As it says about itself, this book is truly written for an audience that knows little about modern science. In that context, it does a reasonable job at invoking the wonder that science can bring.

The scientific ideas and discoveries it touches on are mostly approached via their human scientists and their stories. It felt as if the book was dancing around the scientific subject matter itself. It reminded me of scientists writing in newspapers, where there is little space to elaborate, and an audience too general to make meaningful assumptions on their prior knowledge. Seeing it from that perspective, I think these seven lessons are actually very nicely constructed.

It makes me wonder how the seven brief lessons on computer science would be written. Could I write a riveting short text that invokes the feeling of understanding of ideas in computer science, while at the same time it remains approachable to an audience like readers of the weekend's supplement of a large newspaper. And which topics should it discuss?

Some ideas (also see Wikipedia):

The internet

Briefly touch on its inception at American research institutes, and then try to convey the amazing feat of so many computer networks around the globe being interoperable. Give a high-level intuition on the hierarchy of autonomous systems. Touch on the idea of an IP packet.

Could we include more human perspectives on this story? Find more people who developed this and tell their stories with a slightly dramatized arc?


Give an intuition for how computation using binary digits works. Introduce the concept of the Turing machine. Extrapolate to modern computer systems and architecture.

Artificial intelligence

I have the feeling that there are many such weekend-newspaper-introduction to the concept of AI already, because of it huge scientific leaps in the last few years. But when I tried to find some, I mostly ran into articles on what can this specific AI do and how does it help you as an ordinary human?

Anyway, a dramatized explanation would include the initial research efforts, the AI winter, and then the reinvigoration in the past decades. It would try to give an intuition for probabilistic methods, statistical learning methods, and artificial neural networks.