Key Takeaways The European Commission will introduce the new International Digital Strategy that will focus on tech collaboration with the US and other countries. This is in contradiction to the growing pressure in Europe that calls for tech sovereignty and reducing tech dependence on the US. Low venture capital funding and a diverse regulatory landscape have been major challenges for tech innovation in Europe. Europe is seeing an increasing push to establish technological sovereignty and reduce the region’s reliance on US technology. However, there’s always been an undertone of acceptance that the EU is years behind the US when it comes to technological innovation and advancements. Now, the European Commission is planning to acknowledge this publicly. The EC will introduce a new International Digital Strategy, which will focus on collaboration with the United States and other tech-forward countries, such as Japan, South Korea, and India. The lawmakers believe that “decoupling” from the West is unrealistic and will instead push Europe further back in the technological race. Europe’s Call for Tech Sovereignty Several prominent political leaders and lawmakers have advocated for European sovereignty over technology and artificial intelligence.  For instance, Emmanuel Macron, the president of France, said in a speech in 2024 that Europe’s strategic autonomy is a conscious choice to end the region’s dependence on others. In an earlier speech, he also said that if Europe fails to build champions in areas such as digital and artificial intelligence, its choices will be dictated by others.  Similarly, Thierry Breton, the former EU Commissioner for Internal Markets, said that digital spending in the EU will breach the 20% target, underlining the importance of investing in European tech sovereignty. He focused on Europe’s declining market share in the semiconductor industry and called for the development of groundbreaking European tech. The Eurostack movement in the EU has also been gaining a lot of traction and support from various think tanks, academic researchers, and industry voices. Eurostack staff calls for the development of an indigenous infrastructure stack in the European region, including cloud, AI, semiconductors, digital services, and data centers. The main aim is to reduce Europe’s dependence on Chinese and US technology. This growing concern among EU well-wishers is quite understandable. Excessive reliance on the United States puts the US (meaning Donald Trump) in a controlling position, where he can arm-twist the European Union in matters of trade and even politics.  We have already seen an example of this during the tariff war, where Trump imposed a 25% tariff on automobiles (and their parts) and steel and aluminum products imported from the EU. Also, the fact that Google, Microsoft, and Amazon account for around 69% of the cloud market in the EU is quite concerning, too. Europe Wakes Up to Reality Despite positive speeches and statements by people in power in the EU, the fact remains that Europe is still lagging behind the United States. Bulgarian lawmaker Eva Maydell said that Europe should “sober up” and accept that the train has left the station. Dan Nechita, the current EU director for the Transatlantic Policy Network, said that it’s not the right time to be politically absolute and say that “we are going to do everything in Europe.” EU tech chief Virkkunen has been working hard to bring home the support of influential tech lobbies and emphasized the need to continue working with the United States. To put it in a nutshell, the European Commission is ready to accept the fact that the damage is done, and now Europe needs to play second fiddle and forge strategic partnerships with key technological leaders (primarily in the US) to stay alive in the race. Lack of Investments and the EU’s Regulation-First Approach One of the major reasons behind the European Union’s sluggish tech development is the lack of venture capital investments in the region. As per an IMF post, EU VC funds raised around $130B between 2013 and 2022. During the same time, the US raised $924B.  Similarly, annual VC investments in the EU are only 0.2% of the GDP when compared to 0.7% in the US. Currently, the United States accounts for a massive 52% of the global VC funds, whereas the EU holds just 5%.  Lack of investments has forced European startups to look elsewhere, especially the United States, for funding and support. One of the major reasons for such low venture capital interest in Europe is its diversity. Each of the 27 countries in the EU has its own regulatory and legal challenges, which make it difficult for multinational corporations to operate in the region.  Plus, the EU has adopted a regulation-first approach, which is very different from the United States. Of course, this approach has its own merits, but it has surely slowed down the speed of technological investments in the region.  For instance, the GDPR puts a truckload of regulatory and moral responsibility on companies to protect user data. Similarly, the AI Act focuses on the more ethical development of artificial intelligence that’s aligned with human values and refrains companies from exploiting public data. Sure, all of these are positive tech regulations important to protect the long-term sovereignty of the public at large. Even global tech advocates have praised the EU’s efforts for the development of safe and ethical technologies. However, we cannot ignore the fact that this has come at the cost of sluggish tech investments and overall growth. With its back against the wall, Europe needs to reassess its strengths and focus on areas such as open-source technologies, such as France’s La Suite numérique, and government-backed technological initiatives to have a say in the upcoming artificial intelligence and semiconductor race. Krishi is a seasoned tech journalist with over four years of experience writing about PC hardware, consumer technology, and artificial intelligence.  Clarity and accessibility are at the core of Krishi’s writing style. He believes technology writing should empower readers—not confuse them—and he’s committed to ensuring his content is always easy to understand without sacrificing accuracy or depth. Over the years, Krishi has contributed to some of the most reputable names in the industry, including Techopedia, TechRadar, and Tom’s Guide. A man of many talents, Krishi has also proven his mettle as a crypto writer, tackling complex topics with both ease and zeal. His work spans various formats—from in-depth explainers and news coverage to feature pieces and buying guides.  Behind the scenes, Krishi operates from a dual-monitor setup (including a 29-inch LG UltraWide) that’s always buzzing with news feeds, technical documentation, and research notes, as well as the occasional gaming sessions that keep him fresh.  Krishi thrives on staying current, always ready to dive into the latest announcements, industry shifts, and their far-reaching impacts.  When he's not deep into research on the latest PC hardware news, Krishi would love to chat with you about day trading and the financial markets—oh! And cricket, as well. View all articles by Krishi Chowdhary Our editorial process The Tech Report editorial policy is centered on providing helpful, accurate content that offers real value to our readers. We only work with experienced writers who have specific knowledge in the topics they cover, including latest developments in technology, online privacy, cryptocurrencies, software, and more. Our editorial policy ensures that each topic is researched and curated by our in-house editors. We maintain rigorous journalistic standards, and every article is 100% written by real authors.

