Value elicitation and normative uncertainty
Value elicitation is the process of identifying and clarifying what individuals or groups consider important, often to guide decisions or policies. Normative uncertainty arises when there is doubt or disagreement about which values, principles, or moral rules should apply in a given situation. Together, these concepts highlight the challenges in decision-making when both the relevant values and the correct ethical framework are unclear or contested, requiring careful reflection and dialogue.
Value elicitation and normative uncertainty
Value elicitation is the process of identifying and clarifying what individuals or groups consider important, often to guide decisions or policies. Normative uncertainty arises when there is doubt or disagreement about which values, principles, or moral rules should apply in a given situation. Together, these concepts highlight the challenges in decision-making when both the relevant values and the correct ethical framework are unclear or contested, requiring careful reflection and dialogue.
💡 Key Takeaways
- Understand what value elicitation is and why it matters for AI design and policy
- Identify stakeholders and the values they bring to AI risk decisions
- Define normative uncertainty and how it affects choosing principles in AI
- Explore approaches to resolve value conflicts and manage normative uncertainty in ethical AI governance
❓ Frequently Asked Questions
What is value elicitation in AI ethics?
Value elicitation is the process of identifying and clarifying what people or groups consider important, to guide AI design, policy, and governance. It uses methods like surveys, interviews, and deliberation to surface priorities and trade-offs.
What is normative uncertainty and why does it matter for AI?
Normative uncertainty is doubt or disagreement about which values or moral rules should apply in a situation. It matters for AI because systems may need to operate under contested norms, affecting fairness, accountability, and legitimacy.
How can value elicitation inform AI design and policy?
By engaging stakeholders to surface values and trade-offs, value elicitation helps set requirements, guide governance frameworks, and influence risk assessments so AI aligns with societal priorities.
What strategies address normative uncertainty in AI?
Strategies include deliberative forums, multi-stakeholder participation, scenario planning, robust decision-making, and sensitivity analyses to explore how different values affect outcomes.