Governance of Ethical and Trustworthy Al Systems: Research Gaps in the ECCOLA Method

Abstract

Advances in machine learning (ML) technologies have greatly improved Artificial Intelligence (Al) systems. As a result, Al systems have become ubiquitous, with their application prevalent in virtually all sectors. However, Al systems have prompted ethical concerns, especially as their usage crosses boundaries in sensitive areas such as healthcare, transportation, and security. As a result, users are calling for better Al governance practices in ethical Al systems. Therefore, Al development methods are encouraged to foster these practices. This research analyzes the ECCOLA method for developing ethical and trustworthy Al systems to determine if it enables Al governance in development processes through ethical practices. The results demonstrate that while ECCOLA fully facilitates Al governance in corporate governance practices in all its processes, some of its practices do not fully foster data governance and information governance practices. This indicates that the method can be further improved.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 18 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.