Intelligence agencies are sitting on large volumes of raw data. Now they are banking their data processing hopes on artificial intelligence to make sense of it all.
For example, even well before the age of Big Data, J. Edgar Hoover collected and recorded information by hand beginning in the 1920s.
After over half a century of amassing information, the next step will be to organize it, because what good is having all of that data unless you know how to use it?
How will these agencies start to organize this information into actionable intel?
Using AI and Social Media
According to Dawn Meyerriecks, the CIA’s deputy director for science and technology, the Agency has 137 projects directly related to artificial intelligence (AI).
Most of these projects are being done collaboratively between the Agency and developers in Silicon Valley.
The projects range from predictive models for future events using big data to automatic object tagging in videos.
These programs will allow the CIA to better sift through information gathered.Intelligence Agencies are using AI and Social Media to gather & process DataClick To Tweet
AI is not only changing the way intelligence agencies process data but also how they gather it.
Collecting data from social media by intelligence agencies is nothing new. What is new, is how they are able to scale it enormously with the aid of these AI programs.
In fact, data gathered from social media presently makes up a huge percentage of overall data collected.
8 million Potential Jobs Lost?
In a speech given by the director of the National Geospatial-Intelligence Agency, Robert Cardillo at GEOINT 2017, he said:
“If we were to attempt to manually exploit the commercial satellite imagery we expect to have over the next 20 years, we would need eight million imagery analysts,”
Cardillo said this as a remark to the anticipated exponential increase in the amount of data that can be collected with advancements in satellite and signals intelligence collection technology.
As a response to this inevitable possibility, his goal is to automate 75% of the work of analysts and will rely heavily on AI to achieve this goal.
However, we shouldn’t worry about automation killing these jobs. Instead, it will elevate these analysts to supervisory roles vs. menial data crunching.