TY - JOUR
T1 - Applying the ethics of AI
T2 - a systematic review of tools for developing and assessing AI-based systems
AU - Ortega-Bolaños, Ricardo
AU - Bernal-Salcedo, Joshua
AU - Germán Ortiz, Mariana
AU - Galeano Sarmiento, Julian
AU - Ruz, Gonzalo A.
AU - Tabares-Soto, Reinel
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/5
Y1 - 2024/5
N2 - 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.
AB - 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.
KW - AI life cycle
KW - Artificial Intelligence
KW - Ethics of AI
KW - Governance
KW - Machine learning
KW - Responsible development
UR - http://www.scopus.com/inward/record.url?scp=85193537035&partnerID=8YFLogxK
U2 - 10.1007/s10462-024-10740-3
DO - 10.1007/s10462-024-10740-3
M3 - Article
AN - SCOPUS:85193537035
SN - 0269-2821
VL - 57
JO - Artificial Intelligence Review
JF - Artificial Intelligence Review
IS - 5
M1 - 110
ER -