The promise and perils of using artificial intelligence to fight corruption

【Author】 Koebis, Nils; Starke, Christopher; Rahwan, Iyad

【Source】NATURE MACHINE INTELLIGENCE

【影响因子】25.898

【Abstract】Despite the growing number of initiatives that employ AI to counter corruption, few studies empirically tackle the political and social consequences of embedding AI in anti-corruption efforts. The authors outline the societal and technical challenges that need to be overcome for AI to fight corruption. Corruption presents one of the biggest challenges of our time, and much hope is placed in artificial intelligence (AI) to combat it. Although the growing number of AI-based anti-corruption tools (AI-ACT) have been summarized, a critical examination of their promises and perils is lacking. Here we argue that the success of AI-ACT strongly depends on whether they are implemented top-down (by governments) or bottom-up (by citizens, non-governmental organizations or journalists). Top-down use of AI-ACT can consolidate power structures and thereby pose new corruption risks. Bottom-up use of AI-ACT has the potential to provide unprecedented means for the citizenry to keep their government and bureaucratic officials in check. We outline the societal and technical challenges that need to be overcome to harness the potential for AI to fight corruption.

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【发表时间】

【收录时间】2022-06-06

【文献类型】理论性文章

【主题类别】

区块链应用-实体经济-司法领域