How to navigate toxic lab workplaces, according to UH research

Houston voices

Just like any workplace, labs can get toxic. Graphic by Miguel Tovar/University of Houston

There are many types of toxic bosses. The Micromanager. The Narcissist. The Incompetent Boss. The list goes on. But labs led by toxic PIs not only make for an abysmal workplace they can actually encourage research misconduct.

According to Charles Wood, author of “When lab leaders take too much control,” there are two types of toxic labs most at risk for this type of behavior: the executive model and the competition model.

Executive model

Wood described the executive approach to lab management as one where the mentor sets expectations for trainees, often with a particular goal in mind. In its negative form, this includes specifying experimental outcomes and instructing trainees on particular experiments to achieve a desired result.

It comes as no surprise that experimenting with the answer already in mind goes against scientific principles. Spiking biological samples, manipulating instruments – all these things have been suspected in labs according to the U.S. government’s Office of Research Integrity. The first line of defense is having the investigators replicate their experiment while being closely supervised. The consequences of misconduct, if the allegations are found to be credible, can include being debarred from further federal funding and having data sequestered.

Competition model

The competition model pits graduate students or postdocs against one another. In this case, whoever gets the result first is rewarded, while the others are punished. This makes a perfect breeding ground for misconduct. Imagine if a foreign student’s citizenship status is affected by whether or not they can produce the results their PI wants them to obtain. Of the competition model, Wood said that what students and postdocs learn can be catastrophic: “competition over collaboration and conformity over creativity.” He posits that researchers graduating from the PI’s toxic lab may be influenced to drop out of science completely or go on to run their own labs in a toxic way.

A correlation between mentors and ethical decision-making

Michael D. Mumford, et al. in “Environmental influences on ethical decision making: Climate and environmental predictors of research integrity” (Ethics & Behavior journal) found that for first-year doctoral students, “environmental experiences (including professional leadership) exert stronger effects on ethical decision making than the climate of the work group.”

Wood also noted that, regardless of the management style, certain scientists may be more prone to cheating. However, active involvement and openness by the principal investigator can serve as a preventive measure against this.

What can you do about it?

Chris Sowers in the “Toxic Boss Syndrome: How To Recover and Get Your Mojo Back” episode of his Better Humans podcast, shared how a few toxic bosses affected his job performance, self esteem and even interpersonal relationships. His first piece of advice is to get out quickly, even if you need to take a pay cut – he says a few thousand dollars are not worth the hit to your mental and physical health.

Vetting your lab’s PI will help enormously. Does the PI have a good track record of being a fair and kind mentor?

“If your principal investigator starts to exhibit toxic behavior, address this with him or her,” said Wood. He goes on to advise that “if you find yourself in a truly toxic environment, seek guidance from a graduate coordinator, assistant dean or other authority figure who oversees the pre- or postdoctoral training programs — and ask for help in finding another mentor.”

The Big Idea

No one has time or energy to dedicate to a toxic workplace. The costs are way too high to risk manipulating data. For one, all authors on a paper will be held responsible for the misconduct– not to mention the physical and mental stress a toxic lab will invite into your life.

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

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"ChatGPT, even with improved filters or as it continues to evolve, will never be able to replace the critical and creative thinking we need in these disciplines.” Graphic by Miguel Tovar/University of Houston

Houston expert: Analyzing the impact of generative AI on research

houston voices

Researchers have to write extremely specific papers that require higher-order thinking — will an intuitive AI program like OpenAI’s ChatGPT be able to imitate the vocabulary, grammar and most importantly, content, that a scientist or researcher would want to publish? And should it be able to?

University of Houston’s Executive Director of the Research Integrity and Oversight (RIO) Office Kirstin Holzschuh puts it this way: “Scientists are out-of-the box thinkers – which is why they are so important to advancements in so many areas. ChatGPT, even with improved filters or as it continues to evolve, will never be able to replace the critical and creative thinking we need in these disciplines.”

“A toy, not a tool”

The Atlantic published, “ChatGPT Is Dumber Than You Think,” with a subtitle advising readers to “Treat it like a toy, not a tool.” The author, Ian Bogost, indulged in the already tired trope of asking ChatGPT to write about “ChatGPT in the style of Ian Bogost.” The unimaginative but overall passable introduction to his article was proof that, “any responses it generates are likely to be shallow and lacking in depth and insight.”

