Facial recognition technology uses biometrics to identify similarities in two facial images. The software uses information from a database of photos or videos to identify a person. In its basic element, facial recognition is a security device.
You can’t access the building if the algorithms do not authenticate you. The same applies to locking devices like smartphones.
But now, the technology is evolving further with some unique features. For example, facial emotion recognition identifies things like disgust, anger, or fear. And companies are adopting the use of such in their organizations.
Facial recognition technologies can help in the recruiting process. AI recruitment platforms have become popular because they remove bias from the hiring process.
HR uses them to source candidates based on experience and best fit for the job. And, emotion recognition software ‘read’ candidates without relying on what they say. Instead, the algorithms determine candidate attitudes, confidence, or feelings. It allows for a better assessment of new hires.
The AI face analysis scans word choice, facial expressions, vocal tone, and movements. It generates data-driven insights to help in decision-making. This removes subjective judgments or biases that the interviewers may have.
Companies can identify employee morale using AI face recognition technologies. It is especially helpful where employees may be afraid to express themselves.
HR can get insights with AI facial emotion recognition software to get insights. By looking at facial features, AI systems can determine some things. Such include stress levels, emotional responses, and happiness.
A company can then take the necessary steps to improve the work environment. The result is better employee performance, employee engagement, and higher morale amongst employees.
One of the biggest issues around facial recognition technologies is privacy. Constant surveillance can increase stress levels amongst employees.
What happens if you know that someone is watching your every move, including nonverbal cues? Well, for most, it will hurt performance.
The only thing it will do is make employees look for ways to con the system. They will self-censor or change behavior if they know they are under surveillance.
Some concerns exist about the science behind such technologies. There is no scientific proof that facial expressions reflect an emotional state.
Take the example of a customer care agent or air hostess. Their job requires them to smile at all times. But, this does not always represent what they feel inside.
Such technologies base results on basic emotions. These include fear, anger, sadness, surprise, disgust, and joy. But, human emotions are complex.
An employee getting a promotion could experience joy and fear at the same time — joy for the new opportunity and fear at the expectations and his ability to handle them. But, unfortunately, AI technologies cannot generate such insights from facial expressions.
AI technologies rely on data to generate reliable results. Insufficient or lack of diversity in the datasets can generate inaccurate feedback.
There is still a lot of validation that needs to go into ensuring accuracy. It would be hard to understand an employee’s behavior using blanket baseline data. For example, a study by MIT showed a 35% error margin for dark-skinned women.
There may even be bias towards black men who appear angrier than white men. So it brings in the element of bias, which technology should remove.
The adoption of AI emotion recognition technology is subject to use. This is because there is no rigid industry regulation on implementation. However, some organizations provide some type of guidelines, including GDPR.
But, private use is largely unregulated. Companies that collect such biometric data must ensure its security.
Source: Artificial Intelligence Magazine
