In a strongly worded order, Judge Julie A. Robinson of the U.S. District Court for the District of Kansas publicly admonished and sanctioned four lawyers representing a plaintiff company in a patent infringement case for using ChatGPT to find caselaw to support a response to a motion to exclude an expert witness, and a response
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When Chats Become Evidence: Court Affirms Order Requiring OpenAI to Produce 20 Million De-Identified ChatGPT Logs
On January 5, 2026, the federal U.S. District Court for the Southern District of New York upheld two discovery orders requiring OpenAI to produce a sample of 20 million de-identified user logs from ChatGPT as part of wide-ranging copyright litigation brought by news organizations and class plaintiffs. This decision offers important insights into how federal…
Privacy Tip #470 – Consumer Group Warns that AI Chatbots in Toys Contain Sexually Explicit Messages
In its 40th anniversary report, Trouble in Toyland 2025, the Public Interest Research Group (PIRG) warns that “[T]oys with artificial intelligence bots or toxics present hidden dangers. Tests show A.I. toys can have disturbing conversations. Other concerns include unsafe or counterfeit toys bought online.”
The report outlines PIRG’s testing of four toys (Curio’s Grok…
Privacy Tip #464 – Pitfalls of Dating a Bot
Dating sure has changed since I was in the market decades ago. Some of us can’t imagine online dating, let alone dating a bot. Get over it—it’s now reality.
According to Vantage Point, a counseling company located in Texas, it surveyed 1,012 adults and a whopping 28% of them admitted to having “at least one…
Privacy Under Pressure: What the NYT v. OpenAI Teaches Us About Data Governance
The rise of large language models (LLMs) such as ChatGPT has created novel legal implications surrounding the development and use of such artificial intelligence (AI) systems. One of the most closely watched AI cases currently is New York Times Co. v. Microsoft Corp., No. 1:23-cv-11195 (S.D.N.Y. filed Dec. 27, 2023), in which the New York…
How Does Your AI Platform Rank?
Incogni recently issued its “Gen AI and LLM Data Privacy Ranking 2025” where it “delved deep into the most popular LLMs and developed a set of 11 criteria for assessing data privacy risks associated with advanced machine learning programs like ChatGPT and Meta AI. The results are synthesized into a comprehensive privacy ranking, including an…
Privacy Tip #448 – Privacy Tips for 2025: A Timely Reminder
After writing over 500 privacy tips in my career, it gets a little difficult to find new content to keep the tips relevant and timely. I came across a recent post by the CyberGuy, Kurt Knutsson, that I thought our readers would get some insightful tips from, including up to date ideas on how…
When Satire Meets Statute: The Onion’s VPPA Class Action
Video Privacy Protection Act (VPPA) class action lawsuits have been on the rise, and the owner of the The Onion, a popular satire site, finds itself the subject of a recent one. On May 16, 2025, a plaintiff-initiated litigation against Global Tetrahedron, LLC, the owner of The Onion, alleges that the defendant installed the Meta…
AI Governance: The Problem of Shadow AI
If you hang out with CISOs like I do, shadow IT has always been a difficult problem. Shadow IT refers to refers to “information technology (IT) systems deployed by departments other than the central IT department, to bypass limitations and restrictions that have been imposed by central information systems. While it can promote innovation and…
AI Lands in the Workplace
This blog post was co-authored by Labor, Employment, Benefits + Immigration Group lawyer Abby M. Warren.
It doesn’t seem fair that human resources (HR) personnel have to manage both labor shortages and overwhelming employee management tasks, but here we are. Companies are facing a critical shortage of skilled workers that is outpacing educational institutions’ training ability, not to mention a mismatch of skills. Yet, HR personnel are expected to sift through thousands of resumes with dubious potential to find skilled workers to replace the ones who are leaving at an increasing rate. As workers retire without sufficient workers to replace them, the problem will only get worse.
To meet these challenges and demands, a lot of companies are spending money on artificial intelligence (AI) to compensate for labor shortages in the hope that it alleviates these increasing burdens. AI generally refers to computers that can perform actions that typically require human intelligence. For example, whereas we used to write our texts and emails ourselves, our phones’ generative AI now offers to finish our texts and emails, or even suggests the entire message.
Most frequently, HR personnel use AI in their recruiting process — specifically to screen and review talent (e.g., scan resumés). Theoretically, AI can review more resumés more quickly than an entire HR department can. Trained properly, AI can select the best resumés and enable your team to interview higher quality candidates. And at the interview stage, AI can transcribe and summarize live interviews.
AI can also help train new employees. AI chatbots can guide new hires through the onboarding process and provide answers to questions in real time. It can send welcome emails and schedule training sessions, which can help make an employee’s onboarding experience smoother, with less effort from an HR department.
After training, generative AI can answer employees’ questions about various company policies and functions in real time including:
- Vacation, parental, and other leaves;
- Insurance (life and health)
- Expense reports
- Retirement accounts
- Health and wellness
- Disability coverage
- Family benefits
Answering these questions can allow HR personnel time to perform more value-added tasks.
Theoretically, generative AI can also help manage employees. Just like your phone’s AI can help you write texts, generative AI like ChatGPT can write or revise entire emails. And AI can adjust the tone of an email, making it more professional, more friendly, more detailed, etc., as the situation requires.
However, every rose has its thorn — or multiple thorns. When evaluating resumés, AI can rely upon outdated stereotypes as easily as people can. A recent study by Rippl found that prompts for doctors, engineers, carpenters, electricians, manufacturing workers, and salespeople produced only male results. When asked to generate images for a HR manager, marketing assistant, receptionist, and nurse AI provided only pictures of women. When asked to generate images of a CEO, AI offered only white, middle-aged men, whereas manufacturing workers were always young men of color and housekeepers were all young women. This can be especially dangerous, because according to one recent survey, 73 percent of HR professionals said they trust AI to recommend whom to hire.
As if that weren’t enough, AI can use its generative abilities to formulate a response that is linguistically correct but factually wrong. This phenomenon, called “hallucination,” has gained attention through media reports of AI guiding people to eat poisonous mushrooms or make other mistakes. That is, the “answers” that your generative AI bot provides employees and AI’s email “corrections” may contain hallucinations that might mislead your employees. Used incorrectly, AI can make mistakes that could take hours or days of HR time to correct.
Unfortunately for employers, their legal obligations under local, state, and federal employment laws remain regardless of whether they are engaging in recruiting, hiring, and managing applicants and employees directly, through a vendor, or through the use of AI. Further, if there are issues with regard to discrimination or bias in recruiting, hiring, and managing, those issues are typically systemic — that is, they have impacted numerous applicants and employees and may result in costly enforcement actions, government investigations, or litigation.
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