Artificial Intelligence - A.I.

Artificial intelligence is the attempt to make machines that think like humans. In this article the abbreviation Al will be used to refer to this enterprise, and the phrase artificial intelligence technologies (AIT) will be reserved for new technologies that initially grew out of AI but that mimic only some aspects of human abilities, such as a subset of speech recognition or pattern recognition, while avoiding the deep problems. AIT and AI are often confused with one another.

AI proper has an important bearing on sociology in general, and social studies of science in particular, because of the light it can shed on the notion of the social. Most sociologists believe that most of a person's capacities are gained through the person's embedding in social groups. If machines could succeed in mimicking human reasoning, then either humans would have learned to "socialize" machines or there would be something wrong with the idea of "the social." Al the moment, humans have no idea how to socialize machines; there are no machines that can be raised from birth and learn language within a family, nor any that are imprinted with a ready-made set of social abilities and a capacity to continue to build them through social interaction.

From time to time such abilities have been claimed for machines as they have evolved. For example, neural nets appear to be capable of learning by themselves, but only in a
crude, behavioristic way, as one might train a pigeon or the like, so the deep problem of socialization has not been approached. This means that any real successes in Al would threaten the sociologist's idea of the social.
This is not the only kind of relationship between artifical intelligence and the social sciences. Sociologists are interested in the way new technologies change society, and die changes brought about by AIT are one such area of inquiry, One might think of machines of all sorts as already an integral part of society, but this is to use the notion of "the social" in a way that bears less directly on sociology as an enterprise.

Also, social studies of science have a legitimate concern with the development of AlTs of various kinds, and especially their relationship lo military projects.Returning to Al proper, the attempt to automate scientific discovery is a hard case for those who would wish to maintain the idea of the social. At the heart of the sociology of scientific knowledge (SSK) is the idea that even scientific knowledge is deeply invested with the social, whereas dominant models of science take it to be a paradigm of universality divorced from social influence. Thus, imagine a human community that has developed in isolation from other communities: There would be no grounds to expect such a community to develop, say. the English language, still less the nuances of any particular dialect spoken at a given moment in history. One accepts that such capacities would not develop in the absence of social contact between the community and the social group that embodied the dialect.

On the other hand, the dominant view of science would lead us to be less surprised should such an isolated community rediscover many of our scientific and mathematical laws. It is this view of science that is challenged by SSK, which treats any body of scientific knowledge as very much like a dialect in a natural language. If the current generation of asocial machines could rediscover scientific laws on their own, this would support the dominant view and challenge the sociological view of science. The sociology of scientific knowledge is, then, a hard case for the larger argument about Al and the social. If the sociologists can hold their ground in the case of science, then the ground can be held much more easily in the case of social activity as a whole.

Attempts to develop Al can be seen, then, as an expensive experiment to test the deep ideas of sociology in general and of SSK in particular. Like all experiments, however, this one suffers from indeterminacies in its outcome associated with the experimenter's regress and the like. One important source of confusion is the confusion between AIT and Al, which is amplified by humans' ability to "repair" the deficiencies in others' communication and attribute far more competence to partners in discourse that they deserve. The need for repair is crucial to ordinary communication, because speech is normally indistinct, broken, overlaid with other sounds, and invested with allusion to shared but unspoken contexts. It is only by "reading" within context and repairing the "mistakes" that we are able to make sense of others' speech and action. On these tendencies depends the success of confidence tricksters and fraudsters of various
kinds, who can rely on the "mark: to do most of the work necessary to see what they do as a competent performance.


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