By Rachel Scharf ( December 4, 2024, 8:14 PM EST) — A Manhattan federal judge rejected the U.S. Department of Justice’s bid to see emails between Live Nation Entertainment Inc. lawyers and counsel for arena operator Oak View Group, holding Wednesday that these communications discussed a joint legal strategy for the government’s antitrust investigation…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

PLD Space has secured an €11mn loan to help fund the development of a liftoff site for its partially reusable Miura 5 rocket, which is set to become Europe’s first privately developed satellite launcher — unless one of its competitors gets there first.  The loan will help the Spanish startup construct the launch facility, located at Europe’s primary spaceport in French Guiana and estimated to cost around €16mn overall. PLD Space launched its first, smaller rocket, Miura 1, from Spain last year. However, for a bigger orbital launcher like Miura 5, the company needs a facility with specific capabilities. These include a large launch pad, a comprehensive mission control centre, and access to a geographically optimal location for orbital trajectories.   PLD Space plans to conduct test and flight campaigns for MIURA 5 from the site. The rocket’s maiden flight is scheduled for late 2025.  Raúl Torres and Raúl Verdú, university classmates, founded PLD Space in 2011 with a vision to create something akin to a European version of Elon Musk’s SpaceX. The company now employs over 250 people. It has raised €170mn in funding to date. What day is today? It’s CYBER MONDAY! TNW Conference is offering an exclusive 30% discount on their startup and scaleup programs this week only. This is the best deal you’ll get before prices change in January. The company’s ambitions extend beyond MIURA 5. It plans to develop Miura Next,  a family of heavy-lift reusable rockets by the 2030s and the Lince capsule, Europe’s first private manned spacecraft. Europe’s space race is firing up  Morgan Stanley predicts the space economy will grow from €355 billion in 2020 to over €1 trillion by 2030 — and competition for the rewards is fierce. The USA remains a global leader, while China is emerging as a powerful challenger. Then there’s Europe, which has historically lagged behind in the space race.  Against this backdrop, companies like PLD Space are seen as crucial for ensuring Europe doesn’t become too dependent on foreign powers — and companies like SpaceX — for access to space. PLD Space hopes to be the flagbearer for a new era of private European spaceflight. But it’s not alone. The company faces stiff competition from other startups with similar ambitions and similar timelines.  Two of the most promising are Rocket Factory Augsburg (RFA) and Isar Aerospace, both from Germany. These startups are developing partially reuseable, orbital launchers with a similar carrying capacity to Miura 5 — 1000-1500kg.  All three contenders are rushing to become the first private company to launch a European-built satellite launcher into orbit.  RFA faced a setback in August when its rocket blew up during testing, pushing back its projected launch date to 2025 at the earliest. Meanwhile, Isar Aerospace commenced hot-fire tests of its Spectrum rocket in September, but with the year almost over it looks like the company’s original 2024 launch date projection will slip away.  Whoever gets there first, one thing’s for sure: Europe’s private space race is heating up. And that’s good for the continent’s celestial ambitions whichever way you slice it. source

The question “Is the open web dying?” might evoke Betteridge’s law of headlines, which suggests that any headline ending in a question mark can be answered with “no.” But here, the answer is, unfortunately, closer to “yes.” To understand why the open web is faltering and to assess AI’s role in this decline, let’s first define what we mean by “open web.” For the purposes of this article, the open web is: Publicly accessible without barriers like paywalls or subscription fees Unfiltered by governmental censorship Free from platform-based algorithmic control, allowing content to be discovered through open browsing and linking Interoperable, meaning that it fosters connections between sites without restrictions The open web was once the backbone of online information, enabling anyone with an internet connection to freely share, link, and access content. But a combination of shifting business models, regulatory changes, and technological advancements — most recently AI — is reshaping the internet into a more closed, restrictive environment. The squeeze on small content providers and diversity A primary threat to the open web is the gradual exclusion of small content providers. Unlike large corporations with abundant resources, independent websites and niche creators often struggle to compete with the heavily promoted and easily accessible content hosted on major platforms. These smaller providers contribute significantly to the diversity of online information. When they’re squeezed out by competition or forced to hide behind paywalls to sustain themselves, it reduces the variety of voices and viewpoints available on the web. Algorithm-driven platforms are partly to blame for this problem. On platforms like