James Gleick’s “The Information: A History, a Theory, a Flood” was the pick for this month’s Knewton book club. The book covers the history of information — from the invention of scripts and alphabets to the Morse code and the arrival of the Information Age. We’ll be posting reviews throughout the month; read others here.
One of the most impressive things about “The Information” is how dynamic it feels as it covers the same ground again and again. We see a wide variety of characters (including Charles Babbage, inventor of the first great mechanical computer and Ada Byron, the world’s first programmer), scattered through history, briefly grasp an aspect of the nature of information, and use it to tremendous effect. The epiphany is almost always a variation on the same theme: when we separate the sign from the signified (the symbol from what it means), the former becomes light, swift, and malleable and lends itself to experimentation and discovery.
These ideas have ramifications for the field of data science, which is concerned with testing and analyzing data. On the adaptive learning team here at Knewton, a lot of what we do is abstraction. As we work, we ask ourselves questions like the following: in what ways are a video about fractions and a paragraph about analogies different versions of the same thing? Is the relationship between a book and a chapter similar to the relationship between a quiz and a question? If we use data to recommend study groups in which students teach each other, where exactly do we draw the line between a student and a teacher? These questions could come off as trivial, esoteric, or even disruptive, but for us they are the key to linking, comparing, and understanding the huge range of learning experiences with which our work puts us in contact.
At the same time, it’s possible to take abstraction too far. The last 10 years are full of examples, from the financial crisis to no-fly lists, in which separating data too completely from the reality it represents has caused great harm. As we begin using our models to help shape the learning process, one of our top priorities is to maintain close relationships with the students and the educators affected. With their feedback, we can strike the right balance between freeing information, so that it can be used in new ways, and keeping our feet on the ground regarding what’s actually happening in the classroom.