Business & Entrepreneurship

�鶹��Ѱ��Boulder ranked No. 1 in startups based on university discoveries

Elizabeth Lock — Mon, 15 Sep 2025 18:16:16 +0000

�鶹��Ѱ��Boulder ranked No. 1 in startups based on university discoveries Elizabeth Lock Mon, 09/15/2025 - 12:16

�鶹��Ѱ��Boulder launched 35 startups based on university intellectual property in fiscal year 2024, more than any other U.S. campus that year. The achievement also places �鶹��Ѱ��Boulder at No. 2 for the most startups launched in any single year by a U.S. campus.

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Want to get ahead at work? Learn to be funny

Katy Hill — Wed, 10 Sep 2025 14:02:00 +0000

Want to get ahead at work? Learn to be funny Katy Hill Wed, 09/10/2025 - 08:02

Katy Marquardt Hill

Humor in the workplace has long been seen as a soft skill, useful for breaking the ice or bonding over awkward moments on Zoom. But Tony Kong, professor in the Leeds School of Business, believes it’s far more than that. A leading researcher on workplace humor, he sees it as a powerful leadership tool that could help professionals navigate power dynamics, build trust and even elevate their status on the job.

Tony Kong

“Humor is a life skill. It’s great at a party, and it’s great in a meeting. But it’s not just about being funny. It’s about understanding your audience, your timing and your intent,” said Kong, who also directs Leeds’ Business Leadership Certificate program. “When done right, humor can increase trust, boost creativity, promote emotional well-being and even facilitate conflict resolution.”

An emerging field

Once dismissed as more playful than practical, humor is gaining traction as a serious subject of study in management. Researchers have been exploring its impact—both positive and negative—on leadership, negotiations, team dynamics and workplace culture.

Kong has spent a decade studying humor in professional settings and has published numerous papers on its role in leadership and organizational settings.

“There’s been a surge in research,” said Kong. “People are realizing humor plays an important role in negotiations, leadership, teamwork and culture. It’s also important to people’s health and well-being.”

His latest research proposes a framework for understanding workplace humor that shifts the focus from the content of the joke to the motive behind it. Instead of labeling humor as sarcastic, dry or self-deprecating, he classifies it by purpose: Is the humor meant to build connection, ease tension, impress others or cover up discomfort?

That perspective echoes what leadership coaches have noted—that humor can build inclusion, ease tension and break down hierarchies, but it’s also often misunderstood. Kong’s advice: Think more about how your intent will be received. “One should take the perspective of the audience and think ahead whether and how a joke can convey a constructive motive and thus be appreciated in a given situation,” he said.

Humor is a powerful but risky tool, Kong added, especially in diverse or global workplaces.

“Humor can be inclusive or exclusive,” Kong said. “It can strengthen bonds or reinforce hierarchies. That’s why we need to study it more seriously, especially in diverse and cross-cultural settings.”

10 reasons we tell jokes at work

Researchers classify our reasons for telling jokes into two broad categories: agentic motives, which aim to advance personal goals or influence others, and communal motives, which focus on connecting with people and building relationships.

Agentic motives:

Attack or demean third parties
Attain status
Ingratiate
Motivate
Relay information
Subvert authority

Communal motives:

Alleviate boredom
Build rapport
Seem more approachable
Signal solidarity and inclusion

Intent matters

Kong’s newest research on workplace humor, published online in May in the Journal of Management Studies and co-authored by Cecily D. Cooper of the University of Miami in Florida and Sharon B. Sheridan of Clemson University in South Carolina, draws on six studies and more than 1,000 participants. The goal: to rethink how humor is measured and studied in organizations and to build a stronger foundation for future research. The findings suggest that whether humor helps or harms depends less on the joke itself and more on how it is perceived.

For example, a roast or teasing among colleagues might seem risky on the surface, but when interpreted as communal (for example, relationship-building) rather than self-serving or aggressive, it can build trust. One study cited in the paper found that “putdown humor” among police officers fostered team cohesion when framed as a sign of group belonging.

“Humor is all about how it’s received,” Kong said. “The same joke can land very differently depending on who tells it, who hears it, when and how it’s told, and what the perceived motive is.”

That perception can matter in high-stakes situations, too, like job interviews. A well-placed joke, particularly one that reveals self-awareness, can be disarming and memorable. However, a bad joke or over-use of jokes can undermine one’s credibility and create awkwardness.

“Answering ‘What’s your greatest weakness?’ with a bit of humor can work—if it shows authenticity and emotional intelligence,” Kong said.

