In Honor Of

We bought the sky, the greatest ticket the universe had to offer. 100,000 of the best and brightest Terra had to offer. Brave pioneers who sacrificed everything for a chance to make it on new planet, free from the troubles of home. They said we were fools; there was no way to build something that big, that the cryosystems would never work, that our ship would break. They said we were traitors; Earth needed our skills, the resources that went into our ship came out of the mouths of the starving. But we were heroes, out on the grand question for evolution. Some of us died before the work was completed, their children carried on. When the time came, we took the shuttles to geosynchronous orbit, started the fusion Orion/pulse drive, sealed up the cyrochambers, and slept. We dreamed of green fields and blue skies.

A stranger opened the cyrochamber door. “Welcome to Eredani Prime. Please present your papers for inspection?” Not an alien, not a pioneer, just the children of those who had take waited for the technology of interstellar colonization to become accessible to the masses. They had brought everything we hated about home with them. We closed the cyrochamber, turned our ship towards the outer darkness, and engaged the main drive.

Fuck physics, and fuck FTL.

The Rightful Place of Science Policy

This previous post on the goals of neuroscience (and the ensuing flamewar) got me thinking. What is it that I am trying to do?

I'll freely admit it, I am not a scientist. I don't generate testable hypothesis, knowledge about the natural universe, or anythng that can be nailed down with a reasonable degree of certainty. Why then should I be trusted (and publicly funded?). As science policy expert, I believe that I provide a unique skillset and viewpoint for decision-making in the 21st century.

Science policy has two research thrusts: guiding the development of the natural sciences through funding mechanism and other incentives, and understanding and responding to the effects of science and technology on our society. Science does not exist in a vacuum, every it of knowledge or technological artifact has associated social processes, what Sheila Jasanoff calls 'co-production.' The ultimate goal of science policy is to combine the two research thrusts into a means of steering society by favoring certain research paths. Though this seems at anti-democratic, elitist, or even Orwellian, it is the state of the world. We are always making choices vis a vis science policy, even relinquishment or defunding counts as a choice. The work of the science policy professional is to make good choices, in a full understanding of the technosocial context in which they are made, and as broad of public participation as possible.

The origins of science policy as a discipline can be traced back to WW2, where America rapidly mobilized its scientists and engineers to produce war-winning weapons: the proximity fuse, operations research, and the atomic bomb. Vannevar Bush's Office of Scientific Research and Development organized thousands of scientists to turn knowledge towards military ends, but despite its spectacular success, it could only be tempory. Bush ruled in a climate of secrecy and military necessity which justified any decision. The war forced people to work together, and Bush was a managerial genius. The conditions of the OSRD could not be replicated indefinitely, and so Bush moved to create a civilian successor to the OSRD for basic research, the National Science Foundation, and pressed for more scientific expert participation at the highest echelons of government.

Within the decade, spurred on by sputnik terror, Federal science funding had become a permanent part of the political landscape. Dozens of agencies, from the Department of Defense to the National Institutes of Health, funded basic and applied science. Corporate labs served as epicenters of invention in Silicon Valley and along Route 128. But while this era brought forth wonders, science remained a servant only of those wealthy enough to directly support it; the military and high tech. The vast majority of America's scientific output languished in academia. In 1980, Congress fundamentally reorganized science policy with Bayh-Dole Act, which allowed patents for the products of federally funded research. Now, scientists did not need to choose between the public and private sectors, their work could be universally applied. The Federal government took on the role of a basic driver of innovation.

At the same time, citizens became more aware of the role of science and technology in constituting their world. The environmental and anti-nuclear movements exposed people to the hazards of modern technology, while making science itself an object of contention. Neo-luddite responses to computerization, suburbanization, and militarization further mobilized ordinary people and academics to seriously consider the state of science, technology, and society.

We stand now poised at the edge of a great transformation. Convergent technologies in nano, biological, information, and cognitive realms propose to alter and redefine human beings. A combination of population growth and industrialization has placed the planetary ecosystem and resource supply under near critical stress. In this delicate scenario, we can no longer trust to the blind forces of the market to make the best decisions, or leave it entirely in the hermetic hands of a self-selecting technological elite.

Science policy is therefore about making good decisions. It is about a set of intellectual tools that allow you to analyze issues and expose critical elements, consequences, and constituencies in political decisions involving human beings and scientific knowledge. I do not believe that science policy experts should have a preeminent role at the table, that's just as bad as turning decision-making over to politicians, or bankers, or generals, or engineers. Instead, we try and get as many people at the table as possible, as many views to ensure that science is working towards socially desirable ends, that people are not being unjustly excluded, and that there is a full and fair engagement with the future.

