2026-09-03 02:00:03
In the 1960s NASA began developing a system of reusable space shuttles to make its work more efficient and to reduce costs. The shuttles could launch like rockets, maneuver in Earth’s orbit, and land like airplanes. They also could carry large satellites to and from orbit.
Like other types of transportation, machinery eventually breaks down, and parts need to be replaced or fixed. And the cargo being carried to and from Earth has to be moved to its final destination. To complete such tasks, Spar Aerospace (now part of MDA Space) of Brampton, Ont., Canada, and the National Research Council in Ottawa developed a robotic arm, the Shuttle Remote Manipulator System. The project was a joint venture between the U.S. and Canadian governments.
Known as Canadarms, the robotic tools attached to shuttles’ exteriors. They allowed astronauts to handle and transfer tools, satellites, and other payloads. Inspections of the shuttle and repairs could be completed using the robots.
The system was first deployed in 1981 aboard Columbia’s second flight. Canadarm was used for 30 years on five shuttles and on the International Space Station.
The robotic arm was dedicated on 19 June as the 300th IEEE Milestone. The ceremony was held at MDA Space headquarters. The IEEE Toronto Section sponsored the nomination.
“It is appropriate that the 300th Milestone is the Canadarm,” says Michael Geselowitz, senior director of the IEEE History and Heritage group. “The technology spans aerospace, robotics, and computing fields of interest. It involves international cooperation between the United States and Canada, and it shows how IEEE and its members are at the cutting edge of many frontiers of science and technology.”
Seeking to collaborate with other countries on the reusable spacecraft, NASA invited Canada to participate in 1969. It took some time for the country’s officials to determine what technology it could contribute. They learned of a robot that loaded and replaced spent fuel bundles in Canada’s deuterium uranium nuclear reactors, according to the Milestone webpage. That robot, developed by DSMA-Atcon (also now part of MDA Space), inspired what would become the Canadarm.
A proposal was submitted in 1974 to design and build the Shuttle Remote Manipulator System. The robotic arm would unload the contents of the space shuttle’s payload bay. NASA approved the project, and development began in 1975.
Canada had no space agency at the time, so the country’s National Research Council coordinated the organizations that collaborated on the project. Spar Aerospace led the subcontractor team, which included DMSA-Atcon, CAE, and the Canadian subsidiary of RCA Corp. Engineers from the University of Toronto’s Institute for Aerospace Studies contributed to the project.
NASA had strict requirements for the robot: The arm had to be lightweight and small enough to fit on the shuttle, as detailed in an article published by the University of Toronto. It also had to move forward and backward, up and down, left and right, and rotate along three perpendicular axes (known as six degrees of freedom).
To achieve all that, engineer Peter Carlisle Hughes designed the robot with two shoulder joints, one elbow, and three rotating wrists.
“Each joint had six degrees of freedom, and the arm had six links so that it could grab anything from any angle and move it anywhere,” Hughes said in the article. The IEEE life member worked at the Institute for Aerospace Studies.
“This milestone is a reminder of the privilege we all have at MDA Space—as engineers, designers, builders, operators—to build technology that shapes history.” —Holly Johnson, MDA Space vice president
The arm was 50 meters long and weighed 400 kilograms. It was made of materials that could withstand outer space’s harsh environment: titanium, stainless steel, and graphite epoxy. The arm was so lightweight that it couldn’t support itself under Earth’s gravity, so it lay on air bearings on the lab floor at Spar’s Brampton headquarters.
CAE engineers, including IEEE Life Member David A. Weston, designed the display and control panel as well as the hand controllers astronauts would use to monitor and operate the robot.
Because the robotic arm was meant to work in zero gravity, a room that simulated a weightless environment was built to test it. A computer-based simulation facility was constructed in Spar’s headquarters to evaluate its controllability using two simulation models, according to the University of Toronto. RIGID, an early computer simulation model, tested every part of the arm except for its flexible properties. ASAD, which stood for “all singing, all dancing,” examined the arm’s movements, ensuring the joints operated correctly. Both were created by Hughes and Spar engineer Andrew A. Goldenberg, who is now a professor emeritus at the University of Toronto.
The facility was also used to train astronauts on how to use Canadarm.
It took five years for the first Canadarm to be completed. In February 1981, it was presented to NASA at the Kennedy Space Center in Cape Canaveral, Fla., and deployed that November.
Astronaut Stephen Robinson is anchored to a foot restraint on the extended Canadarm2 attached to the International Space Station during an extravehicular activity he conducted in 2005.NASA
The Canadarm was attached to the outside of the shuttle. Astronauts were able to monitor the arm’s movements through a live video feed provided by cameras installed on the wrist and elbow joints, according to the Milestone webpage. Using a hand controller and monitors located in the shuttle’s flight deck, astronauts handled and transferred tools, satellites, and other payloads weighing up 266,000 kilograms using minimal electricity.
NASA ordered four more systems. In 2001, Canadarm2 was attached to the International Space Station and used to help build the orbiting laboratory. It is a permanent part of the station, still completing maintenance tasks and moving supplies.
During the course of the 30-year shuttle program, the arms performed successfully and achieved the flight’s mission.
