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Shares of Intel slumped Thursday after President Donald Trump said in a social media post that the chipmaker’s CEO needs to resign. The CEO of Intel is highly CONFLICTED and must resign, immediately, Trump posted on Truth Social. There is no other solution to this problem. Thank you for your attention to this problem! Trump made the post after Sen. Tom Cotton sent a letter to Intel Chairman Frank Yeary expressing concern over CEO Lip-Bu Tans investments and ties to semiconductor firms that are reportedly linked to the Chinese Communist Party and the Peoples Liberation Army, and asked the board whether Tan had divested his interests in these companies to eliminate any conflicts of interest. Cotton specifically called out Tan’s recent leadership of Cadence Design Systems in the letter. The tech company admitted in July to selling its products to Chinas National University of Defense Technology in violation of U.S. export controls. In March 2025, Intel appointed Lip-Bu Tan as its new CEO,” Cotton wrote in the letter. “Mr. Tan reportedly controls dozens of Chinese companies and has a stake in hundreds of Chinese advanced-manufacturing and chip firms. At least eight of these companies reportedly have ties to the Chinese Peoples Liberation Army. U.S. companies who receive government grants should be responsible stewards of taxpayer dollars and adhere to strict security regulations, Cotton wrote on the social platform X. Intel had been a beneficiary of the Biden administration’s CHIPS Act, receiving more than $8 billion in federal funding to build computer chip plants around the country. Intel did not immediately respond to a request for comment. The demands made by Trump and Cotton come as economic and political rivalries between the U.S. and China increasingly focus on the competition over chips, AI and other digital technologies that experts say will shape future economies and military conflicts. Cotton, the chairman of the Senate Intelligence Committee, has raised concerns that Chinese spies could be working at tech companies and defense contractors, using their positions to steal secrets or plant digital backdoors that give China access to classified systems and networks. On Thursday the Arkansas Republican wrote to the Department of Defense urging Defense Secrectary Pete Hegseth to ban all non-U.S. citizens from jobs allowing them to access DoD networks. He has also demanded an investigation into Chinese citizens working for defense contractors. The U.S. government recognizes that Chinas cyber capabilities pose one of the most aggressive and dangerous threats to the United States, as evidenced by infiltration of our critical infrastructure, telecommunications networks, and supply chains, Cotton wrote in an earlier letter calling on the Pentagon to conduct the investigation. National security officials have linked Chinas government to hacking campaigns targeting prominent Americans and critical U.S. systems. Shares of the California company slid 3.5%, while markets, particularly the tech-heavy Nasdaq, gained ground. Founded in 1968 at the start of the PC revolution, Intel missed the technological shift to mobile computing triggered by Apples 2007 release of the iPhone, and its lagged more nimble chipmakers. Intels troubles have been magnified since the advent of artificial intelligence a booming field where the chips made by once-smaller rival Nvidia have become techs hottest commodity. Intel is shedding thousands of workers and cutting expenses including some domestic semiconductor manufacturing capabilities as Tan, who took over as CEO in March, tries to revive the fortunes of the struggling chipmaker. Michelle Chapman, AP business writer
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First things first: Whenever possible, science says don’t have so many meetings. Here’s why: A meta-analysis of more than a decade of research shows employee productivity increases by more than 70% when the number of meetings is reduced by 40%. A study published in Journal of Organizational Behavior found that meetings that start late don’t just waste time: Meetings that start 10 minutes late are one-third less effective in terms of both actual and perceived outcomes than meetings that start on time. A study published in Transcripts of the Royal Society of London found that people placed in small groups asked to solve problems experience an individual IQ drop of approximately 15%. Walk into a meeting, instantly get dumber. So yeah: Stop having so many meetings. (Besides: A full calendarespecially a calendar full of meetingsis never a proxy for productivity.) But what if you really need to have a meeting? How can you make that meeting as focused and productive as possible? Borrow a move from Oprah Winfrey’s leadership tool kit. Start with intention Brendon Burchard, the author of High Performance Habits: How Extraordinary People Become That Way, says Oprah starts every meeting by asking three questions: What is our intention for this meeting? Whats important? What matters? The premise behind that approach is simple. High performers constantly seek clarity. (And employees who aren’t high performersyetneed clarity.) They work hard to sift out distractions so they can focus and continually refocus on what is important. Clarity? It isn’t something you get. Clarity is something you have to seek: You gain clarity, and focus, only when you actively search for them. Keep in mind the same holds true on a personal level. Successful people dont wait for an external trigger to start making changes. Successful people dont wait until New Years, or until Monday, or until the first of the month; they decide what changes they want to make and they get started. Now. Thats why no meeting agenda should include words like recap, information, review, or discussion. Bringing everyone up to speed, whether formally stated as an intention or not, is a terrible reason to have a meeting. And if information is required to make a decision during a meeting, share it ahead of time. Send documents, reports, etc., to participants in advance. Good meetings result in decisions. What. Who. When. Clear direction. Clear actions. Clear accountability. And stick to that intention That’s why the most productive meetings typically have one-sentence agendas: “Set product launch date.” “Select supplier.” “Determine roll-out responsibilities.” Those agendas are much easier to accomplish when you start a meeting the right way: by clearly stating intentions, and then sticking to those intentions. Try it. The next time you hold a meeting, kick it offon timeby answering the three questions for the group. State the intention. Explain why it’s important. Explain why it matters. If you find yourself in a meeting that’s drifting, help everyone focus by asking the three questions. Ask what you’re really trying to accomplish. Determine why it’s important, and why it matters. While it might feel awkward, everyone in the meeting will thank you for it. Because no one likes an unproductive meeting. And nor should you. By Jeff Haden This article originally appeared in Fast Companys sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
