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The United States is no stranger to adapting its education system to address the challenges of the times. In 1957, the Soviet Union’s successful launch of Sputnik prompted the U.S. to implement programs like the National Defense Education Act, which emphasized science, math, and foreign language education. This resulted in the rapid growth in federal funding for K-12 and higher education STEM programs, and an increase in STEM graduates in the following decades. Today, we face a similar pivotal moment. The Biden-Harris administration recognized this urgency, releasing a comprehensive Federal Strategic Plan for Advancing STEM Education and Cultivating STEM Talent in November 2024. This plan aims to develop the workforce needed to address critical challenges like climate change and artificial intelligence, focusing on three key principles: access and opportunity, partnerships and ecosystem development, and transparency and accountability. However, with current political shifts, the continuity of such initiatives hangs in the balance. The U.S. faces an unprecedented challengenot from external competitors, but from rapid AI advancement that our education system isn’t prepared for. While federal STEM initiatives often focus on bureaucratic solutions through agencies like the Department of Education (only established in 1980), the real imperative is transforming how we teach and learn. Our curriculum needs radical updating to emphasize lifelong learning, rapid prototyping, and creative problem-solving skills. With software development jobs expected to grow at a rate of 17% from 2023 to 2033, resulting in an average of 140,100 job openings a year, we must streamline education, reduce administrative overhead, and focus on practical skills that prepare students for an AI-driven future. Deregulation and local control could actually accelerate this transformation, allowing schools to adapt more quickly to technological change and workforce demands. The AI revolution and the gender gap From 2017 to 2021, we saw how the Trump era’s education policies prioritized deregulation and school choice. As Trump returns, well no doubt see the same. The government and educational institutions across the country are going to have to step up as deregulation occurs. This is not necessarily a bad thing. After all, the Department of Education is only 25 years old. As the founder and CEO of a leading global technology and AI education nonprofit for girls, Ive seen firsthand how AI presents both opportunities and challenges. While AI can automate tasks, it also demands a workforce skilled in areas like data analysis, critical thinking, and human-centered design. However, the U.S. education system continues to graduate a disproportionately low number of women in STEM fields. Women make up just 35% of the STEM workforce, despite classes being offered through the formal school system. Women are already behind and will be even further left behind without the right intervention. An analysis analysis conducted by researchers from Berkeley Haas, Stanford University, and Harvard Business School shows that women are significantly less likely to learn about AI, use AI tools and build AI technologies. Because women arent involved in the development, the data sets AI is trained on are therefore biased. And when women dont have access to economic opportunity, they cant invest back into the community, slowing progress. Thankfully, we can prevent it. We have all the insights and data from past decades to inform our strategy and powerful tools and partners to implement proven strategies at scale. Research proves its possible In 1995, at Carnegie Mellon University (CMU), only 7% of the incoming computer science undergraduates were women. The administration was alarmed and supported a study to determine how to bring more women into the field. The Unlocking the Clubhouse study outlined that its not enough to provide access to coursework for women and minorities. There has to be a full spectrum of support that helps move their interest in a particular field to one they identify with. CMU implemented their recommendations and in 2021 welcomed more than 51% women into the program. It proved that we must set ambitious and measurable goals. The AI Forward Alliance did just that. Our recent Women in AI report highlights that to achieve 50-50 gender parity in the AI workforce by 2035, we need to engage around 600,000 U.S. high school girls in evidence-based tech programs every year, starting now. Without this intervention, womens representation in tech will remain stagnant, perpetuating inequities and stifling economic and technological growth. We have to create a sense of urgency, ensuring stakeholders and communities prioritize equitable participation in the tech workforce. This may require a specific U.S. coalition and campaign dedicated to gender equality in AI. Build a workforce for the AI era The U.S. education system will have to play a meaningful role to ensure the country can compete in the AI era. First and foremost, we need a complete overhaul of our education system. Several key areas can help position the U.S. as a leader in AI education and