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PDF 物理页索引 73 · Digital Barricades: Interventions in Digital Culture and Politics

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人工智能和资本主义的未来
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65
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73(从 0 开始)
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Digital Barricades: Interventions in Digital Culture and Politics
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This chapter has demonstrated that a project is underway to make AI capacities for cognition and perception generally available. But could it be true that Virno’s impossible-to-automate human capacities are indeed such? We do not believe so. This chapter has already surveyed some examples of those capacities being offloaded to AI systems, but we address them now directly.

Virno emphasizes the human capacities for communication. Communication (between machines and between humans and machines) has been one of the most successful applications of AI research. Natural language processing, speech synthesis and chatbots are only some of the ways in which AI enables the implementation of communicative capacities. As far back as 2012, Narrative Science was using AI to write formulaic sports and finance stories for newspapers and news websites. In 2019, the company is now selling the product Quill, which processes big data with Natural Language Generation (NLG) to create narrative-structured reports for businesses.

Related to communication is cooperation, which Virno also cites as distinctively human. AI is only beginning to implement cooperation, but already the examples are compelling. Generative adversarial networks (GANs) are a recent AI development in which two ML systems engage in an adversarial relationship which can be compared to the relationship between counterfeiters who produce fake currency and police who attempt to detect it (Goodfellow et al. 2014). One system attempts to generate data which closely resembles, but is not included in, a training set. The other system attempts to pick out fakes. Both systems learn over many instances of this exchange and eventually ‘both teams … improve their methods until the counterfeits are indistinguishable from the genuine articles’ (Goodfellow et al. 2014: 1). This is a kind of rudimentary cooperation which produces novel outputs.

A more vivid example comes from OpenAI who have constructed a team of five neural networks called the OpenAI Five which work together to play the popular multiplayer computer game Dota 2 (Defence of the Ancients 2). In 2018 the five networks defeated a team of professional players (Park 2018). The developers explain that the team members cooperate not by explicit communication: instead, ‘Teamwork is controlled by a hyperparameter we dubbed “team spirit”. Team spirit ranges from 0 to 1, putting a weight on how much each of OpenAI

means of cognition

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