Making Sense of AI. Anthony Elliott. Читать онлайн. Newlib. NEWLIB.NET

Автор: Anthony Elliott
Издательство: John Wiley & Sons Limited
Серия:
Жанр произведения: Математика
Год издания: 0
isbn: 9781509548910
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argue, to see that other forms of power, different stocks of knowledge and other ideologies lurk inside the discourse of AI – all of which have unintended consequences and impact upon social development in the current period. In the opening section of the chapter, I outline some general notions connected with the development of AI, which will help construct key underlying themes of this book as a whole. My focus is on unravelling the many different definitions of AI. In the second section, I situate AI in the broad context of both globalization and everyday life. Notwithstanding the dominance of technical thinking which privileges a ‘black box model’ of inputs and outputs, my argument is that the rise of automated intelligent machines should be studied as expressing or incorporating forms of sociality, stocks of cultural knowledge, and unequal power relations that provide a focal point for the investigation of AI.

      In the case of artificial intelligence, it is widely, though erroneously, assumed that its history can and ought to be mapped, measured and retold by recourse and recourse only to AI studies – and that if any of this history falls outside of the purview of the disciplines of engineering, computer science or mathematics, it might justifiably be ignored or assigned perhaps only a footnote within the canonical bent of AI studies. Such an approach, were it attempted here, would aim at reproducing the rather narrow range of interests of much in the AI field – for example, definitional problems or squabbles concerning the ‘facts of the technology’.1 What, precisely, is machine learning? How did machine learning arise? What are artificial neural networks? What are the key historical milestones in AI? What are the interconnections between AI, robotics, computer vision and speech recognition? What is natural language processing? Such definitional matters and historical facts about artificial intelligence have been admirably well rehearsed by properly schooled computer scientists and experienced engineers the world over, and detailed discussions are available to the reader elsewhere.2

      Where does all of this leave AI? The field has advanced rapidly since the 1950s, but it is salutary to reflect on the recent intellectual history of artificial intelligence because that very history suggests it is not advisable to try to compress its wealth of meanings into a general definition. AI is not a monolithic theory. To demonstrate this, let’s consider some definitions of AI – selected more or less at random – currently in circulation:

      1 the creation of machines or computer programs capable of activity that would be called intelligent if exhibited by human beings;

      2 a complex combination of accelerating improvements in computer technology, robotics, machine learning and big data to generate autonomous systems that rival or exceed human capabilities;

      3 technologically driven forms of thought that make generalizations in a timely fashion based on limited data;

      4 the