Experts Matter. Find Yours.

How to Make Your Experts “AI-Ready"

AI is changing how people discover expertise.  Today, journalists, event organizers, researchers, and the public increasingly turn to tools like ChatGPT, Claude, Perplexity, and Google Search’s AI summaries powered by Gemini. Instead of clicking through pages of links, they expect clear, credible answers—often delivered instantly, with citations. That shift has major implications for organizations. It’s no longer enough for your experts to “rank well.” They need to be understood, trusted, and accurately represented by AI systems. So the real question becomes: When AI talks about your experts, does it get it right? This is where LLMs.txt plays an important role—especially when paired with an ExpertFile-powered Expert Center. What is LLMs.txt (In Plain English)? ...and why is it essential for expert content LLMs.txt is a small, machine-readable file placed on your organization’s website—in the case of your expert content alongside your main Expert Center. Its purpose is simple: to explain your expertise to AI systems clearly and unambiguously. “AI systems don’t just scan for keywords; they look for clear meaning, consistent context, and clean formatting — precise, structured language makes it easier for AI to classify your content as relevant.” Microsoft: Optimizing Your Content for Inclusion in AI Search Answers Rather than forcing AI to infer meaning from scattered pages, LLMs.txt explicitly tells systems: Who your experts are Which pages represent official, curated content How expert profiles differ from articles, Q&A, or research content How your organization’s expertise should be interpreted as a whole Think of it as a table of contents and usage guide for AI —helping large language models understand your site the way a communications professional would. Why This Matters for Visibility and Trust It Establishes Your Organization as the Source of Truth AI systems routinely synthesize information from multiple places. Without guidance, they may rely on outdated bios, scraped content, or secondary references. LLMs.txt provides a clear signal: This is our official expert content. This is what represents us. For ExpertFile clients, this matters because the platform already centralizes and curates expert content—from profiles and directories to Spotlights and Expert Q&A—ensuring that what AI sees is current, governed, and institutionally endorsed. The result: Greater accuracy, stronger attribution, and reduced risk of misrepresentation when your experts appear in the ever growing AI-generated overviews and answer. ahrefs: AI Overviews Have Doubled How It Improves Discovery Across AI Platforms It Makes Structured Expertise Easier for AI to Use ExpertFile is purpose-built to publish structured expert content at scale—content that goes well beyond static bios. LLMs.txt simply helps AI recognize and use that structure correctly. It clarifies the role of key ExpertFile content types, including: Expert Profiles → Canonical identity, credentials, and areas of expertise Spotlight Posts → Timely commentary, thought leadership, and research insights Expert Q&A → Authoritative answers to real-world questions Directories, Research Bureaus, and Speakers Bureaus → Curated collections of expertise by topic or audience This makes it easier for AI systems to: Match your experts to breaking news and trending topics Pull accurate summaries for AI-generated responses Identify the right expert for journalists, event organizers, and researchers Combined with ExpertFile’s extended distribution through expertfile.com and the ExpertFile Mobile App, your expertise is not only published—but actively discoverable across channels used by key audiences . How It Builds Organizational Authority It Connects Individual Experts to Institutional Credibility Without context, AI may treat expert pages as isolated profiles. LLMs.txt helps connect the dots. It tells AI that: Your experts are curated and endorsed by the organization Their insights are part of a broader expertise ecosystem Your institution has depth across priority subject areas This aligns closely with how ExpertFile structures content to support E-E-A-T (Experience, Expertise, Authority, Trust)—not just at the individual level, but across the organization . The outcome: Your organization is recognized not just as a collection of experts, but as an authoritative source of knowledge. How It Works with Google, Gemini, and AI Search Supports AI Summaries, Citations, and Knowledge Panels LLMs.txt helps ensure that when Google’s AI: Summarizes your organization Cites expert commentary Builds “about this topic” panels …it draws from your official, structured ExpertFile content, rather than fragmented third-party sources. This complements ExpertFile’s existing SEO and AI-discoverability foundation, which includes clean code, proper meta data, schema markup, and frequent crawling by both search engines and AI bots. How LLMS.txt Fits with SEO, Meta Tags, and Schema LLMS.txt doesn’t replace SEO—it builds on it. Traditional SEO elements such as page titles, meta descriptions, schema.org markup, and internal linking remain essential for helping search engines index and rank your content. ExpertFile already delivers these fundamentals out of the box, continually testing and evolving SEO and GEO (Generative Engine Optimization) standards as search changes . “Semantic SEO helps search engines understand context... it now helps bridge a critical gap between traditional SEO and newer generative engine optimization (GEO) and AI optimization (AIO) efforts.” Search Engine Land: Semantic SEO: How to optimize for meaning over keywords LLMS.txt adds a layer designed specifically for AI systems: Schema explains individual pages LLMs.txt explains your entire expertise ecosystem In simple terms: SEO helps your content get found LLMs.txt helps AI understand, summarize, and cite it correctly Together, they ensure your experts are not only visible—but accurately represented wherever AI is shaping discovery. Why This Is Especially Powerful on ExpertFile ExpertFile was designed to future-proof expert visibility—offering structured publishing, governance, distribution, inquiry management, analytics, and professional services as part of a continuously evolving SaaS platform . LLMS.txt acts as a multiplier on that foundation: Turning your Expert Center into a machine-readable expertise hub Strengthening AI discovery without adding operational burden Supporting emerging use cases like automated expert matching and AI-assisted research It’s not about chasing new technology. It’s about ensuring your expertise is clearly defined, properly attributed, and trusted—now and in the future. The Takeaway An LLMs.txt file on your ExpertFile organization page helps ensure that: Your experts are found by AI tools, not overlooked Your content is interpreted correctly, not flattened or misrepresented Your organization earns authority and trust in AI summaries, citations, and search results “AI search isn’t eliminating organic traffic. But it is reducing visits to source websites… Measure presence (citations, mentions) alongside traffic to see real impact.” Semrush: AI Search Trends for 2026 & How You Can Adapt  As AI becomes the front door to information, LLMs.txt helps make sure that when people ask for expertise, your organization is the answer they get.