But humor can also backfire. Kong points to recent research by organizational scholars showing that employees often feel pressured to laugh at a boss’s jokes, regardless of whether they’re funny. That kind of “forced laughter,” Kong says, can contribute to emotional exhaustion and job dissatisfaction.

A teachable tool

So what does this mean for ambitious professionals? As Kong sees it, humor is a strategic skill worth developing.

He believes business schools—and business leaders—should take humor seriously, as it’s a fundamental element of interpersonal communication and it intersects with power, status, inclusion, creativity, trust, ethics, psychological safety and well-being.

“Business schools have a lot to gain from incorporating humor into their curriculum,” Kong said. “I’ve been exploring and ideating how to teach it through both research-based insights and interactive learning experiences in business schools in different regions of the world.”

Some MBA programs are beginning to explore humor more formally. For example, Stanford’s business school offers a course on humor in business, focused on using levity to build stronger teams and drive innovation.

While the goal isn’t to turn business school students into comedians, Kong said, teaching future leaders to read the room, build genuine and healthy connections with humor, lead with authenticity, and help others enhance emotional well-being can give them a competitive edge in today’s dynamic, fast-changing and stressful workplaces.

Plus, humor can help people laugh together, and leaders should laugh with others. Humor, when used appropriately, can create a more cohesive, egalitarian, and healthy workplace in which people thrive, Kong said lightheartedly, adding: “We take our work seriously, but can we not take ourselves too seriously?”

Organizational leadership expert Tony Kong says humor is a strategic skill that can help you lead, connect and stand out—and his research shows why intent matters more than the punchline.

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AI is headed back to school

Katy Hill — Tue, 26 Aug 2025 02:43:03 +0000

AI is headed back to school Katy Hill Mon, 08/25/2025 - 20:43

Katy Marquardt Hill

Artificial intelligence is everywhere, from Google search results to social media—and now it’s showing up in classrooms. How is AI changing the way students learn in 2025, and what does it mean for teaching? �鶹��Ѱ��Boulder Today spoke with Jeremiah Contreras, associate teaching professor of accounting at the Leeds School of Business, about how AI is being integrated into courses, how students can use it responsibly and what skills will matter most in an AI-driven world.

Jeremiah Contreras

AI was the story of 2023 and 2024. How is it showing up in classrooms as students head back to school in 2025?

In 2025, AI is no longer a novelty—it’s becoming a core part of the educational experience. While students have been using it on their own at increasing rates, at Leeds, every student in our Business Core courses now engage with AI in some form, whether it’s using generative AI to analyze a case study, brainstorming ideas through dialogue with AI, or learning about a topic with a custom learning agent created by faculty. The goal in the classroom is to model effective uses of AI for learning, as opposed to simply having students get answers through these chatbots.

You’ve helped lead a campuswide effort to integrate AI across �鶹��Ѱ��Boulder’s business curriculum. What lessons from higher ed should K–12 educators consider as they face pressure to adopt AI tools?

The biggest lesson is: Start with purpose, not tools. Don’t just add AI because it’s trendy. Decide what problem it’s solving or what skill it’s building. Provide teacher training before expecting classroom adoption, and integrate AI into existing learning goals rather than treating it as an add-on. At the same time, create a supportive space for experimentation: Pilot in a few classrooms, learn from the process, and scale up intentionally.

What are the biggest misconceptions parents, teachers or even students have about using AI in the classroom?

One misconception is that teaching students how to use AI to get answers is the most important aspect. The reality is that AI inherently reduces effort, but learning requires struggle. Students who use it well often work harder, because they’re iterating, fact-checking and refining their thinking. Finally, some believe AI will “replace” teaching, when the most effective uses can actually deepen teacher-student interaction.

How do you teach students not just to use AI, but to use it ethically and critically?

There is a huge difference between learning to use AI and using AI to learn. We not only need to teach students how to use AI (known as AI literacy), but when we embed AI into a course, we should be using the power of AI to ask questions of the student as opposed to simply providing an answer.

This is the magic behind custom learning agents, which are just AI that have been given a task. We give AI the job of walking a student through a learning process. Instead of providing answers to students, it helps them think about a topic and guides them through the learning process. With more complexity, these agents can create entire simulations where students can engage with different characters throughout an assignment.

We should also explicitly address ethics in our AI-related activities, rather than isolating it to one lecture. Students should learn to ask: Where did this data come from? Who benefits? Who might be harmed?

Some educators fear AI will discourage original thinking or be used for shortcuts. What have you seen in practice? Are students getting lazier … or sharper?