Bogost expressed qualms similar to those of Ezra Klein, the podcaster behind, “A Skeptical Take on the AI Revolution.” Klein and his guest, NYU psychology and neural science professor Gary Marcus, mostly questioned the reliability and truthfulness of the chatbot. Marcus calls the synthesizing of its databases and the “original” text it produces nothing more than “cut and paste” and “pastiche.” The algorithm used by the program has been likened to auto-completion, as well.

However, practical use cases are increasingly emerging, which blur the lines between technological novelty and professional utility. Whether writing working programming code or spitting out a rough draft of an essay, ChatGPT does have a formidable array of competencies. Even if just how competent it is remains to be seen. All this means that as researchers look for efficiencies in their work, ChatGPT and other AI tools will become increasingly appealing as they mature.

Pseudo-science and reproducibility

The Big Idea reached out to experts across the country to determine what might be the most pressing problems and what might be potential successes for research now that ChatGPT is readily accessible.

Holzschuh, stated that there are potential uses, but also potential misuses of ChatGPT in research: “AI’s usefulness in compiling research proposals or manuscripts is currently limited by the strength of its ability to differentiate true science from pseudo-science. From where does the bot pull its conclusions – peer-reviewed journals or internet ‘science’ with no basis in reproducibility?” It’s “likely a combination of both,” she says. Without clear attribution, ChatGPT is problematic as an information source.

Camille Nebeker is the Director of Research Ethics at University of California, San Diego, and a professor who specializes in human research ethics applied to emerging technologies. Nebeker agrees that because there is no way of citing the original sources that the chatbot is trained on, researchers need to be cautious about accepting the results it produces. That said, ChatGPT could help to avoid self-plagiarism, which could be a benefit to researchers. “With any use of technologies in research, whether they be chatbots or social media platforms or wearable sensors, researchers need to be aware of both the benefits and risks.”

Nebeker’s research team at UC San Diego is conducting research to examine the ethical, legal and social implications of digital health research, including studies that are using machine learning and artificial intelligence to advance human health and wellbeing.

Co-authorship

The conventional wisdom in academia is “when in doubt, cite your source.” ChatGPT even provides some language authors can use when acknowledging their use of the tool in their work: “The author generated this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.” A short catchall statement in your paper will likely not pass muster.

Even when being as transparent as possible about how AI might be used in the course of research or in development of a manuscript, the question of authorship is still fraught. Holden Thorp, editor-in-chief of the Science, writes in Nature, that “we would not allow AI to be listed as an author on a paper we published, and use of AI-generated text without proper citation could be considered plagiarism.” Thorp went on to say that a co-author of an experiment must both consent to being a co-author and take responsibility for a study. “It’s really that second part on which the idea of giving an AI tool co-authorship really hits a roadblock,” Thorp said.

Informed consent

On NBC News, Camille Nebeker stated that she was concerned there was no informed consent given by the participants of a study that evaluated the use of a ChatGPT to support responses given to people using Koko, a mental health wellness program. ChatGPT wrote responses either in whole or in part to the participants seeking advice. “Informed consent is incredibly important for traditional research,” she said. If the company is not receiving federal money for the research, there isn’t requirement to obtain informed consent. “[Consent] is a cornerstone of ethical practices, but when you don’t have the requirement to do that, people could be involved in research without their consent, and that may compromise public trust in research.”

Nebeker went on to say that study information that is conveyed to a prospective research participant via the informed consent process may be improved with ChatGPT. For instance, understanding complex study information could be a barrier to informed consent and make voluntary participation in research more challenging. Research projects involve high-level vocabulary and comprehension, but informed consent is not valid if the participant can’t understand the risks, etc. “There is readability software, but it only rates the grade-level of the narrative, it does not rewrite any text for you,” Nebeker said. She believes that one could input an informed consent communication into ChatGPT and ask for it to be rewritten at a sixth to eighth grade level (which is the range that Institutional Review Boards prefer.)

Can it be used equitably?

Faculty from the Stanford Accelerator for Learning, like Victor Lee, are already strategizing ways for intuitive AI to be used. Says Lee, “We need the use of this technology to be ethical, equitable, and accountable.”

Stanford’s approach will involve scheduling listening sessions and other opportunities to gather expertise directly from educators as to how to strike an effective balance between the use of these innovative technologies and its academic mission.

The Big Idea

Perhaps to sum it up best, Holzschuh concluded her take on the matter with this thought: “I believe we must proceed with significant caution in any but the most basic endeavors related to research proposals and manuscripts at this point until bot filters significantly mature.”

