Perceptual Categorization: Connectionist Modelling and Decision Rules

Although it is currently popular to model human associative learning using connectionist networks, the mechanism by which their output activations are converted to probabilities of response has received relatively little attention. Several possible models of this decision process are considered here, including a simple ratio rule, a simple difference rule, their exponential versions, and a winner-take-all network. Two categorization experiments that attempt to dissociate these models are reported. Analogues of the experiments were presented to a single-layer, feed-forward, delta-rule network. Only the exponential ratio rule and the winner-take-all architecture, acting on the networks' output activations that corresponded to responses available on test, were capable of fully predicting the mean response results. In addition, unlike the exponential ratio rule, the winner-take-all model has the potential to predict latencies. Further studies will be required to determine whether latencies produced under more stringent conditions conform to the model's predictions.     

THE GOLEM LEGEND AND THE ENIGMA OF FACEBOOK

We are easily misguided as to the true nature of Facebook, and tend to treat it simply as a powerful technological instrument in the service of human intentions. We can, however, gain a better picture of it through recourse to the Jewish tradition of the golem, an image of human beings, created by them in a re-enactment of their own creation by God. It turns into a magic servant in modernity with an inherent dynamic running between its human and its subhuman characteristics. This dynamic is the main cause behind its becoming uncontrollable. In like manner, what is subhuman in Facebook serves its masters and functions under their total control, but also empowers Facebook's increasingly human operation, an algorithm-based capability which raises growing doubts about what counts as human. Facebook implies the crisis of humanity which coincides with the “death of God,” that is, the obsolescence of the idea of a divine creator.     

Training Observers to Detect Deception Effects of Self-Monitoring and Rehearsal

It was predicted that trained observers would detect deception more accurately than untrained observers. More specifically, it was predicted that the highest deception detection accuracy would be found among trained observers judging the veracity of low self-monitors and unrehearsed liars, whereas the lowest detection accuracy would be found among untrained observers judging the veracity of high self-monitors and rehearsed deceivers. It also was hypothesized that the discrepancy between observers‘actual ability to detect deception and their certainty in the accuracy of their judgments would be smaller for trained observers than for untrained observers. Observers trained to detect deception used six behavioral cues based on research by deTurck and Miller (1985): (a) message duration, (b) response latency, (c) adaptors, (d) pauses, (e) nonfluencies, and (f) hand gestures. Results confirmed both hypotheses.