The original Canadarm took its final flight in July 2011 aboard the Atlantis shuttle.
The IEEE Milestone dedication ceremony was held at MDA Space’s headquarters in Toronto, where the division that developed the Canadarm was located. The event brought together IEEE leaders and many of the engineers who helped develop the robotic system. Jill Gostin, the 2026 IEEE president‑elect, gave the opening remarks at the ceremony. She emphasized that the Milestone was not only celebrating the technology but also “the engineers, builders, programmers, and visionaries who believed technology could expand human possibility and who dared to push the boundaries of what humanity could achieve beyond Earth.”
To commemorate the achievement, Holly Johnson, vice president of MDA Robotics and Space Operations, and IEEE Life Senior Member David Michelson, chair of the IEEE Communications Society’s Communications History Committee, unveiled a bronze plaque that honored the technology. Michelson was the Milestone’s proposer.
“This milestone is a reminder of the privilege we all have at MDA Space—as engineers, designers, builders, operators—to build technology that shapes history,” Johnson said. “That same pioneering spirit that drove our team in those early days of space exploration now propels us into a new era as we work to build the infrastructure for the moon and beyond.”
The plaque, which was placed at MDA Space headquarters, reads:
In 1981 NASA first deployed a Shuttle Remote Manipulator System aboard the Space Shuttle. Developed by Spar Aerospace (now MDA Space) and the National Research Council of Canada, the Canadarm allowed astronauts to safely and reliably manipulate and transfer heavy payloads outside of the Shuttle, and to conduct inspections and repairs. This robotic system played a key role in the Shuttle and International Space Station programs, and revolutionized human spaceflight.
Reviewed by the IEEE History Committee and approved by the IEEE Board of Directors, IEEE Milestones recognize outstanding technical developments around the world that are at least 25 years old. The Milestone program is administered by the IEEE History and Heritage group.
To learn more about historical figures in engineering, IEEE Milestones, and IEEE History Center programs and events, check out The Institute’s IEEE Tech History collection. IEEE Spectrum also covers aspects of tech history.
2026-09-02 21:00:04
A little over a decade ago, I led the controls design for a first-of-its-kind full digital-control system for a U.S. nuclear plant. It was, on paper, a beautiful machine—engineered to run itself the way a modern airliner does, with operators watching over a system that rarely needed them. And we made a decision that, to an efficiency-minded observer, looked backward: We deliberately left manual steps inside sequences the system could execute on its own.
We were solving a specific problem. An operator who only ever supervises automation slowly stops being an operator. The hands go cold. The mental model of what the plant is actually doing gets fuzzy. Then comes the day the automation hands control back. It’s always the worst day, because automation only quits when it’s confused or in trouble. But by then, you have a person in the chair who hasn’t truly operated the thing in years. The manual steps were there to keep the human current. It was inefficient by design, on purpose.
That plant, as it happened, was never built. It was shelved amid the politics and economics that surround nuclear power in this country, for reasons that had nothing to do with the engineering. But the design instinct outlived the project, and I’ve come to believe it’s the most useful idea I can offer to the argument now consuming every boardroom: What happens to human expertise when AI does the work that used to build it?
The data has gotten hard to wave away. A Harvard University working paper covering some 65 million workers at more than 280,000 U.S. firms found that after companies adopted generative AI, junior employment fell roughly 9 percent within six quarters relative to nonadopters, while senior employment kept right on growing. A Stanford analysis of ADP payroll records points the same way: The youngest workers in the most AI-exposed occupations lost ground after late 2022 while their more-experienced colleagues held theirs. The Stanford researchers found that the losses concentrate where AI automates the work; where it merely augments, junior employment holds steady or rises.
The causal story is still contested, and honesty requires saying so. Researchers at the New York Fed attribute much of the rise in young-graduate unemployment not to AI but to remote work, arguing that firms are reluctant to hire inexperienced people whom they cannot train and mentor at a distance. But notice what the explanations share. Whether a model is absorbing the formative work or distance is severing the mentorship around it, both describe the same broken mechanism: the apprenticeship channel through which expertise passes from senior to junior. Either way, “entry-level” has quietly come to mean “three years of experience required.”
Strip away the noise and you’re left with one deceptively simple problem: You cannot become a senior engineer without first being a junior one. Expertise is not downloaded. It is earned through failed builds, dead-end debugging sessions, and the “why on earth did that work” moments that a capable AI will now happily spare the newcomer. Spare them enough of those and you produce a cohort that can supervise a model on paper but never developed the gut sense to know when the model is confidently, catastrophically wrong.
Most of the commentary stops at the diagnosis, or reaches for policy solutions that treat the loss of junior jobs as an economic problem. Yet it’s also an engineering problem, and safety-critical fields have already spent decades learning how to solve it.
My own career started at the sharp end of automation. My first job out of school was verifying and validating the software in the digital jet-engine controller that decides, faster than any pilot could, how a fighter plane’s engine responds. Even then, in the late 1980s, the central tension was visible: The machine outperforms the human in routine cases, but the human is all that stands between the aircraft and disaster in the cases the machine didn’t anticipate. This tension is known as the automation paradox, in which increasingly capable automation gives human operators less practice, while leaving them only the most difficult situations.
