I found an essay written by David Marr called Artificial Intelligence -- a personal view that I thought was fairly insightful. Marr first discusses how information processing problems are generally solved:

The solution to an information processing problem divides naturally into two parts. In the first, the underlying nature of a particular computation is characterized, and its basis in the physical world is understood. One can think of this part as an abstract formulation of what is being computed and why, and I shall refer to it as the "theory" of a computation. The second part consists of particular algorithms for implementing a computation, and so it specifies how.

This is reminiscent of Marr's three levels of analysis.

Next, Marr draws a distinction between a Type 1 information processing problem and a Type 2 problem. A Type 1 problem has a solution that naturally divides along lines mentioned above: first one can formulate the computational theory behind it, and then one devises an algorithm to implement the computation. Marr proposes, however, that there is a class of problems that doesn't fit this description:

The fly in the ointment is that while many problems of biological information processing have a Type 1 theory, there is no reason why they should all have. This can happen when a problem is solved by the simultaneous action of a considerable number of processes, whose interaction is its own simplest description, and I shall refer to such a situation as a Type 2 theory. One promising candidate for a Type 2 theory is the problem of predicting how a protein will fold. A large number of influences act on a large polypeptide chain as it flaps and flails in a medium. At each moment only a few of the possible interactions will be important, but the importance of those few is decisive. Attempts to construct a simplified theory must ignore some interactions; but if most interactions are crucial at some stage during the folding, a simplified theory will prove inadequate.

More discussion about Type 1 and Type 2 problems follows, but I'm not going to summarize it. It well-worth reading, however. I did think this critique of the GOFAI program was pretty sharp for having been formulated in 1977:

For very advanced problems like story-understanding, current research is often purely exploratory. That is to say, in these areas our knowledge is so poor that we cannot even begin to formulate the appropriate questions, let alone solve them

...

Most of the history of A.I. (now fully 16 years old) has consisted of exploratory studies. Some of the best-known are Slagle's [24] symbolic integration program, Weizenbaum's [30] Eliza program, Evans" [4] analogy program, Raphaers [19] SIR, Quillian's [18] semantic nets and Winograd's [32] Shrdlu. All of these programs have (in retrospect) the property that they are either too simple to be interesting Type 1 theories, or very complex yet perform too poorly to be taken seriously as a Type 2 theory

... 

And yet many things have been learnt from these experiences--mostly negative things (the first 20 obvious ideas about how intelligence might work are too simple or wrong)... The mistakes made in the field lay not in having carried out such studies--they formed an essential part of its development--but consisted mainly in failures of judgement about their value, since it is now clear that few of the early studies themselves formulated any solvable problems.

If we accept this taxonomy, then where does Friendliness fit in? My hunch is that it's a Type 2 problem. If this is so, what Type 1 problems can be focused on in the present?

I originally titled this post "The Less Wrong wiki is wrong about group selection", because it seemed wildly overconfident about its assertion that group selection is nonsense. The wiki entry on "group selection" currently reads:

People who are unfamiliar with evolutionary theory sometimes propose that a feature of the organism is there for the good of the group - for example, that human religion is an adaptation to make human groups more cohesive, since religious groups outfight nonreligious groups.

Postulating group selection is guaranteed to make professional evolutionary biologists roll up their eyes and sigh.

However, it appears that the real problem is not that the wiki is overconfident (that's a problem, but it's only a symptom of the next problem) but that the traditional dogma on the viability of group selection is wrong, or at least overconfident. I make this assertion after stumbling across a paper by Martin Nowak, Corina Tarnita, and E. O. Wilson titled "The evolution of eusociality", which appeared in Nature in August of this year. I found a PDF of this paper through Google scholar, click here. A blog entry discussing the paper can be found here (bias alert: it is written by a postdoc working in Martin Nowak's Evolutionary Dynamics program at Harvard).