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

Understanding the Fly America Act is important for all researchers planning government-funded travel. Graphic by Miguel Tovar/University of Houston

What Houston researchers should know about the Fly America Act

houston voices

Commercial aviation witnessed a transformative shift following World War II. Initially reserved for military purposes, commercial air travel began to flourish as civilians embraced its convenience. This surge in air travel highlighted the necessity for regulating the industry.

In response, the Federal Aviation Administration, or FAA, emerged from the Federal Aviation Act of 1958, later becoming a component of the Department of Transportation under the Department of Transportation Act in 1967.

The evolution of air travel regulation continued in 1974 with the enactment of the Fly America Act. Designed to safeguard U.S. interests in international air travel funded by the government, this act prioritizes U.S. airline carriers. This initiative serves both to support domestic airlines and promote the U.S. aviation industry on a global stage when passengers travel on federal funds.

What some might not know is this legislation can impact researchers and their organizations.

Importance for researchers

Adhering to the Fly America Act applies not only to federal government employees but also their dependents, grantees, and other travelers funded by federal resources. Even foreign researchers visiting the U.S. under federally funded grants must choose U.S. flag air carriers for their travel.

A U.S. flag air carrier should not be confused with a traditional flag carrier. These are airlines that have historically been government-owned or are otherwise closely tied to the identity of a particular country, like British Airways or Aeroméxico. U.S. flag air carriers encompass a wide range of airlines, including smaller entities like Air Wisconsin Airlines and Avelo, a new carrier based in Houston. You can find a comprehensive list of U.S. flag air carriers here.

Navigating exceptions

While the Fly America Act carries strict guidelines, exceptions do exist. Instances where no U.S. flag air carriers serve the destination or where such carriers would extend the trip by over 24 hours warrant special consideration. In these cases, maintaining meticulous records is essential in order to validate the use of non-U.S. airlines. A list of exceptions can be found here.

Open Skies Agreements introduce another facet to the Fly America Act. These agreements between the U.S. Government and other countries enable travelers, including researchers, to use foreign air carriers for government-funded international travel. Several countries, including those in the European Union, Australia, Switzerland, and Japan, maintain Open Skies Agreements. Flights on British Airways are no longer permitted under an Open Skies Agreement due to the United Kingdom’s exit from the European Union. Proper documentation is essential when claiming a Fly America Act exception, even if covered under an Open Skies Agreement. Detailed travel itineraries, internal agency forms, and evidence of a Fly America exception must be included in travel receipts.

The Big Idea

Compliance with the Fly America Act ensures your travel expenses are reimbursable on government grants. It’s important to remember that cost and convenience are not exceptions to the act. A thorough understanding of Fly America Act’s provisions and exceptions is a must before you book your next flight.

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

Absolutism has no bearing on the scientific process. Graphic by Miguel Tovar/University of Houston

Why absolutism has no place in research, according to University of Houston

Houston voices

Science, like politics, can elicit polarizing opinions. But with an ever-expanding body of knowledge — and the especially dizzying flurry of findings during the pandemic — is it fair to say that views on science are becoming more extreme?

Measuring the polarization

“A standard way of measuring polarization in the U.S. is asking Democrats and Republicans how warmly they feel toward members of their own group and members of their outgroup on a feeling thermometer from 0 to 100,” said Jessica Gottlieb, professor at the UH Hobby School of Public Affairs. “The difference in ingroup-outgroup warmth is then considered a measure of polarization. This has been measured by the American National Elections Studies systematically over the past several decades, and indeed the level of affective polarization has been increasing in the U.S.”

“Absolutism is the culprit.”

In an article in Foreign Affairs entitled, “How Extremism Went Mainstream,” the author notes that “the tools that authorities use to combat extremists become less useful when the line between the fringe and the center starts to blur.”

Science has traditionally been one such tool. However, this extremism — where everything is black and white — in politics, has made its unfortunate way into academia. John Lienhard is a professor at the University of Houston and host of “Engines of Our Ingenuity,” a national radio program which has been telling stories of how creativity has shaped our culture since 1988. According to Lienhard, extremism — as seen within the scientific enterprise — goes by a different name.

