People Powered Supervised Training Algorithms: Google Does it Again?

If you ever do a course on artificial intelligence or machine learning, you are likely to presented with the idea of supervised learning. In a supervised learning algorithm, training examples are presented to a system being trained to perform some sort of classification task, along with information about the class that the training example falls into. The learning algorithm uses this desired output to reward the classifier if it produces the correct output classification for a given input, or punish it otherwise. (The strength of the reward/punishment may also depend on how close the actual output is to the desired output for a given input.)

Machine learning algorithms like these have been used for a long time in the context of machine learning, but what do you do you training set does not contain examples of the the correct answers? How then can you supervise the training of the system?

In the GWAP – Games With a Purpose [PDF] – approach pioneered by Luis von Ahn, people are used to provide the training signal (von Ahn also calls this approach Human Computation…)

Whenever you use the Google search engine, you potentially contribute to the training of the Google search algorithm. Each click on a result can be used to train the search algorithm that result (or that advert) is potentially a good match for the current search term.

Recently, Google bought ReCaptcha, publishers of a popular system for checking that there’s a human on the end of a browser by presenting them with two hard to read words and getting the user to type them in. The clever thing about ReCaptcha is that the machine itself doesn’t necessarily know what one of the words says – it’s using the human to teach it. But you knew that already right? After all, Charlie (aged 14) does…

So when I saw Google’s new toy – Google Building Maker – announced today, watched through the promo video:

and even had a play, I saw it not as “a very smart way for Google to enhance the 3D experience in Google Earth” (ReadWriteWeb) or as “crowdsourcing building making to their users” (TechCrunch), I saw it as a way of helping train Google image processing edge detection algorithms so that they can automate the creation of 3D models from multiple satellite images…

If you try out Google Building Maker, you’ll soon see how it could even start to use the information gathered from your own models in the first few images presented to you to start suggesting where to place the lines in the later images…