Here's some quotes (bolding is mine):

It has further turned out that selection forces exist in groups that diminish the advantage of close collateral kinship. They include the favouring of raised genetic variability by colony-level selection in the ants Pogonomyrmex occidentalis and Acromyrmex echinatior—due, at least in the latter, to disease resistance. The contribution of genetic diversity to disease resistance at the colony level has moreover been established definitively in honeybees. Countervailing forces also include variability in predisposition to worker sub-castes in Pogonomyrmex badius, which may sharpen division of labour and improve colony fitness—although that hypothesis is yet to be tested. Further, an increase in stability of nest temperature with genetic diversity has been found within nests of honeybees and Formica ants. Other selection forces working against the binding role of close pedigree kinship are the disruptive impact of nepotism within colonies, and the overall negative effects associated with inbreeding. Most of these countervailing forces act through group selection or, for eusocial insects in particular, through between-colony selection.

Yet, considering its position for four decades as the dominant paradigm in the theoretical study of eusociality, the production of inclusive fitness theory must be considered meagre. During the same period, in contrast, empirical research on eusocial organisms has flourished, revealing the rich details of caste, communication, colony life cycles, and other phenomena at both the individual- and colony-selection levels. In some cases social behaviour has been causally linked through all the levels of biological organization from molecule to ecosystem. Almost none of this progress has been stimulated or advanced by inclusive fitness theory, which has evolved into an abstract enterprise largely on its own

...

The question arises: if we have a theory that works for all cases (standard natural selection theory) and a theory that works only for a small subset of cases (inclusive fitness theory), and if for this subset the two theories lead to identical conditions, then why not stay with the general theory? The question is pressing, because inclusive fitness theory is provably correct only for a small (non-generic) subset of evolutionary models, but the intuition it provides is mistakenly embraced as generally correct.

Check out the paper for more details. Also look at the Supplementary Information if you have access to it. They perform an evolutionary game theoretic analysis, which I am still reading.

Apparently this theory is not that new. In this 2007 paper by David Sloan Wilson and E. O. Wilson, they argue (I'm just pasting the abstract):

The current foundation of sociobiology is based upon the rejection of group selection in the 1960s and the acceptance thereafter of alternative theories to explain the evolution of cooperative and altruistic behaviors. These events need to be reconsidered in the light of subsequent research. Group selection has become both theoretically plausible and empirically well supported. Moreover, the so-called alternative theories include the logic of multilevel selection within their own frameworks. We review the history and conceptual basis of sociobiology to show why a new consensus regarding group selection is needed and how multilevel selection theory can provide a more solid foundation for sociobiology in the future.

From the other camp, this seems to be a fairly highly-cited paper from 2008. They concluded:

(a) the arguments about group selection are only continued by a limited number of theoreticians, on the basis of simplified models that can be difficult to apply to real organisms (see Error 3); (b) theoretical models which make testable predictions tend to be made with kin selection theory (Tables 1 and 2); (c) empirical biologists interested in social evolution measure the kin selection coefficient of relatedness rather than the corresponding group selection parameters (Queller & Goodnight, 1989). It is best to think of group selection as a potentially useful, albeit informal, way of conceptualizing some issues, rather than a general evolutionary approach in its own right.

I know (as of yet) very little biology, so I leave the conclusion for readers to discuss. Does anyone have detailed knowledge of the issues here?

This recent discussion post by SarahC got me thinking about how one can rationally manage research. It seems like software might be useful here, but I don't know how exactly the software should work. I'm intrigued by mind mapping software, but it's possible that all that structure is unnecessary and you could do quite well with less. For instance, I'm considering trying a system of timestamped notes which are managed by a tagging system. If the tagging was done thoroughly enough, you could filter through all the posts sharing a cluster of tags and fairly easily get access to every idea you've recorded on a certain topic.

The only problem is, I think I'd want even more specialized software than that. I'd want to integrate my notes with some form of bibliography management, and at least a to-do list. And I can imagine more, for example perhaps there could be a "sticky note" capability where I could pin up and move around things that I either want to remember or that will help me with my research, like an inspirational quote if I'm not feeling motivated to do research, or the Litany of Tarski or some other rationality technique if I really need to remember to use it.

I'm not sure if these ideas are all sound, but a basic requirement for the software would be to document the structure of your research so that it can be analyzed for effectiveness.

I know there are some people on Less Wrong who do research, so I suppose I should defer to the experts here: how do you organize your research? What methodologies and tools do you use? Why?