Some quick points: The computer doesn't "read" the essays in any ordinary sense. It simply learns to classify them. How does it do that? It's trained. First, expert human readers grade a largish number of essays–in the hundreds. Then then computer examines what the humans have done, noting the features that characterize the A essays, the B essays, and so forth. It then takes those characterizations and applies them to essays it is given.
It is not useful for grading seminar papers or creative writing courses. It only makes sense in large courses where students are writing relatively circumscribed essays on the same topic.
And then there's this:
Machine learning gives us a computer program that can be given an essay and, with fairly high confidence, make a solid guess at labeling the essay on a predefined scale. That label is based on its observation of hundreds of training examples that were hand-graded by humans, and you can point to specific, concrete features that it used for its decision, like seeing webbed feet in a picture and calling it a duck.H/t Tyler Cowen.
Let’s also say that you can get that level of educated estimation instantly – less than a second – and the cost is the same to an institution whether the system grades your essay once or continues to give a student feedback through ten drafts. How many drafts can a teacher read to help in revision and editing? I assure you, fewer than a tireless and always-available machine learning system.
We shouldn’t be thinking about this technology as replacing teachers. Instead, we should be thinking of all the places where students can use this information before it gets to the point of a final grade. How many teachers only assign essays on tests? How many students get no chance to write in earlier homework, because of how much time it would take to grade; how many are therefore confronted with something they don’t know how to do and haven’t practiced when it comes time to take an exam that matters?