Innovation is defined not only by the type of technology used, but also by who creates it and the processes by which it is developed and deployed. This chapter explores the development of AI-based anti-corruption technologies by providing empirical evidence on applications implemented by governmental and non-governmental organisations in Italy, Estonia, Germany, Brazil and Venezuela. Based on in-depth desk research and interviews with public officials, activists, developers and journalists, we identify three types of development models for AI-based ACTs: in-house development, outsourcing off-the-shelf solutions, and co-creation. The adoption of each model depends on funding availability, urgency for innovative solutions, and AI expertise. The chapter also discusses key drivers, opportunities, and challenges of each model. It reflects on the benefits and risks of AI-based ACTs, which, while offering potential powerful solutions, may also add complexity to an already discordant world, facing political instability, social fragmentation, and technological disruption.
Gerli, C., Odilla, F. (In stampa/Attività in corso). AI to innovate anti-corruption: Exploring development models for governmental and non-governmental applications. Londra : Routledge.
AI to innovate anti-corruption: Exploring development models for governmental and non-governmental applications
Carolina Gerli;Fernanda Odilla
In corso di stampa
Abstract
Innovation is defined not only by the type of technology used, but also by who creates it and the processes by which it is developed and deployed. This chapter explores the development of AI-based anti-corruption technologies by providing empirical evidence on applications implemented by governmental and non-governmental organisations in Italy, Estonia, Germany, Brazil and Venezuela. Based on in-depth desk research and interviews with public officials, activists, developers and journalists, we identify three types of development models for AI-based ACTs: in-house development, outsourcing off-the-shelf solutions, and co-creation. The adoption of each model depends on funding availability, urgency for innovative solutions, and AI expertise. The chapter also discusses key drivers, opportunities, and challenges of each model. It reflects on the benefits and risks of AI-based ACTs, which, while offering potential powerful solutions, may also add complexity to an already discordant world, facing political instability, social fragmentation, and technological disruption.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


