I have been involved in secondary school computing since its earliest days. I took a full-year course in computer math at my public high school in 1962 and had a full-time computer terminal in my college dorm room in 1967. I then joined Digital Equipment Corp. where I installed small timesharing systems in both high schools and colleges.A turning point for me came in 1985 when I joined Thinking Machines Corp. and encountered scientists, including Stephen Wolfram, who were doing their science in seemingly bizarre bottom-up and parallel ways. Understanding these new habits of thought and their potential impact on the history of ideas has been my focus ever since. My 1996 book After Thought (Basic Books) chronicles three eras of computational thinking, starting with the circles and lines of ancient Greece and culminating with the neural networks of today. The assertion that these learning algorithms will compete with numbers and equations for the starring role in 21st century science was controversial in the nineties. Less so today.
The new prominence of "deep learning" has only reinforced my belief that kids need to understand this stuff. College is too late and physics class is too narrow. Thw way computers are learning how to learn is eye-opening for all of us, poets and proteomists alike. Hence my current interest is making neural networks teachable right in the K-12 curriculum. I am a graduate of Brown University and a member of Phi Beta Kappa.