Tag Archives: Brains

General Evolvable Brains

Human brains today can do a remarkably wide range of tasks. Our mental capacities seem much more “general” than that of all the artificial systems we’ve ever created. Those who are trying to improve such systems have long wondered: what is the secret of human general intelligence? In this post I want to consider we can learn about this from fact that the brain evolved. How would an evolved brain be general?

A key problem faced by single-celled organisms is how to make all of their materials and processes out of the available sources of energy and materials. They do this mostly via metabolism, which is mostly a set of enzymes that encourage particular reactions converting some materials into others. Together with cell-wall containers to keep those enzymes close to each other. Some organisms are more general than others, in that they can do this key task in a wider range of environments.

Most single-celled organisms use an especially evolvable metabolism design space. That is, their basic overall metabolism system seems especially well-suited to finding innovations and adaptations mostly via blind random search, in a way that avoids getting stuck in local maxima. As I explained in a recent post, natural metabolisms are evolvable in part because they have genotypes that are highly redundant relative to phenotypes: many sets of enzymes can map any given set of inputs into any given set of outputs. And this redundancy requires a substantial overcapacity; the metabolism needs to contain many more enzymes than are strictly needed to create any given mapping.

The main way that such organisms are general is that they have metabolisms with a large library of enzymes. Not just a large library of genes that could code for enzymes if turned on, but an actual large set of enzymes usually created. They make many more enzymes than they actually need in each particular environment where they find themselves. This comes at a great cost; making all those enzymes and driving their reactions doesn’t come cheap.

A relevant analogous toy problem is that of logic gates mapping input signals onto output signals:

[In] a computer logic gate toy problem, … there are four input lines, four output lines, and sixteen binary logic gates between. The genotype specifies the type of each gate and the set of wires connecting all these things, while the phenotype is the mapping between input and output gates. … All mappings between four inputs and four outputs can be produced using only four internal gates; sixteen gates is a factor of four more than needed. But in the case of four gates the set of genotypes is not big enough compared to the set of phenotypes to allow easy evolution. For [evolvable] innovation, sixteen gates is enough, but four gates is not. (more)

Note that evolution doesn’t always use such highly evolvable design spaces. For example, our skeletal structure doesn’t have lots of extra bones sitting around ready to be swapped into new roles in new environments. In such cases, evolution chose not to pay large extra costs for generality and evolvability, because the environment seemed predictable enough to stay close to a good enough design. As a result, innovation and adaptation of skeletal structure is much slower and more painful, and could fail badly in novel enough environments.

Now let’s consider brains. It may be that for some tasks, evolution found such an effective structure that it chose to commit to that structure, betting that its solution was stable and reliable enough across future environments to let it forgoe the big extra costs of more general and evolvable designs. But if we are looking to explain a surprising generality, flexibility, and rapid evolution in human brains, it makes sense to consider the possibility that human brain design took a different path, one more like that of single-celled metabolism.

That is, one straightforward way to design a general evolvable brain is to use a extra large toolbox of mental modules that can be connected together in many different ways. While each tool might be a carefully constructed jewel, the whole set of tools would have less of an overall structure. Like a pile of logical gates that can be connected many ways, or metabolism sub-networks that can be connected together into many networks. In this case, the secret to general evolvable intelligence would be less in the particular tools and more in having an extra large set of tools, plus some simple general ways to search in the space of tool combinations. A tool set so large that the brain can do most tasks in a great many different ways.

Much of the search for brain innovations and adaptations would then be a search in the space of ways to connect these tools together. Some aspects of this search could happen over evolutionary timescales, some could happen over the lifetime of particular brains, and some could happen on the timescale of cultural evolution, once that got started.

On the timescale of an individual brain lifetime, a search for tool combinations would start with brains that are highly connected, and then prune long term connections as particular desired paths between tools are found. As one learned how to do a task better, one would activate smaller brain volumes. When some brain parts were damaged, brains would often be able to find other combinations of the remaining tools to achieve similar functions. Even losing a whole half of a brain might not greatly reduce performance. And these are all in fact common patterns for human brains.

Yes, something important happened early in human history. Some key event changed the growth rate of human abilities, though not immediate ability levels, and it did this without much changing brain modules and structures, which remain quite close to those of other primates. Plausibly, we had finally collected enough hard-wired tools, or refined them well enough, to let us start to reliably copy each others’ behaviors. And that allowed cultural evolution, a much-faster-than-evolutionary search in the space of practices. Such practices included choices of which combinations of brain modules to activate in which contexts.

What can this view say about the future of brains? On ems, it suggests that human brains have a lot of extra capacity. We can probably go far in taking an em that can do a job task and throwing away brain modules not needed for that task. At some point cutting hurts performance too much, but for many job tasks you might cut 50% to 90% before then.

Regarding other artificial intelligence, it suggests that if we still have a lot to learn via substantially random search, with no grand theory to integrate it all, then we’ll have to focus on collecting more better tools. Machines would gradually get better as we collect more tools. There may be thresholds where you need enough tools to do a certain jobs well, and while most tools would make only small contributions, perhaps there are a few bigger tools that matter more. So key thresholds would come from the existence of key jobs, and from the lumpiness of tools. We should expect progress to be relatively continuous, except perhaps due to the discovery of especially  lumpy tools, or to passing thresholds that enable key jobs to be done.