Aviation learned, repeatedly and expensively, what happens when human skills atrophy inside that gap. The canonical example is Air France flight 447, which fell into the Atlantic in 2009. The proximate cause was mundane. Iced-over airspeed sensors fed the autopilot bad data, and it did what it is designed to do: It disconnected and handed control of the airplane back to the crew. What followed was not a hardware failure. It was a competence failure. A recoverable situation became an unrecoverable one because the pilots, conditioned by thousands of hours of watching the automation fly, could not read a high-altitude aerodynamic stall and hand-fly their way out of it. The airplane was working. The training the automation had quietly eroded was not.
The industry’s response is instructive, and it’s the same move we made in that nuclear control room. It did not rip out the autopilot. It built deliberate manual practice back in. In 2017 the FAA issued Safety Alert for Operators 17007, “Manual Flight Operations Proficiency,” declaring that “manual flight is the foundation upon which other technical flying skills are built.” The alert formally recognized skill decay as a hazard in its own right. Some airlines amended their procedures to encourage hand-flying both the initial climb and initial descent in benign conditions, knowingly trading a sliver of fuel efficiency to keep the crew’s raw flying skills alive. That trade is the whole point. A perfectly optimized system that produces incompetent operators is not optimized at all. It has simply moved its failure mode somewhere the spreadsheet can’t see it.
Put the aviation lesson and the nuclear instinct side by side and they point to one design pattern we now need in AI-augmented work: the deliberate “manual gate.”
A manual gate is a point in a workflow where a human takes the controls, not because it is the fastest way to get the task done, and not only as a safety interlock, but specifically to exercise and preserve a skill that would otherwise decay. The distinguishing feature is that it is chosen. You decide, as a matter of design, which competencies your organization must keep alive in human beings because those are the ones you will need on the bad day. Then you engineer the friction required to keep them warm.
Picture how this might work on a software team that leans on AI for most of its code. The team places a manual gate around the skill it can least afford to lose: debugging. When a defect surfaces in a critical module, the assigned engineer—deliberately, often a junior one—must first reproduce the failure, trace it to root cause, and write an automated test that captures the bug, all with the AI assistant switched off. Only after the engineer commits to a diagnosis does the model come back on, to propose the fix, generate alternatives, and sweep the code base for similar bugs. The engineer then compares their diagnosis against the model’s. When the two disagree, that’s the design working, surfacing the disagreement before the bad day instead of during it.
This approach reframes the junior engineer entirely. The instinct today is to let AI do the entry-level work because it is faster and cheaper. But some of that work is not overhead to be eliminated. It is the training apparatus of your future senior staff, and you should protect it the way you’d protect any other piece of critical infrastructure. It may not be efficient this quarter, but dismantling it quietly mortgages your capability a decade out.
None of this is free, and pretending otherwise would insult the people who have to sign the budgets. A deliberate manual gate is, by construction, less efficient in the near term than full automation. Keeping juniors doing formative work and running the manual sequences costs something now to protect something later.
That’s a hard sell in a market that judges most leaders on quarterly results. A hired executive who carries “unnecessary” humans that AI could replace will hear about it from the board long before the payoff arrives. The math only works for someone insulated from that pressure: a founder with control, a private company, an institution with a genuinely long horizon, or a regulator willing to require workers to demonstrate their skills regularly, as pilots must. Which means the organizations most likely to preserve their own expertise are the ones structurally able to spend short-term margin on long-term capability; everyone else will need that outside push.
So here is the argument, in one line: Deliberate inefficiency is not waste. In safety-critical engineering we have always known it as insurance, and we buy it on purpose. As AI takes over the work where expertise is forged, the smart move is not to resist the automation. It is to keep our hands on the controls by design—so that when the automation fails, as it always eventually does, there is still someone in the chair who knows how to fly.
2026-09-02 02:00:04
Across IEEE, our strength lies not only in the excellence of our individual communities but also in our ability to bring them together around shared problems that demand interdisciplinary solutions. Our mission as a public charity—to advance technology for the benefit of humanity—is becoming an increasingly powerful differentiator. It is more than a statement of principle; it is a strategic advantage. When engineers and technologists serve with purpose and lead with heart, they strengthen the future of our profession and demonstrate why IEEE is uniquely positioned to lead at the intersection of technology and societal impact.
IEEE Humanitarian Technologies is a consortium of programs and initiatives—supported by a global network of volunteers and technical professionals—working together to apply technology to solve the world’s most pressing problems. These include Empower a Billion Lives, EPICSinIEEE, MOVE, IEEE REACH, IEEE SIGHT, IEEE Smart Village, and IEEE Tech4Good. These programs embody our mission in action. They are not simply charitable activities; they are strategic assets that help IEEE lead globally, innovate boldly, and remain essential to technical professionals at every stage of their careers. While deeply human in purpose, humanitarian technologies are fundamentally engineering challenges, demanding the full depth of engineering rigor and realized through disciplined, deeply technical work.
