Policy on Education

Education is at the forefront of change. Ways to learn are expanding and improving. Ways to evaluate learning are under strain, and are being forced to return to individual personal interaction. What we need to learn is about to make an historic shift.

To learn about anything, from cleaning mould in grouting to higher mathematics, there are wonderful videos explaining them clearly. But we only learn by doing. There are places where you can learn by doing. A nice one is at BBO (Bridge Base Online) teaching declarer play. But there isn't yet one for defence at Bridge, which is a cooperative activity. What is surely coming is AI systems that watch what you do, in the real world as well as online, and uses that to determine the gaps in your knowledge, and recommend ways to bridge those gaps.

Even before AI, using unsupervised homework for evaluation was unacceptably prone to cheating. The rise of AI has made that problem worse. A rough remedy is to have tutoring staff interview the student about their submission. An obvious step is to train AI to do that interviewing, but it would need to happen in a controlled environment. In the previous paragraph, I speculated on education by AI watching attempts at learning by doing. It is tempting to think that that could be combined with evaluation, but that would then be a bad learning experience, or a bad evaluation method, or, very likely, both.

I suggest that Australia should put its main effort into providing curriculum development with a trusted evaluation system. It should unambiguously link a person, with multiple biometric identifiers, to an unfakeable evaluation result for a specific curriculum. It should provide education for that curriculum, but people should be able to just pay for the evaluation and get their training elsewhere.

Which brings us to the question of what we should teach. Historically some people get to give orders while most of us get to receive them. So training to give orders and manage the people carrying out the orders was an elite role. The future will be different.

Everyone will manage AI things which: (a) know a lot; and (b) are good at reasoning. However the intelligence of these things is not human. They lack empathy, and they lack their own motivation. Dealing with them is an important skill that everyone will need to learn.

The useful skill that AI has now is coding. But to take advantage of that you have to know exactly what you want to create, and you have to express the instructions in clear unambiguous English. This is far from easy. Indeed, though coding is not trivial, it has never been the hardest part of getting computers to do useful things.

So coding is where we start with educating people to use these alien intelligences. But soon enough everyone will need to extend this capability into every area of life. Whether we want the dishes washed or to build a skyscraper or design a machine to do some task, managing and coordinating intelligent machines will be the way it is done. You have to take advantage of the machine's wide knowledge and reasoning ability, but it doesn't understand the human needs that we are meeting, though it is very likely that it thinks it does.

We expect that everyone will be able to get more done, but to do that correctly and successfully means that they have to understand a lot. That is the challenge of future education.