TikTok, Instagram, and Facebook, what you see is largely determined by engagement-driven algorithms. These algorithms prioritize content that keeps users hooked, which tends to favor big brands, viral content, and sensationalized news over niche, independent content. Smaller creators who can’t afford to engage in paid promotion or optimize their content for these algorithms struggle to gain visibility, further eroding the diversity that once characterized the open web. Algorithmic search and the downfall of small organizations Algorithmic control is not limited to social media platforms; search engines are also shifting how they prioritize and display content. In a TheVerge.com article (“Google is getting even worse for independent sites”), a series of changes to Google’s search algorithm were shown to heavily impact small websites. In one example provided in the article, a website stated that its search traffic decreased 91% within a few months, devastating its business. Google’s Pandu Nayak was quoted during a Q&A at the most recent Google Web Creator Summit, when asked about the massive drop in traffic for smaller sites following a search algorithm change, “Our goal is to surface great content for users. I suspect there is a lot of great content you guys are creating that we are not surfacing to our users, but I can’t give you any guarantees, unfortunately” (“Google Algorithm Update Due Soon, But Don’t Expect Lost Ranking Recovery,” userp.io). The platform dependency problem: The case of Facebook and Zynga When platforms dominate traffic, they gain power over businesses that depend on them. Facebook’s relationship with game developer Zynga is a prime example. For a period, Zynga relied almost entirely on Facebook to drive users to its games. This dependency made Zynga vulnerable to Facebook’s policy shifts, and following one set of changes to Facebook’s policies, Zynga’s reach and revenue collapsed. This “platform dependency problem” is increasingly common. Businesses and content providers have become overly reliant on platforms, such as Facebook, Instagram, WeChat, TikTok, and YouTube, as gateways to their audiences. With fewer visitors discovering sites through open browsing, websites find themselves at the mercy of platform algorithms and policies. This trend harks back to the early days of the internet when AOL’s walled-garden approach reigned supreme; users were funneled through a closed environment rather than navigating the open web. It now often means users won’t even leave the platforms to experience the diversity of the open web. The rise of internet filtering and regional “internets” Countries around the world are exerting increasing control over their domestic web landscapes. Nations like China and Russia maintain tightly controlled “national internets” that restrict content accessible to their citizens. Countries like Turkey and India have also taken steps toward internet filtering, limiting content to align with governmental priorities or ideological positions. This segmentation of the web into national silos directly undermines the open web’s mission of universal accessibility. The trend threatens to balkanize the internet, creating isolated digital ecosystems where content is available only to specific audiences, subject to government oversight (“Internet Censorship: A Map of Internet Censorship and Restrictions,” comparitech.com). Even the United States has proposed a ban to TikTok (which seems to have died) that demonstrates how even in democracies there is a similar sentiment that leads to fragmentation of the internet. When the global web becomes partitioned by national borders, the open web becomes a casualty of political agendas. AI’s impact on the open web: Breaking the covenant AI, particularly generative AI, is also playing a role in the decline of the open web. Traditionally, web creators shared content with the implicit understanding that they’d receive traffic and recognition in return. Generative AI is disrupting this relationship by enabling users to access summarized or rephrased information without visiting the original source. For instance, Google’s AI-powered search features provide answers directly on the search results page, often synthesizing information from multiple sources without directing users to those sites. Similarly, services like OpenAI’s recent search technology license content from large sites and position links to the sites in the search results, but smaller organizations don’t have the power to enforce licensing fees or prominent placement, meaning they are denied both licensing revenue and advertising and traffic. These approaches are a departure from the web’s initial covenant: Creators provide content, and in return, they receive traffic and visibility. AI effectively decouples content creation from website traffic, depriving creators of the benefits they once enjoyed from direct engagement. When users can obtain comprehensive answers without clicking