House in Palm Springs | © Sydney Turturro via Unsplash Moving from an apartment to a house is a major life milestone. It usually means more space, more responsibility, and more freedom. But unless you plan it right, it can also come with more stress.  Whether upgrading to accommodate a growing family or simply looking for more room to breathe, here are five essential steps to help you move from an apartment to a house confidently and easily. 1. Start with a Clear Plan and Timeline One of the most common mistakes people make when moving from an apartment to a house is underestimating how long it takes. It’s not just about packing up your belongings; it’s about handling logistics, paperwork, and scheduling around daily life.  As soon as you know your moving date, create a moving checklist.  Outline what needs to be done weekly: notifying your landlord, scheduling the elevator if you’re in a high-rise, collecting packing materials, and booking your moving company. Planning ahead helps you avoid last-minute stress and unexpected costs. If possible, give yourself at least 6–8 weeks. That gives you enough time to declutter, coordinate with service providers, and ensure you’re fully prepared for move-in day. The earlier you start, the smoother everything flows. Hiring professional movers early in the process can also secure your preferred date and provide access to helpful services, such as packing, storage, or specialized transportation. With everything scheduled well in advance, you’ll have the peace of mind needed to focus on your new adventure. 2. Downsize Before You Upsize It may sound counterintuitive, but moving to a bigger space doesn’t mean you should bring everything with you.  Over time, we accumulate furniture, clothes, gadgets, and kitchen tools that serve little purpose. And in a small apartment, many of these items might have been crammed into closets or storage bins and forgotten altogether.  Now’s the perfect time to declutter and lighten the load before the move. Start by walking through your apartment and taking stock of everything. Ask yourself what truly adds value to your life and what’s just taking up space. If you haven’t used something in over a year, it’s probably safe to let it go. You can donate, sell, or recycle items as needed. A good rule of thumb is to be ruthless. A cleaner move means a cleaner start in your new home. By purging the excess, you’ll reduce moving costs and arrive at your new house with a fresh mindset. There’s no sense in transporting items you no longer want or need. Instead, you’ll be able to unpack more quickly and enjoy your new space without clutter. 3. Prepare for a Different Kind of Space Living in a house is very different from apartment life. The layout, square footage, and storage options all change, which means your furniture and lifestyle habits may also need to adapt. That cozy loveseat that fits perfectly in your apartment living room might look dwarfed in a larger house.  Before moving, visit the house if possible and take room measurements.  Consider creating a rough floor plan to determine where each piece of furniture will fit. This not only helps your local movers place items on move-in day, but it also ensures you don’t waste time and energy relocating things that won’t work in the new space. Apps and online tools can help you visualize your layout ahead of time. Beyond furniture, also think about what your new home may need.  Will you have a backyard that needs maintenance? A garage that requires storage shelving? An extra guest room or home office that needs furnishing?  While you don’t have to buy everything at once, it’s smart to budget for future purchases so you can comfortably and intentionally grow into your home. 4. Handle Utilities, Address Changes, and Logistics © Peter Thomas via Unsplash © Mitch via Unsplash Unlike apartments, where utilities may be partially covered or managed by the landlord, houses typically require you to set up and manage everything yourself.  This includes electricity, water, gas, internet, trash collection, and sometimes even lawn care services. Don’t wait until the last minute; contact providers at least a week before your move to schedule installation or transfers. At the same time, update your address with your bank, subscription services, and relevant government agencies. This helps ensure you continue to receive important mail and prevents service disruptions. If you’re moving within the same city, this can be fairly straightforward. If you’re moving to a different region or province, however, make sure you check for local utility providers and regional services. Elevator bookings and parking permits are other key details to address, especially when moving out of an apartment in a busy area.  Confirm all building rules and moving hours in advance, and inform your movers so they can plan accordingly. Clear communication on these details makes the moving day smoother for everyone involved. 5. Rely on a Trusted Moving Partner Perhaps the most important step in this process is choosing the right moving company.  