Thinking slow, acting reflexively

I just finished the cover story in Communications of the ACM on Human-Level Intelligence or Animal-Like Abilities?. Overall interesting and insightful, but what really caught my eye was Adnan Darwiche‘s discussion of models and maps:

  • “In his The Book of Why: The New Science of Cause and Effect, Judea Pearl explained further the differences between a (causal) model and a function, even though he did not use the term “function” explicitly. In Chapter 1, he wrote: “There is only one way a thinking entity (computer or human) can work out what would happen in multiple scenarios, including some that it has never experienced before. It must possess, consult, and manipulate a mental causal model of that reality.” He then gave an example of a navigation system based on either reasoning with a map (model) or consulting a GPS system that gives only a list of left-right turns for arriving at a destination (function). The rest of the discussion focused on what can be done with the model but not the function. Pearl’s argument particularly focused on how a model can handle novel scenarios (such as encountering roadblocks that invalidate the function recommendations) while pointing to the combinatorial impossibility of encoding such contingencies in the function, as it must have a bounded size.”
  • This is a Lists and Maps argument, and it leaves out stories, but it also implies something powerful that I need to start to think about. There is another interface, and it’s one that bridges human and machine, The dynamic model. What follows is a bunch of (at the moment – 10.8.18) incomplete thoughts. I think that models/games are another sociocultural interface, one that may be as affected by computers as the Ten Blue Links. So I’m using this as a staging area.
  • Games
    • Games and play are probably the oldest form of a dynamic model. Often, and particularly in groups, they are abstract simulations of conflict of some kind. It can be a simple game of skill such as Ringing the Bull, or a complex a wargame, such as chess:
      • “Historically chess must be classed as a game of war. Two players direct a conflict between two armies of equal strength upon a field of battle, circumscribed in extent, and offering no advantage of ground to either side. The players have no assistance other than that afforded by their own reasoning faculties, and the victory usually falls to the one whose strategical imagination is the greater, whose direction of his forces is the more skilful, whose ability to foresee positions is the more developed.” Murray, H.J.R.. A History of Chess: The Original 1913 Edition (Kindle Locations 576-579). Skyhorse Publishing. Kindle Edition.
    • Recently, video games afford games that can follow narrative templates:
      • Person vs. Fate/God
      • Person vs. Self
      • Person vs. Person
      • Person vs Society
      • Person vs. Nature
      • Person vs. Supernatural
      • Person vs. Technology
    • More on this later, because I think that this sort of computer-human interaction is really interesting, because it seems to open up spaces that would not be accessible to humans because of the data manipulation requirements (would flight simulators exist without non-human computation?).
  • Moving Maps
    • I would argue that the closer to interactive rates a model is, the more dynamic it is. A map is a static model, a snapshot of the current geopolitical space. Maps are dynamic because the underlying data is dynamic. Borders shift. Counties come into and go out of existence. Islands are created, and the coastline is eroded. And the next edition of map will incorporate these changes.
    • Online radar weather maps are an interesting case, since they reflect a rapidly changing environment and often now support playback of the last few hours (and prediction for the next few hours) of imagery at variable time scales.
  • Cognition
    • Traditional simulation and humans
      • Simulations provide a mechanism for humans to explore a space of possibilities that larger than what can be accomplished by purely mental means. Further, these simulations create artifacts that can be examined independently by other humans.
        • Every model is a theory—a very-well specified theory. In the case of simulations, the models are theories expressed in so much detail that their consequences can be checked by execution on a computer [Bryson, 2015]
      • The assumptions that provide the basis for the simulation are the model. The computer provides the dynamics. The use of simulation allows users to explore the space in the same way that one would explore the environment. Discoveries can be made that exist outside of the social constructs that led to the construction of the simulator and the assumptions that the simulator is based on.
      • What I think this means is that humans bring meaning to the outputs of the simulation. But it also means that there is a level of friction required to get from the outputs as they are computed to a desired level of meaningfulness to the users. In other words, if you have a theory of galaxy formation, but the results of the simulation only match observations if you have to add something new, like negative gravity, this could reflect a previously undiscovered component in the current theory of the formation of the universe.
      • I think this is the heart of my thinking. Just as maps allow the construction of trajectories across a physical (or belief) spaces, dynamic models such as simulation support ways of evaluating potential (and simplified/general) spaces that exist outside the realms of current understanding. This can be in the form of alternatives not yet encountered (a hurricane will hit the Florida panhandle on Thursday), or systems not yet understood (protein folding interactive simulators)
      • From At Home in the Universe: Physicists roll out this term, “universality class,” to refer to a class of models all of which exhibit the same robust behavior. So the behavior in question does not depend on the details of the model. Thus a variety of somewhat incorrect models of the real world may still succeed in telling us how the real world works, as long as the real world and the models lie in the same universality class. (Page 283)
    • Traditional simulation and ML(models and functions)
      • Darwiche discusses how the ML community has focused on “functional” AI at the expense of  “model-based” AI. I think his insight that functional AI is closer to reflex, and how there is an analogical similarity between it and “thinking fast“. Similarly, he believes that model-based AI may more resemble “thinking slow“.
      • I would contend that building simulators may be the slowest possible thinking. And I wonder if using simulators to train functional AI that can then be evaluated against real-world data, which is then used to modify the model in a “round trip” approach might be a way to use the fundamental understandability of simulation with the reflexive speed of trained NN systems.
      • What this means is that “slow” AI explicitly includes building testable models. The tests are not always going to be confirmation of predictions because of chaos theory. But there can be predictions of the characteristics of a model. For example, I’m working with using agent-based simulation moving in belief space to generate seeds for RNNs to produce strings that resemble conversations. Here, the prediction would be about the “spectral” characteristics of the conversation – how words change over time when compared to actual conversations where consensus evolves over time.

2 thoughts on “Thinking slow, acting reflexively

  1. Pingback: Phil 11.5.18 | viztales

  2. Pingback: The Great Socio-cultural Interfaces: Lists, Stories, and Maps | Phlog

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