“Absolutism is the culprit – the need on the part of so many of us to know The Right Answer. The absolutists in the world will glom onto whatever vehicle suits them – religion, politics, education, and ultimately, science itself,” said Lienhard. In other words, good scientists amend and revise, while “the absolutist finds the honest practice of science hateful,” he says, “because science is a way of life where everything lies open to question.”

A series of approximations

In an article entitled, “If You Say Science Is Right You’re Wrong,” professor Naomi Oreskes introduces this quote by Nobel Prize–winning physicist Steven Weinberg:

“Even though a scientific theory is in a sense a social consensus, it is unlike any other sort of consensus in that it is culture-free and permanent.”

Well, no. Even a modest familiarity with the history of science offers many examples of matters that scientists thought they had resolved, only to discover that they needed to be reconsidered.

Some familiar examples are Earth as the center of the universe, the absolute nature of time and space, the stability of continents and the cause of infectious disease.

Absolutism in science is dangerous. Good scientists know how important it is to ask probing questions. In his book entitled, Science versus Absolutism: Science Approaches Truth by a Series of Approximations, the chemist T. Swann Harding asks the question: “What are scientific laws?” He goes on to answer:

“Most people appear to regard them as singularly exact and unalterable things … to violate them brings swift retribution. They are unchanging and eternal in character. Yet the so-called laws of science are really rules pieced together by man on a basis of much observation and experiment.”

In the past, so much of science was just plain wrong – until another researcher came around and amended the original belief (think Galileo). How are our modern times any different? There are still many situations where scientific thought has needed to be amended. Even as recently as the COVID crisis, researchers were revising their thoughts about the spread and contagiousness of the disease.

Allowing for dissent

In a Scientific American blog, Matt Nolan writes that “Dissent in Science Is Essential–up to a Point.” In it, he said, “It is the public who pay the price when marginalized science informs policy. History reminds us this is unsafe territory.” However, Lienhard adds that Einstein set limits on the validity of Newton’s laws just as nuclear fission provided an amendment to the conservation of energy law. There is always a new question to formalize where experimentation is being conducted.

Referred to as the “file drawer effect,” another predicament occurs when a researcher does not get the answer they were expecting, and therefore, decides to not publish the negative findings. Every answer is meaningful. And sometimes a negative answer — or no answer — is an answer.

Dissent, and perhaps a certain measure of disappointment, is a critical part of scientific inquiry.

The Big Idea

Science can be thought of as the best we know to the degree we understand a given problem at a given place and time. Absolutism has no bearing on the scientific process and in some cases actively obscures and colors that understanding. And that’s not black and white at all; that’s about as gray as it gets.

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

If there are fewer grant proposals, does that mean innovation has slowed? UH gets to the bottom of the question. Graphic by Miguel Tovar/University of Houston

University of Houston: What a drop in NSF proposals means for the country's rate of innovation

houston voices

A 17 percent drop in proposals over the past decade to the National Science Foundation may be a mixed blessing.

A consistently rising budget – and this is in billions of dollars – is the preferred method of keeping the number of funded proposals ever higher. But a dip in the number of proposals submitted in the first place can have a similar effect of increasing the number of funded proposals, since the pool of submissions is much smaller.

In an article for Science Magazine, author Jeffrey Mervis poses the question: Has there been a decline in grant-worthy ideas? In NSF’s biology sector, Mervis notes that “demand has tumbled by 50 percent over the decade and the chances of winning a grant have doubled, from 18 percent in 2011 to 36 percent in 2020.” NSF’s leadership suggests two possible reasons for this phenomenon.

Eliminating fixed deadlines

“Dear Colleague” letters went out to numerous directorates within the NSF notifying PIs that fixed deadlines for small projects ($500,000 and less) would be taken out of the equation. For instance, the Directorate for Computer and Information Science and Engineering’s letter read: “in order to allow principal investigators (PIs) more flexibility and to better facilitate interdisciplinary research across disciplines” deadlines would be eliminated. The letter goes on to state that by eliminating fixed deadlines, PIs will be free to think more creatively and collaboratively – without the added stress of a deadline.

Wouldn’t less stress mean more applications? This doesn’t seem to be the case. In one instance, according to another article in Science, proposals dropped when the program ceased annual deadlines and replaced them with rolling deadlines.

Reducing stress for grant reviewers

That article goes on to say that these changes alleviate the strain on the grant reviewers without lowering standards. James Olds, assistant director of the Directorate for Biological Sciences, anticipated that the NSF program managers would get somewhat of a break, and that the new policy would relieve university administrators who process the applications from being overwhelmed.

