Leveraging Knowledge to Manage Your Data Risks
This post was authored by William Ollayos, Summer Associate. William is not admitted to practice law.
On June 27, 2025, the U.S. Supreme Court upheld a Texas law requiring pornography websites to verify users’ ages through government-issued ID. The 6–3 decision in Free Speech Coalition v. Paxton marks a significant shift in First Amendment jurisprudence…
This post was co-authored by Government Enforcement + White-Collar Defense partner David E. Carney.
On June 6, 2025, President Donald Trump signed two executive orders aimed at significantly reshaping the future of drone policy in the United States. One focuses on protecting national airspace from malicious drone threats, while the other seeks to supercharge…
This post was co-authored by Summer Legal Intern Mark Abou Naoum. Mark is not admitted to practice law.
This week, the U.S. District Court for the Northern District of California ruled in favor of children’s clothing retailer Janie & Jack, which sought to enjoin over 2,400 individual arbitration claims resulting from alleged violations of the…
This post was authored by Class Action Defense team chair Wystan Ackerman and is also being shared on our Class Actions Insider blog.
Some data breach class actions settle quickly, with one of two settlement structures:
(1) a “claims made” structure, in which the total amount paid to class members who submit valid claims is…
Thank you to Jon Schaefer for this post. Jon focuses his practice on environmental compliance counseling, occupational health and safety.
On July 30, 2024, the U.S. EPA Office of Inspector General issued a fraud alert to bring attention to an increasing number of companies reporting that they have received fraudulent EPA Notice of Violation…
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:
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.Continue Reading AI Lands in the Workplace
Below is an excerpt of a legal update co-authored with Government Enforcement + White Collar Defense Partner David E. Carney.
On June 17, the Department of Justice (DOJ) announced settlements of alleged False Claims Act (FCA) violations associated with cybersecurity requirements in contracts to provide a secure environment for online applications for federal housing…
This week we are pleased to have a guest post by Robinson+Cole Artificial Intelligence Team patent agent Daniel J. Lass and Counsel Kyle G. Hepner
The U.S. Patent and Trademark Office (USPTO) issued guidance on the use of AI-based tools to prepare and prosecute patent and trademark applications. This announcement supplements the previous guidance issued…
*This post was co-authored by Josh Yoo, legal intern at Robinson+Cole. Josh is not admitted to practice law.
Health care entities maintain compliance programs in order to comply with the myriad, changing laws and regulations that apply to the health care industry. Although laws and regulations specific to the use of artificial intelligence (AI) are limited at this time and in the early stages of development, current law and pending legislation offer a forecast of standards that may become applicable to AI. Health care entities may want to begin to monitor the evolving guidance applicable to AI and start to integrate AI standards into their compliance programs in order to manage and minimize this emerging area of legal risk.
Executive Branch: Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence
Following Executive Order 13960 and the Blueprint for an AI Bill of Rights, Executive Order No. 14110 (EO) amplifies the current key principles and directives that will guide federal agency oversight of AI. While still largely aspirational, these principles have already begun to reshape regulatory obligations for health care entities. For example, the Department of Health and Human Services (HHS) has established an AI Task Force to regulate AI in accordance with the EO’s principles by 2025. Health care entities would be well-served to monitor federal priorities and begin to formally integrate AI standards into their corporate compliance plans.
National Institute of Standards and Technology: Risk Management Framework
The National Institute of Standards and Technology (NIST) published a Risk Management Framework for AI (RMF) in 2023. Similar to the EO, the RMF outlines broad goals (i.e., Govern, Map, Measure, and Manage) to help organizations address and manage the risks of AI tools and systems. A supplementary NIST “Playbook” provides actionable recommendations that implement EO principles to assist organizations to proactively mitigate legal risk under future laws and regulations. For example, a health care organization may uphold AI governance and non-discrimination by deploying a diverse, AI-trained compliance team.Continue Reading Forecasting the Integration of AI into Health Care Compliance Programs
This week we are pleased to have a guest post by Robinson+Cole Business Transaction Group lawyer Tiange (Tim) Chen.
On February 28, 2024, the Justice Department published an Advanced Notice of Proposed Rulemaking (ANPRM) to seek public comments on the establishment of a new regulatory regime to restrict U.S. persons from transferring bulk sensitive…
