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About a year ago, an advertisement caught the attention of Ashleigh Ruane, a PhD student in physics at the University of Cambridge. The ad was simple but unusual: Teach AI about physics. Curious, she clicked. She learned that experts across fieldsfrom physics and finance to healthcare and lawwere now being paid to help train AI models to think, reason, and problem-solve like domain specialists. She applied, was accepted, and now logs about 50 hours a week providing data for Mercor, a platform that connects AI labs with domain experts. Ruane is part of a fast-growing cohort of professionals who are shaping how AI models learn. According to Freelancer, thousands of new AI data training and annotation roles have appeared on their marketplace, with most of the growth taking hold in just the past 18 months. These roles range from highly technical expert tasks, like evaluating complex reasoning or diagnosing model errors, to nuanced judgment calls that large models still struggle with. Were entering a really interesting time period, says Freelancer CEO Matt Barrie. AI models need more and more data. Were seeing professionals from every field in every part of the world taking part in this AI data training work. The trend raises bigger questions: If AI models have already been trained on the open internet and vast corporate datasets, why do they still need human experts? What exactly are these experts doing? And how long will this new kind of work be around? AI has read the whole internet’and still needs real experts Theres a common assumption that todays largest AI models already know everything they need to know. After all, theyve been trained on millions of books, articles, papers, and posts. But industry leaders say domain experts are now more important than ever. Models trained on the entire internet can get you to an 80% answer, but in legal or tax, 80% isnt useful, explains Joel Hron, CTO of Thomson Reuters. Our customers demand a high level of accuracy and trust. Leveraging experts ensures accuracy to the highest degree that we can. Ana Price, vice president of supply at Prolific, which provides human data for AI labs, agrees that experts are becoming even more important as AI models move into regulated, high-stakes domains. The demand for human expertise and domain specific feedback from AI models is growing and growing and growing, says Price. As these models have gotten bigger, the errors are becoming harder to spot. Real expertise is needed to judge the substance of what models are producing, and not just the surface level correctness. In other words, the internet alone is not a substitute for structured professional knowledge. The more organizations rely on AI for serious, high-stakes work, the more they need experts to show models how real professionals think. What expert AI trainers actually do Linda Yu spent the last decade as an investor, deploying $4 billion of investments into technology enabled businesses. She started working with Mercor as an expert contributor a year ago, where typical projects involve coaching AI models to think like an investment professional. My role as a domain expert is to evaluate whether the model response is not just technically correct, but whether the complex reasoning behind the response is accurateincluding assumptions the model made, where it may have overreached, where it missed, and what a better answer would be, shares Yu. The work feels less like training an AI model, and more like mentoring a junior analyst. Experts like Yu say the work varies from project to project, and is being applied across industries from law, medicine, engineering, and beyond. Participants are typically paid hourly$85 per hour on averageand may be asked to evaluate a models reasoning on a technical question, rewrite incorrect answers into correct, step-by-step explanations, and compare multiple model outputs and choose which best reflects real-world practice. The output isnt generic content, but high-fidelity reasoning data designed to shape how AI systems operate. AI interviewers interviewing AI trainers The work requires real expertise, which means AI labs need data from experts who are vetted. To assist with the vetting, some platforms rely on AI interviewers to assess the actual expertise of potential AI trainers. Experts jump on a call, and they interview with AI, says Arsham Ghahramani, founder of Ribbon, an AI interviewer with more than 500 customers, including an AI training data provider who is interviewing more than 15,000 experts a month. Youll likely be asked the best interview questions youve ever been asked. AI interviewers assess experts for signals that would indicate red flags around expertise, like irregular response cadence, whether they respond naturally, and of course, whether they have the required expertise for a given domain. It was actually my first interview with not a real person, says Yu. It scanned my resume and came up with really relevant questions. After each answer, the AI interviewer acted