Other factors at play

“It is highly unlikely there was one specific reason for the decrease,” said David Schultz, assistant vice president for Sponsored Projects in the Office of Contracts and Grants at the University of Houston, “but rather multiple factors contributing over time. One potential cause is that many major research institutions are diversifying their funding sources away from NSF and into other federal agencies more aligned with their strategic areas of research interest, such as NIH, DOD, and DOE. The NIH has seen an 11 percent increase in proposals over the same period, from 49,592 in 2011 to 55,038 in 2020.”

Tenure

“Another component is the documented decrease in the number of tenured faculty across the nation. Generally tenured faculty are more research-focused, as their ability to obtain externally funded research is a major criterion for promotion and tenure,” said Schultz. “While this may lead to fewer proposals, it does encourage new tenure track faculty to focus more efforts on the higher likelihood of being awarded an NSF grant.”

The Big Idea

Some people work better and more efficiently when presented with a deadline. Could that be the reason fewer proposals are being turned in? In his article, Mervis, deliberates over whether the number of proposals means that the nation is innovating more slowly than before. But how could that be?

The National Science Board, NSF’s presidentially appointed oversight committee, is trying to get to the bottom of the issue so as to mitigate it. Olds stands by the decision to remove deadlines, pointing out that it should be the strength of the proposal not the threat of a deadline which motivates the research project.

Schultz sees a silver lining. “With fewer proposals being submitted to the NSF, the shift creates an opportunity for smaller, emerging universities to increase their proposal submission and success rates.”

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

Every situation is unique and deserves a one-of-the-kind data management plan, not a one-size-fits-all solution. Graphic by Miguel Tovar/University of Houston

Houston research: Why you need a data management plan

Houston voices

Why do you need a data management plan? It mitigates error, increases research integrity and allows your research to be replicated – despite the “replication crisis” that the research enterprise has been wrestling with for some time.

Error

There are many horror stories of researchers losing their data. You can just plain lose your laptop or an external hard drive. Sometimes they are confiscated if you are traveling to another country — and you may not get them back. Some errors are more nuanced. For instance, a COVID-19 repository of contact-traced individuals was missing 16,000 results because Excel can’t exceed 1 million lines per spreadsheet.

Do you think a hard drive is the best repository? Keep in mind that 20 percent of hard drives fail within the first four years. Some researchers merely email their data back and forth and feel like it is “secure” in their inbox.

The human and machine error margins are wide. Continually backing up your results, while good practice, can’t ensure that you won’t lose invaluable research material.

Repositories

According to Reid Boehm, Ph.D., Research Data Management Librarian at the University of Houston Libraries, your best bet is to utilize research data repositories. “The systems and the administrators are focused on file integrity and preservation actions to mitigate loss and they often employ specific metadata fields and documentation with the content,” Boehm says of the repositories. “They usually provide a digital object identifier or other unique ID for a persistent record and access point to these data. It’s just so much less time and worry.”

Integrity

Losing data or being hacked can challenge data integrity. Data breaches do not only compromise research integrity, they can also be extremely expensive! According to Security Intelligence, the global average cost of a data breach in a 2019 study was $3.92 million. That is a 1.5 percent increase from the previous year’s study.

Sample size — how large or small a study was — is another example of how data integrity can affect a study. Retraction Watch removes approximately 1,500 articles annually from prestigious journals for “sloppy science.” One of the main reasons the papers end up being retracted is that the sample size was too small to be a representative group.

Replication

Another metric for measuring data integrity is whether or not the experiment can be replicated. The ability to recreate an experiment is paramount to the scientific enterprise. In a Nature article entitled, 1,500 scientists lift the lid on reproducibility, “73 percent said that they think that at least half of the papers can be trusted, with physicists and chemists generally showing the most confidence.”

However, according to Kelsey Piper at Vox, “an attempt to replicate studies from top journals Nature and Science found that 13 of the 21 results looked at could be reproduced.”

That's so meta

The archivist Jason Scott said, “Metadata is a love note to the future.” Learning how to keep data about data is a critical part of reproducing an experiment.

“While this will be always be determined by a combination of project specifics and disciplinary considerations, descriptive metadata should include as much information about the process as possible,” said Boehm. Details of workflows, any standard operating procedures and parameters of measurement, clear definitions of variables, code and software specifications and versions, and many other signifiers ensure the data will be of use to colleagues in the future.