By Bryan Koenig ( December 4, 2024, 1:09 PM EST) — President-elect Donald Trump signaled a full steam ahead approach to reining in major technology platforms with the announced nomination Wednesday of former Federal Trade Commission staffer and Trump administration economic adviser Gail Slater to run the U.S. Department of Justice’s Antitrust Division…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Best for creating and sending quotes and invoices: Jobber Best for tracking projects through a pipeline: Pipedrive Best CRM tool with construction integrations: Capsule Best for design coordination and collaboration: Procore Best CRM tool for field and D2D sales management: SalesRabbit Best for marketing and ongoing support: HubSpot Best for scheduling and tracking calendar tasks: monday CRM Best AI-powered CRM software for customization: Salesforce Construction companies, agencies, and general contractors can all greatly benefit from implementing a customer relationship management tool. The software can act as a hub for all client information as well as facilitate collaboration between architects, site managers, and builders. In addition to basic project management features, the CRM software can also track invoicing, quotes, and payments. 1 monday CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Calendar, Collaboration Tools, Contact Management, and more 2 Creatio CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Medium, Large, Enterprise Features Dashboard, Document Management / Sharing, Email / Marketing Automation, and more 3 HubSpot CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Micro (0-49 Employees), Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees) Micro, Small, Medium, Large Top construction CRM software comparison The top general CRM providers typically offer process management, integrations and other general core features. The main features a construction company might look for in any CRM tool include project management and tracking, mobile application or invoice management. Since a construction business may require more niche features, some of the most popular providers offer specialized versions of their software or help customize their tool to meet the precise needs of the construction industry. Software Star rating Project management Native or third-party integrations Document and design tracking Mobile app Invoicing and quote management Starting price* Jobber 4.1/5 Yes Third-party only Yes Yes Yes $49 per month for 1 user, $29 for additional users Pipedrive 4/5 Yes Third-party only Yes Yes Limited $14 per user per month Capsule 3.9/5 Yes Third-party only Limited Yes Limited $18 per user per month Procore 4/5 Yes Third-party only Limited Yes Yes Contact for quote SalesRabbit 3.9/5 Yes Both Limited Yes Limited Free starting price HubSpot 4/5 Yes Both Yes Yes Yes Free starting price monday CRM 3.5/5 Yes Third-party only Yes Yes Limited $12 per user per month Salesforce 4.3/5 Yes Both Yes Yes Yes $25 per user per month *Starting premium price, when billed annually. Jobber: Best for creating and sending quotes and invoices Image: Jobber Jobber is an easy-to-use field service management tool with additional business operations software. Jobber allows users to build quotes in minutes, price jobs with precision, automate quote follow-ups and more. The quote builder tool keeps the customer in mind with professional and concise quotes and invoices. The software also offers consumer financing with a Wisetack integration, allowing clients to pay over time. Why I chose Jobber Jobber serves over 50 home service industries by offering a platform where businesses can stay on top of requests from prospects, create quotes, schedule and manage jobs, and even make it easy to accept payment. These job tracking and customer communication tools make it a great option for small to mid-sized businesses looking for an industry-specific solution. Jobber’s features make it perfect for general contractors but if you’re interested in a more scalable platform to fit your business size, consider looking into SalesRabbit or Salesforce. Pricing Core: $49 per month, billed annually, or $69 per month, billed monthly. This grants access for one user plus 24/7 self-service hub, job management and quoting tools. Connect: $129 per month, billed annually, or $169 per month, billed monthly. This supports up to five users, digital payments and automated invoice reminders. Grow: $249 per month, billed annually, or $349 per month, billed monthly. This tier supports up to 15 users, two-way message, QuickBooks online, job costing and more. Features Credit card processing: Process payments with convenient payment options, automatic billing and instant payouts from the office or from the field. Time tracking: Automatically track visit times to maintain accurate and up-to-date timesheets. Lead management: Tag prospects as leads to manage them separately from active clients. This tool also integrates with Mailchimp and QuickBooks Online. Sample invoice shown through desktop and mobile app. Image: Jobber Jobber pros and cons Pros Cons 14-day free trial. Limited features available in the Core plan. Free product coaching. Premium add-ons are costly. 