IEEE Humanitarian Technologies sits at the intersection of engineering excellence, societal need, and global opportunity. Its programs allow our members to show the world that engineering and technology are forces for good, capable of addressing urgent challenges with precision, creativity, and compassion. These programs do more than inspire; they strengthen the technical ecosystem that underpins IEEE’s leadership.
Bringing together experts from power and energy, communications, computing, robotics, biomedical engineering, and many other domains to address real-world problems, these interdisciplinary intersections are where breakthroughs emerge. When engineers and technologists collaborate with the right humanitarian frameworks across sectors and cultures, they illuminate new constraints, design pathways, and opportunities that traditional project environments rarely reveal. This is how humanitarian technologies help shape the future of engineering itself.
These efforts also illustrate a broader opportunity for IEEE. By identifying critical challenges that can be addressed only through collaboration across disciplines, IEEE can mobilize the power of its global community toward solving problems around the world. In doing so, we strengthen both our impact on society and the value we provide to members, partners, and future generations.
These programs also build the leadership capacity our profession needs. Engineers working in humanitarian contexts learn to navigate ambiguity, engage diverse stakeholders, manage constraints, and design for environments where failure has real human consequences. They develop systems thinking, ethical reasoning, and cross‑cultural fluency—competencies increasingly essential in a world where technology and society are deeply intertwined. They also learn to transition from R&D to implementation by engineering the support, manufacturing, and delivery systems that make solutions viable in specific countries, all while balancing competing requirements. In doing so, humanitarian programs equip professionals with the capabilities that define modern technical practice.
Humanitarian technologies also help prepare the future technical workforce. Students and young professionals increasingly seek meaningful, high‑impact work. By engaging in purpose‑driven projects, they can discover their own capacity to grow, strengthen their technical skills, and become the leaders and problem‑solvers who will guide our profession forward.
Our members feel this deeply. Engagement research shows that members increasingly cited “giving back to my profession and the world community” as a reason for joining the organization and renewing their membership. Those with higher membership grades identify “participation in humanitarian technology efforts” as one of the most satisfying experiences IEEE offers. These are not just data points; they are also signals of what our community values and what it expects IEEE to champion.
Younger generations amplify this even more. Millennials view IEEE through a global lens, prioritizing “humanitarian impact” and “large-scale collaboration.” One millennial member shared that teaching robotics to children in under-resourced communities transformed them into a deeply engaged member. Gen Z members emphasize inclusivity, environmental responsibility, and purpose-driven engineering, recommending that IEEE offer humanitarian-based challenges and competitions to increase engagement.
These findings reveal something powerful: Humanitarian programs are not only meaningful; they also are magnetic. They attract younger engineers, keep them engaged, and help them build a professional identity rooted in purpose and impact. They also create loyalty and develop the leadership pipeline IEEE needs for the decades ahead.
These programs also strengthen our brand. Members across segments describe IEEE as an organization that works hard to make real changes in the world. That perception is not just flattering, it is strategic. It positions IEEE as a global leader in responsible innovation that can be trusted to guide technology for the public good, catalyzing innovation that benefits society at scale.
As we look ahead, IEEE has an opportunity to become the world’s leading convening force for developing interdisciplinary technology solutions to solve humanity’s most important challenges. Our future relevance will be defined not only by the technologies we advance but also by the problems we choose to help solve.
Read more powerful stories about how technology is improving lives across global initiatives in the 2025 IEEE Social Impact Report at ieee.org/advancing-technology/building-better-world/social-impact-report.
—MARY ELLEN RANDALL
IEEE president and CEO
Please share your thoughts with me: [email protected].
2026-09-01 02:00:01
For many high school students, summer vacation is a time to unplug. For Ruchira Shree, a rising sophomore at West Windsor–Plainsboro High School South, in New Jersey, the break allows her to ramp up her extracurricular pursuits.
Much of her time is spent assisting with IEEE Princeton Central Jersey Section activities. She got involved with the PCJS because of her mother, IEEE Senior Member Shubha Bommalingaiahnapallya, who is the section’s vice chair. Bommalingaiahnapallya is a principal engineer at Intel.
“I started going to the IEEE meetings when I was little,” Shree says. “I used to go with my mom and just sit in the back of the room.”
This summer she says she’s focusing on improving her mathematics skills by attending the Program in Algorithmic and Combinatorial Thinking summer course on math and computer science. She wants to qualify for the American Invitational Mathematics Examination, an event for the top American Mathematics Competitions scorers. She earned a place on the AMC 8 honor roll—a recognition awarded to the top 1 percent of participants in the national competition—when she was in seventh grade.
Shree’s IEEE involvement and her advanced math skills caught the attention of an internship recruiter for the Alliance for Indigenous Math Circles, a group dedicated to expanding STEM opportunities for Native American students. The AIMC organizes and sponsors weeklong overnight camps. Interns assist with activities and teach some of the sessions. Shree met a recruiter at one of the section’s events, and she interned at one of the camps last year.
Shree’s involvement with the PCJS evolved naturally as she got older, she says, along the way preparing name badges and tackling similar assignments. She met Francis O’Connell, an IEEE life senior member and founder of FXO, in Plainsboro, N.J. O’Connell is the treasurer of the IEEE Integrated STEM in Education Conference (ISEC).
