Final answer:
Ethical predictive models must prioritize accuracy, fairness, and explainability to align with ethical standards, facilitate trust, and ensure unbiased, understandable outcomes that are based on empirical evidence and SMART criteria.
Step-by-step explanation:
For building an ethical predictive model, our goals should be focused on ensuring that the results are Accurate, Fair, and Explainable. Accuracy is crucial as it ensures that predictions closely match real-world outcomes. Fairness is important to prevent biased outcomes that could disadvantage specific groups. Explainability allows us to understand the model's decision-making process, which is necessary for trust and ethical considerations. Predictive models must also be able to be tested and proven wrong, provide measurable results, and be based on empirical evidence. Moreover, such models need to be SMART, meaning they should be Specific, Measurable, Achievable, Relevant, and Time-bound.