In other words, making data accessible, useable and reproducible is of the utmost importance. You make reproducing experiments that much easier if you are doing a good job of capturing metadata in a consistent way.

The Big Idea

A data management plan includes storage, curation, archiving and dissemination of research data. Your university’s digital librarian is an invaluable resource. They can answer other tricky questions as well: such as, who does data belong to? And, when a post-doctoral student in your lab leaves the institution, can s/he take their data with them? Every situation is unique and deserves a one-of-the-kind data management plan, not a one-size-fits-all solution.

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

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Houston lab explores how AI bots can help the elderly

AI for aging

The University of Houston’s Empathetic Lifespan AI & Robotics for Aging (ELARA) Lab is currently conducting research into how AI bots may be able to help the elderly live more social and independent lives through several ongoing initiatives.

The lab officially launched last month as part of the Gerald D. Hines College of Architecture & Design under the leadership of Assistant Professor Chorong Park. Part of the lab’s mission is tackling ongoing problems with aging, such as dealing with disabilities and social isolation. Researchers’ current work is focused on designing a new AI companion bot specifically tailored to the needs of older people.

“We need to take all the needs of older adults seriously,” Park said in a news release. “They won't use the robot if they don't feel at ease or if they feel they are being constantly watched.”

The field testing of new AI bots in this population hopes to overcome several traditional obstacles in technology use among the elderly. A study by Park shows that many older people have a fear of overt surveillance when using advanced AI. There is also ageism to consider. Most new technologies are designed with younger and employed buyers in mind, not retirees who may need help remembering daily tasks or accessing important information.

“The more older adults are excluded from technology development, the worse those technology gaps will become,” Park said. “AI and the majority of technologies are created for younger people, so my research method integrates older adults directly into the design process.”

ELARA recently collaborated with the Mamie George Community Center in Richmond, Texas, to track seniors’ response to desktop AI bots like Emo and Cupboo. Researchers also had participants use air-dry modeling clay to create their ideal robotic companion.

While the eventual AI bot may be able to help the elderly feel less isolated and more supported, there are concerns to consider. A study published in the Asian Journal of Psychology charted the development of delusional thinking in a 72-year-old woman who became convinced the empathic-response bot was in love with her. The rise of “AI psychosis” has the potential to exacerbate mental health problems, particularly in socially isolated people, which a quarter of Americans over the age of 65 are.

ELARA’s research is focused on creating “pet-like” AI models with enhanced trust cues. If it can overcome the dangers of socially isolated people relying on AI for companionship, it could be a big step forward for independent aging.

SpaceX IPO set to be biggest ever and could make Elon Musk a trillionaire

IPO News

SpaceX says it plans to raise up to $75 billion when it goes public this month, setting the stage for the largest-ever stock market debut and putting Elon Musk on course to becoming the world's first trillionaire.

The company, formally known as Space Exploration Technologies Corp., said Wednesday it will sell 555.6 million shares at $135 a piece in an initial public offering. The estimated proceeds would easily top the $26 billion raised by oil giant Saudi Aramco in 2019. The offering would also give SpaceX a market value of $1.77 trillion. Only six companies in the S&P 500 are currently worth more, with Nvidia tops at $5.2 trillion.

Besides the size of the offering and the expected proceeds, SpaceX's amended prospectus updates details about how much control of the company Musk will have. As SpaceX's CEO, chief technical officer and chairman, Musk's voting power will come primarily through his ownership of 5.22 billion Class B shares, which give the holder 10 votes for every share held. According to the filing, Musk would have 82.4% of the voting power in the company.

Forbes currently values Musk's net worth at $826 billion and his stake in SpaceX at $542 billion. The estimated value of his SpaceX holdings was based on an overall value for the company of $1.25 trillion. Based on those numbers, a $1.77 trillion valuation for SpaceX would boost Musk's net worth by $223 billion, making him a trillionaire. However, much of Musk's worth is in stock that he has yet to cash in.

Even as it makes a bid for a blockbuster market debut, SpaceX is currently losing billions of dollars a year. The filing shows that the company lost $2.6 billion from operations last year on $18.7 billion in revenue, and the losses kept piling up at the start of this year, too.

Fantastical plans

Time will tell how SpaceX fares on the market. Musk's plans for the company are as fantastical as the money he hopes raise in the sale.

