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 (AI) systems. As a result, AI systems have become ubiquitous, with their application prevalent in virtually all sectors. However, AI 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 AI governance practices in ethical AI systems. Therefore, AI development methods are encouraged to foster these practices. This research analyzes the ECCOLA method for developing ethical and trustworthy AI systems to determine if it enables AI governance in development processes through ethical practices. The results demonstrate that while ECCOLA fully facilitates AI 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.

With Clear Intention—An Ethical Responsibility Model for Robot Governance

“…(2) security-adaptability and adversarial robustness; (3) privacy-IP capture and impacted users; and (4) transparencyexplainability and intent. These stable factors resonate with contemporary ethical AI principles, guidelines and methods (see e.g., Vakkuri et al, 2020;Agbese et al, 2021;Halme et al,…”

“…Discourse ethics is invested in communicative rationality, examining moral insight and expressions of normative validity (Habermas, 1990(Habermas, , 1991. Thus, communication is seen as key to building and sustaining ethical practice, it can also be witnessed in contemporary approaches to ethical design and ethical AI development (e.g., Baldini et al, 2018;Vakkuri et al, 2020;Agbese et al, 2021). In particular, this communicational factor is pronounced in some key facets of AI ethics-explainability, transparency and understandability.…”