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Personality Is Overt

If the human mind is split to parts that manage overt appearances, and parts that manage covert strategies, which parts do you think more control our personalities? Yup, personalities are closer to overt appearances:

By using composite images rendered from three dimensional (3D) scans of women scoring high and low on health and personality dimensions, we aimed to examine the separate contributions of facial shape, skin texture and viewing angle to the detection of these traits, while controlling for crucial posture variables. After controlling for such cues, participants were able to identify Agreeableness, Neuroticism, and Physical Health. … Information allowing accurate personality identification is largely lateralized to the right side of the face. (more)

Chimpanzees, other primates, and humans produce asymmetrical facial expressions with greater [emotional] expression on the left side of the face (right hemisphere of the brain). (more)

In most animals, left brains tend to manage and initiate actions within the current mode, while right brains watch in the background for patterns and reasons to veto current actions and switch modes. In humans, it seems the current-action-sequencer brain half was recruited to focus more on managing overt rule-following language, decisions, and actions, ready to explain away any apparent rule-violations. The less-introspectively-accessible pattern-recognizing background-watcher brain half, in contrast, was apparently recruited to focus on harder-to-testify-on-and-so-more-easily-covert meaning, opinion, and communication, including art and music. (more)

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Whence Better Brains?

The cover story of the July Scientific American is on brain physics. It persuades me that raw brain hardware was more important than I’d thought in our history.  Here is my current best guess on brain history.

Across diverse species we see strong convergence in brain organization, especially conditional on brain size. Species differ more in their brain hardware components, and their energy sources. For example, primates have innovative cell designs allowing higher neuron density. Given access to such cells, primates could afford to evolve bigger brains, and then bigger pair-bond-based social groups.

Humans found a way to use big primate brains to support big-group far-traveling long-life versions which could access richer energy sources, which in turn supported large energy-hungry brains. Humans found a way to use those huge old social brains to support robust accumulation of culture, which is our main advantage over other primates. This was probably supported by only minor changes in brain organization.

While the brains of smarter humans today may use a better set of long term connections, probably most of their advantage comes from using more energy-intensive brain hardware. So it probably wasn’t until our recent cheap energy era that high IQ humans gained large advantages. The tendency 0f smarter humans to choose lower fertility lowers their advantage today.

Many quotes from that article: Continue reading "Whence Better Brains?" »

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Two-Faced Brains

Although human language allowed egalitarian rules whose uniform enforcement would have greatly reduced the advantages to big-brain conniving, humans had the biggest brains of all to unequally evade such rules. (more)

As with most lying or self-deception, homo hypocritus faces a serious implementation problem: how to keep the lies it tells separate from the “real” beliefs on which it acts. Since brains tend to be liberal with interconnections, there is a real risk of cross-talk between contradictory sets of opinions; lies may infect beliefs, and beliefs may infect lies.

I’ve previously discussed one solution: have the different sets of opinions apply to different topics. For example, hold socially-acceptable opinions on far topics, where the personal consequences of actions tend to be smaller, and keep more realistic opinions on near topics, where such consequences tend to be larger. Yes there’s a risk others may notice that you change opinions without good reason as items move from near to far or far to near, but that may be a relatively small price to pay.

A different solution is to have two distinct processing centers, each highly-connected internally, but with only modest between-center connections. One center would manage a coherent set of lies, while the other managed a coherent set of true beliefs. And in fact real brains have exactly this architecture! Left and right brains are highly connected internally, but only modestly connected to each other. Does the left brain manage a coherent set of overt opinions, while the right brain manages a coherent set of covert opinions? Consider:

  1. In all vertebrates left brains tend to control routine behavior (e.g. feeding) while right brains tend to respond to unusual events (e.g. fight/flight).
  2. Left brains tend to initiate actions, via positive feelings, while right brains tend to inhibit actions, via negative feelings.
  3. Compared to other primates, left vs. right human brains differ a lot more in function.
  4. The left human brain manages language’s literal quotably-overt syntax, vocabulary, and semantics, while the right brain handles language’s less-socially-verifiable tone, accent, metaphor, allegory, and ambiguity.
  5. Split brain patients show that left brains are adept at making up respectable explanations for arbitrary right brain behavior.
  6. Right brains tend to be used more in crafting lies, and they can read subtle emotion clues better.
  7. Left brain damage tends to distort behavior in more obvious and understandable ways.
  8. Left brains emphasize decision-making, fact retrieval, numbers, and careful sequenced acts like throwing, while right brains emphasize art, music, spatial manipulation, and recognizing of shapes, patterns, and faces.

It seems that in most animals, left brains tend to manage and initiate actions within the current mode, while right brains watch in the background for patterns and reasons to veto current actions and switch modes. In humans, it seems the current-action-sequencer brain half was recruited to focus more on managing overt rule-following language, decisions, and actions, ready to explain away any apparent rule-violations. The less-introspectively-accessible pattern-recognizing background-watcher brain half, in contrast, was apparently recruited to focus on harder-to-testify-on-and-so-more-easily-covert meaning, opinion, and communication, including art and music.

I’m not saying that overt vs. covert human beliefs map exactly to human left vs. right brains, any more than socially-useful vs. action-practical beliefs map exactly onto far vs. near beliefs. I’m just suggesting that human brain design took pre-existing animal brain structures, such as near vs. far modes and left vs. right brain splits, and recruited them to the task of managing the uniquely human task of hypocrisy: simultaneously espousing and evading rules. In particular, the left-right brain split become an important tool for minimizing undesirable leakage between the overt rule-following images we present to others, and the cover rule-evading actions and communication which better achieve our real ends.

More quotes:

The left hemisphere is specialized not only for the actual production of speech sounds but also for the imposition of syntactic structure on speech and for much of what is called semantics – comprehension of meaning.  The right hemisphere , on the other hand, doesn’t govern spoken words but seems to be concerned with more subtle aspects of language such as nuances of metaphor, allegory and ambiguity. (Ramachandran, quoted in TMHH p56)

No other [vertebrate] species consistently prefers the same hand for certain skilled actions. … The human brain is distinguished from the brains of the great apes by an extraordinary extent of lateralization of function. (more)

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