Apartment-to-house moves require experience, careful coordination, and physical effort, especially when dealing with tight stairwells, narrow hallways, or long distances from the apartment to the truck.  A professional moving team can handle the logistics efficiently while protecting your belongings from damage. Instead of doing it all yourself, you can count on us to carry the load literally. We bring the right equipment, vehicles, and muscle, so you don’t have to worry about heavy lifting or unexpected delays. More importantly, we offer peace of mind during an exciting and overwhelming time. A good moving experience sets the tone for your new chapter. Let us help make that transition smooth, stress-free, and even enjoyable. Final Word Moving from an apartment to a house is more than just a physical shift; it’s a lifestyle change. With the right planning, thoughtful decisions, and support from experienced movers, you can make the process simple and even fun. Whether it’s your first home or your dream upgrade, we’re here to guide you every step of the way. Frequently Asked Questions  1. How far in advance should I book a moving company when moving from an apartment to a house? We recommend booking your moving company at least 4–6 weeks in advance, especially during peak moving seasons (spring and summer). This gives you the best chance to secure your preferred date and time while also allowing time for proper planning, packing, and coordination with building management if needed. 2. What’s the best way to downsize before moving into a house? Even though you’re moving to a larger space, it’s wise to declutter before your move. Sort items by category, keep, donate, sell, or discard, and be honest about what you actually use. Unused furniture, duplicate kitchenware, and old clothes often don’t need to make the move. A lighter load means a faster, more affordable, and more organized transition. 3. Will all my apartment furniture fit properly in a house?  Some furniture from a compact apartment may not always feel too small or awkward in a larger home. We recommend measuring key pieces and comparing them with the dimensions of the new space before moving. Our team can help you decide what’s worth moving and even assist with layout planning to ensure everything fits where it should. 4. What should I do about utilities when moving into a house?  Unlike apartment living, homeowners are responsible for setting up all their utilities individually. Be sure to contact providers for electricity, water, internet, gas, and waste collection at least a week before your move. Scheduling ahead ensures your new home is move-in ready, and you won’t experience any service interruptions. 5. Do I need professional movers for a short move from an apartment to a house? Even if you’re moving just a few blocks, a professional moving team makes the process faster, safer, and far less stressful. We handle the heavy lifting, stairs, tight corners, and transportation logistics, so you don’t have to. Our experience ensures that your belongings arrive safely, regardless of the distance. GuidesTips by ArchEyes Team Leave a comment

Chinese propaganda and social engineering operations have been using ChatGPT to create posts, comments and drive engagement at home and abroad. OpenAI said it has recently disrupted four Chinese covert influence operations that were using its tool to

Amazon’s revamped Alexa at center of Reddit’s legal fight with Anthropic.

The Interlock ransomware gang has claimed a recent cyberattack on the Kettering Health healthcare network and leaked data allegedly stolen from breached systems. [...]

프린시펄 파이낸셜 그룹(Principal Financial Group, PFG)은 지난 몇 년 동안 AI 활용이 급증하면서 이를 종합적으로 관리할 수 있는 AI 거버넌스 전략과 이를 실행할 도구가 절실해졌다. PFG의 부사장 겸 최고 데이터 및 분석 책임자인 라제시 아로라는 “현재 자연어 처리, 머신러닝, 생성형 AI 모델 등 100건 이상의 AI 사용례를 운영 중이며, 이를 통해 사기 탐지, 보험

The cloud has changed everything. It’s faster, cheaper, and easier to scale than traditional infrastructure. Initially, most companies chose a single cloud provider. That’s no longer enough. Now, nearly 86% of businesses use more than one cloud. This approach—called multi-cloud—lets teams choose the best features from each provider. But it also opens the door to new security risks. When apps, data, and tools are scattered across platforms, managing security gets harder. And in today's world of constant cyber threats, ignoring cloud security is not an option. Let’s walk through real-world challenges and the best ways to protect business data in a multi-cloud environment. 1. Know What You’re Working With Start with visibility. Make a full inventory of the cloud platforms, apps, and storage your business uses. Ask every department—marketing, finance, HR—what tools they’ve signed up for. Many use services without informing IT. This is shadow IT, and it’s risky. Once you have the list, figure out what data lives where. Some workloads are low-risk. Others involve customer records, credit card data, or legal files. Prioritize those. 