The method used to arrive at this conclusion is really more fascinating than the answer and provides, perhaps, a view into the ways Big Data will in the future be used to understand all types of consumer preferences to inform marketing decisions and how the information trail we all leave behind online and in our driveways enlightens artificial intelligence (AI). Researchers recently reported how they taught and then used AI to scrutinise 50 million Google Street View images to find 22 million cars to build more than 2,600 automobile categories to find out if you voted Democrat or Republican. The idea was to learn if socioeconomic status and political persuasion could be gleaned from identifying what was parked in your driveway. Two weeks after putting the question to the AI, researchers could accurately predict if a community would vote Democrat or Republican just by looking at parked cars. Communities with a preponderance of sedans had an 88% chance of voting Democrat; neighbourhoods with extended cab pick-ups had an 82% chance of voting Republican.

While this may have some potential positive benefits like decreasing healthcare costs and nudging you to eat better foods, exercise more and use cheap preventive health care services - it is rife with diagnostic accuracy problems at this time considering the high rate of false positives, bad data, patterns that mean nothing, correlations that do not equal causation, and discounting genetic and other factors. Human physiology is a high causal density environment and assessing overall health is tricky even for trained physicians.