A video demonstration showing how HP’s photo tracking software doesn’t work with an African American. The video is pretty funny and a nice example of how technology is far from neutral (but instead can treat particular groups of people differently). Another similar example was how a voice recognition technology, developed in Massachusetts, wouldn’t work for people with a southern accent.
We are working with our partners to learn more. The technology we use is built on standard algorithms that measure the difference in intensity of contrast between the eyes and the upper cheek and nose. We believe that the camera might have difficulty “seeing” contrast in conditions where there is insufficient foreground lighting
This article investigates the surveillance dimensions of “intelligent transportation systems” in the United States, with a particular focus on the mediation of data by engineers in transportation control centers. These communication systems lend themselves to surveillance by means of “function creep” beyond their primary intended purposes and through the everyday collection and manipulation of data to manage mobilities. In the U.S., dominant system protocols privilege vehicular throughput and discipline those who deviate from that norm.
I found some interesting insights. First, these intelligent transportation agencies are very secretive. It is difficult to gain access to them (as an academic) and there is little written about their capabilities. Second, Torin discusses the significant surveillance capabilities these agencies wield. Obviously, it is intended that the surveillance be used for transportation and emergency needs. But Torin is able to tease out some examples of function creep, where these surveillance powers are used for other purposes, such as police work. A good read for people interested in transportation systems and the ever growing creep of surveillance.
The Urban Institute is conducting a study on the surveillance cameras in Chicago. Here is an article with their preliminary results:
Preliminary results from the study show crime has fallen in parts of both cities where the cameras are located. For example, violent crime and larcenies fell by 25 percent — or 30 incidents per month — in downtown Baltimore, starting in the fourth month after the cameras were installed in 2006, the study says. The cameras, according to the study, have helped identify suspects and getaway cars and find weapons used to commit crimes. “It has helped solve literally thousands of crimes,” Chicago police spokesman Roderick Drew said. “In fact, our detectives have reviewed over 20,000 video segments this year alone.”
The Urban Institute’s study, meanwhile, has found the cameras are not without their problems. When they automatically pan areas, they may capture only portions of a sequence of events. At night and during bad weather, they might not capture images strong enough for evidence. They are sometimes targeted by vandals. And their maintenance costs can be high.
I will be looking forward to the final study and its associated data. I don’t fully understand the results stated in the article. It took 4 months before crime fell? Maybe it was something other than the cameras?
Stephen Russell of 3VR Security recently gave me the chance to ask him some questions on smart cameras. He has posted his responses over at his blog, In Hard Focus. HIs responses are very informative and insightful. I urge all of you to read his full responses. Here are the questions I asked:
1. Privacy: What should the industry approach be towards privacy? Should they incorporate features that protect privacy? Should they have default settings that protect privacy or delete information? Or should we not worry about this? Is there a need for an industry-wide approach to this issue?
2. Comparing Vendor Solutions: What can be done to make it simpler for end users to compare and contrast different solutions? It’s very confusing now for end users to sort through claims by tens of companies on effectiveness, costs, technology, etc.
3. Connections to Academia: Explain if anything needs to be done to expand the connection between industry and academia. After all, much of the engineering talent has come directly from universities. Are there any suggestions you have for universities and their research?
4. Future Growth of Smart Cameras: Have cameras hit a period of steady growth or do you foresee a potential boom ahead? If so, what are the crucial factors that you see that are limiting growth of that will cause growth to increase? Do we need to improve technology, better end-user experience, etc.
A few weeks ago, I was contacted by a representative of William Kelly, who is the host of a Chicago TV show, Sportsaholic. Bill was mugged and beaten to the ground in front of his Gold Coast/Streeterville residence. He noticed some blue light cameras and was hoping they could help identify his attackers. After almost two weeks, Bill was finally able to review the tape. The camera was too far away and not at the correct angle to capture his attackers. This led Bill Kelly to characterize the camera system as wasteful. After all, from what he saw, the camera system was was not terribly useful.
As a scholar on cameras, I try to take a big picture view. This leads me to wonder how many others have had similar or disimilar experiences as Bill. How many crimes are solved by cameras? We don’t have this kind of data, because most police departments don’t collect it. Jeff Roush over at Fighting Crime From Above argues that we need more data on cameras. This leads him to recommend more data in the following four areas:
Real time apprehensions
Apprehensions based upon video or images
Prosecutions based on camera evidence
Effectiveness of camera operators
I agree with Jeff and I would urge everyone to try to push for the collection of this data. It is the only way we can move from anecdotes to a more through scientific understanding of how cameras affect crime.
