Final answer:
An ethical, evolved predictive model should mimic the ability of a researcher to eliminate bias, using cognitive skills and heuristics similar to the scientific method of observing phenomena, proposing hypotheses, and conducting experiments to confirm them.
Step-by-step explanation:
An ethical, evolved predictive model would need to mimic a researcher’s ability to eliminate bias. This involves using techniques that help reduce the influence of preconceived notions or prejudices in the design, implementation, and interpretation of data and models. Predictive models incorporating machine learning or artificial intelligence should be designed to use cognitive skills to make decisions, much like a human researcher would when scrutinizing a hypothesis.
Researchers often utilize heuristics and cognitive skills during the scientific process; they observe natural phenomena, infer and propose hypotheses based on objectivity, and design and perform experiments that produce empirical evidence to support or refute their hypotheses. The goal is to reach conclusions that are as accurate and unbiased as possible, and an evolved predictive model should aspire to do the same. To achieve this, developers may use accuracy nudges to crowdsource falsity labels so that algorithms can learn to identify incorrect information and thereby minimize bias further.