20+ built-in reports. Users report limited advanced and custom analytics. Pipedrive: Best for tracking projects through a pipeline Image: Pipedrive Pipedrive is a scalable CRM tool that offers a mixed bag of features for pipeline management, activity tracking, reporting analytics and more. Businesses can create custom pipelines with a highly user-friendly interface to visualize every part of their sales and building process. Pipedrive is also a cloud-based CRM solution that enables users to view contact information, project processes and contact suppliers wherever they have internet access. This way, project managers, site managers and contractors all know the status of each ongoing project. Why I chose Pipedrive Pipedrive is a popular and innovative sales software that offers niche offerings for certain industries like automotive sales, banking and more. Its general tools can be scaled up or down to fit the size of any business, from startups to enterprises in need of a straightforward tool. Pipedrive is a great general CRM software with an intuitive interface, if you’re a contractor or independent contributor wanting a similar option with a free tier, check out Capsule. Head over to our Pipedrive review for more information. Pricing Essential: $14 per user per month, billed annually, or $24 per user, billed monthly. Essential tier offers custom fields, data importing and exporting, product catalogs and more. Advanced: $34 per user per month, billed annually, or $44 per user, billed monthly. This tier includes everything in

UK startup PhysicsX, founded by former Formula 1 engineering whizz Robin “Dr. Rob” Tuluie, has unveiled an AI tool that could fast-track the time it takes to design a new aircraft from months to just a few days.  Dubbed LGM-Aero, the software creates new designs for aeroplanes. Using advanced algorithms trained on more than 25 million geometries, the model predicts lift, drag, stability, structural stress and other attributes for each shape. It then tailors the design according to what you want your plane to do. PhysicsX said the AI is the first-ever Large Geometry Model (LGM) for aerospace engineering. A barebones version of the model, Ai.rplane, is also accessible free of charge. “This is a first step in transforming the way engineering is practised in advanced industries [like automotive, aerospace, and manufacturing],” said Tuluie, founder and chairman of PhysicsX. The 💜 of EU tech The latest rumblings from the EU tech scene, a story from our wise ol’ founder Boris, and some questionable AI art. It’s free, every week, in your inbox. Sign up now! “Over time, we will bring new capabilities to LGM-Aero and Ai.rplane, allowing users to select powertrains, add controls and further content to reach mature designs in days rather than months or years,” he said.   Tuluie wasn’t always an entrepreneur. For the first half of his life, he worked alongside Nobel Prize winners as an astrophysicist. Then, at 41, he entered the F1 scene where he devised designs that helped Renault, and later Mercedes, win four Formula One world championships between them.  In 2019, Tuluie founded PhysicsX alongside Jacomo Corbo, a Harvard-educated engineer who ran McKinsey’s AI lab. Together, the duo have assembled a 50-strong team of some of the world’s top minds in data science, AI, and machine learning. PhysicsX, based in London, emerged from stealth in November 2023 with €30mn in funding. The company is on a mission to reimagine simulation for science and engineering using AI in sectors such as automotive, aerospace, and manufacturing.  PhysicsX says it is looking to help engineers better anticipate design bottlenecks, such as the drag of a new aeroplane or car design before they set out on building a physical prototype — saving them time and money. Its software acts like a supercharged wind tunnel for ideas.  “In the same way that large language models understand text, Ai.rplane has a vast knowledge of the shapes and structures that are important to aerospace engineering,” explained Corbo.  “The technology can optimise across multiple types of physics in seconds, many orders of magnitude faster than numerical simulation, and at the same level of accuracy.” Corbo called LGM-Aero “an important stepping stone” towards developing physics foundation models. These are AI systems designed to simulate and solve complex physical problems by learning patterns from data and physical laws. Applying AI to complex scientific problems is gaining traction. In 2020, Google Deepmind’s Alphafold model famously cracked a puzzle in protein biology that had confounded scientists for centuries. The discovery has accelerated research in drug discovery, molecular biology, and bioengineering.   Other companies, like Dutch scaleup VSParticle, are using algorithms to fastrack the discovery and synthesis of potentially game-changing materials.   While the applications of AI in science may differ from discipline to discipline, the benefits are shared: artificial intelligence can supercharge scientific discovery by analysing data, simulating complex systems, and uncovering insights faster than humans ever could. So AI isn’t all about asking ChatGPT what to eat for dinner? No, dear reader, it’s a actually pretty big deal.  source

