only at low temperatures and in a vacuum, their impact and economic importance would be virtually nil.

The entire article is definitely worth a read. Jones advocates more attention to "soft" nanotech, which is nanomachinery with similar design principles to biology -- the biomimetic approach -- as the most plausible means of making progress in nanotech.

As far as near-term room-temperature innovations, he seems to make a compelling case. However the claim that "If ... such devices can function only at low temperatures and in a vacuum, their impact and economic importance would be virtually nil" strikes me as questionable. It seems to me that atomic-precision nanotech could be used to create hard vacuums and more perfectly reflective surfaces, and hence bring the costs of cryogenics down considerably. Desktop factories using these conditions could still be feasible.

Furthermore, it bears mentioning that cryonics patients could still benefit from molecular machinery subject to such limitations, even if the machinery is not functional at anything remotely close to human body temperature. The necessity of a complete cellular-level rebuild is not a good excuse not to cryopreserve. As long as this kind of rebuild technology is physically plausible, there arguably remains an ethical imperative to cryopreserve patients facing the imminent prospect of decay.

In fact, this proposed limitation could hint at an alternative use for cryosuspension that is entirely separate from its present role as an ambulance to the future. It could perhaps turn out that there are forms of cellular surgery and repair which are only feasible at those temperatures, which are nonetheless necessary to combat aging and its complications. The people of the future might actually need to undergo routine periods of cryogenic nanosurgery in order to achieve robust rejuvenation. This would be a more pleasant prospect than cryonics in that it would be a proven technology at that point; and most likely the vitrification process could be improved sufficiently via soft nanotech to reduce the damage from cooling itself significantly.

(This is the second post in a short sequence discussing evidence and arguments presented by Christopher Ryan and Cacilda Jethá's Sex at Dawn, inspired by the spirit of Kaj_Sotala's recent discussion of What Intelligence Tests Miss. It covers Part II: Lust in Paradise and Part III: The Way We Weren't.)

Forager anthropology is a discipline that is easy to abuse. It relies on unreliable first-hand observations of easily misunderstood cultures that are frequently influenced by the presence of modern observers. These cultures are often exterminated or assimilated within decades of their discovery, making it difficult to confirm controversial claims and discoveries. But modern-day foraging societies are the most direct source of evidence we have about our pre-agricultural ancestors; in many ways, they are agriculture's control group, living in conditions substantially similar to the ones under which our species evolved. The standard narrative of human sexual evolution ignores or manipulates the findings of forager anthropology to support its claims, and this is no doubt responsible for much of its confused support.

Steven Pinker is one of the most prominent and well-respected advocates of the standard narrative, both on Less Wrong and elsewhere. Eliezer has referenced him as an authority on evolutionary psychology. One commenter on the first post in this series claimed that Pinker is "the only mainstream academic I'm aware of who visibly demonstrates the full suite of traditional rationalist virtues in essentially all of his writing." Another cited Pinker's claim that 20-60% of hunter-gatherer males were victims of lethal human violence ("murdered") as justification for a Malthusian view of human nature. 

That 20-60% number comes from a claim about war casualties in a 2007 TED talk Pinker gave on "the myth of violence", for which he drew upon several important findings in forager anthropology. (The talk is based on an argument presented in the third chapter of The Blank Slate; there is a text version of the talk available, but it omits the material on forager anthropology that Ryan and Jethá critique.)

At 2:45 in the video Pinker displays a slide which reads

Until 10,000 years ago, humans lived as hunter-gatherers, without permanent settlements or government.

He also points out that modern hunter-gatherers are our best evidence for drawing conclusions about those prehistoric hunter-gatherers; in both these statements he is in accordance with nearly universal historical, anthropological, and archaeological opinion. Pinker's next slide is a chart from The Blank Slate, originally based on the research of Lawrence Keeley. Sort of. It is labeled as "the percentage of male deaths due to warfare," with bars for eight hunter-gatherer societies that range from approximately 15-60%. The problem is that of these eight cultures, zero are migratory hunter-gatherers.

(This post is the beginning of a short sequence discussing evidence and arguments presented by Christopher Ryan and Cacilda Jethá's Sex at Dawn, inspired by the spirit of Kaj_Sotala's recent discussion of What Intelligence Tests Miss. It covers Part I: On the Origin of the Specious.)

Sex at Dawn: The Prehistoric Origins of Modern Sexuality was first brought to my attention by a rhapsodic mention in Dan Savage's advice column, and while it seemed quite relevant to my interests I am generally very skeptical of claims based on evolutionary psychology. I did eventually decide to pick up the book, primarily so that I could raid its bibliography for material for an upcoming post on jealousy management, and secondarily to test my vulnerability to confirmation bias. I succeeded in the first and failed in the second: Sex at Dawn is by leaps and bounds the best evolutionary psychology book I've read, largely because it provides copious evidence for its claims.¹ I mention the strength of my opinion as a disclaimer of sorts, so that careful readers may take the appropriate precautions.

The book's first section focuses on the current generally accepted explanation for human sexual evolution, which the authors call "the standard narrative." It's an explanation that should be quite familiar to regular LessWrong readers: men are attracted to fertile-appearing women and try to prevent them from having sex with other men so as to confirm the paternity of their offspring; women are attracted to men who seem like they will be good providers for their children and try to prevent them from forming intimate bonds with other women so as to maintain access to their resources.

Summary: The significance of the Compression Rate Method (CRM) is that it justifies a form of empirical inquiry into aspects of reality that have previously resisted systematic interrogation. Some examples of potential investigations are described. A key hypothesis is discussed, and the link between empirical science and lossless data compression is emphasized.

In my previous post, the protagonist Sophie developed a modified version of the scientific method. It consists of the following steps:

1. Obtain a large database T related to a phenomenon of interest.
2. Develop a theory of the phenomenon, and instantiate the theory as a compression program.
3. Test the theory by invoking the compressor on T and measuring the net codelength achieved (encoded data plus length of compressor).
4. Given two rival theories of the phenomenon, prefer the one that achieves a shorter net codelength.

This modified version preserves two of the essential attributes of the traditional method. First, it employs theoretical speculation, but guides and constrains that speculation using empirical observations. Second, it permits Strong Inference by allowing the field to make decisive comparisons between rival theories.

The key difference between the CRM and the traditional method is that the former does not depend on the use of controlled experiments. For that reason, it justifies inquiries into aspects of empirical reality that have never before been systematically interrogated. The kind of scientific theories that are tested by the CRM depend on the type of measurements in the database target T. If T contains measurements related to physical experiments, the theories of physics will be necessary to compress it. Other types of data lead to other types of science. Consider the following examples:

This is a report from a LessWrong perspective, on the 30th Soar workshop. Soar is a cognitive architecture that has been in continuous development for nearly 30 years, and is in a direct line of descent from some of the earliest AI research (Simon's LT and GPS). Soar is interesting to LessWrong readers for two reasons:

1. Soar is a cognitive science theory, and has had some success at modeling human reasoning - this is relevant to the central theme of LessWrong, improving human rationality.
2. Soar is an AGI research project - this is relevant to the AGI risks sub-theme of LessWrong.

The paper "Strong Inference" by John R. Platt is a meta-analysis of scientific methodology published in Science in 1964. It starts off with a wonderfully aggressive claim:

Scientists these days tend to keep up a polite fiction that all science is equal.

The paper starts out by observing that some scientific fields progress much more rapidly than others. Why should this be?