When Betting Goes Mobile: The Hidden Cost to Young Adults’ Finances

As online gambling and sports betting surge across the United States, concerns are mounting about the financial and social consequences—particularly for young people. Dr. Jared Pincin, Associate Professor of Economics at Cedarville University, offers journalists a data-driven economic lens on how the rapid expansion of digital gambling is reshaping personal finances and increasing financial risk among younger Americans. What's Happening Mobile betting apps have transformed gambling into an always-available activity, accessible anywhere and at any time. With aggressive marketing tied to professional and collegiate sports, online gambling has become normalized—especially among young adults. As participation rises, so do reports of debt, financial instability, and problem gambling, raising questions about consumer protection, regulation, and long-term economic impact. Dr. Jared Pincin primary research interests explore the intersection of public choice economics with foreign aid as well as issues in sports economics. Pincin has published in popular publications such as The Hill, Real Clear Markets, Foxnews.com, and USA Today and scholarly journals such as Oxford Development Studies, Applied Economic Letters, and the Journal of Sport and Social Issues. View his profile here Key Insights  Online Gambling Is Built for Continuous Spending Modern gambling platforms are designed to encourage repeated engagement. Gamified interfaces, instant wagers, and constant prompts make it easy for users to lose track of spending, increasing the likelihood of financial loss over time. Young Adults Face Elevated Risk Young people, particularly college-age students and adults in their twenties, are among the fastest-growing users of online betting platforms. Limited financial experience, combined with easy credit access and social pressure, makes this group especially vulnerable to poor financial outcomes. Personal Finances Are Directly Impacted Gambling losses often come at the expense of savings, rent, tuition, and long-term financial planning. Dr. Pincin emphasizes that gambling platforms generate profit only when users lose, making sustained participation a negative-sum financial activity for individuals. Economic Incentives Drive Expansion From an economic standpoint, gambling growth is fueled by state revenue incentives and private profit motives. Dr. Pincin helps explain how these incentives can conflict with consumer well-being, particularly when regulatory safeguards lag behind technological innovation. About Jared Pincin Dr. Jared Pincin is an Associate Professor of Economics at Cedarville University. He holds a Ph.D. in economics and specializes in public choice, behavioral economics, and sports economics. His work examines how incentives shape individual decision-making and how policy choices affect financial outcomes at both the personal and societal levels. Let Us Help with Your Coverage Jared Pincin can assist reporters by: Explaining why online gambling participation has risen so quickly among young people Breaking down the economic mechanics of betting platforms and personal financial risk Providing context on the long-term financial consequences of habitual gambling Contributing expert insight to stories on regulation, advertising, and consumer protection Why This Matters As gambling becomes increasingly embedded in American culture, its financial consequences are no longer limited to isolated cases. Understanding how online gambling affects young people’s financial stability is essential for informed public reporting. Dr. Pincin offers clear, accessible analysis that helps audiences understand the economic realities behind the headlines.

