From the course: Threat Modeling: Information Disclosure in Depth
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Interpretation
From the course: Threat Modeling: Information Disclosure in Depth
Interpretation
- It's easy to glide through the data to the data indicates to the data shows. Let's say you have access to lots of phone call logs. You might be tempted to infer that someone who repeatedly calls a suicide prevention hotline is suicidal, but it might not be about them. They might be looking for help dealing with a loved one. There was an interesting demonstration of the gap between data and a story in a spat between Tesla and the New York Times. Undisputed is that a reporter ran out the battery of a review loaner car driving around the parking lot. Tesla claims that the reporter did so intentionally. The reporter claims to have been looking for the chargers. The data is published. The reporter's initial story was negative. What really happened? I don't know. And more importantly, the data doesn't tell us. There are lots of cognitive biases that make this sort of thinking easy. And confirmation bias means it happens a…
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