2. Build a Unified Security Strategy One of the biggest mistakes companies make is treating each cloud provider as a separate system. Every provider has its own rules, tools, and settings. If your security strategy is broken up, gaps will appear. Instead, aim for a single, connected approach. Use the same access rules, encryption standards, and monitoring tools across all clouds. You don’t want different policies on AWS and Azure—it just invites trouble. Tools like centralized dashboards, SIEM (Security Information and Event Management), and SOAR (Security Orchestration, Automation, and Response) help you keep everything in one place. 3. Enforce Strict Access Controls In a multi-cloud world, identity and access control are one of the hardest things to get right. Every platform has its own login system. Without proper integration, mistakes happen. Someone might get more access than they need, or never lose access when they leave the company. Stick to these practices: Use role-based access control. Limit permissions to the bare minimum. Turn on multi-factor authentication. Link logins across platforms using identity federation. The more consistent your access rules are, the easier it is to control who gets in and what they can do. 4. Use the Zero Trust Model Zero Trust means never assume anything is safe. Every user, device, and app must prove itself—every time. Even if a user is on your network, don’t trust them by default. This model reduces risk. It checks each request. It verifies users. And it looks for signs of abnormal behavior, like someone logging in from a new device or country. Zero Trust works well with automation and real-time monitoring. It also forces teams to rethink how data is shared and accessed. 5. Encrypt Data—Always Encryption is a basic but powerful layer of defense. It protects data whether it’s sitting in storage or moving between systems. If attackers get in, encrypted data is useless without the keys. Most cloud platforms offer built-in encryption. But don’t rely only on that. You can manage your own keys with tools like AWS KMS or Azure Key Vault. That gives you more control. To stay safe: Encrypt both at rest and in transit. Avoid default settings. Rotate encryption keys regularly. 6. Monitor in Real Time Security is not a one-time task. You need to watch your systems around the clock. Set alerts for things like large file downloads, unusual logins, or traffic spikes. Centralized monitoring helps a lot. It pulls logs from all your platforms and tools into one place. That way, your security team isn’t flipping between dashboards when something goes wrong. Also, use automation to filter out noise and surface real threats faster. 7. Set Up Regular Audits and Compliance Checks Multi-cloud setups are great for flexibility, but complex when it comes to compliance. Each platform has its own set of controls and certifications. Managing them all can be overwhelming. That’s why audits matter. Run security checks on a regular schedule—monthly, quarterly, or after every major change. Look for misconfigured permissions, missing patches, or unsecured data. And document everything. Also, make sure your tools help meet regulations like GDPR, HIPAA, or PCI DSS. Automated compliance scans can help stay on top of this. 8. Prevent Data Loss with Smart Policies Sensitive data is always at risk. Employees might share it by mistake. Attackers might try to steal it. That’s where Data Loss Prevention (DLP) comes in. DLP tools block unauthorized sharing of personal data, financial records, or internal files. You can create rules like “Don’t send customer SSNs over email” or “Block uploads of credit card data to personal drives.” DLP also supports compliance and helps avoid lawsuits or fines when accidents happen. 9. Automate Where You Can Manual work slows things down, and mistakes happen. That’s why automation is key in cloud security. Automate things like: Patch management Access reviews Backup schedules Security alerts Automation speeds up your response time. It also frees your security team to focus on serious issues, not routine tasks. 10. Centralized Security Control One major downside of multi-cloud isa lack of visibility. If you’re jumping between different tools for each cloud, you miss things. Instead, use a centralized security management system. It collects data from all clouds, shows risk levels, flags issues, and helps you fix them from one place. This unified view makes a huge difference. It helps you react faster and stay ahead of threats. Final Thought Cloud providers have made data storage and computing easier than ever. But with great power comes risk. Using multiple clouds gives more choice, but also more responsibility. Most businesses today are not ready. Only 15% have a mature multi-cloud security plan, says the 2023 Cisco Cyber Security Readiness Index. That means many are exposed. The good news? You can fix this. Start with simple steps. Know what you use. Lock it down. Watch it closely. Keep improving. And above all, treat cloud security not as a technical box to check, but as something critical to your business. Because in today’s world, a single breach can shut you down. And that’s too big a risk to ignore.