When AI is used appropriately, students can actually learn more deeply. We’ve seen them explore ideas in more depth, test different approaches to a problem, and take risks when learning. There is far less fear talking with an AI to explore a topic than talking with a teacher or even a teaching assistant. The problem comes when assignments are purely product-focused, such as grading a paper that could be written with AI in an unchecked environment. When we take the time to assess the process a student goes through and the thinking behind the work, AI becomes a tool for deeper engagement rather than simply a shortcut to an answer.

Colorado recently passed one of the nation’s first comprehensive AI laws. How should schools—K-12 and universities—start preparing for a regulated AI environment?

Schools need to get comfortable with documenting and explaining how AI is used. That means knowing which tools are being deployed, where the data goes, and how decisions are made. This shouldn’t just be about compliance, but rather about building a culture of responsible AI use that can stand up to public scrutiny. If AI is used to assist in any type of assessment, that process must be disclosed and have a way for students to question the process. The Colorado law covers any AI system that affects the “well-being or opportunities” of individuals, which includes grades.

You’ve emphasized that AI should be a helper, not a crutch. What are some concrete ways students can use AI to boost and not bypass their learning?

Students should learn to use AI for brainstorming, cleaning up their outlines, or helping review their writing. It should not be used as a replacement for learning to do those things. There are also very powerful new learning tools in many of the AI products, such as ChatGPT’s “Study and Learn” feature or Gemini’s “Guided Learning” tool. This can help students use AI as a coach for practice problems or to simulate a debate partner that challenges your arguments. And most importantly, use it to get feedback on drafts or ideas, then decide which feedback to keep. AI should expand our thinking, not replace it.

What advice do you have for school administrators or faculty who feel overwhelmed by the pace of AI change and don’t know where to start?

Start now. You can start small or take some big steps forward, but ensure you have an approach that is adding to effective uses of AI in education, not just throwing AI into the mix in an uncoordinated way. Pick one or two use cases that solve real pain points: maybe grading rubrics or re-writing lesson plans. Build a peer learning group so educators can share wins and challenges. The perfect AI plan doesn’t exist; momentum comes from experimenting, reflecting and iterating. It takes having people who are willing to play with the tools and begin experimenting.

Looking ahead, what skills will define the most successful students in this AI-driven world and how can schools help nurture them right now?

The most successful students will be those who can ask better questions, evaluate AI outputs critically and adapt quickly to new tools. Most importantly, they will need strong human skills around collaboration, communication, creativity, ethical reasoning and learning to trust their judgment. Schools can nurture this by making AI a regular part of projects, emphasizing reflection and encouraging students to work on problems with no single right answer.

Leeds professor and AI-in-education expert Jeremiah Contreras explains how classrooms are using artificial intelligence and what the rest of us can learn from it.

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Your next airline ticket could be priced by AI

Katy Hill — Wed, 20 Aug 2025 15:43:05 +0000

Your next airline ticket could be priced by AI Katy Hill Wed, 08/20/2025 - 09:43

Katy Marquardt Hill

Delta is testing technology that could charge you more (or less) for the same flight based on what it predicts you’re willing to pay. While lawmakers are calling it “pain point pricing” and putting privacy at risk, the airline says it’s not using personal data and that the tool simply helps fine-tune prices the airline would already be adjusting.

Övünç Yılmaz

Experts say Delta’s move marks a major shift and a glimpse of where pricing is headed. To unpack what this means for travelers, �鶹��Ѱ��Boulder Today spoke with Övünç Yılmaz, assistant professor of operations and a pricing expert at the Leeds School of Business. He’s spent years studying revenue management for airlines, hotels and events, and he sees Delta’s latest move as a window into the future—one that is both interesting but may raise questions about fairness, transparency and consumer trust.

What exactly is Delta’s new AI-driven pricing, and how does it differ from the pricing strategies airlines already use?

Airlines have been using dynamic pricing for years to adjust ticket prices in real time based on demand and availability. The price you see can depend on a few key factors, like how early you are booking and how many seats are still available. For example, if a flight from Denver to New York is filling up quickly, the price will probably go up. But if there are still lots of empty seats close to departure, the airline might lower the fare to attract more buyers.

What’s new about Delta’s approach is that they’re using AI to take pricing a step further, potentially tailoring fares to individual customers. There are really two sides to what they’re doing. On one side, they’re using AI to assist the work of human pricing analysts. That feels natural to me, and I expect we’ll see more of this as AI can help humans make faster and better decisions.

