{"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":60,"pdf_page":68,"physical_index":68,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"27e94b18d5f961c63c534fe79b339258f5908b7559b68820fbed212133d9a3a3"},"chapter":"Digital Barricades: Interventions in Digital Culture and Politics","content":"2019, a tenth branch is under construction. Go, billed by Amazon as ‘just walk out shopping’, uses ‘computer vision, deep learning algorithms, and sensor fusion’ to dispense with cashiers and check-out lines (Amazon 2016). Essentially, Amazon Go relies on an array of devices for machine perception, the data from which is processed and synthesized by AI. Customers sign in to the store with the Amazon app and their actions within are tracked such that whichever items they pick up are automatically noted by the store, and upon walking out, their account is charged. Despite Amazon’s automation rhetoric, as of 2019, Go stores still involve human fixers and overseers, much as autonomous vehicles do (Del Ray 2017). Melville (2017) suggests that rather than seriously delving into the low-margin grocery industry, Amazon is merely using it as a venue for testing out a new method of payment, i.e. a new interface for retail transactions. Through pervasive AI-powered machine perception, Amazon Go transforms the retail transaction from a human-to-human interaction, in the case of a cashier, or a human-to-machine interaction, in the case of self-checkout, into a commodity-to-machine interaction which remains invisible to the human customer.\n\nExtrapolating from these examples, we can begin to imagine what it would be like if capacities for machine perception and cognition were generalized throughout society and thus became a general condition for production. Like electricity, AI perception and cognition could be put to many uses. In the cases discussed above, they are employed with the obvious goal of the replacement of human labour – we turn to the topic of AI effects on employment in the next chapter. But if we approach these cases from the perspective of limited human cognitive capacities as fetter posed by Microsoft, we can see how they might be more generally applied. In the cases of AI-enabled chatbots and automated retail, AI cognition and perception are being deployed to streamline processes of social interaction by converting them into simplified, easily digestible forms administered by machines. Complex workplace social interactions among software developers and customer service transactions are thus reduced to dialogue with a chatbot which facilitates the process. In the case of Amazon Go, the retail transaction disappears altogether from human phenomenology, transformed by the integration of various data streams.\n\nIn both cases AI acts as an interface which simplifies a complex situation. This is nothing new for the capitalist mode of production. As Vincent Manzerolle and one of us (Manzerolle and Kjøsen 2015) show in the context of near-field communication (NFC) devices, capital has enthusiastically embraced technologies which simplify and speed up transactions. Excited by AI’s capacities for further simplification and speed, the consulting firm Accenture (2017) has declared that AI will be the next user interface (UI), replacing the graphic user interface that is ubiquitous on our screens today. One of us has pointed out that analysts at Accenture deploy the unusual term ‘curation’ to describe the novelty of AI when it is considered as an interface (Steinhoff 2019a). Accenture declares that ‘at the height of sophistication, AI orchestrates. It collaborates across experiences and channels, often behind the scenes, to accomplish tasks. AI not only curates and acts based on its experiences, but also learns from interactions to help suggest and complete new tasks’ (Accenture 2017: 20). The vagueness of this description confirms the imagined widespread applicability of the function of curation – an intelligent, adaptive technique of cognitive automation. AI functions as an interface which not only represents some information to a user, but by perceiving and cognizing, actively gathers, processes, reveals and hides information before and while the user acts on it. This is the imagined function of the ‘new intelligent layer’ posited by ambient intelligence advocates (Panetta 2017) and Kelly’s ‘cheap, reliable, industrial-grade digital smartness’ (2014).\n\n60\n\ninhuman power","previous_page":59,"next_page":61}