Greg Conti and Woody Hartzog dwell on the possible advantages and disadvantages for the society given that law enforcement gets increasingly automated.
Greg Conti: So, clearly, there’re advantages to this, but there’re certainly disadvantages as well, and it really depends on your perspective: are you the subject, are you the law enforcement agency, or are you the judicial system? So we’re going to roll though some examples.
Some would argue that these systems provide a more secure society and a safer society. They clearly have the potential, in theory, to offer increased efficiency, and for some they’ll be financial incentives (see right-hand image). And really, what underlies this, I believe, is incentives. Who’s motivated to employ these systems?
They have the potential to reduce bias (left-hand image), and depending on where you’re coming from, that may be a good thing. For example, there is some great research literally called Driving While Black that shows bias of police officers. There’re also stop-and-frisk activities in certain parts of the country.
There can be protection from abuse, or these systems can be abused, so it depends on your perspective. And if you go back and look at the history of various countries around the world, none are without their blemishes.
And certainly there’re false positives (see left-hand image). If any of you have seen ED-209 from movies, where in Robocop they’re demonstrating the robot: point your gun at 209, and then response: “Please put down your weapon.” He puts down the weapon, the robot responds: “You have 15 seconds to put down your weapon”, and after time runs out: “I’m now authorized to use physical force.” Things don’t end so well.
And there are also false negatives, and this is a classic example from Google Street View (see right-hand image). This individual could be doing exercise or could have lost his keys, but these systems could see a crime could be occurring and could miss it. We argue that’s probably better than a false positive in most cases.
A key component is the identification of the people in the pictures. Well, historically we’ve had issues with improper identification or incorrect identification. A classic example is Senator Ted Kennedy, who got held up at the airport for being on a terrorist watchlist (see left-hand image).
The results of this could be a less complying populace, because we as citizens have to agree; it’s a contract, we have to agree to support the law, to believe in the law on some level. If you take that decision-making out of people’s hands, there can be problems.
And there’s always the risk of unproportional response, that the system will respond in a way that’s inappropriate, and this is a Texas speed trap motivational poster, a chain gun (see left-hand image). And clearly, this has the ability to enforce social control on a larger scale, particularly as we move forward. It really depends on whether your local politicians want you to have 32-ounce sodas or not, or a variety of other activities, they can force it with automated means.
Some won’t like the loss of power – yes, and that’s Batman (see right-hand image), and it turns out Batman was pulled over for incorrect plates, but he was actually going to a children’s hospital and his plates were expired, so they let him go. But it was a good picture, so I thought I’d include it. But law enforcement and, I assume, some in power, like the professional courtesy, perhaps that the current law enforcement system provides to them. Well, they might not enjoy that loss of power if you have an unbiased automated law enforcement system. And there’s a nice example of Montgomery County Police Department in Maryland photographed speeding past the camera with their extended middle finger.
The unions and other police-related organizations will certainly have something to say, because efficiency could very well mean lost jobs. There are many questions necessary as we move forward in this area; I will be followed by Woody.
Woody Hartzog: So, what can we do? Chances are that we’re not going to see full automation overnight. It’s going to happen piece by piece. It’s going to automate a little bit on the surveillance side, and maybe a little bit on the decision-making side. And we think that the appropriate response is to start asking questions now, to start demanding answers in that if a system is going to be implemented it will be implemented responsibly, and there are some things that need to be attended to if that’s going to happen (see right-hand image).
So, for example, the method of implementation: are they going to use the sensors that we’re carrying around on our bodies, or are they going to mandate that everyone install a government brand sensor. Control: who gets control over the enforcement system? Is it going to be low-level administrators? Is it going to be third parties, perhaps, software vendors that create the code? And if so, what kind of influence are they going to have over the decision making process? Because ultimately, if they’re the ones writing the code, they are the final stop in interpreting law, and there are some potential problems with that.
Legal integration of algorithms: are we going to reach a point where there’s going to be an incredible incentive to personalize the law? So, for example, if I’m a very good driver, I can perhaps drive 10 mph over the speed limit because I’ve been proven to be trustworthy, whereas someone who has a horrible driving record perhaps only gets about 5 mph. And they should perhaps be able to integrate all kinds of algorithms that will be able to determine that.
Do you stop the violation before it happens or do you wait until after it happens and then give a fine? That may seem like a simple question, but I think that the political pressure could be great when these systems are already implemented and entrenched, for someone to say: “You can’t stop the crime; if you can stop the violation of the law, why wouldn’t you stop the violation of the law?” But I think there are significant problems with preemptive enforcement of the law.
System error and malfunction: how much error are we willing to tolerate in a system? No system is without error, we’ve got to make the decision: “Well, if it’s only got a 5% error rate, then that’s good”, or 10%, or 15%, and we need to determine who makes that call.