On the other side, they could show two people different prices for the same flight, even if they’re searching at the same time, based on things like their previous bookings or browsing history. That’s what we call personalized pricing, and it’s a big shift from how airline pricing has traditionally worked.

Personally, I think it’s a bold move, and we’re going to see a lot of debate around it.

Historically, have we ever seen this kind of highly personalized pricing in airlines or other industries?

We’ve seen some forms of personalized pricing before, especially in e-commerce, but this kind of AI-driven personalized pricing is still new when it comes to airlines. One early case that got a lot of attention was Amazon in the early 2000s. People noticed that different customers were seeing different prices for the same DVD, and it caused immediate backlash. Amazon said it was just a pricing test, but they quickly pulled back.

Since then, companies have been more subtle. Instead of clearly showing different prices to different people, they’ve been using targeted promotions. You can see these everywhere: ride-sharing apps offering special deals to select users and online retailers sending personalized discount codes based on browsing history. These are generally accepted because they’re presented as discounts rather than personalized pricing.

The Federal Trade Commission is currently studying these kinds of practices, which it refers to as surveillance pricing. Its initial findings suggest that the practice is already widespread, with data covering industries from grocery to apparel, among many others.

Does AI-driven personalized pricing risk exploiting consumers or pushing prices to their “pain point”? What protections are in place, and are there potential upsides for travelers?

Hypothetically, if AI could perfectly estimate each customer’s true willingness to pay, it could absolutely be used to extract more revenue. For example, if a flight is normally priced at $100 and AI identifies that one customer is willing to pay $200, it might try to charge them that amount. At the same time, another customer who appears more price-sensitive might be offered a lower fare, like $80, to secure the sale.

Of course, accurately predicting how much someone is willing to pay is extremely difficult. But AI can make educated guesses based on browsing data and online behavior. For example, the first customer might have recently purchased a luxury bag, suggesting a higher willingness to pay. Meanwhile, the second customer may have been comparing prices across multiple airline websites, signaling price sensitivity.

Without knowing the exact details of how Delta’s AI-driven pricing works, it’s hard to say how far they’re going in terms of the information they use. After the initial public backlash, Delta stated, “There is no fare product Delta has ever used, is testing or plans to use that targets customers with individualized prices based on personal data.” So, for now, we’ll just have to wait and see how this develops.

What changes do you anticipate in the coming years? Will AI and personalized pricing become even more widespread, or could public backlash or regulatory pressure slow down their adoption?

These days, nearly every click and scroll on the way to a purchase is tracked, so it’s not surprising that companies use that data to inform pricing. Over time, I think people will also get used to it. We’ve already seen this happen with dynamic pricing. What once felt strange or even unfair has gradually become pretty common.

That said, it’s still not well-defined how much data companies should be allowed to use, and what exactly they can use it for. Companies can’t legally discriminate based on protected characteristics, but beyond that, the boundaries are unclear. I think we’ll start seeing more legal and policy discussions around what’s fair, what’s allowed, and where the line should be. But in the meantime, I believe it would benefit everyone if companies are transparent about how they use data in pricing.

Is there anything else consumers should know about these strategies?

Yes—first, there’s Delta’s recent comment about “amazingly favorable unit revenues” from the tests they’ve been running. It might be worth taking a closer look at what’s actually driving those results. Is it simply that AI is doing a better job with dynamic pricing compared to their previous system? Or is some of the lift coming from price personalization? I think that distinction really matters.

Second, consumers tend to get savvier over time, especially if they feel pricing isn't working in their favor. If people start to suspect they’re being charged more based on personal data, they might switch devices, clear cookies or use incognito mode. Some may even move toward companies that feel more transparent. In the long run, trust and clarity can be just as important as short-term revenue, especially in industries like air travel where customer loyalty and lifetime value are critical.

Delta is testing an AI-powered pricing system that could charge two travelers different fares even if they are purchasing at the same moment. Pricing strategy expert Övünç Yılmaz explains what this shift means for consumers—and why we should expect more of it.

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Wanted: Entrepreneurs to launch startups based on �鶹��Ѱ��Boulder innovations

Megan Maneval — Fri, 15 Aug 2025 12:07:23 +0000

Wanted: Entrepreneurs to launch startups based on �鶹��Ѱ��Boulder innovations Megan Maneval Fri, 08/15/2025 - 06:07

�鶹��Ѱ��Boulder's Embark Deep Tech Startup Creator will hire up to seven Embark Startup Founders to serve as CEOs of new deep tech companies built around technology developed in �鶹��Ѱ��Boulder's world-class research enterprise.