He has been a mentor to Shree for the past two years, he says.
At last year’s ISEC, she assisted at the registration desk and met Harini Frederickson, an AIMC intern recruiter for New Jersey.
Frederickson invited Shree, along with nine other students, to volunteer at an upcoming camp being held in Santa Fe, N.M.
“Ruchira is a real go-getter,” Frederickson says. “When she has an idea, she follows through and doesn’t get easily discouraged.”
The AIMC was created to address an important need, says math teacher Donna Fernandez, codirector of the organization. U.S. Indigenous students have the lowest rate of pursuing STEM studies across all demographics, according to the U.S. National Science Foundation. Systemic barriers such as a lack of role models in STEM fields, socioeconomic inequities, and Eurocentric teaching frameworks are some of the reasons, Rechel Shrisunder and Dwight Figueiredo wrote in a chapter of Minorities: New Challenges and Horizons, a book edited by John R. Hermann.
Indigenous people have a long tradition of mathematics, Fernandez says. She cites the Navajo code talkers from World War II as examples. The Navajo, along with 14 other Indigenous tribes, used their native languages to code and transmit critical messages for the U.S. military during the war.
There was a student at camp whose grandfather was a code talker, Shree says.
Navajo people also use math to build hogans: conical dwellings that require precise calculations to construct. Native communities have used math when building the structures for centuries, Fernandez says.
Fernandez believes typical classroom math curricula overlook the importance of mathematics in Indigenous cultures. Combining STEM activities with cultural elements helps Indigenous students better understand their ancestors’ role as mathematicians, she says.
That, in turn, helps the students see themselves in those careers, she adds.
The AIMC was built upon a program already in place: the Navajo Nation Math Circles, founded in 2012 by three university professors. Their goal was to provide the Navajo Nation’s students with tools to overcome barriers to STEM education.
To expand the math circle program, the AIMC was added to reach Indigenous students in the Four Corners area of Arizona, Colorado, New Mexico, and Utah.
Since 2017, the organization has run two camps every year at the Navajo Preparatory School in Farmington, N.M. In 2025 one camp was moved to the Santa Fe Indian School.
During each weeklong event, students and interns work in math circles. It’s a cooperative way to solve problems creatively, organizers say. Students collaborate on STEM-focused projects and learn from Indigenous STEM professionals. Interns also get the opportunity to experience an off-site cultural event.
The camps are free for students, thanks to sponsorships and donations. Teachers and interns cover their own travel expenses. Shree secured a US $1,500 sponsorship grant through the PCJS.
Relationships are an influential part of the week, Fernandez says: “One of the best things we see at the camp is that students return the following year and ask, ‘Is so-and-so intern coming back this year?’ They remember the relationships they developed, especially the cultural exchanges they had.
“Those exchanges go both ways, benefiting the interns too.”
Students spend mornings at camp working in math circles, then gather for a wrangle, during which each team defends its math circle answer and challenges other teams’ solutions. Shree and the other interns are on hand to answer questions and observe the teams as they work through the math circle problems.
“Math problems typically have very binary answers,” she says. “But in math circles, you focus more on talking through your answers to open-ended questions and learning from each other.”
Students spend afternoons working on projects. In one, the students used household items to create a replica of the Batmobile, Shree says. The car was required to be self-propelled without an engine. Balloons were a popular alternative.
Another activity focused on the Indigenous tradition of basket weaving. Students learned the cultural meaning behind traditional designs while understanding how geometry concepts influenced the finished product.
These Native American middle school students work on solving a mathematical pattern-matching game, one of the activities held at the summer camp.Ruchira Shree
“Because there’s a lack of Indigenous STEM role models, many Native American students don’t see themselves in mathematics or science,” Shree says.
To bridge that gap, Fernandez ensures Indigenous role models are part of the camp. Some of the people who spoke with students during Shree’s internship were Jessica Benally, a Ph.D. student in the learning sciences and human development program at the University of California, Berkeley, and engineers from the New Mexico Mathematics, Engineering, and Science Achievement program, which supports underrepresented preuniversity students.
“I believe the students were very inspired,” Shree says, “because they could see how they themselves could pursue STEM careers. They had people to look up to in the field who had come from backgrounds just like theirs.”
The interns’ primary responsibility was leading a two-hour, after-dinner Radio Weaves session. They taught students about a popular communication technology that doesn’t require the Internet or cell towers.
Ham radio, also known as amateur radio, is a communication method that uses designated frequencies. In the United States, anyone can listen to amateur radio transmissions; to legally transmit on the frequencies, though, a user needs a Federal Communications Commission license. The Radio Weaves project is designed to prepare students to pass the FCC technician license exam.
To make that happen, the interns customized Gimkit, a learning game, loading it with radio-specific content that mirrored topics that could appear on the test.
Each intern worked with two or three students to complete the Gimkit materials.
Frederickson, who was on hand for the camp, says the aim was to send students home with something tangible that demonstrated their STEM accomplishments.
Nearly all the students passed the exam on the first try, she says, and she worked with those who didn’t to retake the test.
All the students ultimately received their license, she says.