The deterministic loop between advances in science, deployment of new technologies, changes in society, and new socially supported science to advance certain ends is an exaggeration. It is impossible to predict the future. But we can give people the tools to make the best decisions they can.

Paper Review : Neural Plasticity and Consciousness

For neuroscientists, treating "The Hard Problem of Consciousness" outside of bar-room speculation is a risky career move. This is why we have true doctors of philosophy, and why the philosophy paper "Neural Plasticity and Consciousness" by Susan Hurley and Alva Noë is a good thing. Hurley and Noë's thesis relates to some recent activity on WeAlone [1,2, maybe 3] , so I will attempt to summarize the article in a language that makes most sense to me.

First Hurley and Noë note that the "hard problem of consciousness" is equivalent to what they call an "absolute gap", i.e. "why should we assume that neural activity is solely responsible for conscious perception at all ?". My interpretation is that Hurley and Noë say "we can't, this is a leap of faith", and for the purposes of the paper accept as an axiom that neural activity corresponds to perception. The meat of the paper then, discusses why some neural activity should take on a particular quality, like seeing, and other neural activity should take on a distinct quality, like hearing.

Lately, I've been throwing around the term "neural topology" and "manifold structure" in an embarrassingly non-rigorous manner. I'd like to say "the topology of qualia acquires the topology of stimuli via learning of the intrinsic statistical structure of the stimuli, and in a sense, the stimulus stimulus model constitutes the nature of qualia", but this is vague. Hurley and Noë express, I believe, a similar sentiment clearly and without abusing terms from mathematics :

It is argued that the different characteristics of input activity from specific sources (visual vs. auditory) generate not just representational structure specific to that source but also source-specific sensory and perceptual qualities.

That is to say, when the brain learns the topology of stimuli ( possibly in union with the topology of motor outputs as they modify stimuli ), the brain acquires the qualia corresponding to said stimuli.

Earlier we talked about the possibility of defining an algebraic structure representing the shape of information coded in the brain. The take-away point was that it might be possible to rigorously say "these two areas have effectively the same abstract structure, since you can relate them by some structure preserving relationship". The Hurley and Noë paper provides anecdotes which suggest that, when two physically distinct neural circuits have the same abstract structure (topology), then the subjective experience (qualia) are also the same. Specifically, they discuss experiments in which blind patients were able to acquire visual qualia through a tactile stimulation device that translates camera images into stimulation of the skin.

After a period of adaptation (as short as a few minutes), subjects report perceptual experiences that are distinctively non-tactile and quasi-visual. … However, Bach-y-Rita emphasizes that the transition to quasi-visual perception depends on the subject’s exercising active control of the camera. … Perceivers can acquire and use practical knowledge of the common laws of sensorimotor contingency that vision and TVSS-perception share. For example, as you move around an object, hidden portions of its surface come into tactile-visual view, just as they would if you were seeing them."

This experiment suggests that giving a system a new topology induces qualia of that topology, and that learning the new topology does not necessarily require expensive and lengthly re-wiring. That camera control was necessary for inducing visual qualia from tactile stimulation suggests that the structure of visual stimuli and the experience of seeing must necessarily incorporate how our actions : movement of the eyes and head, and translation in space, alter the content of visual stimuli. Thus, when we talk about the "topology" of a stimulus, we must also incorporate how our actions change the stimulus (how our motor operators transform the stimulus space).

Hurley and Noë cover a number of other interesting anecdotes, including what happens when the brain fails to adapt its structure to reality, and pointing out that, in a left-right reversal of vision, reversing the interpretation of visual data is topologically equivalent to reversing the coordinates of motor output and proprioception, such that many different possible explanations of neural adaptation may be topologically equivalent.

So, I really do feel like, if we can make this notion of "neural topology*" more rigorous, we will have a satisfying answer to the portion of "the hard problem" that is amenable to scientific and mathematical investigations.

*neural topology : the idea that, in high dimensional sensory spaces, the distribution of probable stimuli occupy a reduced subset of said high dimensional space, and that one can move about this subset in a differentiable manner to transition smoothly between probable stimuli. This is a vague notion. It is related to "statistical structure" and "manifold", although I should note that we don't have enough information to say that the space of probably sensory-motor states is actually a manifold.