Colorful, even frightening in parts, the IPO document strikes a contrast with the typically dry, technical prose in IPO documents, detailing plans to use proceeds from the sale to help put men on the moon again and perhaps even Mars. In one section, it talks of a need to build "a permanent human colony" on the red planet with "at least one million inhabitants" as existential threats loom that could consign man to "the same fate as the dinosaurs."

Musk has almost equally ambitious plans for his other publicly traded company, Tesla. His goal is to transform the maker of electric vehicles into a producer of robotaxis and humanoid robots. Dan Ives of Wedbush Securities wrote in a research note that he expects Tesla and SpaceX to merge next year.

AI plays a key role

Key to the success of both companies — and any merged entity — is artificial intelligence. In its IPO filing, SpaceX says it sees potential revenue from AI of up to $26.5 trillion. But that depends on another lofty Musk ambition — putting data centers in space, which is not technologically possible at the moment.

Transforming his space company into a primarily AI-focused company will be a challenge for Musk, who started xAI in 2023 with 11 other co-founders who have all since left. Some were recruited away by rivals.

Its main AI product, the chatbot Grok, is "less impressive than anything that we see from any other major player in the space, whether that's OpenAI, or Anthropic, or (Google's) Gemini," said IDC analyst Arnal Dayaratna.

Dayaratna said that doesn't mean SpaceX doesn't have potential as a major AI player, thanks in part to its computing partnership with Anthropic and Musk's recent deal that gave SpaceX the rights to buy AI coding tool Cursor for $60 billion later this year. Folding in Cursor's capabilities would give SpaceX access to the coveted business customers now using Anthropic's Claude or OpenAI's ChatGPT.

SpaceX plans to use the net proceeds from the IPO to fund the expansion of infrastructure for its AI and rocket businesses, and to beef up the constellation of satellites that power Starlink Mobile, among other investments.

The company plans to list on the Nasdaq under the symbol "SPCX" and could begin trading as soon as the end of next week.

And SpaceX isn't the only colossal market debut investors are now bracing for. Earlier this week, Anthropic submitted a confidential filing with the U.S. Securities and Exchange Commission to officially start its own IPO clock.

OpenAI has not yet reported filing the initial SEC paperwork, but an IPO from the ChatGPT maker is widely expected.

"This listing represents the first major test for public markets after years of muted IPO activity with SpaceX paving the way for AI giants Anthropic and OpenAI to follow soon after," Ives wrote.

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Associated Press Technology Writer Matt O'Brien contributed.

New UH survey reveals concerns over AI data center growth in Houston

data findings

A new report out of the University of Houston shows that area residents remain wary of the long-term effects of operating data centers.

The recent survey from the University of Houston’s latest SPACE City Panel, conducted by the Center for Public Policy at the Hobby School of Public Affairs, shows that while 85 percent of Houston-area residents use AI, nearly 63 percent oppose the construction of AI data centers within 1 mile of their homes.

Respondents’ concerns centered around data centers’ high energy demand and the area’s power grid reliability. According to the survey, 32 percent of residents who oppose local data center projects would be more likely to support the centers if they relied on renewable energy over fossil fuels.

“Respondents understand that AI can bring economic and educational benefits, but they are also concerned about the physical infrastructure needed to fuel AI, especially data centers,” Soran Mohtadi, post-doctoral fellow at the Hobby School and a researcher on the report, said in a news release. “This physical infrastructure demands more electricity and water, leading to environmental impacts.”

Experts estimate that 6.5 gigawatts of data center capacity will be added to the Texas grid by 2030. And Houston’s data center capacity is predicted to more than double by 2028.

The Electric Reliability Council of Texas also projects electricity demand could reach 218 gigawatts by 2031, which would be more than double the record peak set in August 2023. Data centers are expected to account for 86 gigawatts of that new demand.

Survey respondents also said they are concerned about the state's future water supply, given the large amounts of water that data centers need to stay cool.

In terms of who’s responsible for that issue, 57.6 percent of respondents said they put the onus on Texas lawmakers, while 31.5 percent say tech companies should be responsible.

Additionally, more than 75 percent of respondents believed that data center developers and technology companies—not residents—should bear the cost of infrastructure upgrades to support data centers.

“Every decision legislators make has implications on residents’ everyday lives and local infrastructure now and in the future,” Maria P. Perez Arguelles, lead researcher on the report and research assistant professor at the Hobby School, added in the news release. “This issue is going to become more important in years to come, so this is just the beginning.”

Read the full report here.

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