There's no "I" in team, but getting your coworkers on the same "we" perspective can be tough. Here's why it's important, according to Rice University's research. Pexels

You just got a promotion — along with a brand-new work team whose members barely speak to one another. But first-rate cooperation is essential if you're going to deliver for your client. So you decide to spend a month getting to know each of your workers.

One is competent but bitter, frustrated by years of small mistakes by a colleague, mistakes that add to her own workload. Another, the one making the mistakes, seems so distracted he may as well be working at another company. Others have their own quirks. And to make matters worse, another department is set to merge its employees with your creaky, cranky team in a few months. How are you going to understand all these individuals, much less get them into shape as a unit?

For many managers, training and reading can help provide guidance. Others may hire an outside consultant and resort to team-building activities. But where does that outside expertise — not to mention training and reading — come from? It's based on academic research.

Rice Business professor Utpal Dholakia and colleagues René Algesheimer of the University of Zurich and Richard P. Bagozzi of the University of Michigan are among the scholars updating what we know about the dynamics of group decisions. Starting with classic group behavior theory, the scholars developed a series of sociologically-based models for analyzing small teams.

To better understand the existing shared intentions and attachment between teammates, Dholakia and his colleagues used a novel set of questions to survey 277 teams of computer gamers, each comprised of three people. They ran the survey responses through variations of a classic model called the Key Informant, which depends on the observations of group members about the social relationships inside a group.

Next, the researchers applied a sociological theory called Plural Subject Theory, focused on what's known as "we-attitude." That's exactly what it sounds like: verbally and actively treating an endeavor as a group project.

The core of this theory, the notion that successful teams frequently use collective pronouns when they discuss themselves and cognitively conceive of themselves as "we," has been heavily studied. Groups whose members think in terms of "we" act more cohesively and are measurably more committed to collectively reaching their goal.

To enhance the way these attitudes are measured, Dholakia created multiple variations of a new model. These differ from previous models because they include information not just from a "key informant," but from every member of a group. The researcher asks group members questions about themselves, their impressions of others in the group, their impressions about how others in the group think of each member and impressions about the group as a whole. This longer, more elaborate approach offers fresh insights about a group's shared consciousness — which provides a valuable new research outcome.

The professors found that this revision of classic key informant model generally worked the best of the various group-analysis models they tested — even improving on the original key informant approach. Future researchers, Dholakia notes, should consider the context of the team situation to decide which configuration of members is best to analyze.

So the next time you find yourself nonplussed by a chaotic group dynamic at work, remember you are in time-honored company — and that help is out there. By updating the key informant model, Dholakia and his colleagues have added to the analytical toolbox something that can help whip that team into shape. Whether it's an army of accountants or a network of hospital workers, Dholakia writes, the first step to creating a real team is analyzing which intentions they truly share.

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This article originally appeared on Rice Business Wisdom.

Utpal Dholakia is the George R. Brown Professor of Marketing at Jones Graduate School of Business at Rice University.

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New report ranks Texas among top 10 states where AI could disrupt jobs

AI Workforce

A new nationwide report examining where AI could "reshape" the most jobs has ranked Texas No. 9 among the most at-risk states for AI job disruption.

The new SmartAsset report compared all 50 states and the District of Columbia to calculate the estimated percent of the workforce employed in the 26 occupations with the highest AI exposure, as determined by June 2026 research by the Virginia Economic Information and Analytics Division.

The findings revealed that 500,000 Texas workers, or 3.55 percent of the total workforce, are employed in occupations with "high exposure to potential AI disruption."

This also places the Lone Star State as the 9th most at-risk state in the U.S. where AI exposure can lead to "declining hiring demand, wage pressure, task automation, and other forms of disruption."

"States with larger concentrations of highly exposed occupations could experience more pronounced labor-market changes, particularly in roles where core tasks are more vulnerable to AI-driven restructuring," the report's author wrote.

Texas' biggest cities, like Houston and Austin, are known for their thriving tech and business industries, and the study noted that many of the occupations within those sectors are the most at risk. The Virginia Economic Information and Analytics Division said the top five most AI-exposed occupations in the U.S. are: mathematicians, proofreaders, correspondence clerks, court reporters, and media and communication workers. Additionally, computer programmers, database administrators, web developers, telephone operators, and communications equipment operators round out the top 10 most at-risk positions.

These are the 16 remaining occupations most exposed to AI disruption, in order:

  • Data Entry Keyers
  • Statistical Assistants
  • Office Support Workers
  • Interpreters and Translators
  • Database Architects
  • Software Quality Assurance Analysts
  • Medical Transcriptionists
  • Software Developers
  • Writers and Authors
  • Payroll Clerks
  • Web Designers
  • Miscellaneous Computer Occupations
  • Insurance Claims Processors
  • Telemarketers
  • Computer Numerically Controlled Tool Programmers
  • Bookkeeping and Accounting Clerks

A separate SmartAsset report from April 2026 found about 20.5 percent of Texas workers use AI to do their jobs in some capacity. That trend will continue to shift further as employers and employees choose to adopt — or reject — AI implementation.

Across the U.S., Washington topped the list as the state with the highest concentration of AI-exposed jobs, with nearly 5.7 percent of the state's workforce employed in the 26 most at-risk positions. SmartAsset said Washington's high prevalence of technology companies is a significant factor that skyrocketed the state to the top of the list.

"Home to major technology companies including Microsoft, Amazon, T-Mobile and Expedia, the state has large numbers of computer programmers and software developers, two occupations with high exposure," the report said.

Meanwhile, Mississippi ranked No. 51 with the lowest concentration of AI-exposed jobs in the nation. About 22,500 workers in Mississippi, or 1.93 percent of its workforce, are at risk for AI disruption.