Researchers warn of rise in AI-created non-consensual explicit images

A team of researchers, including Kevin Butler, Ph.D., a professor in the Department of Computer and Information Science and Engineering at the University of Florida, is sounding the alarm on a disturbing trend in artificial intelligence: the rapid rise of AI-generated sexually explicit images created without the subject’s consent. With funding from the National Science Foundation, Butler and colleagues from UF, Georgetown University and the University of Washington investigated a growing class of tools that allow users to generate realistic nude images from uploaded photos — tools that require little skill, cost virtually nothing and are largely unregulated. “Anybody can do this,” said Butler, director of the Florida Institute for Cybersecurity Research. “It’s done on the web, often anonymously, and there’s no meaningful enforcement of age or consent.” The team has coined the term SNEACI, short for synthetic non-consensual explicit AI-created imagery, to define this new category of abuse. The acronym, pronounced “sneaky,” highlights the secretive and deceptive nature of the practice. “SNEACI really typifies the fact that a lot of these are made without the knowledge of the potential victim and often in very sneaky ways,” said Patrick Traynor, a professor and associate chair of research in UF's Department of Computer and Information Science and Engineering and co-author of the paper. In their study, which will be presented at the upcoming USENIX Security Symposium this summer, the researchers conducted a systematic analysis of 20 AI “nudification” websites. These platforms allow users to upload an image, manipulate clothing, body shape and pose, and generate a sexually explicit photo — usually in seconds. Unlike traditional tools like Photoshop, these AI services remove nearly all barriers to entry, Butler said. “Photoshop requires skill, time and money,” he said. “These AI application websites are fast, cheap — from free to as little as six cents per image — and don’t require any expertise.” According to the team’s review, women are disproportionately targeted, but the technology can be used on anyone, including children. While the researchers did not test tools with images of minors due to legal and ethical constraints, they found “no technical safeguards preventing someone from doing so.” Only seven of the 20 sites they examined included terms of service that require image subjects to be over 18, and even fewer enforced any kind of user age verification. “Even when sites asked users to confirm they were over 18, there was no real validation,” Butler said. “It’s an unregulated environment.” The platforms operate with little transparency, using cryptocurrency for payments and hosting on mainstream cloud providers. Seven of the sites studied used Amazon Web Services, and 12 were supported by Cloudflare — legitimate services that inadvertently support these operations. “There’s a misconception that this kind of content lives on the dark web,” Butler said. “In reality, many of these tools are hosted on reputable platforms.” Butler’s team also found little to no information about how the sites store or use the generated images. “We couldn’t find out what the generators are doing with the images once they’re created” he said. “It doesn’t appear that any of this information is deleted.” High-profile cases have already brought attention to the issue. Celebrities such as Taylor Swift and Melania Trump have reportedly been victims of AI-generated non-consensual explicit images. Earlier this year, Trump voiced support for the Take It Down Act, which targets these types of abuses and was signed into law this week by President Donald Trump. But the impact extends beyond the famous. Butler cited a case in South Florida where a city councilwoman stepped down after fake explicit images of her — created using AI — were circulated online. “These images aren’t just created for amusement,” Butler said. “They’re used to embarrass, humiliate and even extort victims. The mental health toll can be devastating.” The researchers emphasized that the technology enabling these abuses was originally developed for beneficial purposes — such as enhancing computer vision or supporting academic research — and is often shared openly in the AI community. “There’s an emerging conversation in the machine learning community about whether some of these tools should be restricted,” Butler said. “We need to rethink how open-source technologies are shared and used.” Butler said the published paper — authored by student Cassidy Gibson, who was advised by Butler and Traynor and received her doctorate degree this month — is just the first step in their deeper investigation into the world of AI-powered nudification tools and an extension of the work they are doing at the Center for Privacy and Security for Marginalized Populations, or PRISM, an NSF-funded center housed at the UF Herbert Wertheim College of Engineering. Butler and Gibson recently met with U.S. Congresswoman Kat Cammack for a roundtable discussion on the growing spread of non-consensual imagery online. In a newsletter to constituents, Cammack, who serves on the House Energy and Commerce Committee, called the issue a major priority. She emphasized the need to understand how these images are created and their impact on the mental health of children, teens and adults, calling it “paramount to putting an end to this dangerous trend.” "As lawmakers take a closer look at these technologies, we want to give them technical insights that can help shape smarter regulation and push for more accountability from those involved," said Butler. “Our goal is to use our skills as cybersecurity researchers to address real-world problems and help people.”

The Ads are Coming ! OpenAI is testing ads inside ChatGPT starting this month.

