Albania appoints AI bot'minister' to fight corruption in world first Albanian Prime Minister Edi Rama has put an artificial intelligence-generated "minister" in charge of tackling corruption in his new cabinet. Diella, which means "sun" in Albanian, was appointed on Thursday, with the leader introducing her as a "member of the cabinet who is not present physically" who will ensure that "public tenders will be 100 percent free of corruption". Corruption is a key factor in Albania's bid to join the bloc. Rama's Socialist Party, which recently secured a fourth term in office, has said it can deliver EU membership for Albania in five years, with negotiations concluding by 2027. Lawmakers will soon vote on Rama's new cabinet, but it was unclear whether he would ask for a vote on Diella's virtual post.

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. 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 continues to be one of the biggest societal challenges of our time. New hope is placed in Artificial Intelligence (AI) to serve as an unbiased anti-corruption agent. Ever more available (open) government data paired with unprecedented performance of such algorithms render AI the next frontier in anti-corruption. Summarizing existing efforts to use AI-based anti-corruption tools (AI-ACT), we introduce a conceptual framework to advance research and policy. It outlines why AI presents a unique tool for top-down and bottom-up anti-corruption approaches. For both approaches, we outline in detail how AI-ACT present different potentials and pitfalls for (a) input data, (b) algorithmic design, and (c) institutional implementation. Finally, we venture a look into the future and flesh out key questions that need to be addressed to develop AI-ACT while considering citizens' views, hence putting "society in the loop".