The interns took an afternoon off to attend a Pueblo Feast Day, a celebration filled with music and dance that culminated in visits with nearby families, with whom they shared dinner.
“The tradition is very generous and community-based,” Shree says. “It represents that every home in the village will welcome any guest to have a meal.”
The feast was the highlight of Shree’s week, she says: “I got to really experience Native American culture firsthand.”
The students inspired her, she says.
“Seeing the joy on their faces when they passed the technician exam or when they got a math problem correct showed me how much joy they find in learning,” she says. “It made me realize that I want to help provide more opportunities for them to learn and challenge themselves.”
“Because there’s a lack of Indigenous STEM role models, many Native American students don’t see themselves in mathematics or science.” —Ruchira Shree
That realization spurred her idea for a new initiative. After she returned home, she founded Rukie Cookie to create “safe, inclusive, and inspiring spaces where youths explore STEAM [and] build curiosity, strategic thinking, and innovation—empowering them to become confident leaders and active contributors to a more just and equitable society,” according to the project’s website.
Baking is one of Shree’s hobbies, and she sees it as a way to fulfill a financial need she observed at camp.
“I noticed that at lunch breaks, they [camp students] used to play chess on the side, but they couldn’t actually participate in tournaments because that requires a U.S. Chess Federation (USCF) membership fee, which they couldn’t afford,” she says. Shree bakes cookies and sells them at PCJS events. Proceeds go toward youth chess classes and USCF memberships for children in underrepresented communities.
She has raised enough money to sponsor six USCF memberships, five of whom are camp attendees, she says.
“I hope that the students I have gotten a membership for will continue growing their passion for chess,” she says, “but also that it will encourage them to challenge themselves with difficult problems.”
Shree planned to attend an AIMC camp this year, she says, but it was canceled due to resourcing issues. She says she intends to return next year with goals of adding a formal chess component to the schedule and continuing to help more students overcome financial hurdles to join the USCF.
She’s also writing a novel about Alzheimer’s disease and identity loss, and she’s conducting independent research on cognitive decline at the New Jersey Institute of Technology. Watching her great-grandmother struggle with the condition sparked her interest in the subject, she says.
She is confident STEM will be part of her future, she says. Math and cognitive science are areas of interest she plans to study, but she’s still undecided about a major. Her interest in Alzheimer’s research and a desire to apply AI to health care will influence her decision, she says.
She adds that she plans to join IEEE once she’s eligible.
2026-08-31 22:00:04
This story was originally published by Tech Policy Press.
The European Union’s push for technological sovereignty faces an uncomfortable contradiction.
As the E.U. rolls out AI factories, gigafactories, and new data centers, it is creating a surge in demand for the advanced semiconductors that underpin artificial intelligence. Yet Europe produces fewer than 10 percent of the world’s chips and remains heavily dependent on U.S. designers and Asian manufacturers for the most advanced processors.
That tension sits at the heart of Chips Act 2.0, the European Commission’s planned overhaul of its flagship semiconductor strategy.
The original Chips Act, adopted in 2023, sought to raise Europe’s share of global semiconductor production to 20 percent by 2030. But the European Court of Auditors has warned that target is unlikely to be met, while the Commission’s own projections put Europe’s market share at about 11.7 percent.
The Commission now wants to correct what officials see as a major weakness in the first law: It focused on expanding supply without doing enough to stimulate demand. To address that gap, Chips Act 2.0 is expected to introduce demand-side measures, including public procurement tools, demand accelerators, and closer coordination between semiconductor producers and industrial users. The Commission’s calculation is straightforward: Stronger domestic demand will encourage companies to invest in designing and manufacturing chips in Europe.
But the strategy carries a paradox. The AI infrastructure that the Commission hopes will anchor a European semiconductor ecosystem will initially rely almost entirely on advanced processors designed by U.S. companies and manufactured in Asia.
“Key positions are held by a small number of firms, mostly outside Europe,” Claire Godfrey, executive director of the Balanced Economy Project, told Tech Policy Press.
The European Commission’s AI Continent action plan includes 19 AI factories, computing facilities that integrate energy sources, specialized chips, and other infrastructure for running AI models and applications, plans for up to five AI gigafactories (since upgraded to seven), and a proposal to at least triple the bloc’s data-center capacity within five to seven years under the Cloud and AI Development Act. That expansion will require a large supply of advanced AI processors.
The Center for European Policy Studies (CEPS) estimates that each planned AI factory site requires up to 25,000 advanced chips, while a gigafactory requires at least 100,000.
Almost all of those processors are expected to come from Nvidia. The company supplies most of the graphics processing units deployed in Europe, while its proprietary CUDA software underpins much of the AI software ecosystem. CEPS warns this could create an “Nvidia dependency trap,” where computing infrastructure is physically located in Europe but remains technologically dependent on a single U.S. supplier.
Recent AI infrastructure projects in Europe illustrate the problem. Mistral has lined up 13,800 Nvidia GPUs for a data center near Paris. Deutsche Telekom’s Munich Industrial AI Cloud is being built with nearly 10,000 Nvidia Blackwell GPUs. And Nscale says its deployment for Microsoft, in Sines, Portugal, will start with more than 12,600 Nvidia Blackwell Ultra GPUs before expanding to more than 66,000 in 2027.