How does a business stand out in a competitive market with AI? For some, it might be implementing a custom chatbot, or personalized recommendations built on advanced analytics and pushed out through a mobile app to customers. For others, it may simply be a matter of integrating AI into internal operations to improve decision-making and bolster security with stronger fraud detection. The transformative power of AI is already evident in the way it drives significant operational efficiencies, particularly when combined with technologies like robotic process automation (RPA). By eliminating time-consuming tasks such as data entry, document processing, and report generation, AI allows teams to focus on higher-value, strategic initiatives that fuel innovation. Unfortunately, implementing AI at scale is not without significant risks; whether it’s breaking down entrenched data siloes or ensuring data usage complies with evolving regulatory requirements. As AI adoption accelerates, it demands increasingly vast amounts of data, leading to more users accessing, transferring, and managing it across diverse environments. Each interaction amplifies the potential for errors, breaches, or misuse, underscoring the critical need for a strong governance framework to mitigate these risks. Above all, robust governance is essential. Failing to invest in data governance and security practices risks not only regulatory lapses and internal governance violations, but also bad outputs from AI that can stunt growth, lead to biased outcomes and inaccurate insights, and waste an organization’s resources. Keeping Data Governance at the Core of Effective AI Data falling into the wrong hands should be a concern of any business—regardless of size or status in the market. Examples include the  2008 breach of Société Générale, one of France’s largest banks, when an employee bypassed internal controls to make unauthorized trades, leading to billions of dollars lost. Similarly, in 2017 Equifax suffered a data breach that exposed the personal data of nearly 150 million people. This type of data mismanagement not only results in financial loss but can damage a brand’s reputation. Data breaches are not the only concern. An evolving regulatory landscape presents significant challenges for enterprises, requiring them to stay ahead of complex, shifting requirements while managing compliance across jurisdictions. Organizations must navigate frameworks like the EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and sector-specific mandates such as the Health Insurance Portability and Accountability Act (HIPAA). With the rise of AI and data-driven decision-making, new regulations like the EU Artificial Intelligence Act and potential federal AI legislation in the U.S. are creating additional layers of accountability. To meet current and future requirements, enterprises must implement robust compliance frameworks that include real-time monitoring and proactive reporting mechanisms And business leaders know the risk of ineffective data governance strategies. According to a Cloudera survey, 72% of business leaders agree that data governance is an enabler of business value, underscoring the critical link between secure data and impactful AI. The analytics that drive AI and machine learning can quickly become compliance liabilities if security, governance, metadata management, and automation aren’t applied cohesively across every stage of the data lifecycle and across all environments. Ensuring these elements are at the forefront of your data strategy is essential to harnessing AI’s power responsibly and sustainably. As AI usage spreads, data frequently moves between different infrastructures, making it harder to keep track of and protect. Solutions like Cloudera’s platform address a variety of constraints—organizational, regulatory, or otherwise—through a federated service that consistently secures, governs, and tracks data across hybrid cloud environments. The platform also offers a deeply integrated set of security and governance technologies, ensuring comprehensive data management and reducing risk. As AI adoption expands across entire enterprises, organizations must implement strong defensive measures and continuously monitor for potential threats as AI is integrated into various environments. Learn more about how Cloudera can help your organization ensure data governance and security are equipped to keep pace with accelerating AI adoption. source

By Al Barbarino ( December 4, 2024, 11:22 AM EST) — Insight Partners-owned Veeam Software said Wednesday it has sold off a $2 billion stake in the company through a secondary offering to a group led by TPG and including Temasek, Neuberger Berman Capital Solutions and other new investors, valuing the software company at $15 billion. … Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Most voters say that the 2024 elections were run and administered well, both in their local communities and across the country. 