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'Selling anger': How cable news profits from outrage

Katy Hill — Wed, 30 Jul 2025 16:38:35 +0000

'Selling anger': How cable news profits from outrage Katy Hill Wed, 07/30/2025 - 10:38

Katy Marquardt Hill

It’s no secret that cable news networks have partisan reputations: Fox News on the right, MSNBC on the left and CNN somewhere in between. But new research shows the divide extends beyond which party a network appears to support. Over the past decade, these networks have increasingly focused on criticizing the opposing political party, a tactic researchers say is less about informing viewers and more about “selling anger.”

“These networks are more interested in talking about the opposing political party rather than their own candidates. This was not the case 15, 20 years ago,” said Diego Garcia, the Burridge Endowed Chair in Finance in the Leeds School of Business and co-author of the working paper.

Diego Garcia

Garcia and his co-authors—Ryan Lewis, associate professor of finance at Leeds, and Maximilian Rohrer, associate professor of finance at the Norwegian School of Economics—analyzed closed-caption data from six major cable news networks between 2012 and 2024, including CNN, Fox News, MSNBC, CNBC, Bloomberg TV, and Fox Business using a form of AI called natural language processing. They tracked which public figures were mentioned, matched those names to Wikipedia data to classify traits like political affiliation, race and gender, and assessed whether the coverage was positive or negative based on the 150 words surrounding each mention.

The findings show that politics dominates cable news, accounting for about 60% of all named individuals mentioned—rising to over 75% during election years. But more revealing is who gets talked about: MSNBC spends more time discussing Republicans than Democrats, while Fox News focuses more heavily on Democrats. In 2024, Fox covered Democrats 60% of the time, with MSNBC showing the reverse.

The trend holds for business channels too. Fox Business mirrors Fox News, with more frequent and more negative coverage of Democrats compared to Republicans, according to the researchers. CNBC and Bloomberg show more balanced and less political coverage overall.

While the study didn’t explore what’s driving the shifts in coverage, Garcia has a theory: “Social media has made it very easy for these media firms to experiment with what sells. And anger is very powerful,” he said. “It seems to work to increase engagement.”

Garcia speculates that cable networks began to test different kinds of content when social media became widespread in the mid-2010s, and discovered that outrage boosts viewership.

“I think Fox was the first one to figure this out, and they started pushing this negative rhetoric in their news,” he said. “They’re actually now the No. 1 cable news channel in the U.S. by far.”

Indeed, Fox News now commands over 60% of the cable news audience—a dramatic jump from a more evenly split landscape a decade ago.

Beyond politics: race, gender, and LGBTQ coverage

The researchers also examined coverage of other identity groups. Women made up just 17% of all people mentioned on cable news—far below their share of the population. Fox News mentioned women more than other networks but focused largely on female politicians (mostly Democrats). CNN gave slightly more attention to women who were not politicians, while MSNBC was more positive in tone toward female political figures.

Black Americans were mentioned in roughly 11% of daily coverage, closely mirroring their share of the U.S. population. But sentiment varied widely: MSNBC was the most positive, especially toward Black people who were not politicians. Fox News, on the other hand, showed significantly more negative sentiment, particularly during moments of racial tension, such as the George Floyd protests.

“LeBron James, Fox News really doesn’t like him at all,” Garcia noted. “If you look at a sentiment score on LeBron, it’s actually very negative on Fox.”

Coverage of LGBTQ individuals was sparse at under 2% overall. CNN and MSNBC offered more frequent and more positive mentions. Fox News provided the least coverage and displayed a consistently negative tone, particularly around issues like Florida’s “Don’t Say Gay” law, which prohibits classroom instruction on sexual orientation or gender identity in public schools.

Supreme Court justices were rarely mentioned—making up just 0.5% of all people named—but their coverage spiked during key rulings. Fox News significantly reduced coverage of the Court after it agreed to hear the case that eventually overturned Roe v. Wade. CNN and MSNBC, in contrast, increased coverage during that period.

“Fox News is very quiet about the Supreme Court, even though it was big news,” Garcia said.

Tuning out bias

Garcia, who describes himself as socially left-leaning and economically conservative, said the findings changed how he consumes media.

“I force myself to try to listen to different sources because of these very strong biases,” he said.

He believes political coverage should shift away from stoking outrage and emphasize fair coverage of real issues.

“We should be discussing immigration. We should be discussing climate change,” he said. “Not conspiracy theories and trash talk.”

His advice for viewers: Don’t rely solely on your favorite cable station for your news. “If you just go to the source that caters to your confirmation bias, there’s going to be very negative news about the opposing party,” Garcia said. “That’s the business model right now.”

