From the course: Data Ethics: Making Data-Driven Decisions

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Trace your black box decisions

Trace your black box decisions

From the course: Data Ethics: Making Data-Driven Decisions

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Trace your black box decisions

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- Remember that in algorithmic decision traceability, the two biggest challenges are accessibility and comprehensibility. You have to figure out if you have a moral obligation to give people access to the data and your decision making, then see if you have an obligation to help them understand it. The biggest challenge around comprehensibility, or understanding the data, is the widespread use of machine learning. Machine learning is when a machine looks at data and makes decisions based on different patterns. In the past, people at your organization would typically make explicit decisions. So a health insurance company might say that you have higher health risks because you smoke. You might also be seen as a higher risk because your parents have a history of disease. A human made each of these decisions. They might have even created a way to measure this, like a health score. They bumped you up and down based on the…

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