CCNC/SfN/Epirob/AAAI Conference Blogging

I am currently in San Diego, in the second day of a three-city, four-conference tour during which I’ll be attending the CCN Conference, Society for Neuroscience, Epigenetic Robotics, and the AAAI Fall Symposium on Computational Approaches to Representation Change during Learning and Development.

This is the longest and most complicated conference travel adventure I’ve ever undertaken. Especially since I’m presenting either a poster or a talk at all four conferences. In addition, it is my first time attending SfN, which draws 20-30,000 attendees, making it easily an order of magnitude larger than any conference I’ve ever attended. I have to wonder what the point of such a large conference is, since I’ve been told by several people not to expect to run into anyone I know if we haven’t planned the meeting in advance.

So far, CCNC has been nice — only 200-300 people — with lots of work focused on computational modeling of reinforcement learning and other decision making processes. I’ve run into a couple of people that I knew from elsewhere, as well as a couple of people from CNBC that I’ve met for just the first or second time. I’ve also been slightly disappointed that a couple of people I expected to see are nowhere to be found.

I’m going to try to blog at least once from each location. Newt Gingrich is speaking about research funding priorities for science at SfN on Monday. It’s during the first hour of my poster session, but I may try to attend anyway.


George Lakoff Speaking in Austin

Austin Moving Forward, a progressive political group I’ve never heard of has cognitive scientist George Lakoff as keynote speaker at what I assume is an organizational meeting at St. Edwards University on Saturday, June 25. I’ve mentioned Lakoff here before. He is an expert on the cognition of language, and a Rockridge Institute fellow studying and writing about political debate is framed by the language used and how progressives can frame the debate in their favor. I think all political progressives, in fact the entire Democratic party, should read his essays on framing, especially Simple Framing, and How to Respond to Conservatives.

Lakoff’s main maxim is that the truth won’t set you free, unless it’s framed properly. Progressives tired of beating their heads against the wall of conservative rhetoric would do well to learn this.

Lakoff Starts a Progressive Think Tank

I’ve already mentioned George Lakoff and his applications of the cognitive science of language and metaphor to current political thought. He mentioned that the reason that conservatives were winning the political struggles in this country was that they have better metaphors — they’re better a framing the debate. Then hoped that he would give some constructive help. Looks like he’s doing just that. He and some other UC Berkeley and UC Davis faculty have
started a progressive think tank
to work on how progressives can use language to better frame the issues. The article is an interview with Lakoff, and the deepest quote is on the second page contrasting the conservative approach of investment in cognitive infrastructure to the liberal approach he says:

Also, within traditional liberalism you have a history of rational thought that was born out of the Enlightenment: all meanings should be literal, and everything should follow logically. So if you just tell people the facts, that should be enough — the truth shall set you free. All people are fully rational, so if you tell them the truth, they should reach the right conclusions. That, of course, has been a disaster.

Though I think an equally plausible theory is that Democrats held power in Congress for so long that they became complacent, while the republicans had to struggle to find a way to reach people.

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Lakoff: Liberal and conservative moral metaphors

Much has been made in the media and blogs lately of the Democrats’ lack of leadership and a central message to compete with the republicans. In this 1995 essay cognitive scientist George Lakoff analyses the central metaphors that describe and inform the moral systems of American conservatives and liberals. He argues:

While conservatives understand that all of their policies have a single unified origin, liberals understand their own political conceptual universe so badly that they still think of it in terms of coalitions of interest groups. Where conservatives have organized for an overall, unified onslaught on liberal culture, liberals are fragmented into isolated interest groups, based on superficial localized issues: labor, the rights of ethnic groups, feminism, gay rights, environmentalism, abortion rights, homelessness, health care, education, the arts, and so on. This failure to see a unified picture of liberal politics has led to a divided consciousness and has allowed conservatives to employ a divide-and-conquer strategy. None of this need be the case, since there is a worldview that underlies liberal thought that is every bit as unified as the conservative worldview.