Major networks increasingly focus on criticizing the opposing party–fueling division to boost ratings, according to a 12-year study of TV news.

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Should you be worried about the national debt?

Katy Hill — Tue, 29 Jul 2025 14:50:12 +0000

Should you be worried about the national debt? Katy Hill Tue, 07/29/2025 - 08:50

Katy Marquardt Hill

The national debt just passed $36 trillion, reigniting debates over spending, growth and taxes. But how serious is it, and how will it affect everyday Americans? �鶹��Ѱ��Boulder Today caught up with Shaun Davies, associate professor of finance at the Leeds School of Business, to break down what you need to know.

Shaun Davies

Let’s start simple. What’s the difference between the deficit and the national debt?

The deficit is what happens when the federal government spends more than it collects in a given year. So if the government takes in $4 trillion in tax revenue but spends $5 trillion, the deficit would be $1 trillion. To cover that gap, the government issues debt—for example, U.S. Treasury bonds. The national debt is the total amount we owe from running deficits over time, minus any surpluses, which we have not had since 2001.

So the U.S. owes over $36 trillion. Should we be concerned?

Yes and no. That level of debt could be sustainable if we keep it in check and the economy continues to grow. But our debt-to-(gross domestic product) ratio is now around 120%, which means we owe more than we produce in a year. That’s a red flag. Unfortunately, under both Republican and Democratic leadership, we’ve seen very little fiscal discipline. The real concern is the growth rate of the debt.

How do we compare to other major economies?

We’re in the middle of the pack. I’d give us a C, maybe a C-minus. We’re in better shape than Japan, which has a massive debt load relative to its GDP. But we lag behind most European countries, which tend to keep their debt under 100% of GDP. So we’re not failing, but we’re definitely not excelling.

What are some of the biggest myths about the national debt?

Interest rates are one of the most misunderstood pieces. The Federal Reserve has some control over interest rates, but much less than the average person realizes. The Fed sets short-term rates, like what banks charge each other for overnight loans. But longer-term interest rates—like those on 10-year Treasury bonds, mortgages and auto loans—are determined by the market. If investors get spooked about the U.S. debt, they’ll demand higher returns for holding that debt, which means higher interest rates for all of us.

President Donald Trump’s tax cut and spending bill is projected to add $3 trillion to the debt over the next decade. What’s driving that?

It’s simple math: less revenue and more spending. Tax cuts reduce what the government brings in. New spending increases what it pays out. On top of that, higher interest rates mean the government has to pay more just to service its existing debt. That cost is growing fast.

Is this projected debt increase unusually large?

These large deficit increases are becoming more common—2017’s tax cuts, the COVID relief bills, the Inflation Reduction Act. But just because it’s common doesn’t mean it’s wise. If something keeps making you sick, you probably shouldn’t keep eating it. The troubling trend is not just the level of debt, but how fast it’s growing.

How does the national debt impact the average American?

In the short term, it’s mostly political noise. If you tune it out, you probably won’t notice much. But long term, if the U.S. needs to issue a ton of new debt and the market loses confidence, interest rates could spike. If we're not careful, we could see mortgage rates exceed 10% and maybe even more. Again, longer term interest rates are set by the market, not the Fed. If the market loses faith, look out.

What trade-offs might we face if borrowing continues at this scale?

At some point, we have to get serious about reducing the debt-to-GDP ratio. That likely means higher taxes and lower government spending. It will be unpleasant, but financial stability demands it.

What’s the worst-case scenario if debt keeps growing unchecked?

The U.S. government can’t go bankrupt in the way a company can—it can always print more money. But that would lead to serious inflation. If the world loses faith in the U.S. dollar and our bonds, we could see a spike in interest rates, the dollar could weaken considerably, and economic growth will come to a standstill. It will be a dark day. We need to take our medicine now.

From inflated interest rates to future tax hikes, �鶹��Ѱ��Boulder finance expert Shaun Davies explains what today’s debt levels could mean for tomorrow’s economy—and your wallet.

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New quantum physics and AI-powered microchip design software awarded grants

Amber Elise Carlson — Thu, 24 Jul 2025 04:02:09 +0000

New quantum physics and AI-powered microchip design software awarded grants Amber Elise Carlson Wed, 07/23/2025 - 22:02

Amber Carlson

Semiconductors—substances that can selectively conduct or block electricity—have been dubbed the “brains of modern electronics.” They form the building blocks of the chips that power electronic devices from laptops to smartphones and tablets to sports watches.