like a real person and summarized what I said and asked a question that was a natural extension of our conversation topic. I was fascinated by the technology. AI now evaluates the humans teaching it, a reflection of just how far people have advanced model capabilities. The ‘last mile of information’ still belongs to humans One of the clearest explanations for why expert data remains essential comes from Mark Quinn, senior director of AI operations at Pearl and former head of Waymo engineering operations. He draws a connection between todays AI challenges and autonomous driving. At Waymo, we worked towards the last mile of autonomous mobility. Now, were working towards the last mile of information, Quinn says. Even though AI systems are being developed to close the last mile of information, the reality is that people may still prefer human expert validation if they need an answer on what to do if their dog ate some chocolate. The metaphor resonates across the industry. Even as models get smarter and larger, theres a world full of edge casessituations that require judgment, ethical reasoning, or domain-specific logic that isnt easily captured in general datasets. Some leaders believe the last mile will shrink but never disappear entirely. Hron of Thomson Reuters notes, The base models still have a long way to go to be truly deep. Expert systems and expert knowledge will help models climb to the next level. Price of Prolific adds, Weve only scratched the surface in terms of what AI can do. Humans are a critical piece of the puzzle, especially in niche domains. In other words, the future isnt about replacing experts. Its about scaling the expertise thats essential to making AI models better and safer. A new kind of knowledge work For Ruane, the physics PhD student, expert data work has become a significant source of income. She recently accepted a full-time position, but notes that her new job will only be 38 hours per weekleaving time to continue contributing to AI training projects. What shes experiencing is quickly becoming common: skilled professionals treating AI training work as a supplemental career path, flexible side hustle, or even full-time job. The work plays an increasingly central role in how AI systems operate. As models get more capable, the value of real-world expertise is being redefined, not diminished. Experts arent just using AI. Theyre teaching it how to reason, think, and act like an expert.
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E-Commerce
Sitting on a coffee table in his Chelsea office in New York City and surrounded by framed wedding invitations on the walls, Justin McLeod is worrying about AI. Specifically, the cofounder and CEO of dating app Hinge is concerned that his usersmany of whom have asked him to their weddings over the yearsmight fall in love with it instead of one another. McLeod has spent the greater part of the past 15 years studying the dynamics of human relationships, including what makes one person fall for another, and he sees that chatbots offer exactly what many people crave. Why would I invest in these hard human relationships with people that are not always available or might reject me when I can talk to this thing that is right here and will always say the right thing? he wonders. On this sunny afternoon in late September, chatbots arent yet upending dating apps, but something sure is. Bumble, once the women-first darling, has shed 460,000 paying users since the end of 2024, prompting the return of founder Whitney Wolfe Herd in March. Shes embarked on an aggressive retrenchment campaign that has included laying off 30% of the staff. Tinder, meanwhile, has lost more than 1.5 million paying users since its peak in 2022. Its parent company, Match Group, has also recorded steady revenue declines for the past three years for its business unit that includes former stalwarts like Match.com and OkCupid. Match appointed Spencer Rascoff as a wartime CEO in February 2025; hes slashed head count by 13%. But one app in Match Groups portfolio stands out. Hinge, which has 15 million monthly active users, saw its paying users grow by 17% year over year to 1.87 million in the third quarter of this year. The app took in $550 million in revenue in 2024, and more than $500 million in the first nine months of 2025. Were the fastest-growingand, in fact, the only growingmajor dating app, McLeod says. (Thats not quite true: Grindr, with 1.3 million of what it calls average paying users, is also on the upswing.) Simply put, Hinge is crushing it, Rascoff said on Match Groups Q2 earnings call. Hinges competitors are facing problems of their own making. First was their aggressive pursuit of users, favoring quantity over quality, which has degraded the overall experience of many dating apps. Meanwhile, their lax policing of junk profiles and botsand simultaneous price increases for increasingly important featureshas forced users to pay ever more to find decent matches. People are just tired of endless, expensive swiping that doesnt convert into dates. And now a