But there's a catch: You can’t just buy your way in ChatGPT will soon include “clearly labeled sponsored listings” at the bottom of AI-generated responses. And while the mock-ups don't appear all that sophisticated, it's important to focus on the bigger picture. We're about to see a new wave of 'high-intent advertising' that combines the targeting sophistication of social media with the purchase-intent clarity of search advertising. More on that in a moment. How Do ChatGPT Ads Work? Starting later this month, free users of the ChatGPT platform and those under 18 will begin receiving Ads at the bottom of their screens. First, they will see ChatGPT's answer to their question, which provides a comprehensive, relevant response that builds trust. Then they will see an ad for a sponsored product/service below. An ad that suddenly doesn't feel like a blunt interruption. It feels like a natural next step. This is premium placement. The user has already received value. They've been educated. And now there's a clear call to action (CTA) that's in context. Open AI has stated that their new Ads “support a broader effort to make powerful AI accessible to more people.” Translation: As they approach 1 billion weekly users across 171 countries using ChatGPT for free, OpenAI needs to offset its astronomical burn rate with ads. Makes sense. This New Era of Conversational Ads Will be Complicated But there's a structural difference with these new ads. OpenAI has stated that ads will only appear when they're relevant to that exact conversation. This means you can't just buy your way into ChatGPT Ads. In fact, with ChatGPT you are being selected because you're the right answer the user needs at that time. Put another way: When ChatGPT evaluates which sponsored products to show, it will favor brands with demonstrated authority on the topic. So unlike traditional paid search, where a higher bid gets you ranked in sponsored results, ChatGPT Ads will reward the brands whose content has already been recognized as authoritative by the AI model. Brands with strong organic visibility, topical expertise, and content that aligns with user intent will have a distinct competitive advantage from day one. Brands without that foundation will be paying premium rates to compete with established authorities. How ChatGPT's Ad Strategy is Set to Change Digital Marketing For years, CMOs have treated organic search and paid search as separate budget lines, often managed by different teams. I saw this firsthand, as I helped my client DoubleClick launch it’s first Ad Exchange network in the US market. Programmatic exchanges brought a new efficiency to digital ad buying. It was a very groovy time. This feels very different. Why? Because, the conventional wisdom has always been that paid search and ads drive immediate results while organic search plays the long game. In 2026, that strategy isn’t completely obsolete. But that type of thinking is about to get a lot more expensive for clients if they don't start to appreciate quality "organic" content and its ability to improve their paid advertising ROI. Now organic and paid need to get along, to get ahead. ChatGPT Ads Are Looking for Topical Authority that Experts Can Demonstrate When ChatGPT evaluates which sponsored products to show, it will favor brands with demonstrated authority on the topic. Brands won't simply be able to "buy" visibility. OpenAI in its announcements, has been explicit: ads must be relevant to the conversation. Relevance is determined by topical alignment, not budget. A brand spending millions on generic bidding will lose to a smaller competitor whose product is more precisely aligned with what the user actually asked. The ads aren't live yet. But the infrastructure supporting them is. Open AI, Google and many of the other generative search platforms are building very sophisticated systems that track topical authority and content quality signals. They're already reshaping how organic search, AI recommendations, and paid advertising work together. Topical Relevance + Expert Authority is the Path to Visibility in Search Investing in well-developed thought leadership programs generates compound returns. You get the organic search results plus an improvement in your paid search metrics in Generative AI search platforms. When done right, you build authority for AI citations, which then positions you better for ChatGPT ads. Remember, your organic traffic gains are built on authoritative content. They're built on being the answer that search engines and AI systems select. And once you've built that authority, it works everywhere—traditional search, AI Overviews, ChatGPT, and soon… ChatGPT ads. What To Do Before AI Ad Networks Start to Scale The early advantage will go to brands that invest in quality content right now. Organizations that invest in expert-authored, intent-aligned content over the next six months will have more AI citation visibility from Google Overviews and similar LLM's like ChatGPT. That means more trust signals, making paid ads more effective when they run. Content that is aligned with user intent: Answers a specific question. Not tangentially, not after 2,000 words of context. The answer appears in the opening paragraph, structured for AI extraction. Includes expert perspective. Generic information that could come from anywhere doesn't differentiate you. Expert insight, original research, or proprietary frameworks do. Demonstrates topical authority. A single authoritative article matters less than a cluster of related content that shows comprehensive expertise on a topic. Is structured for scanning. Clear headings (H2, H3), bullet points, tables, Q&A blocks. This structure helps both human readers and AI systems parse meaning. Remember, the brands that get the most value out of ChatGPT Ads will be the ones that built intent-aligned content years before the ads launched. They'll have topical clusters, expert perspectives, and the authority signals that make them the natural choice for sponsorship. Questions CMO’s Should Be Asking their Teams Now to Prepare for ChatGPT Ads Q. Can I pre-purchase Chat GPT Ads? As of today, there are currently no ads in ChatGPT. Open AI has announced that they will begin internal testing ads in ChatGPT later this month for Free users in the US market. Q. Do Ads influence the answers ChatGPT gives you? What about privacy? Open AI in their release states that answers are optimized based on what's most helpful to you. Ads are always separated and clearly labeled from Answers. They also state that they keep your conversations private from advertisers and will never sell your data to advertisers. Q. How do we audit our site content to ensure we're aligned with user intent? For your top 20-30 decision-stage queries (the ones that drive revenue), here's a quick test. Does the content directly answer the question in the opening paragraph? Are you including question-and-answer formats in your content? If you're burying the answer in a 3,000-word article full of tangents, you're losing visibility in organic search, and you're already failing in ChatGPT's environment. Restructure. Q. How do we prepare for ChatGPT Advertising Opportunities? Build topical authority through content clusters. Don't publish isolated blog posts. Organize your content around core topics your audience cares about. Create a long-form hub article that comprehensively covers the topic, then develop additional linked articles that dive into sub-topics and questions. Link them together. This structure helps AI systems over time, recognize your brand as authoritative on that topic, which improves both organic rankings and AI citation rates. Q. Can we still get traction with content that is not authored by experts? Generic AI-written content won't differentiate you. Get expert voices into your content. Feature your subject-matter experts, partner with practitioners, and customers to contribute original insights, case studies, or frameworks. AI systems can detect authenticity, and original expert perspectives is now a ranking signal. This is especially critical as you prepare for ChatGPT ads. OpenAI has prioritized conversations that cite authoritative sources. Q. How does content need to be structured for citations? Implement proper schema markup and structured data. AI systems extract information by parsing content structure. If your pages include proper schema markup (FAQPage, HowTo, Review, Product schema), you're making it easier for AI to pull your content into answers. This increases citation rates, which builds authority before ChatGPT ads scale. Q. How do we allocate our organic and paid programs? Own the organic + paid intersection. For your highest-intent topics, if you have a budget, invest in both organic visibility and paid campaigns. Run ads targeting the same keywords where you rank organically. This takes up more real estate on the results page and signals authority. It also gives you direct feedback on keyword performance, messaging, and landing page effectiveness—data that informs your organic content strategy and drives more citations - a virtuous cycle. Q. What types of creative will work best in these new Ad products? Until they roll out, it's unwise to make too many predictions. The safe bet here is to prepare your team for conversational advertising. ChatGPT ads won't reward traditional ad copy. They'll reward clarity, specificity, and direct value messaging. If you're used to brand-heavy, aspirational creative, this will feel foreign. Start testing conversationally-appropriate messaging now. Short, clear, problem-focused. Test on existing paid channels and refine before ChatGPT ads launch. Our Prediction When ChatGPT ads fully launch and scale, many brands that have invested in organic visibility and content quality will start to pull away from the pack. Remember…The brands that win won't be the ones with the biggest ad budgets. They'll be the ones whose content has already proven they're the right answer. They'll be the ones users already trust, already cite, and already know. The ads are coming. Are you ready?

Analyzing Legal Implications of Venezuela Intervention

Hofstra Law Professor James Sample has emerged as a leading legal analyst in national and regional media following the U.S. operation involving Venezuelan President Nicolás Maduro, offering expert commentary on constitutional authority, international law, and criminal procedure. Professor Sample appeared across major television, radio, and digital platforms, including ABC News, CBS New York, MS NOW, and Pacifica Radio, as developments unfolded surrounding the capture and federal prosecution. In multiple ABC News segments, Professor Sample analyzed the legality of the Venezuela operation under international law, characterizing the action as a potential violation of the United Nations Charter, and explained what to expect procedurally at the arraignment of Maduro and his wife on federal charges. His commentary also addressed the broader implications of asserting U.S. jurisdiction over a sitting foreign head of state.