Posted on : June 5, 2025 By Tech World Times AI  Rate this post Artificial intelligence tools now touch nearly every corner of modern business, from customer service and marketing to supply chain management and HR. These powerful technologies promise speed, accuracy, and insight, but their missteps can cause more than temporary inconvenience. A single AI-driven error can result in regulatory investigations, civil lawsuits, or public scandals that threaten the foundation of a business. Understanding how legal exposure arises from AI mistakes—and how a skilled attorney protects your interests—is no longer an option, but a requirement for any forward-thinking business owner. What Types of AI Errors Create Legal Liability? AI does not think or reason like a human; it follows code and statistical patterns, sometimes with unintended results. These missteps can create a trail of legal liability for any business owner. For example, an online retailer’s AI recommends discriminatory pricing, sparking allegations of unfair trade practices. An HR department automates hiring decisions with AI, only to face lawsuits for violating anti-discrimination laws. Even an AI-driven chatbot, when programmed without proper safeguards, can inadvertently give health advice or misrepresent product claims—exposing the company to regulatory penalties. Cases like these are regularly reported in Legal news as businesses discover the high cost of digital shortcuts. When Is a Business Owner Liable for AI Mistakes? Liability rarely rests with the software developer or the tool itself. Courts and regulators expect the business to monitor, supervise, and, when needed, override AI decisions. Suppose a financial advisor uses AI to recommend investments, but the algorithm suggests securities that violate state regulations. Even if the AI was “just following instructions,” the advisor remains responsible for client losses. Similarly, a marketing team cannot escape liability if their AI generates misleading advertising. The bottom line: outsourcing work to AI does not outsource legal responsibility. How Do AI Errors Harm Your Reputation and Operations? AI mistakes can leave lasting marks on a business’s reputation, finances, and operations. A logistics firm’s route-optimization tool creates data leaks that breach customer privacy and trigger costly notifications. An online business suffers public backlash after an AI-powered customer service tool sends offensive responses to clients. Such incidents erode public trust, drive customers to competitors, and divert resources into damage control rather than growth. Worse, compliance failures can result in penalties or shutdown orders, putting the entire enterprise at risk. What Steps Reduce Legal Risk From AI Deployments? Careful planning and continuous oversight keep AI tools working for your business—not against it. Compliance is not a “set it and forget it” matter. Proactive risk management transforms artificial intelligence from a liability into a valuable asset. Routine audits, staff training, and transparent policies form the backbone of safe, effective AI use in any organization. You should review these AI risk mitigation strategies below. Implement Manual Review of Sensitive Outputs: Require human approval for high-risk tasks, such as legal filings, financial transactions, or customer communications. A payroll company’s manual audits prevented the accidental overpayment of employees by catching AI-generated errors before disbursement. Update AI Systems for Regulatory Changes: Stay ahead of new laws and standards by regularly reviewing AI algorithms and outputs. An insurance brokerage avoided regulatory fines by updating their risk assessment models as privacy laws evolved. Document Every Incident and Remediation Step: Keep records of AI errors, investigations, and corrections. A healthcare provider’s transparency during a patient data mix-up helped avoid litigation and regulatory penalties. Limit AI Access to Personal and Sensitive Data: Restrict the scope and permissions of AI tools to reduce the chance of data misuse. A SaaS provider used data minimization techniques, lowering the risk of exposure in case of a system breach. Consult With Attorneys for Custom Policies and Protocols: Collaborate with experienced Attorneys to design, review, and update AI compliance frameworks. How Do Attorneys Shield Your Business From AI Legal Risks? Attorneys provide a critical safety net as AI integrates deeper into business operations. They draft tailored contracts, establish protocols for monitoring and escalation, and assess risks unique to your industry. In the event of an AI-driven incident, legal counsel investigates the facts, manages communication with regulators, and builds a robust defense. By providing training, ongoing guidance, and crisis management support, attorneys ensure that innovation doesn’t lead to exposure—or disaster. With the right legal partner, businesses can harness AI’s power while staying firmly on the right side of the law. Tech World TimesTech World Times (TWT), a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com

Every few weeks, it seems like there’s a new headline about a lawyer getting in trouble for submitting filings containing, in the words of one judge, “bogus AI-generated research.” The details vary, but the throughline is the same: an attorney turns to a large language model (LLM) like ChatGPT to help them with legal research (or worse, writing), the LLM hallucinates cases that don’t exist, and the lawyer is none the wiser until the judge or opposing counsel points out their mistake. In some cases, including an aviation lawsuit from 2023, attorneys have had to pay fines for submitting filings with AI-generated hallucinations. So why haven’t they stopped?The answer mostly comes down to time crunches, and the way AI has crept into nearly every profession. Legal research databases like LexisNexis and Westlaw have AI integrations now. For lawyers juggling big caseloads, AI can seem like an incredibly efficient assistant. Most lawyers aren’t necessarily using ChatGPT to write their filings, but they are increasingly using it and other LLMs for research. Yet many of these lawyers, like much of the public, don’t understand exactly what LLMs are or how they work. One attorney who was sanctioned in 2023 said he thought ChatGPT was a “super search engine.” It took submitting a filing with fake citations to reveal that it’s more like a random-phrase generator — one that could give you either correct information or convincingly phrased nonsense.Andrew Perlman, the dean of Suffolk University Law School, argues many lawyers are using AI tools without incident, and the ones who get caught with fake citations are outliers. “I think that what we’re seeing now — although these problems of hallucination are real, and lawyers have to take it very seriously and be careful about it — doesn’t mean that these tools don’t have enormous possible benefits and use cases for the delivery of legal services,” Perlman said. Legal databases and research systems like Westlaw are incorporating AI services.In fact, 63 percent of lawyers surveyed by Thomson Reuters in 2024 said they’ve used AI in the past, and 12 percent said they use it regularly. Respondents said they use AI to write summaries of case law and to research “case law, statutes, forms or sample language for orders.” The attorneys surveyed by Thomson Reuters see it as a time-saving tool, and half of those surveyed said “exploring the potential for implementing AI” at work is their highest priority. “The role of a good lawyer is as a ‘trusted advisor’ not as a producer of documents,” one respondent said. But as plenty of recent examples have shown, the documents produced by AI aren’t always accurate, and in some cases aren’t real at all.RelatedIn one recent high-profile case, lawyers for journalist Tim Burke, who was arrested for publishing unaired Fox News footage in 2024, submitted a motion to dismiss the case against him on First Amendment grounds. After discovering that the filing included “significant misrepresentations and misquotations of supposedly pertinent case law and history,” Judge Kathryn Kimball Mizelle, of Florida’s middle district, ordered the motion to be stricken from the case record. Mizelle found nine hallucinations in the document, according to the Tampa Bay Times.Mizelle ultimately let Burke’s lawyers, Mark Rasch and Michael Maddux, submit a new motion. In a separate filing explaining the mistakes, Rasch wrote that he “assumes sole and exclusive responsibility for these errors.” Rasch said he used the “deep research” feature on ChatGPT pro, which The Verge has previously tested with mixed results, as well as Westlaw’s AI feature.Rasch isn’t alone. Lawyers representing Anthropic recently admitted to using the company’s Claude AI to help write an expert witness declaration submitted as part of the copyright infringement lawsuit brought against Anthropic by music publishers. That filing included a citation with an “inaccurate title and inaccurate authors.” Last December, misinformation expert Jeff Hancock admitted he used ChatGPT to help organize citations in a declaration he submitted in support of a Minnesota law regulating deepfake use. Hancock’s filing included “two citation errors, popularly referred to as ‘hallucinations,’” and incorrectly listed authors for another citation. These documents do, in fact, matter — at least in the eyes of judges. In a recent case, a California judge presiding over a case against State Farm was initially swayed by arguments in a brief, only to find that the case law cited was completely made up. “I read their brief, was persuaded (or at least intrigued) by the authorities that they cited, and looked up the decisions to learn more about them – only to find that they didn’t exist,” Judge Michael Wilner wrote.Perlman said there are several less risky ways lawyers use generative AI in their work, including finding information in large tranches of discovery documents, reviewing briefs or filings, and brainstorming possible arguments or possible opposing views. “I think in almost every task, there are ways in which generative AI can be useful — not a substitute for lawyers’ judgment, not a substitute for the expertise that lawyers bring to the table, but in order to supplement what lawyers do and enable them to do their work better, faster, and cheaper,” Perlman said.But like anyone using AI tools, lawyers who rely on them to help with legal research and writing need to be careful to check the work they produce, Perlman said. Part of the problem is that attorneys often find themselves short on time — an issue he says existed before LLMs came into the picture. “Even before the emergence of generative AI, lawyers would file documents with citations that didn’t really address the issue that they claimed to be addressing,” Perlman said. “It was just a different kind of problem. Sometimes when lawyers are rushed, they insert citations, they don’t properly check them; they don’t really see if the case has been overturned or overruled.” (That said, the cases do at least typically exist.)Another, more insidious problem is the fact that attorneys — like others who use LLMs to help with research and writing — are too trusting of what AI produces. “I think many people are lulled into a sense of comfort with the output, because it appears at first glance to be so well crafted,” Perlman said.Alexander Kolodin, an election lawyer and Republican state representative in Arizona, said he treats ChatGPT as a junior-level associate. He’s also used ChatGPT to help write legislation. In 2024, he included AI text in part of a bill on deepfakes, having the LLM provide the “baseline definition” of what deepfakes are and then “I, the human, added in the protections for human rights, things like that it excludes comedy, satire, criticism, artistic expression, that kind of stuff,” Kolodin told The Guardian at the time. Kolodin said he “may have” discussed his use of ChatGPT with the bill’s main Democratic cosponsor but otherwise wanted it to be “an Easter egg” in the bill. The bill passed into law. Kolodin — who was sanctioned by the Arizona State Bar in 2020 for his involvement in lawsuits challenging the result of the 2020 election — has also used ChatGPT to write first drafts of amendments, and told The Verge he uses it for legal research as well. To avoid the hallucination problem, he said, he just checks the citations to make sure they’re real.