rising generation is emerging with an entirely different approach to dating than earlier users, putting apps that dont evolve at risk of being left behind. Gen Zs relationships are increasingly mediatedeven definedby screens. They still use dating apps, but theyre skeptical. Gen Z has set a higher bar, Match CFO Steven Bailey told attendees at Morgan Stanleys Technology, Media, and Telecom conference in March. They want [dating apps] to be safe, they want them to be effective, and they want them to drive the outcomes theyre looking for. But Hinge keeps growing because it has stuck to its promise that it succeeds only if users end up deleting it altogether. We want people to meet up and find love in person, McLeod says. That sounds obvious, but in the world of dating apps, it hasnt always been a priority. While other apps favored ease of use (all that endless swiping) over outcomes, McLeod remained relentlessly focused on designing ways to get his users off the app and dating, even if that meant inserting friction into the user experience. A lot of apps grew much faster than us because they were more engaging and exciting, McLeod admits. But he was playing the long game. McLeod is now preparing for the next stage of Hinge. The company has been rolling out a suite of AI-powered features to appeal to users with rustier social skills (ahem, Gen Z). McLeod is also taking his matching algorithm up a notch, extracting even more information from users to personalize and refine Hinges picks for them. To stop people from falling in love with chatbots, hes fighting AI with AIand trying to engineer something incontestably human: a messy, authentic love story. McLeod knows something about the complexities of the heart. He founded Hinge in 2011 while at Harvard Business School to help people find real-world connections. At the time, though, he was recovering from heartbreak. He had dated someone as an undergrad, but they broke up and got back together several times as he battled substance abuse issues. By the time he got out of rehab, she had moved on. Several years later, with Hinge starting to grow, McLeod conducted an interview with a New York Times reporter where he recounted the story of the one who got away. That inspired him to look up his lost love, who was living in Europe and engaged. Though they hadnt seen each other in nearly a decade, something sparked. She called off her wedding, and a few years later she and McLeod married. Hes recounted this story numerous times. It was even turned into a New York Times Modern Love column and then an episode of the Amazon show based on the column. But as polished as the anecdote is, theres a deeper truth within it: Vulnerability creates possibilities. A decade ago, when Tinder, Bumble, and other apps were orienting themselves around engagementmaking the user experience addictive but the outcomes questionableMcLeod mapped out a different strategy, aimed at fostering emotional risk-taking. He would require users to put in more work during the sign-up process and would place deliberate hurdles for them along the way, all in an effort to get them to open up, not just swipe. Jackie Jantos, chief marketing officer [Photo: Evelyn Freja] Today, Hinge requires users to upload a minimum of four photos and fill out at least three prompts about themselves. The process is designed toget users to slow down, think about what they really want, and present a more unfiltered profile. McLeod says the app tries to give users tasks that signal a level of intention and create a level of vulnerability so that you can actually create connection between two people. The longer sign-up process has made a difference: Hinge has found that users are 47% more likely to go on dates when they engage with the written answers on someones profile rather than simply the photos. Last year, Hinge introduced another hurdlea feature called Your Turn Limitsto curb ghosting. Now Hinge users with too many unanswered messages must send a reply or end the conversation before they can resume swiping. The company even gently nudges users into the real world: Its AI will invite users to set up a date if theyve been chatting online for a couple of weeks and seem compatible based on their conversations. Hinge also uses AI to scan the content of messages and deploys a notification to double-check with a user before they send a message that might not be well received. Thats all well and . . . millennial, but the apps newer challenge is helping Gen Z userswho make up 56% of Hinges overall user basefind value in the app. CMO Jackie Jantos sees a generation that was isolated during the formative years when relationships develop, and that often reverts to interacting on social media rather than in real life. Hinges Gen Z users tend to be uncomfortable with small talk and hyperfocused on digital body language, Jantos says. So theres a lot of reading into the speed [with which] someone replies, how long the persons message is, and what type of emojis and punctuation they use. Match CEO Rascoff puts it more succinctly: They have atrophied social skills and need more help showing up and connecting with other people. Hinges first feature for younger users, launched in 2021, was inspired by TikTok voice-overs. Instead of making users write out their responses to profile prompts, Hinge now allows them to record a 30-second audio introduction. It hit the sweet spot of willingness to do it if Im the person whos posting it and extremely informative if Im the person [experiencing] it, McLeod says. With more than one in five Gen Z adults identifying as LGBTQ, according to Gallup, Hinge has also given users an expanded menu of gender and sexuality identifiers to choose from as they set up their profiles. Gender, relationships, and relationship types are being redefined, Jantos says. In February, the company added Match Note, which allows users to privately share information with matches before chatting with them. People have used it to disclose their STI status or gender identity. (McLeod says single parents also use the feature to let matches know about their kids.) Hinge is tuning its marketing for Gen Z as well. The company has long featured real couples in its campaigns. But Hinge is now focused on stories that showcase all the intricacies and uncertainties of real relationships to show Gen Z that they dont have to be perfect. For 2024s No Ordinary Love campaign, Hinge enlisted writers like Roxane Gay and Hunter Harris to tell the nuanced, real-life stories of people who connected on the app, then published the essays in a zine. This year, Hinge followed up with a second collection, released as a printed book and on a dedicated Substacksupporting it with a flurry of ads in major cities. In one, a couple meets, hits it off, then breaks up for a few months before getting back together. Another tells the story of Lia and Ole, a couple fighting against their preconceived ideas of what they want from a relationship (Lia had imagined a romance with someone more established, more mature). Spoiler: Five years after their first datewhen they jointly deleted Hinge from their phonestheyre still together. Despite his fears of AI keeping Hinge users from meeting real people, McLeod is embracing it to help improve their prospects. In January, Hinge launched an AI-powered coaching tool to help users refine their profiles. Instead of just asking users to type in their response to a profile prompt, an AI chatbot can now interview the answer out of them. If a user says they like to travel, the chatbot might ask them for their best travel story to add to their profile. Those interviews serve an additional purpose: helping improve the apps matching algorithm. Until the advent of generative AI, Hinges algorithm primarily considered the profiles that users liked as they swiped and tried to surface similar onesbut it never really understood why a user might have certain preferences. Now, McLeod says, the algorithm can take in the content of a users profile to deliver better matches. Its thinking about what youve said, what theyve said, what your prompts say, what your photos are, and using it to predict whether you might like someone, he says. Its not waiting for you to send a whole lot of likes for us to learn your taste. If McLeod succeeds, he could lift the fortunes of Match beyond just Hinges revenue. Matchs data shows that Hinge subscribers already tend to use the app alongside one or more of the companys other apps. Rascoff now wants to encourage that behavior, letting users populate their profiles across other apps with one tap. From a financial standpoint, weve found that its additive, he says. The user spend on the second app does not detract from their spend on the first. Rascoff envisions that the matching algorithm behind these apps could also be standardized. We dont want to do AI stuff for the sake of it, McLeod insists. Even so, hes staking his apps future on it. McLeod anticipates that within five years Hinge will work more like a personal matchmaker. Users will spend less time on the platform sifting through profiles and sending messages. Instead, they might provide more information to the app on the front end and simply trust it to show them fewer, better matches. That would represent a sea change for the entire industry, McLeod says: Well think of swiping through endless profiles to find dates as a bit archaic.
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E-Commerce
