{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"a2eab101-adfc-4a0d-8142-63a4d11cee02","title":"人工智能和资本主义的未来","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9780745338613","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"a2eab101-adfc-4a0d-8142-63a4d11cee02","id":"a2eab101-adfc-4a0d-8142-63a4d11cee02","uuid":"a2eab101-adfc-4a0d-8142-63a4d11cee02","title":"人工智能和资本主义的未来","normalized_title":"人工智能和资本主义的未来","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9780745338613","isbns":["9780745338613","9780745338606","9781786803955","9781786803979","9781786803962"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":225,"navigation_url":"https://workshop.closeclaw.top/ai/book/a2eab101-adfc-4a0d-8142-63a4d11cee02","title_url":"https://workshop.closeclaw.top/ai/title/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E5%92%8C%E8%B5%84%E6%9C%AC%E4%B8%BB%E4%B9%89%E7%9A%84%E6%9C%AA%E6%9D%A5","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/a2eab101-adfc-4a0d-8142-63a4d11cee02/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/a2eab101-adfc-4a0d-8142-63a4d11cee02/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/a2eab101-adfc-4a0d-8142-63a4d11cee02","page_url":"https://workshop.closeclaw.top/api/ai/books/a2eab101-adfc-4a0d-8142-63a4d11cee02/page","search_url":"https://workshop.closeclaw.top/api/ai/books/a2eab101-adfc-4a0d-8142-63a4d11cee02/search"},"page":{"printed_page":43,"pdf_page":51,"physical_index":51,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"030b9b684692cf694a431cee93eeaad4443db2c09832aa31ecc7c557bf98d185"},"chapter":"Digital Barricades: Interventions in Digital Culture and Politics","content":"In sum, the AI industry is generating many interconnected commercial ventures – an ‘ecosystem’, to use a term widely adopted by those who like to naturalize capitalist activity. AI is beginning to be generalized beyond the tech industry, propelled by wide applicability, financial incentives and technological advancements. The prospects for further generalization indicate to us the plausibility of a future where capital presupposes access to these means of cognition, or, in other words, where AI becomes part of the general conditions of production.\n\nWhile there may be dramatic changes to the AI industry landscape over the course of this generalization, for now the tech giants occupy an apex position. Control of cloud computing facilities, ownership of large data sets, and the wealth to hire the best from a limited pool of AI talent are some of their many advantages. These factors suggest that the domination of the information technology sector by a handful of corporate behemoths will continue in the age of AI. One likely trajectory for the AI industry is thus that which Marx described as inherent to the general law of capitalist accumulation, namely the centralization and concentration of capitalist power (1990: 777). This is acknowledged even by unequivocally pro-market observers. As The Economist (2017a) argues: ‘It seems likely that the incumbent tech groups will capture many of AI’s gains, given their wealth of data, computing power, smart algorithms and human talent, not to mention a head start on investing.’ And a business-oriented study enthusiastic about the commercial prospects of ML unabashedly acknowledges that there may be a ‘tradeoff between innovation and competition’:\n\nLike most software-related technologies, AI has scale economies. Furthermore, AI tools are often characterized by some degree of increasing returns: better prediction accuracy leads to more users, more users generate more data, and more data leads to better prediction accuracy. Businesses have greater incentives to build [AI] if they have more control, but along with scale economies, this may lead to monopolization. Faster innovation may benefit society from a short-term perspective but may not be optimal in the longer-term. (Agrawal, Gans and Goldfarb 2018: 23)\n\nmeans of cognition\n\n43","previous_page":42,"next_page":44}