Although facial recognition technologies have been used successfully for several years, the debate about the benefits and possible drawbacks continues. Public concerns about privacy and government adoption have increased as technology has become widespread. Much has been reported about this.
Facial recognition technology providers are adjusting and responding to the problems raised, as well as the clients that implement these tools. There is a sweet spot where we can get the benefits of this technology, while minimizing the potential for erroneous applications. Technological advances and greater implementation flexibility help achieve this desired ideal point.
The benefits of facial recognition technology.
The list of beneficial use cases is long, and the benefits provided by technology are difficult to discount.
In the security space, facial recognition technology is indispensable. The cost of alternatives (particularly the application of human capital) is prohibitive. Without facial recognition systems, security would be more expensive and would probably achieve less.
There are also many other application areas. At its core, technology provides a new way to automatically interact with devices and data, and this can make life safer and more convenient. Unlocking your phone with your face is just one example in the convenience category. Many others in the very useful category include applications such as identifying missing children and missing elders, verifying a patient's identity to avoid misadjustments of medication, verifying identity at the ATM, etc. The list is as long as we let our imagination run.
Avoiding the potential for misuse.
There are many technologies in use today that could be considered as potentially promoting the arrival of an Orwellian world. The reality is that we are carrying out a regular and voluntary follow-up, even without the use of facial recognition tools. The GPS of our phone is tracking each of our movements on the street. Online, our clicks are being tracked and correlated. At home, our IoT devices are also controlling us and doing what we do. We are doing this voluntarily. In context, the misuse of facial recognition tools would be, in the best of cases, an incremental contributor to this image, and probably far from being the most significant. Privacy is a very important issue, and the problems that surround it must be seen in a comprehensive and exhaustive if we want to be successful.
Facial recognition software in the facilities: minimizes risks, maximizes rewards
In the current market, we find that some facial recognition tools are offered as a service on the web, and some are available for on-site implementation by the client directly. There are advantages and disadvantages to any of the approaches, but the local approach avoids important security / control issues that are particularly important in government implementations.
Web offers consist essentially of an API (application programming interface) that a programmer uses to send a facial image and get a response (for example, the data that characterizes that face).
These systems tend to be opaque to the end user by their very nature. The images are processed on servers that are owned and controlled by the service provider, which creates gaps in the chain of custody of the data. You can not be sure what happened to the loaded image, which led to a series of questions: Where was it processed? Was it cached or altered? Someone else saw it? What happened to the results returned? Was the data reused? The list of questions is long.
Local solutions can solve these vulnerabilities and serve as an excellent alternative to solutions based exclusively on the web. The fewer "hands" there are in the images / videos / data, the lower the possibility of leakage and misuse. In our opinion, police and government organizations that deal primarily with highly confidential data must have full and exclusive control over their data and processes.
Recently, the Board of Directors of Amazon rejected two shareholder proposals to stop selling facial recognition services (Rekognition) to police and government organizations. The episode highlights an important issue for long-term customers. The metadata that was generated with the software of a service provider can normally only be used with that software. If the supplier withdraws from the market, the client's pluri-annual investment in the previously generated data disappears. This is a stumbling block that can be avoided by installing local facial recognition software. The customer maintains control.
Historically, facial recognition technologies have evolved from the perspective of trying to match a face in conditions in which the person wishes to be recognized (for example, a gate access control point). The scale of this approach to conditions "in nature" or where the subject is an adversary, however, does not work as well. In recent years, facial recognition technology has improved significantly and can now achieve successful recognition in a wide range of difficult conditions. For example, contextual information in the image can help refine the scope of what a user is looking for. This is a great leap in computer vision that brings us closer to the automatic understanding of images. The desire is not only to find the proverbial "needle in a haystack", but also to do it when the "haystack" comprises only good needles and one is interested in a very specific needle. It is important to be able to look at the context of the image to obtain what the user needs. The software must look at everything in the image: objects, text strings, scenes, etc. A face in an image may be partially obstructed, but other aspects (clothing, etc.) may contribute to the confirmation of that coincidence.
In situations where there are a lot of good matches between faces, only some of which are relevant to the researcher, this is another area where the context of the image can help to filter the results (for example, a store name) in the background where the text was also). Detected and recognized automatically, an emblematic building in the image, a type of flower in the background, etc.).
As technology continues to evolve, new capabilities can help make some of the concerns about misuse and misidentification disappear. We are also becoming smarter about how to implement it effectively because we want a better world, not an Orwellian one.
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