Its a little-known fact that Columbia University, in Manhattan, was home to the first mining school in Americathe School of Minesfounded in 1864. For the past three decades, the university’s program has been mothballed. Parts of its curriculum were subsumed into the more fashionable subjects of earth and environmental engineering. But next fall, Columbia University will offer a bachelor of science degree in mining engineering once again. Other schools are barreling down, as well. The University of Texas at El Paso is also relaunching its mining engineering degree, starting in the fall of 2027, after a 60-year hiatus. The University of Texas system is providing $20 million to reestablish the program, which plans to produce up to 100 mining engineers annually. Existing programs at some of the top schools for miningincluding the Colorado School of Mines, the Missouri University of Science and Technology, and Montana Technological Universityare also reporting upticks in enrollment, reversing years of declines. Until the 1970s, most universities had pretty robust programs in mining engineering, says Greeshma Gadikota, professor of earth and environmental engineering at Columbia University, who will also teach in the revived mining program. This rebirth in mining education in the United States is happening for a reason. Its a response to a crisis thats been decades in the making. The underground scene In key measures of mineral wealth and production, the U.S. is failing to keep up. Rising global demand across clean energy, defense, and tech industries has driven prices for critical minerals like copper, silver, and tungsten to record highs. Geopolitical tensions have threatened access to many others. For decades, the U.S. had deprioritized mining and has instead come to rely on rare minerals produced in China. China dominates production of at least 15 critical minerals and mineral groups; it mines about 70% of the worlds rare earth elements and processes about 90% of the global supply. (The U.S. is entirely dependent on China to meet its demand for graphite, an essential component in lithium-ion batteries, for example.) But over the past year, in retaliation for Trumps tariffs, China has banned the export of three rare earth productsgallium, germanium, and antimonyto the U.S. And it has put export restrictions on many others, including ones for which China is the sole supplier, including dysprosium, essential for building superfast computer chips, and samarium, a rare earth metal used in many military applications. Last fall, prices for gallium (used in electronics, semiconductors, and batteries) and germanium (critical to infrared technology used in fighter jets and missiles) hit a 14-year high. Tapping into a domestic supply of rare minerals has become not just an economic imperative for the U.S. but a strategic one. Yet that requires rebuilding a declining workforce. More than half the people currently working in the U.S. mining industryroughly 221,000 workersare expected to retire or switch industries by 2029. The U.S. Bureau of Labor Statistics forecasts 400 annual job openings for mining engineers through 2034. That may not sound like a lotafter all, the Bureau of Labor Statistics anticipates about 5,500 annual openings for civil engineering technologists and technicians, and 17,500 openings for electrical and electronics engineers in the same period. But consider that in 2023, only 312 mining engineering degrees were awarded by U.S. universities. That means its a sellers market for new mining gradsa stark contrast to the outlook for computer science graduates and computer engineering majors, who faced 6.1% and 7.5% rates of unemployment, respectively, according to the Federal Reserve Bank of New York. (It’s no wonder Nvidia CEO Jensen Huang says he would study physical science if he were starting out today.) But the ability of the U.S. to mint new mining engineers is limited by the number of schools that still offer mining and mineral engineering programs, which has fallen from 25 in 1982 to about a dozen today. Edgar Mine field session [Photo: Colorado School of Mines] Those programs started shutting down one after the other, because so much of the work was getting shifted abroad,” Columbia University professor Gadikota says. Other countries took advantage of that, and they started building up capabilities. Today, China has more than 38 mineral processing schools and more than 44 mining engineering programs, according to the nonprofit Center for Strategic and International Studies. Chinas largest mineral processing program, at Central South University, alone has 1,000 undergraduates and 500 graduate students preparing for the field. Now, schools and businesses are trying to spread the word that the mining industry has well-paying jobs to filland that mining today is different. Graduates in mining engineering regularly earn $70,000 and up, right out of school. According to the U.S. Bureau of Labor and Statistics, the median annual pay for mining engineers is $101,200. Specific expertise in the extraction of rare earth elements, for example, and a willingness to work in remote locations can boost compensation. A new gold rush for mining engineers From aluminum and antimony to zinc and zirconium, there are currently 60 critical materials on the U.S. Geological Services list, minerals and rare earth elements that are vital to batteries, semiconductors, planes, lasers, medical imaging devices, cancer therapies, cars, electronics, nuclear power plants, and more.