Since we’ve started this class, I’ve been more aware of digital trends and applications, and I’ve noticed something interesting. If there is a problem in the world, chances are people are trying to solve it using some sort of digital solution.
Don’t want to get up to turn the lights out? The Clapper!
Can’t figure out how to vacuum your carpet? Roomba!
This brought me to think about some other problems in our lives (a little more seriously than a vacuum). I remember reading an article a few years ago about a security review the TSA conducted. Undercover Federal Agents tested airport security strength by running 70 tests to avoid detection. They carried weapons, contraband, and mock bombs while going though pat-downs and scans. Guess how many times they were successful. 67. That’s right, 95% of the time, airport security failed to detect a threat.
So this got me thinking. With a massive budget, $40 Billion for Homeland Security in total, this seems like a prime opportunity for a large investment in digital solutions. The article did say that this was due to both human and technological error, but not to what extent and not to what the mix was. An advancement in technology will obviously help the error rate but I think human error is the telling part of this story.
A great example of human error is the cause of plane crashes. Boeing estimates that 80% of plane crashes are caused by human error. As a former professional pilot myself, I can tell you it’s because of two reasons: tactical and operational human errors. Tactical human errors would point to poor decisions because of fatigue or lack of experience and operational human errors involve poor flight instruction or training.
The main points of human error: “poor decisions” “lack of experience” “poor instruction” “poor training.” Sounds like this could apply to the TSA story above, doesn’t it?
How do you fix human error? Easy actually. Take the human out of it. As it turns out, Homeland Security is already working on it. In June of this year, the department announced that it is working with Google to build computer algorithms that can automatically detect and identify concealed items in images captured by body scanners. It’s a contest actually. A total of $1.5 million dollars is being put up as the prize. Crowd sourcing you say? Sounds familiar.
Neural networks seem to be the best solution for this problem. The basic idea of a neural network is that it can learn to do tasks without task specific programming. If you feed images into a neural network that are labeled “gun” or “not gun,” eventually the neural network will be able to identify pictures of a gun. For this contest, Homeland Security has provided 1000 three-dimensional body scan images for the data scientists to train their algorithms. Down the road, if this goes live, over 2 million people are scanned at checkpoints every day in the US – that’s a lot of learning.
The TSA has also commissioned a team to work on this problem from Duke University. They’re using a neural network structure as well. An interesting point that they repeat several times is that they’re not trying to totally replace humans in the security process; augment and reduce the workload. Going back to tactical human errors, I know from experience that boredom and task saturation are huge causal factors when you find yourself in a bad situation.
The article describes the boredom portion: “A human today has to focus on the whole image—most of which is not a threat, but the human has to look at everything,” Carin said. “It can get quite monotonous to see the same basic luggage images one after the other, and that makes it very difficult for a human to focus and pay attention all the time for that rare event where a threat is present.”
On the flip side, I imagine there is an immense amount of pressure to get people through security quickly, especially at peak times. This would be the task saturation part. When you move quickly and have multiple items to look for, you’re bound to miss something.
So, baby steps. I think the best idea is to augment current TSA employees and eventually, maybe we’ll get to the point of total automation.
In closing, I think about digital maturity. While Homeland Security is not a “company” per se, they need to have a digital culture if they want to improve operations. I would describe them as “Early,” moving into “Developing” digital maturity. We’re seeing some enterprise-wide efforts but I’m not so sure that their organization is very cross functional or their adoption of digital technology internally is very high. On the other side though, they are making investments – and talking about making investments. I think the roadblock here is that they have to contract out most or all of their projects which makes this a very top-heavy decision model.
We’ll see. The government is large and bureaucratic. Let’s hope they’re nimble enough to stay ahead of the threats.