Prejudiced learning: a connectionist account.
Connectionist simulation was employed to investigate processes that may underlie the relationships between prior expectancies or prejudices and the acquisition of attitudes, under conditions where learners can only discover the valence of attitude objects through directly experiencing them. We compared contexts analogous to learners holding either false negative expectancies ('prejudices') about a subclass of objects that were actually good or false positive expectancies about objects that were actually bad. We introduced expectancy-related bias either by altering the probability of approach, or by varying the rate of learning following experience with good or bad objects. Where feedback was contingent on approach, the false positive expectancies were corrected by experience, but negative prejudices resisted change, since the network avoided objects deemed to be bad, and so received less corrective feedback. These findings are discussed in relation to the effects of intergroup contact and expectancy-confirmation processes in reducing or sustaining prejudice.
Department of Psychology, University of Sheffield, Sheffield S10 2TP, UK. j.r.eiser@shef.ac.uk
J Richard
JR
Eiser
Tom
T
Stafford
Russell H
RH
Fazio
D001290:Attitude; D003198:Computer Simulation; D006126:Group Processes; D007858:Learning; D016571:Neural Networks, Computer; D011287:Prejudice; D013647:Task Performance and Analysis