Meta is facing a lawsuit that claims the company used AI-assisted tools to target employees with disabilities or those who took medical leave.AFP via Getty ImagesMeta has dominated the headlines as of late due to a groundbreaking federal lawsuit where the company agreed to pay an $18 billion settlement because of how the company’s social media platforms harmed children and teens. Another important lawsuit Meta is facing involves how the company allegedly used AI-assisted tools to target employees with disabilities or those who took medical leave. According to a lawsuit filed in July, Meta allegedly used AI-powered software to lay off employees who took time off for medical conditions or to care for family members. In a statement regarding the lawsuit, a representative for Meta stated, “These claims lack merit and are not based on facts. Workforce management and organizational decisions were and are made by people, not AI.”“I have had clients come to me in this situation with layoffs becoming more common in Silicon Valley,” shared California-based workplace trauma lawyer Michele Simon, in an email. “In fact, one such client was laid off from Meta while out on pregnancy leave. I told her it’s a simple math problem: of thousands of employees, some proportion are always going to [go] on leave so it is very hard to prove any one person was singled out. In this particular case, if it’s true that Meta used unfair criteria that resulted in disproportionate selection of folks on leave or disabled, that could be a viable case. It will likely depend on the state laws of where the employees are located: the news mentioned California and New York, both states with strong employment laws.”“I actually do feel they have a legitimate claim,” indicated Senior labor and employment counsel and human resources consultant Justin O’Keith Higgs, in an email. “Once discovery begins and we start to see the different filings counsel will make should shed a bit more light upon things. Many people think these very large tech companies run like well-oiled machines. That is far from the truth. There is a great deal of chaos and disorganization in these organizations. As we all see in corporate spaces, many times leadership will make very rash decisions and tell their teams they have a very small timeline to get the goal accomplished. When this happens, many checks we conduct can get missed. The goal is to complete the task by the deadline, not being thorough.” "Many times leadership will make very rash decisions."gettyHiggs went on to explain, “I have worked on many reductions in force where I specifically call out people who are on leave, accommodations, etc. We want to make sure the metrics we are using to select employees for reduction are fair and appropriate. The only time I would truly be comfortable with affecting people on leave, etc. would be where we are doing an across-the-board elimination of roles. For example, we are closing an entire department, work site, office, etc. No one is being singled out because everyone is losing their jobs. If that is not the case, running an analysis regarding employees on leave, accommodations, etc. is one of the first things human resources should be working with the business and legal to lay out.”Higgs also shared, “Meta has been in the news for quite some time regarding these type of activities with their employees, so this is pretty on brand with how they operate. It is very possible Meta could have simply let this AI run with this reduction in force to see how things played out, with legal watching. We shall see what evidence comes out of this and will definitely be a huge learning moment for all businesses.” Organizations should exercise caution before leaning too heavily on AI-assisted tools to make important workplace decisions.gettyTo avoid this situation, Simon advised companies to steer away from using AI-assisted tools like this to make layoff decisions. “I think employers have a long way to go to more compassionate and thoughtful in general in how it goes about layoffs.” Both Simon and Higgs agreed that organizations should exercise caution before leaning too heavily on AI-assisted tools to make important workplace decisions. “AI is still very young in our spaces and we have not fully unlocked its full potential. You also have to have a mind where you truly understand how the tool works and that it is a tool, not a stakeholder in the business. You still need to be able to do the job correctly. These decisions should be tied to people, not the artificial intelligence tool,” Higgs said. These types of situations will continue because more and more companies are now leaning on AI-powered tools to help make important workplace decisions. AI leans on algorithms that are often embedded with biases that existed since its inception. While the use of AI, especially at larger organizations, seems inevitable, AI’s propensity for hallucinations and inequitable outcomes means humans must still play an integral role in workplace decision-making; companies should think twice about AI usage and ensure that there are safeguards in place to avoid these types of situations.