The future will involve artificial intelligence, but (in case you weren't already cautious) we need to be very careful what data we feed into these systems. A team led by computer scientists from MIT examined ten of the most-cited datasets used to test machine learning systems and found that around 3.4 percent of the data was inaccurate or mislabeled. Some have been cited over 100,000 times in machine learning research. Some of the errors are bigger than others, but include mistaking Bruce Springsteen for an orchestra and mislabelling a baby as a nipple. These errors could have huge ramifications for machine learning systems unless addressed. It may still be the early days of artificial intelligence, so we might want to check its homework.