A comparison of human and GPT-4 use of probabilistic phrases in a coordination game.

English speakers use probabilistic phrases such as likely to communicate information about the probability or likelihood of events. Communication is successful to the extent that the listener grasps what the speaker means to convey and, if communication is successful, individuals can potentially coordinate their actions based on shared knowledge about uncertainty. We first assessed human ability to estimate the probability and the ambiguity (imprecision) of twenty-three probabilistic phrases in a coordination game in two different contexts, investment advice and medical advice. We then had GPT-4 (OpenAI), a Large Language Model, complete the same tasks as the human participants. We found that GPT-4's estimates of probability both in the Investment and Medical Contexts were as close or closer to that of the human participants as the human participants' estimates were to one another. However, further analyses of residuals disclosed small but significant differences between human and GPT-4 performance. Human probability estimates were compressed relative to those of GPT-4. Estimates of probability for both the human participants and GPT-4 were little affected by context. We propose that evaluation methods based on coordination games provide a systematic way to assess what GPT-4 and similar programs can and cannot do.

Detecting visual texture patterns in binary sequences through pattern features.

We measured human ability to detect texture patterns in a signal detection task. Observers viewed sequences of 20 blue or yellow tokens placed horizontally in a row. They attempted to discriminate sequences generated by a random generator ("a fair coin") from sequences produced by a disrupted Markov sequence (DMS) generator. The DMSs were generated in two stages: first a sequence was generated using a Markov chain with probability, pr = 0.9, that a token would be the same color as the token to its left. The Markov sequence was then disrupted by flipping each token from blue to yellow or vice versa with probability, pd-the probability of disruption. Disruption played the role of noise in signal detection terms. We can frame what observers are asked to do as detecting Markov texture patterns disrupted by noise. The experiment included three conditions differing in pd (0.1, 0.2, 0.3). Ninety-two observers participated, each in only one condition. Overall, human observers' sensitivities to texture patterns (d' values) were markedly less than those of an optimal Bayesian observer. We considered the possibility that observers based their judgments not on the entire texture sequence but on specific features of the sequences such as the length of the longest repeating subsequence. We compared human performance with that of multiple optimal Bayesian classifiers based on such features. We identify the single- and multiple-feature models that best match the performance of observers across conditions and develop a pattern feature pool model for the signal detection task considered.

Allocentric kin recognition is not affected by facial inversion.

Typical judgments involving faces are disrupted by inversion, with the Thatcher illusion serving as a compelling example. In two experiments, we examined how inversion affects allocentric kin recognition-the ability to judge the degree of genetic relatedness of others. In the first experiment, participants judged whether pairs of photographs of children portrayed siblings or unrelated children. Half of the pairs were siblings, half were unrelated. In three experimental conditions, photographs were viewed in upright orientation, flipped around a horizontal axis, or rotated 180°. Neither rotation nor flipping had any detectable effect on allocentric kin recognition. In the second experiment, participants judged pairs of photographs of adult women. Half of the pairs were sisters, half were unrelated. We again found no significant effect of facial inversion. Unlike almost all other face judgments, judgments of kinship from facial appearance do not rely on perceptual cues disrupted by inversion, suggesting that they rely more on spatially localized cues rather than "holistic" cues. We conclude that kin recognition is not simply a byproduct of other face perception abilities. We discuss the implications for cue combination models of other facial judgments that are affected by inversion.

Lateralization of kin recognition signals in the human face.

When human subjects view photographs of faces, their judgments of identity, gender, emotion, age, and attractiveness depend more on one side of the face than the other. We report an experiment testing whether allocentric kin recognition (the ability to judge the degree of kinship between individuals other than the observer) is also lateralized. One hundred and twenty-four observers judged whether or not pairs of children were biological siblings by looking at photographs of their faces. In three separate conditions, (1) the right hemi-face was masked, (2) the left hemi-face was masked, or (3) the face was fully visible. The d' measures for the masked left hemi-face and masked right hemi-face were 1.024 and 1.004, respectively (no significant difference), and the d' measure for the unmasked face was 1.079, not significantly greater than that for either of the masked conditions. We conclude, first, that there is no superiority of one or the other side of the observed face in kin recognition, second, that the information present in the left and right hemi-faces relevant to recognizing kin is completely redundant, and last that symmetry cues are not used for kin recognition.

Sub-optimal allocation of time in sequential movements.

The allocation of limited resources such as time or energy is a core problem that organisms face when planning complex actions. Most previous research concerning planning of movement has focused on the planning of single, isolated movements. Here we investigated the allocation of time in a pointing task where human subjects attempted to touch two targets in a specified order to earn monetary rewards. Subjects were required to complete both movements within a limited time but could freely allocate the available time between the movements. The time constraint presents an allocation problem to the subjects: the more time spent on one movement, the less time is available for the other. In different conditions we assigned different rewards to the two tokens. How the subject allocated time between movements affected their expected gain on each trial. We also varied the angle between the first and second movements and the length of the second movement. Based on our results, we developed and tested a model of speed-accuracy tradeoff for sequential movements. Using this model we could predict the time allocation that would maximize the expected gain of each subject in each experimental condition. We compared human performance with predicted optimal performance. We found that all subjects allocated time sub-optimally, spending more time than they should on the first movement even when the reward of the second target was five times larger than the first. We conclude that the movement planning system fails to maximize expected reward in planning sequences of as few as two movements and discuss possible interpretations drawn from economic theory.

Kin recognition and the perceived facial similarity of children.

We examine the connection between a hypothetical kin recognition signal available in visual perception and the perceived facial similarity of children. One group of observers rated the facial similarity of pairs of children portrayed in photographs. Half of the pairs were siblings but the observers were not told this. A second group classified the pairs as siblings or nonsiblings. An optimal Bayesian classifier, given the similarity ratings of the first group, was as accurate in judging siblings as the second group. Mean rated similarity was also an accurate linear predictor (R2 = .96) of the log-odds that the rated pair portrayed were, in fact, siblings. Surprisingly, mean rated similarity did not vary with the age difference or gender difference of the pairs, both of which were counterbalanced across the stimuli. We conclude that the perceived facial similarity of children is little more than a graded kin recognition signal and that this kin recognition signal is effectively an estimate of the probability that two children are close genetic relatives.

Where are kin recognition signals in the human face?

We report two experiments that aimed to determine where in the face the cues that signal kinship fall. In both experiments, participants were shown 30 pairs of photographs of children's faces. Half of the pairs portrayed siblings and half did not. The 220 participants were asked to judge whether each pair of photographs portrayed siblings. We measured the effect on kin recognition performance of masks that covered the upper half or the lower half of the face (Experiment 1) and the eye region or the mouth region (Experiment 2). In Experiment 1, we found that the signal detection estimate of performance d' decreased only 5.3% (ns) when the lower face was masked but by more than 65% when the upper face was masked. We tested whether the combination of kinship information from the two halves of the face can be treated as optimal combination of independent cues and found that it could be. In Experiment 2, we found that masking the eye region led to only a 20% reduction (ns) in performance whereas masking the mouth region led to a nonsignificant increase in performance. We also found that the eye region contains only slightly more information about kinship than the upper half of the face outside of the eye region.