The BBC is reporting that a nationwide system of monitoring license plates will be in place in a few months in Britain. The government is tying together various ANPR systems into one central computer. There are no limits on how this information can be used by police according to the article.
This will provide the police with unprecedented knowledge of its citizens’ movements. Just as governments can easily monitor all our activities online, the same is becoming true for real life.
Its only a matter of time until a similar network is setup in the US. ANPR/ALPR is a very useful technology, but is also has significant privacy implications that need to be addressed. I have previously mentioned the long term storage and sharing issues and the abuses with ALPR. These issues need to be addressed.
highlights the potential and limitations of the technology, noting those tasks for which it seems ready for deployment, those areas where performance obstacles may be overcome by future technological developments or sound operating procedures, and still other issues which appear intractable. Its concern with efficacy extends to ethical considerations.
For the purposes of this summary, the main findings and recommendations of the report are broken down into five broad categories: performance, evaluation, operation, policy concerns, and moral and political considerations.
When a camera is used, there maybe certain parts within a camera’s field of view that need to be kept private. The most obvious is if a camera could see into a private area, such as a window or doorway to a house. If this occurs, the appropriate measure is to use masking, privacy zones, or blanking. This can be done physically, by limiting the camera’s field of view during the installation process. This can also be done by software, however, software creates a risk that “someone might, somehow, get access to the video prior to masking, or perhaps turn off the masking” according to Sightmind.
One example of software is Pelco’s window blanking system. It is capable of blocking of specific areas, such as open windows to satisfy privacy issues. “In Spectra III SE, you will be able to define up to eight, four-sided polygons, with sides of any length, and turn on the blanking at specific zoom ratios.”
I don’t know how effective these systems are in practice, but I think most police departments should be using some type of masking system when setting up cameras near residential areas. As a further measure, policy departments should also be keeping system logs concerning what cameras are looked at by what user and when.
Indianapolis has a small camera network, I first mentioned it last year. For background, they have spent over a million dollars and are at 54 cameras with another 40 coming online this year.
The problem noted in the article is the city doesn’t keep any data on the effectiveness of the cameras. As a result, taxpayers and police don’t know if these cameras are really helping to address crime. The article notes recent studies show cameras have limited effectiveness, e.g. San Francisco. The article also states that Chicago “reported that neighborhoods with cameras operating for more than six months saw a 30 percent decrease in crime and a 60 percent drop in drug incidents.” However, Chicago, unlike San Francisco, has not made public its data or analysis for these statistics.
The lack of data will probably not hamper the growth of camera networks. Unlike many other technologies, people believe in their guts that cameras can make a difference. In the absence of data, they will probably prefer cameras. However, for the policy wonks and those that care about the long term, the lack of data will mask the true value of cameras. We won’t know if money should be spent on cameras, officers, other police technologies, or for other strategies.
Modeled on London’s 10,000 camera system, called the “Ring of Steel,” the Lower Manhattan Security Initiative (LMSI) – which has attained the same nickname – will consist of 3,000 networked cameras monitoring 1.7 miles of area south of Canal Street. One-third of the cameras will be city-owned, with the other two-thirds belonging to private businesses, termed “stakeholders” in the guidelines. Automated license plate readers and environmental sensors will also provide data to the police. The cameras will be monitored by officers at a coordination center on Broadway, which opened last November. The system is expected to cost $89 million in local and federal funds. [More info at Danger Room]
The NYC network is a study in contrast with Chicago.
First, the NYC network is much more geographically focused system. Using my previous estimates, if lower manhattan is 4 square miles, then it would need about 5000 cameras to ensure a camera is every 50 yards. So the network is highly likely to complete saturate the area. In contrast, Chicago is far from evenly covering the city and even the downtown area which has a much higher concentration of cameras is not near this density.
Second, we know something about the NYC network. Through the NYCLU and NYPD, the public knows about the camera system and is being asked for their input. (The NYPD is asking for comments on its privacy guidelines, something Chicago has never done).
Third, the NYPD is putting into place policies for how the surveillance technologies (cameras and ALPR) will be used. The policies make it seem the focus of these technologies is counterterrorism and not crime prevention. As a result, there are procedural safeguards to using the surveillance data for other purposes. In Chicago, the city has never publicly stated what its policies are regarding security and privacy of surveillance data.
From my view, I am just heartened that the NYPD is publicly developing such a policy.
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