资本主义
虚拟经济
债务
社会学
信用卡
经济
政治经济学
财务
政治学
政治
法学
人工智能
计算机科学
付款
标识
DOI:10.1080/09502386.2022.2042576
摘要
This paper explores the force of automation and its contradictions and resistances within (and beyond) the financial sector, with a specific focus on computational practices of credit-scoring and lending. It examines the operations and promotional discourses of fintech start-ups LendUp.com and Elevate.com that offer small loans to the sub-prime consumers in exchange for access to their online social media and mobile data, and Zest AI and LenddoEFL that sell automated decision-making tools to verify identity and assess risk. Reviewing their disciplinary reputational demands and impacts on users and communities, especially women and people of colour, the paper argues that the automated reimagination of credit and creditability disavows the formative design of its AI and redefines moral imperatives about character to align with the interests of digital capitalism. The economic, social and cultural crises precipitated by the Covid-19 pandemic have only underscored the internal contradictions of these developments, and a variety of debt resistance initiatives have emerged, aligned with broader movements for social, economic, and climate justice around the globe. Cooperative lending circles such as the Mission Asset Fund, activist groups like #NotMyDebt, and Debt Collective, a radical debt abolition movement, are examples of collective attempts to rehumanize credit and debt and resist the appropriative practices of contemporary digital finance capitalism in general. Running the gamut from accommodationist to entirely radical, these experiments in mutual aid, debt refusal, and community-building provide us with roadmaps for challenging capitalism and re-thinking credit, debt, power, and personhood within and beyond the current crises.
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