Connecting data to the real world - The next sexy job?
Hal talked about his career in academia and at Google. He reminded us of the days when Google was still a small start up with no real idea about how they could actually generate revenue. At that time Eric Schmidt asked him to 'take a look' at advertising because 'it might make us a little money'. Thus, Hal got involved in Google's ad auctions.
|Hal Varian at the Royal Statistical Society conference 2012 |
Another projects Hal talked about was predicting the present. Predicting the present, or 'nowcasting', is about finding correlations between events. The idea is to forecast economic behaviour, which in return can help to answer when to run certain ads. He gave the example of comparing the search requests for 'vodka' (peaking Saturdays) with 'hangover' (peaking Sundays) using Google Insight.
A newer idea is to use consumer surveys as revenue stream for publishers and Google. As publishers are struggling to get paid for their content, surveys are one way of engaging with the reader. Instead of getting money directly from them you ask them for their views/data on a topic that someone else is willing to pay for.
So, the team of statisticians grew bigger and bigger over the years, as more and more colleagues sought their advice, and the little money turned into over $36.5bn of total advertising revenue in 2011. This may help to put Hal's famous 2009 quote "the sexy job in the next ten years will be statisticians" into perspective.
Robotics - the next sexy jobHowever, it was a question from someone in the audience at the end of Hal's talk which resonated with me most. The person refered to Hal's comment on statistician being the sexy job for the next decade. Three years have already passed since Hal's statement, the gentleman said, and hence he wanted to know if Hal would be willing to share what he thinks the next sexy job will be. "Robotics", Hal said without hesitation.
Hal argued that it becomes possible to connect data to the real world. As an example he mentioned the driverless car project at Google. Only a few years ago a driverless car had to learn everything about its environment using its sensors, while today driverless cars know what to expect thanks to information from Google Maps and Street View. So the car, equipped with GPS, anticipates in advanced when to expect a crossing, traffic light, etc.
I wouldn't be surprise if Hal had some ideas up his sleeves how to generate 'some little money' with robotics as well.