My MBA Journey at 69: Because Apparently, Climbing Everest Base Camp Wasn't Enough

If you watched CBS 60-Minutes host, Cecilia Vega set out on a challenging 10-day trek to Everest Base Camp (EBC) in the Himalayas, for last week's episode, you couldn't help but marvel at the gruelling physical demands and the profound experience of being at the foot of Mount Everest.  Her journey, which involved intense training, navigating dangerous suspension bridges, and dealing with extreme altitude, also highlighted the massive industry around Everest and the vital, underappreciated role of the Sherpa community.  Her journey is an inspiring look at how we can push our own boundaries.  Bravo Cecilia! Vega described hiking Everest Base Camp as "the hardest thing I've ever done physically," battling low oxygen (like breathing through a straw) and fatigue, despite months of training.  She experienced sub-freezing temperatures, crossed dizzying suspension bridges, and even witnessed close calls with avalanches, with trusty Sherpas conducting nightly tent checks to ensure her safety. Hiking to Everest Base Camp is hard.  I know.  Because I did it.  At 60 Let me explain. I have a tradition of celebrating milestone birthdays with a bang. When I turned 60, I gave myself six physical challenges — one for each decade lived. The grand finale? Climbing to Everest Base Camp. It was epic, exhausting, and left me with both altitude sickness and lifetime bragging rights. But as I approached 69, I craved something different. Not hiking boots this time — just highlighters. Not mountain peaks — mental peaks. I wanted an intellectual challenge that would prove my brain still had some miles left on it. No oxygen tanks required this time. Just caffeine, reliable Wi-Fi, and an iron will. How I Got Here (And Why I'm Questioning My Sanity) I've always wanted an MBA — partly for the knowledge, but let's be honest, mostly for the prestige. There's something irresistible about joining that club of spreadsheet-loving scholars. For years, I've imagined myself casually tossing around terms like "synergy" and "stakeholder engagement" while sipping something expensive in a sleek business lounge. What I didn't imagine was attempting this after a 46-year hiatus from university. Spoiler alert: It's harder than I thought. Like, significantly harder. Enter the MBA: Twenty-four courses. Two years or so, and approximately one hundred "What was I thinking?" moments. I enrolled at the Sprott School of Business at Carleton University, which offers a generous seniors' discount. I briefly debated whether to ask for the student discount or the seniors' discount — then thought, why not request both? I've earned these wrinkles and this tuition bill. Bonus perks: I qualify for the student medical and dental plans. My classmates use them for wisdom tooth extractions. I'm eyeing the denture clause. Term One: The Tech Tsunami Let's talk about the software situation.  Brightspace. Turnitin. eProctor. Excel (the betrayer). Word. APA 7th Edition. And about a dozen other platforms that might as well have been written in Klingon. I expected a gentle introduction — maybe some academic foreplay before diving into heavy coursework. Instead, I was shoved into the deep end with weights tied to my ankles. Each assignment came with a forest's worth of readings, PowerPoint slides, and discussion board posts. I was up at 5 a.m., trying to squeeze in extra hours in the day. (Spoiler: you can't.) Despite decades spent managing teams, I was barely scraping 60% on quizzes — the open-book ones. How is that even possible? Accounting became my personal Everest. People kept telling me, "Excel is your friend." That's a lie. Excel is that friend who borrows your car, crashes it, returns it on empty, and then asks if you've bothered reading the manual. Casualties of War: Family, Friends, and Dottie My family was neglected. My friends assumed I'd entered witness protection. Even my little dog Dottie stopped talking to me. She'd give me this look — a devastating combination of pity and disappointment — every time I said, "Sorry, no walk today. Mommy has to study debits and credits." You haven't experienced true shame until you've been judged by a 10-pound dog wearing a sweater. The Breaking Point (And the Breakthrough) I'll admit it — I had serious moments where quitting felt like the only rational option. The workload was relentless. The jargon was endless. The pressure was overwhelming. I contacted teaching assistants, professors, and even the university librarian, desperately searching for a lifeline. They were all kind and patient. But ultimately, I had to figure it out myself. And somewhere between the caffeine highs and APA citation lows, something clicked. Even Cs get Degrees! By midterm, I began to suspect something radical: perhaps the large amount of work was the real test. Not the material itself, but the sheer volume. Maybe this was the school's way of differentiating dedicated students from curious ones, the serious from the casual observers. Was it possible that the secret to MBA success was learning what not to do? After all, the passing grade is a B- (70%). At this point in my life, I'd be happy with a 71% and a full night's sleep. Hence the title, Even Cs get Degrees! Working Smarter, Not Harder Somewhere between week three and mild hysteria, I made a radical decision: stop trying to do everything. I focused on lectures and study notes instead of drowning in supplementary readings. I prioritized assignments strategically. I stopped pretending perfection was achievable — or necessary. The results were immediate: • My grades improved • My panic attacks decreased • Dottie started making eye contact again I also began scheduling regular Zoom calls with professors and TAs — not just for assistance, but to foster genuine relationships (my lifelong superpower). Once I stopped pretending, I had everything under control; everything truly improved. School life has improved. Home life has also improved. I was finally able to brush my hair again. Slowing Down to Soak It In Next term, I'm taking just one course. Because honestly, what's the rush? I'm not chasing a promotion or striving for a corner office. I'm doing this for myself — for the simple joy of learning and the satisfaction of knowing I still can.  I want to enjoy the journey, not rush through it gasping. I want to look forward to lectures rather than fear them. I want my sleep score (and my sanity) restored.  The goal isn't speed. It's savouring. What I've Learned So Far Here's what these first two courses have taught me: ✓ I can still learn — even when my brain occasionally reboots mid-sentence  ✓ I can focus — especially with enough coffee ✓ I'm still gloriously, endlessly curious ✓ I need sleep (The 5 a.m. club can keep their membership) ✓ I need fun (Revolutionary concept, I know) ✓ I love to learn (Turns out, I always have) ✓ I make mistakes — and they're not terminal ✓ I need help — and I must ask for it ✓ APA 7th Edition is real — and I finally understand what it means (Sort of. Mostly. Sometimes.) ✓ Even Cs or, in my case, a B- get a Degree — consistent, sustainable B- work will win most every race Looking Ahead: The Big 7-0 By the time I graduate, I'll be at least 70 years old. And honestly? I can't think of a better birthday gift for myself. When most people talk about slowing down, I'm actually ramping up. While others are downsizing, I'm uploading assignments at 11:58 p.m. When my friends ask why I do this, I smile and say: "Because I still want to know what I'm capable of." To Be Continued... This is just the beginning of my MBA adventure. I've completed two courses out of twenty-four. Twenty-two more to go — one term at a time, one course at a time, one small victory at a time. I'll update this blog periodically with new stories, fresh insights, and probably more tales of Dottie's disappointment. As We Start the New Year Here's a toast to all of us who refuse to act our age. To everyone starting something new — whether it's an MBA, a marathon, or a pottery class.  To everyone who believes it's never too late to learn, to laugh, or to start again.  Because learning doesn't stop when you retire. Sometimes, it's only just beginning. Stay tuned for Term Two updates, where I'll tackle another course, hopefully retain my sanity, and continue proving that 69 is just a number (and so is 70, 71, 72...). All the best to you in 2026 and beyond!   Sue Don’t Retire… ReWire! Want to become an expert on serving the senior demographic? Just message me to be notified about the next opportunity to become a "Certified Equity Advocate" — mastering solution-based advising that transforms how you work with Canada's fastest-growing client segment. Here's the link to sign up.

