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Is the AI system's task clearly defined, with well-scoped objectives and boundaries?
Is the AI system's task clearly defined, with well-scoped objectives and boundaries?
- Is the problem you want to solve well defined? Are the system's goals specific and measurable?
- Are the possible benefits clear and aligned with the intended use?
- Clearly defining the AI system’s task and intended purpose helps set boundaries for design, training, deployment, and oversight.
- A vague or evolving objective may lead to scope creep, misaligned optimization, or unintended consequences. This is especially critical in high-risk use cases where safety, fairness, or legal compliance are required.
- The intended purpose must also be documented and traceable throughout the lifecycle, this is essential for risk classification, legal accountability, and effective stakeholder communication (e.g., users, regulators, auditors).
If you answered No then you are at risk
If you are not sure, then you might be at risk too
Recommendations
- Clearly define the problem and outcome you are optimizing for.
- Assess if your AI system will be well-suited for this purpose.
- Always discuss if there are alternative ways to solve the problem.
- Define success. Working with individuals who may be directly affected can help you identify an appropriate way to measure success.
- Make sure there is a stakeholder involved (product owner for instance) with enough knowledge of the business and a clear vision about what the model needs to do.
- Have you considered using analytics first? In this context analytics could also offer inspiring views that can help you decide on the next steps. They can be a good source of information and are sometimes enough to solve the problem without the need of AI/ML.