The challenge extends well beyond Nvidia. Even if Europe succeeds in expanding semiconductor manufacturing, the global supply chain limits how much autonomy any single region can achieve.
“Europe depends on both the United States and Asia, but at different stages of the value chain,” Toni Roldán-Monés, economist and assistant professor of public policy at IE University, told Tech Policy Press.
“The United States maintains a dominant position in areas such as chip design, intellectual property, and certain frontier equipment. Meanwhile, the manufacturing of the most advanced semiconductors is highly concentrated in Asia, especially in Taiwan and South Korea, while China plays a fundamental role in various materials, industrial processes, and critical minerals,” said Roldán.
Europe’s reliance on third countries is more evident in some parts of the chip value chain. In fabrication, Taiwan produces around 90 percent of the world’s most advanced chips. In packaging, assembly, and testing, the E.U. holds just 4 percent of the market and remains highly dependent on Asia, according to Laith Altimime, President of SEMI Europe.
“The objective is…to avoid excessive dependence on a single country, company, or technology.” —Toni Roldán-Monés
“No top 20 assembly, test, and packaging company is headquartered in the E.U.,” Godfrey said. “There is also the materials issue. China dominates several inputs used in key parts of the semiconductor and advanced electronics supply chain.”
Europe nevertheless retains important advantages.
The region is home to ASML, the Dutch company that dominates the market for extreme ultraviolet lithography systems, and to Belgium’s Imec, one of the world’s leading semiconductor-research centers. Europe also remains a key supplier of specialist materials and power electronics.
Those strengths, however, “do not translate into autonomy across the semiconductor value chain,” Roldán said.
Few experts believe complete semiconductor self-sufficiency is achievable.
Instead, the goal should be to reduce strategic vulnerabilities rather than eliminate international interdependence. “It is not conceivable that one country can rebuild the supply chain. Global collaboration is key,” SEMI Europe’s Altimime told Tech Policy Press. SEMI forecasts that by 2028 the Europe, Middle East, and Africa region will only manufacture about 68 percent by volume of the non-memory semiconductor chips it demands.
“The challenge is to reduce dependencies that could become geopolitical vulnerabilities,” argues Roldán. “The sensible approach is to strengthen critical parts of the value chain, diversify suppliers, protect sensitive data, and develop domestic capabilities in strategic sectors. That can coexist perfectly well with foreign suppliers: The objective is not to expel them, but to avoid excessive dependence on a single country, company, or technology.”
That distinction is especially relevant for Europe’s sovereignty ambitions. As Godfrey notes, “European firms are building around Nvidia hardware, CUDA, cloud infrastructure, and the software choices that come with them. That leaves Europe with two problems. It relies on Asian manufacturing and materials chokepoints. It is also at risk of trying to address that exposure by tying itself more closely to U.S.-controlled AI and cloud infrastructure. The Chips Act 2.0 needs to deal with both, or it will miss a large part of the problem.”
Roldán said Europe’s greatest vulnerability is dependence on partners willing to use global supply chains for geopolitical leverage. Whether Chips Act 2.0 reduces that risk, experts say, will depend on whether it diversifies suppliers rather than just shifting dependence from Asian manufacturers to U.S. technology companies.
2026-08-31 20:00:01
In a display case on the lower level of the Faraday Museum at the Royal Institution in London, there’s an unassuming stack of gray metal discs and blotting paper. It’s not at all obvious that this humble object is the starting point of today’s multibillion-dollar global battery industry. The object’s invention in 1799 grew out of a disagreement that Alessandro Volta—the Italian physicist for whom the unit of measurement for electrical potential is named—had with his friend Luigi Galvani over a dead frog.
Galvani was a well-respected Italian physician. In the 1770s, he began investigating the use of electricity to stimulate the muscles of dissected frogs. Armed with an electrostatic generator and an early type of capacitor called a Leyden jar, he was able to create a charge, store it, and then zap his animal specimens at will. He was intrigued when the frog legs twitched as if they were still alive. He spent the last three decades of the 18th century studying the phenomenon, and in 1791, he published De viribus electricitatis in motu musculari commentarius (Commentary on the Effect of Electricity on Muscular Motion).
Luigi Galvani spent decades investigating what he believed to be a natural electric force emanating from animals. Universal History Archive/Getty Images
Galvani saw the frog as embodying an “animal electricity,” an innate vital force that activated nerves and muscles, similar to what had been observed in (living) electric eels and torpedo rays. For Galvani, the frog was an electrical machine analogous to a Leyden jar. The brain was the source of the electrical charge; the nerves conducted the electrical fluid; and the muscles stored opposite charges. The illustrations in his 1791 book are fabulous—frog legs spread all over his laboratory table!
Galvani was wrong in thinking that his frogs were electrical machines, but he was right that the muscle contractions were caused by electric signals.SSPL/Getty Images
At first, Volta, chair of physics at the University of Pavia, concurred with his friend. But after beginning his own experiments, he concluded that Galvani was wrong and that the frog generated no electricity at all. He thought of the frog as nothing more than an electroscope, an instrument to indicate the presence of an electrical charge. Volta posited that the source of the charge Galvani observed came from two different metals in contact with the frog. He termed this “metallic electricity.”