Chasing followers makes crypto traders perform worse on social investment sites

Whether excited about gaining new followers or desperate to win back lost subscribers, investors who saw changes to their subscriber count performed worse than before their subscribers changed, according to a new study. The research tracked performance on social investment sites, where individuals can trade assets like cryptocurrency while attracting audiences based on their performance — like YouTube, but for investments. Both gaining and losing followers led investors to make more frequent, riskier trades. The upshot is that traders performed about 10% worse in the weeks after their subscriber counts changed. “If the number of followers increases a lot, it creates an overconfidence effect. You are more aggressive in trading, and your future trading performance will be worse,” said Liangfei Qiu, Ph.D., a professor in the University of Florida’s Warrington College of Business and co-author of the new study. “So logically we thought that if more followers leads to worse performance, then if we reduce the number of followers, it will reverse the effect, reduce overconfidence and lead to higher trading performance,” Qiu said. “But that’s not what we found. If we reduce the number of followers, they trade even more aggressively and their trading performance becomes even worse.” Qiu and his collaborators at the University of Maryland and University of Washington worked directly with an anonymous social trading platform to examine the impact of gaining or losing followers on traders’ cryptocurrency trading behavior and performance. The research revealed the power of social pressure. This study was focused on cryptocurrency, which is highly volatile and may exacerbate the risk of social trading. But social trading also exists for traditional investments like stocks and bonds, and chasing followers could hurt these types of investments, too. The researchers say that both platforms and investors should guard against the downsides. “If platforms emphasize the social functions too much, it might backfire. Eventually it will hurt the long run performance of the platform,” he said. “The investors should realize their inherent bias and make sure their trading strategies are not too affected by social attention.”

LSU Experts Break Down Artificial Intelligence Boom Behind Holiday Shopping Trends

