No open-access location is known for this record yet.
No open-access location is known for this record yet.
Abstract This article discusses the critical need to find solutions for ethically assessing artificial intelligence systems, underlining the importance of ethical principles in designing, developing, and employing these systems to enhance their acceptance in society. In particular, measuring AI applications’ adherence to ethical principles is determined to be a major concern. This research proposes a methodology for measuring an application’s adherence to acknowledged ethical principles. The proposed concept is grounded in existing research on quantification, specifically, Expert Workshop, which serves as a foundation of this study. The suggested method is tested on the use case of AI-enabled Credit Scoring applications using the ethical principle of transparency as an example. AI development, AI Ethics, finance, and regulation experts were invited to a workshop. The study’s findings underscore the importance of ethical AI implementation and highlight benefits and limitations for measuring ethical adherence. A proposed methodology thus offers insights into a foundation for future AI ethics assessments within and outside the financial industry, promoting responsible AI practices and constructive dialogue.
Loading…
Stored only when both papers are in the corpus — 11 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.