Alessandro Volta came to disagree with Galvani’s theory of animal electricity.Apic/Getty Images
To prove his point, Volta created an “artificial electric organ.” He stacked alternating discs of copper and zinc, separated by cardboard, blotting paper, or cloth soaked in brine or acid. When the top and bottom plates were connected, an electric current flowed through the stack. As opposed to a Leyden jar, which is essentially a capacitor that can store an electric charge and release it in a brief powerful discharge, his stack of discs generated its own electricity through a chemical reaction and delivered a sustained low-current output.
Volta didn’t publicly demonstrate or announce his artificial electric organ until after Galvani died in 1798. But when he finally did, in 1799, it immediately began upending science. Just six weeks after Volta wrote to the Royal Society about his invention, the English scientists William Nicholson and Anthony Carlisle used a voltaic pile to run a current through water to separate it into hydrogen and oxygen. They had discovered chemical electrolysis. Humphry Davy later used a large voltaic pile to isolate a number of elements, including potassium, sodium, calcium, strontium, and barium. Early piles petered out after a few hours. Users who stacked up more metal discs to make more powerful piles found the weight of the discs squeezed out the moisture in the paper or cloth.
Invented in 1799, Volta’s “artificial electric organ” (later known as the voltaic pile) was the first battery. Volta presented this one to Michael Faraday in 1814.Royal Institution of Great Britain/Science Source
One of the most enthusiastic users of the voltaic pile was Galvani’s nephew, Giovanni Aldini, who spent much of his career defending his uncle’s ideas. Aldini created spectacles across Europe in which he used voltaic piles to shock the carcasses of livestock and, occasionally, the bodies of recently executed convicts. Vivid descriptions in the popular press, as well as Aldini’s own writings, raised the question of whether electricity could bring the dead back to life. Mary Shelley provided her answer in her 1818 novel, Frankenstein; or, The Modern Prometheus. In an introduction to an 1831 edition, Shelley cites galvanism as one of her inspirations for the monster’s reanimation process.
Scientists and historians share a common trait: They like stories with clear winners and losers. The narrative of competition helps drive a narrative of progress that makes it look like humanity is always moving forward. In the case of Galvani and Volta, Volta is usually depicted as the clear winner in the debate over animal versus metallic electricity. The Encyclopedia Britannica goes as far as to write that “with his announcement of the first electric battery in 1800, victory was assured for Volta.”
But both science and history are more nuanced than that. In fact, Galvani and Volta were both partially right and partially wrong. There was no universal force of animal electricity, but Galvani was correct that electrical signals caused muscle contractions, which he discussed in his anonymous 1794 publication Dell’uso e dell’attività dell’arco conduttore nella contrazione dei muscoli (On the Use and Activity of the Conductive Arch in the Contraction of Muscles). Volta was right to push back on Galvani’s animal electricity theory, but he was wrong that electrophysiological effects require two different types of metal, or any metal at all; the circuit in the voltaic pile was closed by the wet paper or cloth.
It seems a little presumptuous for the Encyclopedia Britannica to declare Volta the winner and Galvani the loser. Volta definitely thought his friend was wrong, but he waited until after Galvani’s death to make his views public. It’s closer to the truth to say they were both genuinely curious to understand the nature of electricity. In the process, they unknowingly helped develop different fields of inquiry: electrophysiology for Galvani and electrochemistry and battery science for Volta.
Such an outcome is actually quite common in scientific disagreements. For example, Isaac Newton’s dispute with Christiaan Huygens over the nature of light—did light consist of particles, or corpuscles, as Newton termed them, or waves, as Huygens contested—breaks down today into quantum optics and classical optics. Similarly, Louis Pasteur’s and Justus von Liebig’s debate over fermentation (microorganisms versus chemical decomposition) led to two complementary fields: microbiology and biochemistry.
Maybe instead of looking for winners and losers, we would be better off expanding our horizons and considering the multiple paths of inquiry and discovery. Writing in 1816, toward the end of his career, Volta graciously acknowledged Galvani’s pioneering work, saying “it contains one of the most beautiful and surprising discoveries and the germ of many others.” What new revelations are waiting to develop out of today’s scientific debates?
Part of a continuing series looking at historical artifacts that embrace the boundless potential of technology.
An abridged version of this article appears in the September 2026 print issue as “The First Battery.”
On 20 March 1800, a year and three months after the death of Luigi Galvani, Alessandro Volta wrote a letter (in French) to Joseph Banks, president of the Royal Society, describing his invention of an artificial electric organ. It was read before the Society on 26 June and published in Philosophical Transactions on the last day of that year as “On the electricity excited by the mere contact of conducting substances of different kinds.”
The Smithsonian Institution Libraries used their rare books in the online exhibit The Body Electric, which has more information on both Galvani and Aldini.
The website of the Whipple Museum in Cambridge, England, has a number of pages devoted to frogs, including a very informative description of the role frogs played in Galvani’s experiments and how those led to Volta’s work.