It;s seems like artificial intelligence has been “10 years away” for the last 40 years. Back in the mini computer days every computer was custom and configurations were designed by people. I worked for a company that believed that configuring computers was beyond the ability of computer software. From there I went to a different company that was developing rules based artificial intelligence. Using a special language called OPS5 they wrote software that configured computers faster and more accurately than people. Rules based AI was dependent on people to know the rules and properly prognathism. Limitations became apparent.
Today we have machine learning which basically means the computer is developing the rules. Rules is probably not the best definition though. We’re starting to see AI grow into many more areas than ever before. Think self driving cars for example. It’s becoming clear that understanding the world today means understanding something about artificial intelligence. What does that mean for K-12 computer science education?
For now, most of the education is about AI. What it is. How it worse conceptually. What is it being used for. And, perhaps most importantly, what does AI mean for society and the future. The math and science of creating AI platforms s a bit too much for most high school students let alone younger students. That can wait. Although there are tools that exist that students can use for their own projects which is pretty cool.
I am very concerned about bias in artificial intelligence (Bias in Artificial Intelligence. Inequality, racism and discrimination is just one article you will find from an internet search for “Bias in artificial intelligence) Systems that do not recognize that people of color are actually people is only one example Bias against women or various other groups of people can be baked into AI systems if developers are not VERY careful.
Also, how is AI being used? Facial recognition and privacy have become areas of concern in many areas and applications.
These are more than just ethical issues, though ethics has got to be a core part of what we teach, as many other problems are unconscious bias or the result of innocent but false assumptions made by people who mean well but lack understanding of their own environment. Its a reason we need a lot more diversity is AI and CS as a whole. We have to teach students to think about these issues and to think beyond their own identities and beyond “the way we have always done it.”
Companies in industry are taking new looks at AI as well. One useful resource is Microsoft's framework for building AI systems responsibly - Microsoft On the Issues. The blog post talks about some issues Microsoft has faced and how they are addressing them. Companies are asking the “should me” question as well as the “can we” question. We need students to think about those questions from the start. The document itself is at Microsoft-Responsible-AI-Standard-v2-General-Requirements-3.pdf and makes interesting reading. It could start some class discussions as well.
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