Mitigating Risk of Employee AI Use in the Workplace: Key Considerations for Policy Development; Pitfalls to Avoid

Description

With recent advances in generative AI, more companies are exploring ways to use AI to increase productivity, proficiency, and creativity in the workplace. Even where companies do not provide AI tools to their employees, certain AI applications are easily accessible to anyone (e.g., ChatGPT, Google Bard, Bing Chat), and employees may be using AI on their own, without employer knowledge, to perform work functions. The use of AI in the workplace, whether company-sanctioned or not, brings significant risks of which employers should be aware and prepared to handle by creating policies that govern employee use of AI in the workplace.

A non-exhaustive list of some AI risks includes (1) potential discrimination claims, if employees use AI for employment-related decisions without proper oversight and safeguards; (2) potential violations of the National Labor Relations Act associated with bargaining obligations or employee monitoring; (3) the improper disclosure of company confidential information and trade secrets when employees enter information into AI tools; and (4) to copyright infringement or theft if employees use AI to generate content that could come from a third-party protected source.

A well-drafted, comprehensive policy governing employee use of AI is necessary in business today. Counsel should understand the various provisions to include to best protect clients' interests, including clearly defining the scope of the policy, setting guidelines for data privacy and confidentiality, addressing intellectual property rights, indicating whether and to what extent AI may be used in the human resources function, and clearly defining the consequences of policy violation.

Listen as our expert panel describes the risks to an organization when employees use AI and how counsel may help clients mitigate that risk by creating a comprehensive AI policy. The panel will address key drafting considerations and pitfalls to be avoided and provide best practices for implementation.