Consumers are increasingly turning to artificial intelligence tools for holiday shopping—especially Gen Z shoppers, who are using platforms like ChatGPT and social media not only for gift inspiration but also to find the best prices. Andrew Schwarz, professor in the LSU Stephenson Department of Entrepreneurship & Information Systems, and Dan Rice, associate professor and Director of the E. J. Ourso College of Business Behavioral Research Lab, share their insights on this emerging trend. AI is the new front door for search: Schwarz: We’re seeing a fundamental change in how consumers find information. Instead of browsing multiple pages of results, users—especially Gen Z—are skipping to conversational AI for curated answers. That dramatically shortens the shopping journey. For years, companies optimized for SEO to appear on the first page of Google; now they’ll have to think about how their products surface in AI-generated recommendations. This may lead to a new form of “AIO”—AI Information Optimization—where retailers tailor product descriptions, metadata, and partnerships specifically for AI visibility. The companies that adapt early will have a distinct advantage in capturing consumer attention. Rice: This issue of people being satisfied with the AI results (like a summary at the top of the Google results) and then not clicking on any of the paid or organic links leads to a huge increase in what we call “zero click search” (for obvious reasons). For some providers, this is leading to significant drops in web traffic from search results, which can be disconcerting due to the potential loss of leads. However, to Andrew’s point of shortening the journey, it means that the consumers who do come through are much more likely to buy (quickly) because they are “better” leads. This translates to seemingly paradoxical situations for providers: they see drops in click-through rates and visitors/leads, yet revenue increases because the visitors are “better.”  There is a rise in personalized shopping journeys: Schwarz: AI essentially acts as a personal shopper—one that can instantly analyze preferences, budget, personality traits, or past behavior to produce tailored gift lists. This shifts power toward “delegated decision-making,” in which consumers allow AI to narrow their choices. Younger consumers are already comfortable outsourcing this cognitive load. However, as ads enter the picture, these personalized journeys could be shaped by incentives that aren’t always transparent. That creates a new responsibility for platforms to disclose when suggestions are sponsored and for users to develop a more critical lens when interacting with AI-driven recommendations. Rice: This is also a great point. The “tools” marketers use to attract customers are constantly evolving, but this seems in many ways to be the next iteration of the Amazon.com suggestions that you find at the bottom of the product page for something you click on when searching Amazon (“buy all x for $” or “consumers also looked at…,” etc.), based on past histories of search and purchase, etc. One of the main differences is that you can now create virtually limitless ways to compare products, making comparisons less taxing (reducing cognitive load and stress), which may, in some cases, increase the likelihood of purchase. These idiosyncratic comparisons and prompts lead to the truly unique journeys Andrew is discussing. You no longer have to be beholden to a retailer-specified price range. You could choose your own, or instead ask an AI to list the products representing the best “value” based on consumer reviews, perhaps by asking to list the top ten products by cost per star rating, etc.  Advertising is becoming more subtle and conversational: Schwarz: With ads woven directly into AI responses, the traditional boundary between content and advertising blurs. Instead of banner ads, pop-ups, or clearly labeled sponsored posts, recommendations in a conversational thread may feel more like advice than marketing. This has enormous implications for consumer trust. Retailers will likely see higher engagement through these context-aware ad placements, but regulatory scrutiny may also increase as policymakers evaluate how clearly sponsored content is identified. The risk is that advertising becomes invisible—something both platform designers and regulators will need to monitor carefully. Rice: This is definitely true. I was recently exploring an AI-based tool for choosing downhill skis, but the tool was subtly provided by a single ski brand. I’m not sure the distribution of ski brands covered was truly delivering the “best overall fit” for a potential buyer, rather than the best possible ski in that brand. At least in that case, it was somewhat disclosed. It does, however, become an issue if consumers feel misled, but they’d have to notice it first. Still, the advantages are big for retailers, and the numbers don't lie. According to some preliminary Black Friday data, shoppers using an AI assistant were 60% more likely to make a purchase.  Schwarz: This shift is going to reshape multiple layers of the retail ecosystem: Retailers will need to rethink how they show up in AI-driven environments. Traditional SEO, ad bids, and social media strategies won’t be enough. Partnerships with AI platforms may become as important as being carried by major retailers today. Because AI tools can instantly compare prices across dozens of retailers, consumers will become more price-sensitive. Retailers may face increasing pressure to offer competitive pricing or unique value propositions, as AI reduces friction in comparison shopping. Retailers who integrate AI into their own websites—chat-based shopping assistants, personalized gift advisors, automated bundling—will gain an edge. Consumers are increasingly expecting conversational interfaces, and companies that delay will quickly feel outdated. As AI tools influence purchasing decisions, consumers and regulators alike will demand clarity around how recommendations are generated. Retailers will need to navigate this carefully to maintain What I think we are going to see accelerate as we move forward: AI-powered concierge shopping will become mainstream. Within a couple of years, using AI to generate shopping lists, compare prices, and find deals will be as common as using Amazon today. Retailers will create AI-specific marketing strategies. Instead of optimizing for keywords, they’ll optimize for prompts: how consumers might ask for products and how an AI system interprets those requests. More platforms will introduce advertising into AI models. ChatGPT is simply the first mover. Once the revenue potential becomes clear, others will follow with their own ad integrations. Greater scrutiny from policymakers. As conversational advertising grows, transparency rules and labeling requirements will almost certainly. A new era of “conversational commerce.” Buying directly through AI—“ChatGPT, order this for me”—will become increasingly common, merging search, recommendation, and transaction into a single seamless experience. I can speak to this on a personal level.  My college-aged son is interested in college football, and I wanted to get him a streaming subscription to watch the games.  However, the football landscape is fragmented across multiple, expensive platforms. I asked ChatGPT to generate a series of options. Hulu is $100/month for Live TV, but ChatGPT recommended a combination of ESPN+, Peacock, and Paramount+ for $400/year and identified which conferences would not be covered.  What would have taken me hours only took me a few minutes! Rice: On the other hand, AI isn’t infallible, and it can lead to sub-optimal results, hallucinations, and questionable recommendations. From my recent ski shopping experience, I encountered several pitfalls. First, for very specific questions about a specific model, I sometimes received answers for a different ski model in the same brand, or for a different ski altogether, which was not particularly helpful, or specs I knew were just plain wrong. Secondly, regarding Andrew’s point about the conversational tone, I asked questions intended to push the limits of what could be considered reliable. For example, I asked the AI to describe the difference in “feel” of the ski for the skier among several models and brands. While the AI gave very detailed and plausible comparisons that were very much like an in-store discussion with a salesperson or area expert, I’m not sure I fully trust when an AI tells me that you can really feel the power of a ski push you out of a turn, this ski has great edge hold, etc. It sounds great, but where is the AI sourcing this information? I’m not convinced it’s fully accurate. It also seems we’re starting to see Google shift toward a more AI-centric approach (e.g., AI summaries and full AI Mode). At the same time, we’re also starting to see AI migrate closer to Google as people use it for product-related chats, and companies like Amazon and Walmart have developed their own AI that is specifically focused on the consumer experience. I can’t imagine it will be long before companies like OpenAI and their competitors start “selling influence” in AI discussions to monetize the influence their engines will have.  