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U.S. state legislatures are where the action is for placing guardrails around artificial intelligence technologies, given the lack of meaningful federal regulation. The resounding defeat in Congress of a proposed moratorium on state-level AI regulation means states are free to continue filling the gap. Several states have already enacted legislation around the use of AI. All 50 states have introduced various AI-related legislation in 2025. Four aspects of AI in particular stand out from a regulatory perspective: government use of AI, AI in health care, facial recognition and generative AI. Government use of AI The oversight and responsible use of AI are especially critical in the public sector. Predictive AIAI that performs statistical analysis to make forecastshas transformed many governmental functions, from determining social services eligibility to making recommendations on criminal justice sentencing and parole. But the widespread use of algorithmic decision-making could have major hidden costs. Potential algorithmic harms posed by AI systems used for government services include racial and gender biases. Recognizing the potential for algorithmic harms, state legislatures have introduced bills focused on public sector use of AI, with emphasis on transparency, consumer protections and recognizing risks of AI deployment. Several states have required AI developers to disclose risks posed by their systems. The Colorado Artificial Intelligence Act includes transparency and disclosure requirements for developers of AI systems involved in making consequential decisions, as well as for those who deploy them. Montanas new Right to Compute law sets requirements that AI developers adopt risk management frameworksmethods for addressing security and privacy in the development processfor AI systems involved in critical infrastructure. Some states have established bodies that provide oversight and regulatory authority, such as those specified in New Yorks SB 8755 bill. AI in health care In the first half of 2025, 34 states introduced over 250 AI-related health bills. The bills generally fall into four categories: disclosure requirements, consumer protection, insurers use of AI and clinicians use of AI. Bills about transparency define requirements for information that AI system developers and organizations that deploy the systems disclose. Consumer protection bills aim to keep AI systems from unfairly discriminating against some people, and ensure that users of the systems have a way to contest decisions made using the technology. Numerous bills in state legislatures aim to regulate the use of AI in health care, including medical devices like this electrocardiogram recorder. VCG via Getty Images Bills covering insurers provide oversight of the payers use of AI to make decisions about health care approvals and payments. And bills about clinical uses of AI regulate use of the technology in diagnosing and treating patients. Facial recognition and surveillance In the U.S., a long-standing legal doctrine that applies to privacy protection issues, including facial surveillance, is to protect individual autonomy against interference from the government. In this context, facial recognition technologies pose significant privacy challenges as well as risks from potential biases. Facial recognition software, commonly used in predictive policing and national security, has exhibited biases against people of color and consequently is often considered a threat to civil liberties. A pathbreaking study by computer scientists Joy Buolamwini and Timnit Gebru found that facial recognition software poses significant challenges for Black people and other historically disadvantaged minorities. Facial recognition software was less likely to correctly identify darker faces. Bias also creeps into the data used to train these algorithms, for example when the composition of teams that guide the development of such facial recognition software lack diversity. By the end of 2024, 15 states in the U.S. had enacted laws to limit the potential harms from facial recognition. Some elements of state-level regulations are requirements on vendors to publish bias test reports and data management practices, as well as the need for human review in the use of these technologies. Porcha Woodruff was wrongly arrested for a carjacking in 2023 based on facial recognition technology. AP Photo/Carlos Osorio Generative AI and foundation models The widespread use of generative AI has also prompted concerns from lawmakers in many states. Utahs Artificial Intelligence Policy Act requires individuals and organizations to clearly disclose when theyre using generative AI systems to interact with someone when that person asks if AI is being used, though the legislature subsequently narrowed the scope to interactions that could involve dispensing advice or collecting sensitive information. Last year, California passed AB 2013, a generative AI law that requires developers to post information on their websites about the data used to train their AI systems, including foundation models. Foundation models are any AI model that is trained on extremely large datasets and that can be adapted to a wide range of tasks without additional training. AI developers have typically not been forthcoming about the training data they use. Such legislation could help copyright owners of content used in training AI overcome the lack of transparency. Trying to fill the gap In the absence of a comprehensive federal legislative framework, states have tried to address the gap by moving forward with their own legislative efforts. While such a patchwork of laws may complicate AI developers compliance efforts, I believe that states can provide important and needed oversight on privacy, civil rights and consumer protections. Meanwhile, the Trump administration announced its AI Action Plan on July 23, 2025. The plan says The Federal government should not allow AI-related Federal funding to be directed toward states with burdensome AI regulations . . . The move could hinder state efforts to regulate AI if states have to weigh regulations that might run afoul of the administrations definition of burdensome against needed federal funding for AI. Anjana Susarla is a professor of information systems at Michigan State University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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