Pros and cons of facial recognition
metamorworks - stock.adobe.com
When a facial recognition system works as intended, security and user experience are improved. But when it doesn't, user experience suffers and people are put at risk.
Facial recognition is often used for security. When a security system falters, people can be exposed to some level of danger. In some cases, a seemingly mundane malfunction can ruin someone's life.
Take the false implication case of 61-year-old Harvey Murphy Jr. as an example of facial recognition gone wrong. Murphy was falsely identified as a thief by the facial recognition-powered security systems at Sunglass Hut. He was arrested and imprisoned for two weeks before authorities realized he was innocent. He was also assaulted while in jail. Authorities later learned that Murphy wasn't even in Texas during the time of the Houston Sunglass Hut robbery. Murphy alleged the assault left him with "lifelong injuries" in a suit against the Sunglass Hut's parent company, EssilorLuxottica.
Several errors had to occur for Murphy to end up imprisoned.
The first error was the malfunctioning facial recognition system, which is a relatively common occurrence. As of this writing, Murphy is one of seven people who have wrongly been accused of crimes because of malfunctioning facial recognition tools, and one of countless people who are routinely misidentified by the systems on an ongoing basis. Aside from Murphy, every other person wrongfully convicted was Black. The pharmacy chain Rite Aid recently pledged not to use facial recognition security systems for five years as part of a settlement with the Federal Trade Commission based on several false theft accusations levied by the store.
The next errors were the series of decisions that placed a disproportionate amount of trust in the misinformation provided by an automated security system.
These errors illuminate central concerns around other AI technologies as well -- that these automated systems produce false information -- convincing false information -- and are placed so that false information is accepted and used to affect real-world consequences. They are also historically prone to bias.
Despite the examples listed above, facial recognition has the potential to improve different industry sectors when implemented safely, by giving it the appropriate amount of trust.
Facial recognition uses artificial intelligence to match an image of a person's face to images in a database. Facial recognition software does the following:
The accuracy of facial recognition systems depends on a number of factors, including the quality of the image, and the size and quality of the backend database. Some facial recognition providers crawl social media for images to build out databases and train recognition algorithms, although this is a controversial practice.
Aside from loss prevention, facial recognition technology has many uses, including the following:
Some of the benefits of facial recognition include the following:
Some drawbacks of facial recognition include the following:
Ben Lutkevich is a writer for WhatIs, where he writes definitions and features.