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Employers Can Overcome Vaccine Pushback With AI Help

Jan. 5, 2021, 9:00 AM

The newly-approved (under emergency use authorization) Pfizer-BioNTech and Moderna Covid-19 vaccines represent an enormous opportunity for a gradual return to normal after nearly a year of business, social, and personal disruption. Employers will face a number of critical decisions as they approach their workforce with new mandates and, for a second time, attempt to restructure their workplaces around the impacts of the Covid-19 pandemic.

To meet this challenge, employers have a new tool—the marriage of legal services and artificial intelligence-driven computational modeling—to craft everything from vaccine deployment strategies to the relaxation of pre-vaccine safety protocols to rolling risk assessments.

Vaccine Deployment Will Challenge Employers

Existing employment law is not equipped to handle the Covid-19 vaccination process. Aside from health care and education, very few sectors have any precedent—much less regulation—addressing mandatory vaccination. Meanwhile, employers must still comply with requirements for disability exceptions, religious exceptions, and other complications that may preclude universal vaccination.

To make matters worse, it is anticipated that federal or state regulators will start to issue vaccination guidance in the middle of this process, such as the Equal Employment Opportunity Commission’s Dec. 16 bulletin addressing disability accommodation with respect to vaccines.

Also, many workers are already expressing skepticism about the safety of the Covid-19 vaccines. As a result, unlike many other vaccines, resistance to a vaccination may not be limited to non-mainstream groups. Employers will need to plan to carefully communicate the reasoning behind and rules surrounding their vaccination policies to help abate employee concerns.

Finally, community protection against Covid-19 will take time. Meanwhile, as vaccination uptake increases, Covid-19 safety fatigue will only worsen. Employers may face increasing challenges maintaining mask requirements, social distancing, and other protective measures among vaccinated employees who no longer appreciate the ongoing need. Those problems, in turn, could create outbreak risks and general downward pressure on productivity and morale.

AI Tech Partnered With Legal Services Can Help Employers

The challenges described above present legal and human capital management questions. But AI-driven computational technology provides a new tool to help address the questions. It takes information concerning employer-specific circumstances and conducts iterative analyses to model all manner of outcomes.

For example, such technology can show the impact of partial non-compliance with mask mandates, high risk areas in office spaces, and, most critically here, the impact of gradually rising immunity on the need for continued protective measures.

This information, generated through advanced technology, offers a new opportunity for refined legal guidance. Lawyers are in the business of counseling clients through the process of identifying and weighing risks in all aspects of their affairs.

For instance, armed with this data, employment counsel and employers can better determine what policies are required and the level of discipline appropriate for violations to maximize safety without unduly impacting operations. Of similar importance, this data allows employers to justify their decisions if confronted with future challenges—a vast improvement over speculative policy setting in the face of a problem never before confronted in the American workplace.

Meanwhile, pairing this sophisticated AI analysis with legal services and advice will allow employers to engage in critical self-review with all of the benefits of the attorney-client privilege.

For example, Reed Smith has paired up with Haven Diagnostics to deliver such a service to employers. Even before the pandemic, Haven was in the late-stages of developing a new type of computational modeling called agent-based models to measure the probability of an infectious disease outbreak in hospital environments. Scientists at Harvard, Columbia, and Yale have studied agent-based modeling for use in preventing hospital-acquired infections, defending against bioterrorism, and combating the spread of influenza in the workplace.

With regard to the problem of Covid-19 safety and vaccination in the office, employers can input their location, office layout, and policies and procedures, and the models then detect if and how a Covid-19 outbreak occurs in 10,000 simulated days in the workplace. Furthermore, these models can test if stricter policies are more effective or if more relaxed policies can be used while keeping risk low.

Limited Drawbacks

Use of AI-driven technology in this area does come with some limited drawbacks. First, the outputs will only be as good as the information provided. As a result, employers must be comfortable sharing detailed, sometimes sensitive information with counsel and supporting vendors to ensure the analytical process is premised upon sound data.

Second, employers should acknowledge that they may encounter institutional resistance to recommendations derived from AI-assisted analysis. One of the great benefits of iterative analysis is that it can overcome preconceived notions and biases that undermine effective compliance. Nonetheless, employers may find that managers and employees resist changes based on their own “common knowledge” when AI-assisted analysis dictates counter-intertuitive responses.

Ultimately, employers aiming for a return to the office must address a variety of challenges, including monitoring vaccination rates, complying with the law, and understanding, communicating, and counteracting residual Covid-19 risks. The alternative is waiting for population-wide herd immunity—which may take a year, if it occurs at all. A careful examination of how their policies align with legal regulations and with the latest science is warranted.

This column does not necessarily reflect the opinion of The Bureau of National Affairs, Inc. or its owners.

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Author Information

Michael A. Correll is a partner in the Labor & Employment group in Reed Smith’s Dallas office, and represents employers in litigation, including defending employers against claims of discrimination, harassment, retaliation, and wrongful discharge. He litigates Fair Labor Standards Act collective actions and handles a wide range of Americans with Disabilities Act employment and public accommodation claims.

Joseph J. Mammone Jr. is an associate in the Labor & Employment group in Reed Smith’s Dallas office. He represents employers in litigation and administrative actions concerning federal and state labor and employment laws, including defending employers against claims of discrimination, retaliation, wrongful discharge, and whistleblower allegations.

Dr. Michael Gao is the founder of Haven Diagnostics He is an assistant professor of medicine (courtesy) at Weill Cornell and is recognized as a leader in applied AI as the former medical director for transformation at New York-Presbyterian Hospital.

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