99.9% right isn't great: that means 1 in 1000 is bad. If this were a medical condition, that'd be a pretty high rate. I work with large-scale testing, and we u

99.9% right isn't great: that means 1 in 1000 is bad. If this were a medical condition, that'd be a pretty high rate. I work with large-scale testing, and we use a measure called "DPPM", or Defective Part Per Million (manufactured). For my team, a DPPM in 10s is noise/acceptable loss, ~100 we keep an eye on, and 100s-1000 is cause for investigation. Going back to percentage, that translates to 0.001% fail-rate is noise, 0.01% we keep an eye on, and 0.01-0.1% is cause for investigation (and 1% is "Stop The Line"). My point is that the "percentage" scale of failure/risk is one tuned to human perception: "1 in 100 is nothing!", but at the scale of events that we deal with in many areas of our modern life, it's actually huge. Or: don't use humans for dealing with large numbers. Alternatively, exercise them with the occasional positive result to keep them on their toes.