But semiconductors generate heat when they’re working, and they can easily get too hot, which hurts their performance and can damage them. While smaller chips are denser and more efficient at processing, they are harder to keep cool because of their size.

Sanghamitra Neogi, an associate professor in the Ann and H.J. Smead Aerospace Engineering Sciences department, is exploring ways to protect semiconductors and microchips from heat damage. She specializes in nanoscale semiconductors, which are so tiny their parts are measured in nanometers (billionths of a meter).

Sanghamitra Neogi speaks about her startup, AtomTCAD Inc., at �鶹��Ѱ��Boulder's Ascent Deep Tech Community Showcase on June 25, 2025. (Credit: Casey Cass/�鶹��Ѱ��Boulder)

Neogi and her research group, CUANTAM Laboratory, have developed a sophisticated software called AtomThermCAD that can predict how the materials in a microchip respond to heat, which determines whether the chip will ultimately fail from overheating. AtomThermCAD is short for Atom-to-Device Thermal Computer Aided Design software for nanometer-scale semiconductor devices. The research behind this software was primarily supported by a $1 million DARPA MTO Thermonat grant awarded between 2023 and 2025.

Earlier this year, Neogi launched a startup to bring the software to market for semiconductor manufacturers and other customers. To kickstart her new company, AtomTCAD Inc., Neogi received $150,000 in recent grant funding from the state’s Office of Economic Development and International Trade, or OEDIT, matched by another $50,000 from Venture Partners at �鶹��Ѱ��Boulder, which helps �鶹��Ѱ��faculty and researchers turn their discoveries into startups and partnerships through funding and entrepreneurial support.

The grant from OEDIT was an advanced industries proof-of-concept grant for researchers in advanced industries. Managed by OEDIT’s Global Business Development division, this funding is intended to accelerate innovation, promote public-private partnerships and encourage commercialization of products and services to strengthen Colorado’s economy.

OEDIT Executive Director Eve Lieberman said that Neogi’s work will benefit the entire semiconductor industry, a rapidly growing segment of Colorado’s economy.

“Dr. Neogi’s research addresses one of the industry’s toughest challenges by improving heat management at the nanoscale, which boosts chip performance and supports the growth of Colorado’s advanced technology sector,” Lieberman said.

Chip designers use software like Neogi’s to test their designs without needing to actually build the chips. But unlike most chip design software, AtomThermCAD uses AI-accelerated quantum physics calculations to model the semiconductors and their components at an atomic level so it can accurately predict whether semiconductors or transistors too small to be seen by the naked eye will overheat.

The software could accelerate technological advancement by saving chip designers months, if not years, of time they previously had to spend developing and testing their designs.

Neogi drew on her expertise in physics and quantum technology to develop the software. She said as microchip components get smaller and smaller, approaching the level of individual atoms, researchers need to look to quantum physics to understand how the components behave.

Neogi also feels her approach could have applications beyond microchip development.

“What we developed is a method where you can model the thermal phenomena of any kind of nanoscale tech device,” she said. “Beyond microchips, it could be nanoscale medical devices and implants inside your body, or even drug delivery systems.”

Beyond the story

Our quantum impact by the numbers:

60-plus years as the regional epicenter for quantum research
4 Nobel prizes in physics awarded to university researchers
No. 11 quantum physics program in the nation and co-leader on the new Quantum Incubator facility

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Sanghamitra Neogi in �鶹��Ѱ��Boulder’s aerospace engineering department will use $200,000 in grant funding to launch a startup in which she will offer software that uses quantum physics to model microchip designs.

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Podcast episode gives mid-year economic check-in

Megan Maneval — Tue, 01 Jul 2025 15:50:00 +0000

Podcast episode gives mid-year economic check-in Megan Maneval Tue, 07/01/2025 - 09:50

Brian Lewandowski and Richard Wobbekind of Leeds' Business Research Division discuss 2025's economic twists and turns and what may be on the horizon.

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Market mood swings: How fear spreads online—and what it means for investors

Katy Hill — Wed, 18 Jun 2025 16:28:31 +0000

Market mood swings: How fear spreads online—and what it means for investors Katy Hill Wed, 06/18/2025 - 10:28

Katy Marquardt Hill

When the stock market slumps, social media can amplify the anxiety.

New research finds that after major market drops, investor sentiment on platforms like Twitter and StockTwits turns sharply negative and attention to market news surges. But these emotional reactions tend to fade within a few weeks. What may last longer are the effects: That short-lived wave of fear and focus can ripple through the market, influencing trading activity and stock performance even after the initial panic dies down.