&nbs; As defined by the Energy Act of 2020, these materials are essential to the economic or national security of the U.S.; have a supply chain that is vulnerable to disruption; and serve an essential function in the manufacturing of a product, the absence of which would have significant consequences for the economic or national security of the U.S. Many of these materials exist in the U.S., but most of them are still stuck in the ground. Thats starting to change, as big mining companies and startups alike race to develop new domestic sources. MP Materials, a rare earth mining and processing facility on the Nevada-California border, signed a guaranteed-pricing contract in 2025 with the Pentagon and saw its stock surge more than 240% for the year. MIT-founded startup Phoenix Tailings raised $76 million in venture funding last year, supporting the build-out of a next-generation rare earth processing facility in New Hampshire. In December, Ionic Mineral Technologies announced it had discovered rare earth and critical technology metals, including gallium, germanium, cesium, and tungsten, that it says are comparable to Chinas deposits. Global mining giants like Glencore, BHT, and Rio Tinto are also developing critical mineral assets in the U.S. Each of these companies employs its own mining engineersand most of them also contract with other companies that employ them. The growth in critical minerals is creating new kinds of opportunities for young people getting into the industry. And schools are scrambling to revamp curricula to reflect the shifting industry landscape. Kwame Awuah-Offei, who leads the Missouri University of Science and Technologys Department of Mining and Explosives Engineering, says the schools graduates typically fall into three career buckets: construction aggregate materials (a $35 billion-a-year business in the U.S.), mineral mining, and mining services (working for equipment makers, software companies, and others that support the mining industry). Even though U.S. coal mines still employ some 44,000 people, Awuah-Offei says, coal recruiters are having a tough go of it with new grads. There is concern among students that if they want to have a 30- or 40-year career, it’s not in coal. Whether its true or not, the numbers have shrunk quite a bit. Interest in critical minerals is a big factor contributing to larger recent class sizes, Awuah-Offei says. Domestic need for resources is just in the news morehe mentions Trumps talk of invading Greenlandand it drives curiosity on the issue. While undergrad mining engineering enrollment is still small compared with mechanical engineering, electrical engineering, civil engineering, and fast-growing nuclear engineering, it has grown over the past couple of years. Awuah-Offei is confident that graduates will find jobs when they graduatethanks to the new demand in rare metals mining and processing, coupled with very strong job opportunities in the construction materials and aggregate side of the business.” The latter type doesnt pay as much as metal mining jobs, but the attraction is that they tend to be around metro areas. Lifestyle is an important factor for this generation of students, Awuah-Offei says. Even if a job in Bagdad, Arizona”a remote copper mining hubis paying $10,000 more, theyd rather live in Dallas than be in Bagdad. Things come in waves, says Columbia University professor Gadikota. We had a wave around climate. Right now we have a wave around metals and foundational materials. Of course, the two things arent unrelatedwhich might be key to mining engineerings widening appeal. Sustainability and social considerations increasingly define industry practices. Mining meets AI, entrepreneurship, and environmentalism When people see today’s mining tech, they are surprised, Awuah-Offei says. This includes not only massive excavators and tunnel boring machines, but also increasingly common autonomous trucks and robotic equipment. Advances in technology have led to changes in mine design and operation, which in turn have created new challenges that require engineering-based solutions. For example, says Sebnem Düzgün, associate department head of mining engineering at the Colorado School of Mines, one of my students recently analyzed problems with BEV [battery electric vehicle] operations in underground environments. Its highly interconnectedthere’s a societal need for these critical minerals, and mining itself also needs them, to electrify the mines. Sebnem Düzgün [Photo:Colorado School of Mines] Düzgün recently led a recent curriculum update at the school, which included adding classes in things like data science, AI and machine learning, robotics, and autonomous operations. All engineering departments have an industrial advisory committee, she says, and we frequently reflect their requests in our curriculum. Modern mining involves using AI models to analyze geological and satellite data during the exploration phase, deploying predictive analytics to improve mine traffic flow and minimize equipment downtime, and creating digital twins to process real-time sensor data and optimize processes. If you go to the control room of a modern mining processing plant, all you see is big banks of computer screens with someone