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

被引:5
|
作者
Ortega-Bolanos, Ricardo [1 ]
Bernal-Salcedo, Joshua [1 ]
Ortiz, Mariana German [3 ,7 ]
Sarmiento, Julian Galeano [2 ]
Ruz, Gonzalo A. [3 ,5 ,6 ]
Tabares-Soto, Reinel [1 ,3 ,4 ,7 ]
机构
[1] Univ Autonoma Manizales, Elect & Automat Dept, Manizales 170001, Caldas, Colombia
[2] Univ Nacl Colombia, Dept Math & Stat, Manizales 170001, Caldas, Colombia
[3] Univ Adolfo Ibanez, Fac Engn & Sci, Santiago 7941169, Chile
[4] Univ Caldas, Dept Syst & Informat, Manizales 170001, Caldas, Colombia
[5] Ctr Appl Ecol & Sustainabil CAPES, Santiago 8331150, Chile
[6] Data Observ Fdn, Santiago 7510277, Chile
[7] Univ Adolfo Ibanez, Sch Govt, GobLab, Santiago, Chile
关键词
Artificial Intelligence; Responsible development; Governance; Ethics of AI; Machine learning; AI life cycle; ARTIFICIAL-INTELLIGENCE; DILEMMA;
D O I
10.1007/s10462-024-10740-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:30
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