Learning Without Theory
CAMBRIDGE – How can we improve the state of the world? How can we make countries more competitive, growth more sustainable and inclusive, and genders more equal?
One way is to have a correct theory of the relationship between actions and outcomes and then to implement actions that achieve our goals. But, in most of the situations we face, we lack such a theory, or if we have one, we are not sure that it is correct. So what can we do? Should we postpone action until we learn about what works? But how will we learn if we do not act? And if we act, how can we learn whether we did the right thing?
The Contradictions of Chinese Capitalism
Introducing PS On Point.
Making sense of a world of conflict and conflicting ideas.
New advances in machine learning and biological anthropology are shedding light on how learning happens and what makes a learning process successful. But, while theories are important, most of what we learn does not depend on them.
For example, there may be a theory of what makes a cat a cat, but that is not how toddlers learn to recognize them. As Harvard’s Leslie Valiant argues in his 2013 book, we learn the concept of “catness” in a theory-less way by inferring it from a set of pictures of animals that are appropriately labeled as either cats or non-cats. And the more examples we see, the more we become “probably, approximately correct.”
We learn to recognize the spoken language without knowledge of linguistics, and voice-recognition software uses a theory-less learning algorithm called a “hidden Markov chain” on a set of audios and their texts, rather than by using linguistics, as Ray Kurzweil tells us in his book How to Create a Mind. To the chagrin of many of us academics, theory is often dispensable.
…click on the above link to read the rest of the article…
