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Showing posts with the label human oversight

Managing Agentic AI in Real‑World Use: From Outputs to Actions

Agentic artificial intelligence (AI) is the next frontier for companies and organizations that are using AI. Agentic AI can select and carry out actions on a user’s behalf based on instructions, context, and the permissions it has been configured to use . As organizations integrate these systems and capabilities, they face an additional layer of legal risks and governance concerns. As companies begin to use agentic AI, they should consider key risk management practices to ensure responsible adoption . This includes aligning with emerging best practices and standards being studied and promoted by the National Institute for Standards and Technology (NIST) around agentic AI, including the Center for AI Standards and Innovation (CAISI) AI Agent Standards Initiative and the National Cybersecurity Center of Excellence Project addressing Software and AI Agency Identify and Authorization . For example, organizations utilizing agentic AI should look more closely at how the authority of AI age...

How Employers Can Manage Risk When Using AI for Employee Performance Management

Artificial intelligence is increasingly being used by employers to support employee performance management. While AI has the potential to improve talent matching and expand opportunities for growth, it raises significant legal and compliance considerations that employers must take into account before deploying. This Insight will provide an overview of the ways in which you can use AI for performance management, summarize the inherent risks, and provide a list of steps you can take to address that risk. How AI Performance Management Can Boost Your Workplace Qualified employees frequently self-select out of roles they could succeed in because they are scared away by the overly long and all-encompassing job descriptions listing excessive qualifications they don’t believe they can meet. Still others pursue positions misaligned with their actual capabilities, creating frustration for employer and employee alike. AI-driven skills analysis offers a different approach. Instead of focusing on ...

California Bills Would Require Human Review of AI Firings and 90-Day Notice for AI Layoffs

California lawmakers i ntroduced two bills yesterday that would significantly restrict how employers use artificial intelligence to make employment decisions . The coordinated effort by the California Labor Federation targets AI-driven job losses with a two-pronged approach: requiring human oversight when AI is used to fire or discipline workers, and mandating extended advance notice before conducting mass layoffs driven by automation. If enacted, the measures would impose s ome of the strictest AI employment regulations in the nation. Here’s what California employers (and multistate employers watching the trend) need to know about these February 2 proposals. SB 947: The “No Robo Bosses” Act Returns State Senator Jerry McNerney’s  SB 947  is a revised version of legislation Governor Gavin Newsom vetoed last year.  We covered the original proposal  and  the governor’s veto  in detail in 2025. The core provision remains: employers would be prohibited from u...

Managers Who Use ChatGPT to Promote Employees – What Could Go Wrong?

While artificial intelligence (AI) can be a powerful tool in a manager’s arsenal when it comes to efficiently making decisions, it is essential to use it ethically and fairly. Companies are no longer relying on AI solely to automate repetitive tasks or produce predictive analytics —  recent studies  have shown that over 60% of managers use AI for critical employment decisions, such as hiring, firing, layoffs, and/or promotions. And more than one in five managers use AI to make these decisions without any human input. As managers increasingly — and often blindly — rely upon AI, companies may risk significant legal exposure. Although it may be tempting to use AI to streamline employment decisions (e.g., hiring, promotion, workforce reductions), it is critical to remember that AI output merely reflects the data the system receives. These systems have no measurement for context, lack human judgment and empathy, and risk producing outcomes with unintended disparate impacts. A Cauti...