“You don’t just typically send out a junior associate’s work product without checking the citations,” said Kolodin. “It’s not just machines that hallucinate; a junior associate could read the case wrong, it doesn’t really stand for the proposition cited anyway, whatever. You still have to cite-check it, but you have to do that with an associate anyway, unless they were pretty experienced.”Kolodin said he uses both ChatGPT’s pro “deep research” tool and the LexisNexis AI tool. Like Westlaw, LexisNexis is a legal research tool primarily used by attorneys. Kolodin said that in his experience, it has a higher hallucination rate than ChatGPT, which he says has “gone down substantially over the past year.” AI use among lawyers has become so prevalent that in 2024, the American Bar Association issued its first guidance on attorneys’ use of LLMs and other AI tools. Lawyers who use AI tools “have a duty of competence, including maintaining relevant technological competence, which requires an understanding of the evolving nature” of generative AI, the opinion reads. The guidance advises lawyers to “acquire a general understanding of the benefits and risks of the GAI tools” they use — or, in other words, to not assume that an LLM is a “super search engine.” Attorneys should also weigh the confidentiality risks of inputting information relating to their cases into LLMs and consider whether to tell their clients about their use of LLMs and other AI tools, it states.Perlman is bullish on lawyers’ use of AI. “I do think that generative AI is going to be the most impactful technology the legal profession has ever seen and that lawyers will be expected to use these tools in the future,” he said. “I think that at some point, we will stop worrying about the competence of lawyers who use these tools and start worrying about the competence of lawyers who don’t.”Others, including one of the judges who sanctioned lawyers for submitting a filing full of AI-generated hallucinations, are more skeptical. “Even with recent advances,” Wilner wrote, “no reasonably competent attorney should out-source research and writing to this technology — particularly without any attempt to verify the accuracy of that material.”See More:

Missing the big picture US science is being wrecked, and its leadership is fighting the last war Facing an extreme budget, the National Academies hosted an event that ignored it. John Timmer – Jun 4, 2025 6:00 pm | 16 Credit: JHVE Photo Credit: JHVE Photo Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only   Learn more WASHINGTON, DC—The general outline of the Trump administration's proposed 2026 budget was released a few weeks back, and it included massive cuts for most agencies, including every one that funds scientific research. Late last week, those agencies began releasing details of what the cuts would mean for the actual projects and people they support. And the results are as bad as the initial budget had suggested: one-of-a-kind scientific experiment facilities and hardware retired, massive cuts in supported scientists, and entire areas of research halted. And this comes in an environment where previously funded grants are being terminated, funding is being held up for ideological screening, and universities have been subject to arbitrary funding freezes. Collectively, things are heading for damage to US science that will take decades to recover from. It's a radical break from the trajectory science had been on. That's the environment that the US's National Academies of Science found itself in yesterday while hosting the State of the Science event in Washington, DC. It was an obvious opportunity for the nation's leading scientific organization to warn the nation of the consequences of the path that the current administration has been traveling. Instead, the event largely ignored the present to worry about a future that may never exist. The proposed cuts The top-line budget numbers proposed earlier indicated things would be bad: nearly 40 percent taken off the National Institutes of Health's budget, the National Science Foundation down by over half. But now, many of the details of what those cuts mean are becoming apparent. NASA's budget includes sharp cuts for planetary science, which would be cut in half and then stay flat for the rest of the decade, with the Mars Sample Return mission canceled. All other science budgets, including Earth Science and Astrophysics, take similar hits; one astronomer posted a graphic showing how many present and future missions that would mean. Active missions that have returned unprecedented data, like Juno and New Horizons, would go, as would two Mars orbiters. As described by Science magazine's news team, "The plans would also kill off nearly every major science mission the agency has not yet begun to build." A chart prepared by astronomer Laura Lopez showing just how many astrophysics missions will be cancelled. Credit: Laura Lopez The National Science Foundation, which funds much of the US's fundamental research, is also set for brutal cuts. Biology, engineering, and education will all be slashed by over 70 percent; computer science, math and physical science, and social and behavioral science will all see cuts of over 60 percent. International programs will take an 80 percent cut. The funding rate of grant proposals is expected to drop from 26 percent to just 7 percent, meaning the vast majority of grants submitted to the NSF will be a waste of time. The number of people involved in NSF-funded activities will drop from over 300,000 to just 90,000. Almost every program to broaden participation in science will be eliminated. As for specifics, they're equally grim. The fleet of research ships will essentially become someone else's problem: "The FY 2026 Budget Request will enable partial support of some ships." We've been able to better pin down the nature and location of gravitational wave events as detectors in Japan and Italy joined the original two LIGO detectors; the NSF will reverse that progress by shutting one of the LIGOs. The NSF's contributions to detectors at the Large Hadron Collider will be cut by over half, and one of the two very large telescopes it was helping fund will be cancelled (say goodbye to the Thirty Meter Telescope). "Access to the telescopes at Kitt Peak and Cerro Tololo will be phased out," and the NSF will transfer the facilities to other organizations. The Department of Health and Human Services has been less detailed about the specific cuts its divisions will see, largely focusing on the overall numbers, which are down considerably. The NIH, which is facing a cut of over 40 percent, will be reorganized, with its 19 institutes pared down to just eight. This will result in some odd pairings, such as the dental and eye institutes ending up in the same place; genomics and biomedical imaging will likewise end up under the same roof. Other groups like the