relational autonomy

Relational autonomy is a concept from moral and feminist philosophy that reframes traditional, individualistic notions of autonomy. It posits that an individual's choices and identity are not formed in a vacuum but are deeply shaped by their social relationships, cultural context, and community values. In AI risk management, this challenges the adequacy of 'individual consent' as a sole basis for legitimacy. It aligns with principles like 'Human Agency and Oversight' in the EU AI Act and the societal impact considerations in the NIST AI Risk Management Framework (AI RMF). It requires that AI impact assessments extend beyond the individual user to consider potential harms to families, communities, and social structures, thereby providing a more holistic approach to identifying and mitigating AI ethical risks.

Enterprises can apply relational autonomy through a three-step process. First, implement Expanded Stakeholder Engagement by including community leaders and representatives from marginalized groups in the AI design and review process, as guided by the NIST AI RMF's 'Govern' function. Second, conduct Community Impact Assessments that go beyond GDPR's DPIA to evaluate risks like group privacy violations and collective bias. For example, a fintech firm could model a credit scoring AI's impact on different ethnic communities to ensure approval rate disparities remain below a 5% threshold. Third, establish Collective Redress Mechanisms, allowing groups to report systemic harm. This approach can improve compliance rates and reduce the resolution time for risk incidents by an estimated 30%.

Taiwan enterprises face three key challenges: 1) a legal framework, like the Personal Data Protection Act, that focuses on individual rights, lacking clear guidance on 'group privacy' or 'community harm'; 2) training datasets that may underrepresent Taiwan's diverse communities, such as indigenous peoples and new immigrants, leading to biased AI models; and 3) a lack of standardized methodologies and interdisciplinary talent to translate abstract ethical concepts into measurable risk metrics. To overcome these, companies should establish an internal AI ethics committee, adopt frameworks like the NIST AI RMF for bias mitigation, and collaborate with experts to develop localized community impact assessment tools. A priority action is to form the committee within 3 months.

Winners Consulting specializes in relational autonomy for Taiwan enterprises, delivering compliant management systems within 90 days. Free consultation: https://winners.com.tw/contact