{"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":83,"pdf_page":91,"physical_index":91,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"70e57ac09d7a8b2df2c68e5411ff9664d98959faa012fd2718c740300240c374"},"chapter":"Digital Barricades: Interventions in Digital Culture and Politics","content":"Less dramatic than cyber-rigs rolling down highways are the invisible software agents transforming capital’s circulatory processes. Around the globe, day and night, call centres send outgoing messages soliciting sales for everything from phone plans to museum memberships, and answer incoming calls maintaining, repairing and reinforcing customer relations (Brophy 2017; Woodcock 2017). In Europe and North America, they were promoted as replacing jobs lost to deindustrialization, though such work was then substantially outsourced to India and the Philippines. But as wages for repetitive phone-toil overseas rise, call centres are being AI automated. Customers (and workers) have long been familiar with the recorded message that ‘your call may be recorded for training and quality purposes’; that ‘training’ has come to include training ML systems (Marr 2016). AIs capable of applying natural language processing draw on digital banks of frequently asked questions, as well as knowledge of customers’ equipment, competence and past calls to automate answers to common questions, shuttling the more esoteric ones to the remaining human operators, sometimes while simultaneously analysing the callers ‘tone, vocabulary, sentiment, and even silences to gauge emotion and satisfaction’ (Agrawal, Gans and Goldfarb 2018: 90–1).\n\nThe market consultancy company Gartner declared in 2017 that ‘customer service spaces’ were ‘the number one case for applying AI’, accounting for ‘about 70% of all use cases in AI’ (Baraniuk 2018). In 2018, the British retail giant Marks & Spencer replaced 100 switchboard staff with chatbots using Twilio’s speech recognition software and Google’s Dialogflow AI tool to interpret and route customers’ verbal requests. The large US insurer Allstate adopted the digital assistant Amelia – billed as ‘the most human AI’ – to supplement information staff, reducing call durations from an average of 4.6 to 4.2 minutes – an apparently small saving that across millions of calls adds up to huge cuts in labour costs. Call companies like to term such changes ‘augmentation’ rather than ‘automation’ of human staff. For the moment, its main effect may be to intensify the work of human operators, but many observers believe automation will prevail in the long term (Wood 2018). Similar capacities are being extended to other corporate communications. In 2018, Google demonstrated how its Duplex system combines calendar search and natural speech patterns to schedule appointments by phone, with voice simulation difficult to distinguish from a human; it was promoted as ‘useful for the 60% of small businesses in the US that don’t already have an online booking system’ (Solon 2018).\n\nautomating the social factory\n\n83","previous_page":82,"next_page":84}