To understand these dynamics, a team of �鶹��Ѱ�� researchers analyzed millions of posts from 2013 to 2021 on three major investor platforms: StockTwits, Seeking Alpha, and Twitter (now called X). They built two daily indexes: one to track sentiment—how much optimism people feel about the market—and another to measure attention, or how much people are talking about stocks.

Tony Cookson

“Social media is increasingly becoming a forum where investors display their sentiments in public view—it’s a natural setting to take the market’s pulse,” said Tony Cookson, professor of finance at the Leeds School of Business who co-authored the working paper.

“Sentiment captures people’s emotions,” Cookson explained. “In contrast, attention reflects investors’ focus on markets, which can be high when investors are fearful or when they are enthusiastic.”

The researchers used sentiment and attention data on Stocktwits, Seeking Alpha and Twitter posts that were scored as bullish or bearish. After aggregating these firm-level measures to the overall market level, they found that stock prices tend to rise just before high sentiment days, then typically fall over the following few weeks. In contrast, stock prices decline prior to high attention days, followed by a continuation of negative returns.

Their results have implications for investors. “When market attention is high, future returns are lower. On the flip side, after drops in sentiment, returns tend to recover,” Cookson said.

Different forces, different paths

By separating sentiment and attention—two ideas often lumped together in past research—the team was able to trace how each relates to the market. Sentiment, they found, tends to overreact to bad news, reflecting emotional responses that quickly reverse. Attention, on the other hand, grows.

“There’s a clear pattern,” Cookson said. “When markets are going down, we see that sentiment stays down for a while, but then eventually recovers. Whereas attention doesn't exhibit that pattern at all. It tends to reflect yesterday's returns, but then it continues and builds.”

Both forces are closely tied to market activity. When sentiment falls or attention spikes, trading volumes tend to rise. In other words, emotional reactions and market-wide attention—both amplified during times of stress—often drive trading activity together.

“These are happening simultaneously,” Cookson said. “There’s a lot of trading when there’s a lot of negative sentiment. Those two go hand in hand—they’re capturing and reflecting bad times in the market.”

Volatility and asymmetry

While the study doesn’t analyze recent markets specifically, it offers a blueprint for understanding how volatility ripples through investor psychology. In tests using daily spikes in the VIX index—a popular measure of expected market volatility—the researchers found a consistent pattern: When volatility jumps, sentiment drops sharply and attention surges.

That response isn’t symmetric. “We see this for sharp drops in the market—negative news—but we don’t see it for similarly sharp spikes in markets,” Cookson said. “The negative days seem to leave more of a mark in the sentiment index and the attention index.”

The asymmetry is critical. Fear reflects deeper and longer-lasting shifts in online investor mood than enthusiasm. When markets fall, social media sentiment turns negative—and stays that way for several days. Attention, meanwhile, spikes and remains elevated, showing that fear drives sustained investor focus.

But after a market rally? Sentiment and attention barely budge.

Why does fear hit harder? “Fear spreads faster,” Cookson said. “Enthusiasm is kind of a more gradual building process. You don’t see it in the daily patterns. You see fear on display in this daily index.”

How panic travels

The effects don’t stay confined to a single stock. Instead, the researchers found that fear travels across firms.

“It’s not just sentiment about Apple and Tesla and Microsoft added up,” Cookson said. “It’s Apple affecting how you feel about Tesla or Microsoft.”

That emotional spillover means sentiment that spreads across the whole market is less likely to be about information and more likely to reflect emotion. “When sentiment is focused on one thing, it’s more likely to be information,” Cookson said. “When it’s spread across many things, that can’t be information—it has to be emotion.”

What investors can learn

So what does all this mean for investors?

“In fearful times, sentiment tends to overreact—that’s something to keep in mind,” Cookson said. Meanwhile, increased investor chatter online, especially during anxious periods, often signals weaker stock returns ahead.

The old Warren Buffett dictum—“Be fearful when others are greedy, and greedy when others are fearful”—still applies, Cookson said: “Our results show how natural emotion is part of markets—it matters.”

That emotional swing can be costly. “You might be prone to getting out of the market in a way where you end up buying high and selling low,” Cookson said.

The practical takeaway? Stick to the basics.

“Diversification is usually a good idea. Timing markets is usually a folly,” he said. And be wary of the distorted lens social media can create. “Especially if you’re using social platforms like Twitter or even Seeking Alpha, you’re operating in a polarized information environment. Everything seems either good or bad—maybe it's good to fight the natural urge to act on sentiment.”

New research shows how online sentiment and attention predict trading patterns and returns during volatile markets.

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