95% of those who report having voted this year say that elections in their community were run and administered at least somewhat well, including 69% who say they were run very well. 88% of voters also say the elections across the United States were run and administered well, though a smaller share (43%) say they were administered very well. While voters have long had highly positive views about election administration locally, that is not the case for evaluations of how elections were conducted across the country. In 2020, 59% of voters said elections across the country were run and administered at least somewhat well. This was a sharp drop from assessments of the 2018 midterm election and came amid Donald Trump’s challenge to the 2020 election results. Views rebounded in the 2022 midterm, with 74% saying that election was run and administered well. Evaluations of this year’s election administration around the country were even more positive, with 88% saying this. Views of election administration among Trump and Harris voters About nine-in-ten Trump voters (93%) say elections around the country were run well this year. A smaller share of Kamala Harris voters – though still an overwhelming majority (84%) – also say this. This is a departure from both the 2020 and 2022 elections, when Democratic candidate voters were much more likely than Republican candidate voters to say that elections around the country were run and administered at least somewhat well. Following the 2020 presidential election, 94% of Joe Biden voters said elections around the U.S. were run and administered well, while just 21% of Trump voters said this. And voters who selected a Democratic candidate for the U.S. House in 2022 were 43 percentage points more likely than Republican voters to say the elections around the country that year were run well. Most voters are confident in the accuracy of this year’s vote counts Large majorities of voters express confidence that both votes cast in person at polling places and those cast by absentee or mail-in ballot were counted as voters intended this year. Confidence in count of votes cast in person Nine-in-ten voters say they are at least somewhat confident that votes cast in person were counted accurately, including 45% who say they are very confident. More than nine-in-ten Trump voters (94%) say they are confident in-person ballots were counted accurately, including 41% who say they are very confident of this. Trump voters this year are 30 points more likely to say they are confident that in-person ballots were counted accurately than Trump voters were in 2020. A large majority of Harris voters (86%) also say they are confident in the vote count for in-person ballots, including 49% who are very confident. The share of Harris voters expressing confidence in the in-person vote count is lower than the 98% of Biden voters who said this when he won in 2020. Confidence in count of votes cast by absentee or mail-in ballot Voters today are more confident than they were four years ago that absentee and mail-in ballots were counted as voters intended. This is the result of a substantial increase in confidence in absentee vote counts among Republican candidate voters. Overall, 75% of voters say they are very (28%) or somewhat (47%) confident that absentee or mail-in ballots were counted accurately this year, compared with 59% who said this after the last presidential election. Today, 72% of Trump voters say they are confident in the accuracy of mail-in ballot counts. In 2020, just 19% expressed confidence. While Democratic candidate voters remain broadly confident in counts of votes cast using this method, they express lower levels of confidence than they did after the 2020 and 2022 elections. Today, 78% of Harris supporters are at least somewhat confident in the mail ballot count. Following Biden’s 2020 victory, 95% of his voters said they were confident. Most voters are confident their own vote was counted accurately Most voters (92%) say they are very (59%) or somewhat (33%) confident their own vote was accurately counted in this year’s presidential election. This reflects a modest uptick from the share who said this following the 2020 election (85%). Trump voters (96%) are more likely than Harris voters (89%) to say they are at least somewhat confident their own vote was counted accurately. Four years ago, Biden voters (97%) were more likely than Trump voters (72%) to say this. Before-and-after views of election administration Confidence that ineligible voters were prevented from casting a ballot About two-thirds of voters (66%) now say they are very or somewhat confident that people who were not legally qualified to vote were prevented from casting a ballot. In an October preelection survey, a smaller majority of registered voters (59%) said they were confident unqualified voters would be prevented from voting. Trump voters’ confidence that ineligible voters did not vote is much higher than it was before the election. Still, a majority continue to say they are not confident of this: Today, 45% of Trump voters say they are at least somewhat confident ineligible voters were prevented from voting, while 55% say they are not too or not at all confident of this. Before the election, just 30% Trump supporters said they were confident ineligible voters would be prevented from voting. By contrast, an overwhelming share of Harris voters (88%) are confident that ineligible voters were prevented from voting. This is nearly identical to the share of Harris supporters (87%) who had confidence in this in October. Confidence that all eligible voters were able to cast a ballot The share of voters who say they are very or somewhat confident that all legally qualified voters who wanted to cast a ballot were able to do so is nearly identical to the share who predicted this in the preelection survey (91% now, 90% in October). Large majorities of both Trump voters