Applying the ethics of AI: a systematic review of tools for developing and assessing AI-based systems

Ricardo Ortega-Bolaños, Joshua Bernal-Salcedo, Mariana Germán Ortiz, Julian Galeano Sarmiento, Gonzalo A. Ruz, Reinel Tabares-Soto

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Artificial Intelligence (AI)-based systems and their increasingly common use have made it a ubiquitous technology; Machine Learning algorithms are present in streaming services, social networks, and in the health sector. However, implementing this emerging technology carries significant social and ethical risks and implications. Without ethical development of such systems, there is the potential for this technology to undermine people’s autonomy, privacy, and equity, even affecting human rights. Considering the approaches necessary for ethical development and effective governance of AI, such as ethical principles, guidelines, and technical tools, the question arises regarding the limitations of implementing these measures by the highly technical personnel involved in the process. In this context, we propose the creation of a typology that distinguishes the different stages of the AI life-cycle, the high-level ethical principles that should govern their implementation, and the tools with the potential to foster compliance with these principles, encompassing both technical and conceptual resources. In addition, this typology will include relevant information such as developmental level, related tasks, sectors, and language. Our research is based on a systematic review in which we identified 352 resources and tools. We expect this contribution to be valuable in promoting ethical AI development for developers and leaders who manage these initiatives. The complete typology and the comprehensive list of resources are available for consultation at https://ricardo-ob.github.io/tools4responsibleai.

Original languageEnglish
Article number110
JournalArtificial Intelligence Review
Volume57
Issue number5
DOIs
StatePublished - May 2024
Externally publishedYes

Keywords

  • AI life cycle
  • Artificial Intelligence
  • Ethics of AI
  • Governance
  • Machine learning
  • Responsible development

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