Fundamental objectives of decision analysis include:
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Supporting rational choices
- Not finding “the right answer” but supporting better-informed decision-making- its objectives are therefore procedural as much as outcome-oriented.
- To acknowledge rather than eliminate uncertainty and ambiguity – it helps decision-makers to address them through a well-informed, well-structured and transparent process
Make values, trade-offs, and assumptions explicit
- Separating facts (what may happen) from values (what is preferred).
- Making trade-offs between competing objectives explicit.
This transparency is often more important than the final ranking or
recommendation
Improve quality of decisions
- Emphasis on decision quality, not outcome quality.
- A “good decision” is one that uses the best available information, reflects the decision-maker’s values consistently and follows a defensible reasoning process– even if the outcome later turns out badly.
Enable learning, deliberation, and insight
- Promoting structured thinking.
- Improving communication among analysts, experts and stakeholders.
- Supporting learning about what drives outcomes and where disagreements originate.
In participatory decision analysis, this learning objective is often as important as choice
Enhance accountability and justifiability
- Justification of decisions to others.
- Traceability of reasoning.
- Defensibility against critique.
- Especially important in public and environmental decisions.
Key Principles of Decision Analysis
- Focus on decision.
- Explicit structuring of the decision problem.
- Separation of facts and values.
- Explicit treatment of uncertainty.
- Internal consistency (normative coherence).
- Value-Focused Thinking (“What do we care about?” before “What should we choose?”).
- Conditional and context-dependent recommendations (never claims universal optimality).
- Human accountability and learning through exploration and (supports decisions rather than making them).
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Outcome of the phase: Understanding of the reasoning behind applying decision analysis.
Follow up Questions for the AI
Ask the following questions to gather more information from the AI:
- Can you elaborate the fundamental objectives and the key principles of decision analysis?
- Can you elaborate approaches for achieving these fundamental objectives and the key principles of decision analysis?
- Can you give examples of how these objectives can be observed in typical applications of decision analysis in environmental decision-making problems?
- Can you give examples of how [some specific objective or principle] can be observed in typical applications of decision analysis in environmental decision-making problems?
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Benefits and Risks of Using AI
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Benefits (++)
- Synthesizing and elaborating the fundamental objectives and the key principles of decision analysis.
- Explaining the complexity and key characteristics of the decision analysis.
- Providing examples of the realization of the objectives in typical cases of applying decision analysis in environmental decision-making.
- Understanding the possibilities and limitations of, and increasing awareness of the risks of using AI to support decision analysis process
Benefit Scoring: ++ Medium
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Risks (!)
- Superficial understanding of the problem and giving suggestions based on this limited understanding.
- Reduced critical evaluation of the possibilities of decision analysis. These are just objectives, but it depends on the practical application of the decision analysis how well they are achieved.
- Lack of analytical competence in judging which of the objectives are relevant in the case at hand.
Risk Scoring: ! Low
Questions to Better Understand the Benefits and risks of AI
Questions to make use of the benefits
- See the questions above
- How can AI support understanding the fundamental objectives of decision analysis and what are the main risks of using AI?
Questions to avoid the risks
- What are the typical pitfalls in the application of decision analysis that prevent reaching these objectives?
- How can the pitfalls be avoided in my case [with the case description given]?
Questions NOT to ask
- What are the best ways to reach the objectives of decision analysis?
AI can give reasonable answers, but if the decision context is not defined, the answers can be on too general level as all the approaches do not fit into all the cases