The top 10 states where AI could reshape the most jobs are:

  • No. 1 – Washington
  • No. 2 – Virginia
  • No. 3 – District of Columbia
  • No. 4 – California
  • No. 5 – Utah
  • No. 6 – Maryland
  • No. 7 – Colorado
  • No. 8 – New Hampshire
  • No. 9 – Texas
  • No. 10 – North Carolina
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This article originally appeared on CultureMap.com.

UH lands $1.2M NIH grant to fight superbugs using AI, quantum sensing

drug defense

The fight against antibiotic-resistant bacteria like MRSA is getting science fiction-like upgrades at the University of Houston thanks to a new four-year, $1.26 million grant from the National Institutes of Health.

The university says the recent funding brings total federal support up to $3.5 million for 11 years for the project, which uses AI and quantum-sensing technology to better understand how bacterial proteins develop resistance to drugs.

Any medical professional will tell you that one of the worst things that can happen is almost killing an infection. Bacteria that survive attacks from conventional antibiotic treatments emerge tougher, more resistant and more aggressive than before–making them much harder to treat. A good example is the superbug methicillin-resistant Staphylococcus aureus (MRSA).

UH chemistry professors Yuhong Wang and Shoujun Xu are working on this issue. They know full well that fighting superbugs requires new technology and new approaches, which is what they aim to pioneer with their new grant.

“Drug-resistant bacterial infections such as MRSA are becoming harder to treat, creating an urgent need for faster ways to understand how antibiotics and other small molecules interact with bacterial proteins,” Wang said in a news release.

Wang and Xu’s work centers around GTP, a cellular fuel that can cause tiny changes to a cell's structure when it mutates. Sometimes, those shape changes make it easier for drugs to breach the wall and attack the cells.

The UH scientists are employing AlphaFold, an AI-powered tool that can scan large molecular libraries in seconds. From these models, they can see promising drug combinations for future testing.

Once identified, the team uses their invention, super-resolution force spectroscopy, to monitor the cells. Tiny magnetic beads are attached to genetic material, then magnified to see how strong that material is when pulled. They can measure this incredible microscopic process through an atomic magnetometer, typically used in quantum physics. Combined, all these tools allow a high-definition look at how each molecule might respond to new chemical approaches.

“We're the only chemists in the world that use an atomic magnetometer for biological research,” Xu said. “It's a technique developed by physicists, and there is usually a gap between techniques developed by physicists and biological applications. Yuhong and I have been bridging that gap together for the past 10 years.”

Eventually, Wang and Xu hope to develop powerful software that can be used by drug manufacturers to model cellular responses. With enough predictive data, the software could even get ahead of superbugs’ own mutation, allowing drugs to be developed before new strains arrive.

"We want an algorithm where you input a protein sequence, score the mutation hotspots, and develop new inhibitors before a drug-resistant species even emerges," Wang added.

SpaceX to get more than 700 acres of Texas wildlife refuge in land swap

Space News

A federal judge on Monday, September 21, refused to block the Trump administration from giving SpaceX more than 700 acres of wildlife refuge as part of a land swap in Texas, while environmental groups vowed to continue their legal challenge.

U.S. District Judge Fernando Rodriguez Jr. declined the plaintiffs' request for a preliminary injunction to prevent the parcel exchange, saying they failed to prove it would worsen ecological risks to a Gulf Coast region already transformed by billionaire Elon Musk’s rocket operations.

In June, the U.S. Fish and Wildlife Service approved moving forward with the deal with SpaceX, which would surrender 683 acres the company owns in exchange for the federal land in the Lower Rio Grande Valley National Wildlife Refuge. The 103,000-acre refuge spans four counties along the Texas border and is home to animal habitats and historical landmarks.

Maps show the land SpaceX would acquire would be closer to the company's launchpad near the U.S.-Mexico border.

The swap amounts to a gift of public lands to SpaceX, “clearing the way for bulldozers to tear into this wildlife refuge as soon as next week and turn a public treasure into a private payday,” said Laiken Jordahl, a spokesperson with the Center for Biological Diversity, which filed the lawsuit alongside other opponents including tribal groups. Jordahl said Monday that the litigation will continue even as the exchange goes forward.

“This court order is not the final word. These lands hold incredible spiritual, historical and conservation value for the people and wildlife of South Texas. We won’t stop fighting to keep this irreplaceable public wildlife refuge safe from SpaceX bulldozers,” Jordahl said in a statement.

The lawsuit asks the federal court to halt the exchange, which has worried SpaceX opponents in the area who have long criticized the company's expanding footprint over lost access to beaches and concerns over exploding rockets.

The Fish and Wildlife Service didn’t respond to a request for comment on Monday’s decision. Previously, a spokesperson had said the agency does not comment on ongoing litigation.

The agency issued a final environmental assessment report in June that determined the exchange would cause no significant impact to the area. The report said the federal government believed the acquisition would represent a “net conservation benefit” and provide “substantial long-term conservation value and improving landscape-scale habitat connectivity across refuges in South Texas.”

The judge said that the plaintiffs offered “relatively weak” evidence of environmental harm.

“While they rightfully argue that the preservation of wildlife and historical lands furthers the public interest, they present no evidence demonstrating that the Property will suffer aesthetic, environmental, cultural, or historical degradation during the pendency of this lawsuit,” Rodriguez wrote in his ruling.

In addition, the judge said a preliminary injunction would result in modifications to SpaceX’s development plans, “placing additional hardship on the company’s ability to meet milestones and contractual obligations.”

SpaceX did not return an email seeking comment on the judge's ruling.

The space exploration company first broke ground in Texas more than a decade ago and has expanded rapidly, so much that SpaceX employees last year voted to incorporate their own local government called Starbase.