COVID-19 and all its “novelties” have undoubtably resulted in a mass exodus of employees who are unwilling to return to life as it was pre-pandemic. The ‘9-to-5’ lifestyle as we know it, is changing. Shifts in these trends are causing companies and business leaders to refocus more of their efforts on improving the overall employee experience.
Imagine a world where a brief facial scan could tell you everything you need to know about the employee — be it their performance or their mood? With recent developments surrounding AI, this may soon be a reality.
Artificial Intelligence (AI) — What’s All the Hype about?
The fiction that surrounds advancements in technology has made the common man skeptical towards AI. But in reality, he overlooks the fact that AI is all around us already. Every time a smart device uses facial recognition to unlock a user’s home screen, that’s AI at work.
Facial recognition technology is a form of AI that employs the use of biometrics to recognize the differences or similarities between several images (Datafloq). Fundamentally, the algorithm correlates an image to an assortment of photos and/or videos from a database to identify a specific individual (Datafloq). Theoretically, this feature provides additional security than a simple numerical passcode.
Upgrade! Work-life-balance in high gear
Smart devices only scratch the surface of what this technology stands to offer. It’s likely that in near future, AI will objectively identify human emotions in real-time. These face scans will determine a wide variety of information with near certainty without bias or judgment. In a corporate environment that is not conducive to the voluntary exchange of raw emotional reactions, AI can provide a boost.(Datafloq).
While forums like surveys and polls are typically inconclusive due to anonymous negative feedback, facial recognition technology will allow businesses to gain a more holistic understanding of challenges and identify areas for improvement within the organization.
Theoretically, AI enabled insights has the potential to improve the overall performance, productivity, morale, and dynamics of workplace. A win-win for both employee and employer.
No good deed goes unpunished… or does it?
There are many ethical implications that go along with the implementation of any technological advancement.
While a hot topic of conversation, it’s fair to say that there are many warranted concerns of privacy surrounding the promise of facial recognition in the workplace. It’s possible that this utopian idea of a ‘happy and productive’ environment might backfire into becoming a stressful and hostile environment.
What will everyday life look like if you were essentially monitored down do your temperature at all hours of the workday? Is it possible for AI to incorrectly equate feelings unrelated to the work environment? What about concerns of security breach? And who’s to say that the individual sorting and quantifying of data will be accessing it only for good?
Don’t judge a book by its cover, or facial expression
Ever heard of RBF? It’s just one example of an emotional state that may be more cryptic for the facial recognition technology to grasp an understanding of. In fact, recent studies show that, there is no scientific proof that facial expressions reflect an emotional state (Datafloq).
Take any customer service representative, for example. Whether it’s a waitress or an IT personnel, one might argue that their engagement with consumers does not accurately reflect their emotional state. In most cases, it may be quite the opposite.
The idea that facial recognition technology can accurately pin down the true state of a person’s emotional well-being undermines the intrinsic properties of mankind. The challenge lies in quantifying the complexity of a person’s emotions while simultaneously oversimplifying what it means to be human.
Diversity of data can make or break this advancement
The strength of an organization directly correlates with the accuracy of its data. A lack of diversity and quality of data will result in inaccurate findings. A study performed by MIT, for example, showed a 35% error of margin for darker skinned, women of color (Datafloq).
If a technology is not inclusive for all degrees of intersectionality of an individual within an organization, it is not only useless but arguably a form of bias and disenfranchisement within a company’s structure.
AI Facial Recognition: Final Thoughts
To let fear weigh in the decision to explore the applications of AI and Facial Recognition technology will be a mistake. While this technology requires regulation — as with any sort of medical or technological advancement, it is also true that to limit the imagination of our generation’s brightest thinkers will be near sighted.
Fear is the enemy of progress, but a lack of due diligence may result in the demise of society as we know it.
The Systech Solutions, Inc. Blog Series is designed to showcase ongoing innovations in the data and analytics space. If you have any suggestions for an upcoming article, or would like to volunteer to be interviewed, please contact Olivia Klayman at firstname.lastname@example.org.
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