monitoring data streaming in from sensors,” Awuah-Offei says. “They dont necessarily need to walk out there to see whats going on. Technology has enabled a new breed of mining startups to flourish, which has prompted another change to the traditional curriculum. Mining is mainly governed by large industry, Düzgün says. But as new businesses have emerged, weve started incorporating entrepreneurship into our curriculum, and now some of our graduates are entrepreneurs. Some technology-enabled mining startups are even being funded at levels typically associated with AI companies. In January 2025, KoBold Metals, an AI-powered U.S. mining startup backed by Bill Gates and Jeff Bezos, raised a $537 million Series C round. Another part of the mining engineering syllabus is environmental stewardship. To be honest, weve been incorporating the social and environmental aspects of mningthings like mine closure and reclamation issuesinto our curriculum for almost 20 years, Düzgün says. But the industrys handling of these concepts became more pronounced. At Columbia, Gadikota says the mining program had morphed into earth and environmental engineering as the public became more focused on minings environmental footprint. We went so much toward managing environmental impacts that it reached the point where we didn’t even want [mines] in our backyard. Now, the pendulum is swinging back. We are rediscovering and repurposing our mining roots and bringing back all of that knowledge, but not just in the same outdated manner. We need the metals. We also need to clean up the tailingsmaterials left over after ore has been extracted from rockand the emissions, and develop sustainable water systems. We want to be conscious about managing tomorrows liability today, she says. Gadikota oversees a sponsored research agreement, announced in November, between Columbia University and Locksley Resources, which is targeting rare earth elements and antimony (used in energy storage) in California. Students at Columbia will explore approaches including AI-driven ore analysis, innovative electrochemical recovery, and carbon-dioxide-assisted mineral processing to help the company develop sustainable practices that improve upon current methods. If we wanted to build metal recovery capabilities based on technology that exists in other countries, we can certainly do that, Gadikota says. But we know that some of those mining pathways are not as energy-efficient, theyre not as material-efficient. They contribute to a lot of emissions. Then there is the processing side. How do we process the material in a way that allows us to produce not just one product, but multiple co-products? And how can we lower the environmental footprint of doing that? These are all key factors to consider, and that’s why we do what we do. Government spends heavily, but gaps remain Last March, President Trump signed an executive order, Immediate Measures to Increase American Mineral Production, that outlined numerous steps to increase funding and cut red tape for domestic mining and metals processing projects. The government responded: The U.S. Department of Energy announced in August that it would issue nearly $1 billion in funding to advance and scale mining, processing, and manufacturing technologies across critical minerals and materials supply chains. Three months later, the Energy Department’s Office of Fossil Energy announced that it would provide up to $275 million to build U.S. industrial facilities capable of producing valuable minerals from existing industrial and coal byproducts, and $80 million to establish Mine of the Future proving grounds to test next-generation mining technologies. But there hasnt yet been much federal funding specifically earmarked for mining education. We’ve seen an uptick in research funding for faculty to go after, Awuah-Offei says. Traditionally, when theres a lot of funding, universities are more willing to hire people in that area. So that has been good. But apart from programs in some states, like Texas, there hasnt been direct investment in education, necessarily. Introduced in the House of Representatives in March, the Technology Grants to Strengthen Domestic Mining Education Act of 2025 (aka the Mining Schools Act) would establish a grant program to support schools in recruiting and educating future mining professionals, including engineers. It is currently awaiting action by the House Committee on Natural Resources. Most of us support that because it will put direct funding into schools, Awuah-Offei says. Training mining engineers is expensive. You have to have an experimental mine. It’s lab-based and hands-on. Theres little time to waste. We’ll work on cute little mining projects, Gadikota says. But if you want to scale them up and you need a domestically trained workforce to implement and grow them, does that workforce actually exist? The answer to that question is: We are behind, and we are doing everything that we can to develop that talent and get them out again.
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