Lakoff, himself clearly a liberal, goes on to criticize some of the flaws in the conservative moral metaphor, but is disappointingly short on good constructive advice for Democrats on how to unify their message around their central metaphor, The nurturing parent model. Still, I think that the material is here for good leaders to begin crafting a liberal message that resonates with voters.

Forum for AI, Monday April 28

This Monday at 4:00 pm in ACES Auditorium, Robert Hecht-Nielsen will speak at FAI. I haven’t met Robert, but I understand he is an entertaining and provocative speaker. His talk certainly seems provocative — basically a unified theory of cognition based on associative memory between vector quantizors. Right up my alley! The info is below.


Robert Hecht-Nielsen University of California, San Diego

This talk will overview the author’s recently published theory of the cerebral cortex (in: Hecht-Nielsen, R. and McKenna, T. [Eds.] (2003) Computational Models for Neuroscience, Springer-Verlag) and discuss some of its startling implications for neuroscience, AI, and philosophy. Mathematically, the theory views the cortical surface as a collection of about 120,000 notional vector quantizers which are organized and frozen at various points during childhood. These provide a fixed set of terms of reference so that knowledge can be accumulated. Cortical knowledge takes the form of a vast number of pairwise unidirectional links between tokens in these quantizer’s codebooks, with each link having a strength directly related to a particular conditional probability (the antecedent support probability of the source token given the presence of the target token). How this knowledge is used to carry out thinking is explicitly explained and a related local-circuit neuroscience prediction of the theory is described. This talk will show how this weird design, while inherently incapable of directly carrying out any sort of ordinary reasoning i.e., Aristotelian logic, learned neural network input-output mappings, Bayesian inferencing, fuzzy logic, etc.), is nonetheless able to arrive at excellent conclusions. Further, unlike the situation in the cases of existing AI reasoning schemes, the amount of antecedent support knowledge required by cortex, while large, is not combinatorially explosive and can be feasibly obtained during childhood. While scientific testing of this theory is probably a long way off, the theory can be put into service immediately as a new mathematical foundation for AI.

Lakoff: Metaphor and War

Linguist and Cognitive Scientist George Lakoff discusses the metaphors used in framing the war in his
essay Metaphor and War, Again:

One of the most frequent uses of the Nation As Person metaphor comes in the almost daily attempts to justify the war metaphorically as a “just war.” The basic idea of a just war uses the Nation As Person metaphor plus two narratives that have the structure of classical fairy tales: The Self Defense Story and The Rescue Story.

Millions of people around the world can see that the metaphors and fairy tales don’t fit the current situation, that Gulf War II does not qualify as a just war — a “legal” war. But if you accept all these metaphors, as Americans have been led to do by the administration, the press, and the lack of an effective Democratic opposition, then Gulf War II would indeed seem like a just war.

Forum for AI, Friday April 4

This Friday at 3pm in ACES 2.402, Michael Ryan will be speaking at FAI. This title and abstract are below

Using Artificial Neural Networks to Study the Evolution of Animal Communication

Animals often attend to only a few of the cues provided by the complex displays of conspecifics. We suggest that these perceptual biases are influenced by mechanisms of signal recognition inherited from antecedent species. We tested this hypothesis by manipulating the evolutionary history of artificial neural networks, observing how the resulting networks respond to many novel stimuli and comparing these responses to the behavior of females in phonotaxis experiments. Networks with different evolutionary histories proved equally capable of evolving to recognize the call of the tungara frog, Physalaemus pustulosus, but exhibited distinct responses to novel stimuli. History influenced the ability of networks to predict known responses of tungara frogs; network accuracy was determined by how closely the network history approximated the hypothesized history of the tungara frog. Our finding emphasize the influence of past selection pressures on current perceptual mechanisms, and demonstrate how neural network models can be used to address behavioral questions that are intractable through traditional methods.