Centers for Disease Control and Prevention and the Food and Drug Administration will also face major cuts. Issues go well beyond the core science agencies, as well. In the Department of Energy, funding for wind, solar, and renewable grid integration has been zeroed out, essentially ending all programs in this area. Hydrogen and fuel cells face a similar fate. Collectively, these had gotten over $600 billion dollars in 2024's budget. Other areas of science at the DOE, such as high-energy physics, fusion, and biology, receive relatively minor cuts that are largely in line with the ones faced by administration priorities like fossil and nuclear energy. Will this happen? It goes without saying that this would amount to an abandonment of US scientific leadership at a time when most estimates of China's research spending show it approaching US-like levels of support. Not only would it eliminate many key facilities, instruments, and institutions that have helped make the US a scientific powerhouse, but it would also block the development of newer and additional ones. The harms are so widespread that even topics that the administration claims are priorities would see severe cuts. And the damage is likely to last for generations, as support is cut at every stage of the educational pipeline that prepares people for STEM careers. This includes careers in high-tech industries, which may require relocation overseas due to a combination of staffing concerns and heightened immigration controls. That said, we've been here before in the first Trump administration, when budgets were proposed with potentially catastrophic implications for US science. But Congress limited the damage and maintained reasonably consistent budgets for most agencies. Can we expect that to happen again? So far, the signs are not especially promising. The House has largely adopted the Trump administration's budget priorities, despite the fact that the budget they pass turns its back on decades of supposed concerns about deficit spending. While the Senate has yet to take up the budget, it has also been very pliant during the second Trump administration, approving grossly unqualified cabinet picks such as Robert F. Kennedy Jr. All of which would seem to call for the leadership of US science organizations to press the case for the importance of science funding to the US, and highlight the damage that these cuts would cause. But, if yesterday's National Academies event is anything to judge by, the leadership is not especially interested. Altered states As the nation's premier science organization, and one that performs lots of analyses for the government, the National Academies would seem to be in a position to have its concerns taken seriously by members of Congress. And, given that the present and future of science in the US is being set by policy choices, a meeting entitled the State of the Science would seem like the obvious place to address those concerns. If so, it was not obvious to Marcia McNutt, the president of the NAS, who gave the presentation. She made some oblique references to current problems, saying, that “We are embarking on a radical new experiment in what conditions promote science leadership, with the US being the treatment group, and China as the control," and acknowledged that "uncertainties over the science budgets for next year, coupled with cancellations of billions of dollars of already hard-won research grants, is causing an exodus of researchers." But her primary focus was on the trends that have been operative in science funding and policy leading up to but excluding the second Trump administration. McNutt suggested this was needed to look beyond the next four years. However, that ignores the obvious fact that US science will be fundamentally different if the Trump administration can follow through on its plans and policies; the trends that have been present for the last two decades will be irrelevant. She was also remarkably selective about her avoidance of discussing Trump administration priorities. After noting that faculty surveys have suggested they spend roughly 40 percent of their time handling regulatory requirements, she twice mentioned that the administration's anti-regulatory stance could be a net positive here (once calling it "an opportunity to help"). Yet she neglected to note that many of the abandoned regulations represent a retreat from science-driven policy. McNutt also acknowledged the problem of science losing the bipartisan support it has enjoyed, as trust in scientists among US conservatives has been on a downward trend. But she suggested it was scientists' responsibility to fix the problem, even though it's largely the product of one party deciding it can gain partisan advantage by raising doubts about scientific findings in fields like climate change and vaccine safety. The panel discussion that came after largely followed McNutt's lead in avoiding any mention of the current threats to science. The lone exception was Heather Wilson, president of the University of Texas at El Paso and a former Republican member of the House of Representatives and Secretary of the Air Force during the first Trump administration. Wilson took direct aim at Trump's cuts to funding for underrepresented groups, arguing, "Talent is evenly distributed, but opportunity is not." After arguing that "the moral authority of science depends on the pursuit of truth," she highlighted the cancellation of grants that had been used to study diseases that are more prevalent in some ethnic groups, saying "that's not woke science—that's genetics." Wilson was clearly the exception, however, as the rest of the panel largely avoided direct mention of either the damage already done to US science funding or the impending catastrophe on the horizon. We've asked the National Academies' leadership a number of questions about how it perceives its role at a time when US science is clearly under threat. As of this article's publication, however, we have not received a response. At yesterday's event, however, only one person showed a clear sense of what they thought that role should be—Wilson again, whose strongest words were directed at the National Academies themselves, which she said should "do what you've done since Lincoln was president," and stand up for the truth. John Timmer Senior Science Editor John Timmer Senior Science Editor John is Ars Technica's science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots. 16 Comments