| I want to react to 'the long tail can and should be handled by humans' and I find this thinking counter-productive and dangerous. Humans are excellent to handle the long-tail when they're already handling the rest. Take driving. We're already seeing cars with large cognitive assistance, taking more and more an active role in 'easy' tasks. Think Tesla's autopilot. You're supposed to be there and 'take over' in case the 'machine' fails to handle the 'long tail' or decides to give you the responsibility of whatever happens next (because you trained it to do so). Driving is a very complex task, you need training, experience, anticipation and (very important) context. There's no easy way to scramble all the details necessary for a decision in a human brain in the time to take the decision 'correctly'. Similar problem for industrial automation where you call the 'long tail' person once in a while and that person probably doesn't have the expertise of reconstructing the context, after 3 turnover phases in your provider. I think we're taking this problem the wrong way, and aiming for the lower fruits, and higher and higher, while handwaving the long tail and sending it over the fence to the human. We should be putting the human at the center of this, and extend their capabilities, reduce the repetitiveness, help, not take over. The paper I like a lot on this is 'automation should be like Iron Man, not like Ultron'. |
The earlier group often says since Edge cases that they can't automate now constitute only <5% of training scenarios they encounter, they've automated 95% of the job. But with what you're saying, we can't really expect the calculus to work that way.