Google’s AI Wants to Get to Know You Better

Hungry for Data

Google’s years of searching on behalf of internet users has left the search engine with a tremendous amount of data that gives insight into what people want to know. Google has been utilizing this data to remain on the forefront of artificial intelligence and machine learning, and is using our search queries to make their algorithms more human. One of the most valuable insights into understanding human behavior is observing their financial data, and although Google have yet to delve into this realm of analytics, they are well aware of the value in doing so.

Machine Learning

Google’s AI involves a particular subset of AI called machine learning, which can broadly be defined as the use of algorithms that can learn on their own by taking in relevant data.

Google is trying to formalize intelligence in order to not only implement it into machines, but also understand the human brain, as Demis Hassabis explains:

attempting to distil intelligence into an algorithmic construct may prove to be the best path to understanding some of the enduring mysteries of our minds.”

Differentiating itself from other AIs like IBM’s Watson or Deep Blue, which were developed for a pre-defined purpose and only one specific function within its scope, DeepMind is not pre-programmed meaning it learns from experience, using only raw data as input.

How Does it Work?

You are all most likely familiar with CAPTCHAS, as you’ve probably had to complete them at one time or another while on the internet. Although primarily used to verify the user is human, there is a secondary use of CAPTCHAS that is arguably even more valuable than the former. The CAPTCHAS are an example of back propagation, meaning you are essentially verifying a machine’s estimate of what a picture is or what certain characters are. Newer CAPTCHAS may ask you to click on all the photos that contain cars; well, by doing this you have provided Google’s AI with data regarding what a car looks like, and therefore, the machine will be able to more accurately identify a car after receiving your input. Under this method, it does not take long for the machine to accumulate a massive amount of data that initially could only be provided by humans. After millions of inputs, Google’s AI is now capable of estimating the content of photos with higher accuracy than humans. This seemingly harmless method of improving accuracy has more serious implications when the data being inputted is more than just random characters.

What’s Next?

Earlier this year, a partnership was announced between Google and Citigroup in order to bring checking accounts to Google customers. Clearly, there is a lot of information to be gained by entering this field and Google is not going to pass that up. Other large tech companies are deploying similar strategies to amass as much consumer data as possible. Financial data is some of the most valuable and informative data available to corporations, and the integration of their technical services into existing systems is their golden ticket to the data they are looking for. The financial data will be endlessly consumed by Google’s AI in order to paint a picture of consumer behavior including spending habits, saving habits, and much much more.

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