As holiday shopping season nears, UF experts warn retail theft is growing more sophisticated

With the busiest shopping season of the year approaching, new findings from the National Retail Federation’s Impact of Retail Theft and Violence 2025 report — developed by the University of Florida’s SaferPlaces Lab and the Loss Prevention Research Council — show retailers are facing increasingly complex and technology-driven threats. UF researchers say early preparation, better data and stronger collaboration will be essential as stores brace for heavier foot traffic and heightened safety risks. Despite public reports that retail theft is decreasing, Read Hayes, Ph.D., a UF research scientist and director of the LPRC at UF Innovate, said retailer surveys tell a different story: Incidents of shoplifting, organized retail crime, online fraud and other external theft continue to rise, even as some law enforcement statistics appear flat or declining. The gap, he said, reflects how much crime goes unreported or unrecorded. “Retailers have always had a difficult time reporting much of their crime, and if you look only at police data, like calls for service or arrests, it can look like retail crime is flat or even slightly down,” he said. “But when we survey retailers, who are the actual crime victims, they consistently report year-over-year increases in theft and violence.” Criminal groups are also becoming more sophisticated. Hayes said offenders are increasingly using technology to defeat protective systems, disrupt cameras and identify vulnerable stores. They also rely heavily on social media platforms such as TikTok and Reddit to coordinate attacks and share tactics. “It’s a little disconcerting how much criminals rely on social media now to scout stores, map out easy targets, learn from each other or just plain brag about how they did it,” he said. LPRC scientists monitor social media signals to help retailers and law enforcement understand emerging threats — not in real time, Hayes said, but to help build best practices organizations can use to defend themselves. Criminals continue to focus on high-demand items such as branded apparel and footwear, prompting retailers to rethink how those products are displayed and secured. Hayes said many companies are testing new approaches to better protect vulnerable merchandise without driving customers away. One example is automated self-service systems for locked items, where customers can retrieve a product by having a code sent to their phone without waiting for a store employee. Safety remains retailers’ top concern, Hayes said. LPRC’s latest report, developed in collaboration with the security technology company Verkada, found that frontline retail workers report feeling less safe than ever, a trend that typically intensifies during the holiday rush. Rising incidents of in-store violence, limited law enforcement support in some areas and increased guest-related confrontations are pushing retailers to reassess how they protect both employees and customers. “Nothing is more important than protecting the frontline retail associates who keep this industry running,” Hayes said. “This report helps reinforce what retailers need to do to ensure those workers feel safe.” LPRC teams are also studying ways to improve safety beyond store walls, testing parking lot technologies, including license plate readers and flashing deterrent systems designed to discourage potential offenders and reassure law-abiding shoppers. At the federal level, Hayes said he and partners across the country are urging Congress to pass a bill to address organized retail crime and establish a centralized platform for reporting retail theft threats. As the holiday season approaches, Hayes said the need for evidence-based solutions has never been clearer. “Retailers are under pressure to keep their stores safe, welcoming and competitive,” Hayes said. “The more we can understand offender behavior, customer expectations and emerging technologies, the better we can help retailers, communities and law enforcement reduce harm.” The LPRC, headquartered at UF Innovate, brings together more than 200 major retailers, technology companies and public safety agencies to conduct research that strengthens store safety, reduces loss and enhances the customer experience.

Five Million Airbnb Reviews Illuminate Guests’ Crime and Safety Concerns

Concerns about crime and safety have a dramatic impact on the behavior of Airbnb customers, according to new research co-authored by Liad Wagman, Ph.D., Dean of the RPI Lally School of Management. In an analysis of nearly 5 million reviews left by Airbnb guests, Wagman and his colleagues found that a short-term rental property’s occupancy rate and rental price dropped by significant amounts after a guest left a review mentioning safety concerns at or around the property: occupancy rates fell by anywhere from 1.5 to 2.4 percent, while average nightly prices dropped by roughly 1.5 percent. These negative safety reviews influenced the behavior not only of potential future customers, but also of the people who wrote them. A customer who mentioned concerns about crime and safety in the neighborhood around a property, for instance, became 60 percent less likely to ever use Airbnb again. “To see the effect of these dynamics play out in action is always fascinating to me," Wagman said. “Given that humans have different preferences, and that information transmittal is imperfect, it’s unsurprising that the effect of self-experience is larger than that of reading a critical review that resulted from it.” Worries about safety within a property — say, a broken step or a slippery tub — also reduced customers’ willingness to return to the platform, but by a more modest amount. The study also found that when people with neighborhood safety concerns did return to the platform, they tended to book properties in areas with lower rates of crime. The study, co-authored by Aron Culotta of Tulane, Ginger Zhe Jin of the University of Maryland, and Yidan Sun of Binghamton University, was published in the journal Marketing Science. Overall, the researchers found that safety-oriented reviews were rare: only about 0.5 percent of customer reviews mentioned safety concerns. But those reviews tend to be more negative in sentiment than the typical customer review, giving them an outsize impact on the behavior of subsequent would-be customers. The findings illustrate a delicate balancing act digital platforms have to perform, particularly those that rely heavily on user reviews: while highlighting negative experiences can help consumers make more informed choices, too much emphasis can drive customers away completely. The team ran several simulations calibrated by their empirical analysis to test how these dynamics play out in the market. They found that if a platform suppressed negative safety reviews completely, customers might assume that safety information was being hidden, and become more wary of using the platform in general. Conversely, while more transparency around safety issues could lead to fewer bookings of impacted properties in the short term, in the long run such a policy could boost user trust and draw more people to the platform, offsetting the short-term losses. “Platforms with the competitive space to focus on long-term objectives may benefit from a higher level of transparency, which can be facilitated by making information that is relevant to their buyers’ decision-making more readily available,” Wagman said. “Doing so facilitates trust and helps incentivize sellers to work to improve the quality of their offerings, as well as help shape sellers' decisions to enter a market (e.g., offer their listings) in the first place.”