Phil 7.17.17

Big, tough ride on Saturday. Still tired!

7:00 – 8:00 Research

  • Is this an AI stampede/echo chamber??
    • “There was no reward to sticking to English language,” says Dhruv Batra, visiting research scientist from Georgia Tech at Facebook AI Research (FAIR). As these two agents competed to get the best deal–a very effective bit of AI vs. AI dogfighting researchers have dubbed a “generative adversarial network”–neither was offered any sort of incentive for speaking as a normal person would. So they began to diverge, eventually rearranging legible words into seemingly nonsensical sentences. Supporting Facebook papers
  • More C&C:
  • In general, no one remains entirely passive when faced with what emanates from other people. They are approved of, or argued with in one of those interior dialogues, those silent conversations, in which the group with whom we are communicating is no longer outside us but within us – which is what ‘thinking’ means. Arguments are adopted because they are better formulated, or because we believe we have discovered them ourselves, although we are often repeating, without being aware of it, those we have heard at the time. And when we exclaim ‘I’ve always thought so, but I didn’t dare say it,’ or, ‘I’ve always said so, that’s plain,’ it matters little whether we are sincere or not. It is a cry for recognition by the group.
  • Thus the consensus of the great majority of the groups undergoes a polarization effect. The effect is weak when communication is carried on passively and impersonally, but grows stronger as soon as communication becomes intense and touches people personally. This signifies that the convergence observable in a group depends more on the level of participation and on reciprocal action between its members than on their individual qualities.  [p 87]
    • This also explains why the explore <-> flocking <-> stampede spectrum can be modeled by so few variables (heading, speed, and influence radius), as processed by the agent. This is a personal process with global effects.
  • Thurstone scale  A Thurstone scale has a number of “agree” or “disagree” statements. It is a unidimensional scale to measure attitudes towards people.
    • This also could be a way of determining dimensions that have large ranges as opposed to highly constrained ones
  • It is revealing that a situation in which one has to choose in a personal fashion renders the judgments and choices more extreme, whereas a situation demanding an impersonal choice favors compromise, or almost does. [p 91]
  • We should bear in mind that all this related to the portrait of no one young man in particular. What would happen now if the participants were presented with photographs of familiar people, socially typical, such as workers or intellectuals? Inasmuch as their characteristics stand out more and attitudes towards them are more marked, it might be expected that the results might be more extreme. This was indeed the case. After the group discussion. it turned out that judgments on the characteristics became more extreme, even on the less important ones. [p 91]

8:45 – 5:00 BRI

  • Working out how to fit the location/document message into the GEM and GeoMesa
  • Using a HashMap to dedupe locations from the document
  • Think I got it built. My mistake was thinking that the GEM had an inheritance structure. Next thing is to send the message to GeoMesa
  • Off into the rain!
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