workforce development. First, we must fundamentally redesign our curriculum to go beyond traditional STEM education, focusing instead on learning not just how to use AI but how to build better AI. This means developing courses that teach students coding skills, but also critical thinking about AI outputs, understanding of AI’s limitations, and the ability to effectively leverage its potential. Building on this foundation, we need to take lessons from success stories like Carnegie Mellon’s approach to diversity in tech education. Simply offering STEM classes isn’t sufficientwe must actively engage girls and minorities through targeted programs and mentorship, creating an inclusive environment that supports all students in pursuing tech careers. Finally, we must recognize that the skills needed in the AI era will continue evolving rapidly. This requires fostering a culture of lifelong learning throughout our education system, equipping students with the tools and mindset needed to adapt and grow throughout their careers. The ability to continuously learn and adapt will be crucial for success in an AI-driven future. As we stand at this critical juncture in American education, the stakes couldn’t be higher. The contrast between the Biden administration’s forward-thinking STEM initiatives and the potential reversal of progress under a return to Trump-era policies presents a stark choice about our nation’s future. This isn’t merely about maintaining America’s competitive edgethough that’s certainly at riskit’s about ensuring every American student has the opportunity toparticipate in and shape tomorrows AI-driven economy. The path forward requires unwavering commitment to educational equity, sustained investment in STEM programs, and a recognition that in the age of AI, we need all of America’s diverse talent pool engaged and empowered. The question isn’t whether we can afford to make these investmentsit’s whether we can afford not to. Our nation’s future innovation, economic prosperity, and technological leadership hang in the balance, and the time to act is now. Tara Chklovski is founder and CEO of Technovation.
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E-Commerce
When you ask ChatGPT a question, how does it come up with the answer? Most people dont give much thought to whats going on behind the screen or how graphics processing units (GPUs) make the AI magic happen in data centers across the country. GPUs are extraordinary, processing exceptionally large data sets and handling highly intensive computations involving billions of simultaneous calculations. Modern GPUs can train neural networks that enable AI breakthroughs that were once the subject of science fiction films. Thanks to GPUs, AI is being used to more accurately diagnose diseases, accelerate drug discovery, detect fraud, improve transportation efficiency, improve customer service, protect our national security interests, and provide personalized education experiences. Not surprisingly, the parallel processing architecture that makes GPUs excel at training AI requires an immense amount of energy. Thats why, according to Goldman Sachs Research, the power usage of data centers will grow by 160% by 2030. Our country is at a critical inflection point. The surge in energy required to power GPUs presents both a challenge and an opportunity. The United States power grid and service modelsbuilt in the pre-AI eraare not equipped to meet this demand. Today, data centers only account for about 2% of U.S. power consumption. But as AI models grow, data center development will outpace how quickly new electrical energy supply and transmission can be built without a shift in strategy. Seize the AI moment This moment marks an opportunity for utility providers, communities, and the technology industry to come together to turn AI into a source of long-term economic prosperity and growthrather than let it create a chasm. GenAI has the potential to transform the U.S. economy, with some estimating it could increase U.S. labor productivity by 0.5 to 0.9% annually. Investing in our AI infrastructure will ensure American communities can attract and retain highly skilled talent, while accelerating scientific advancements. As global powers invest in AI, the right infrastructure is also necessary to ensure our governments and communities can protect critical infrastructure. So how do we seize this opportunity? We need to rethink our approach to building infrastructure and delivering power. Today, electric utilities have a duty to serve demand as it comes. In laymans terms, that means anyone can say, Im building something over here and I need more power for it, and the utility has to add that request into their queue for service. That can be unfair when some customers are asking for massive amounts of power, which could impact the entire community. In some cases, speculative developers demand power in the early stages of a project, prompting utilities to plan and invest in infrastructure for a data center project without backing that may never come to fruition. These speculative developers operate under the assumption that they can put the pieces of the puzzle in place to later sell to a data center developer or operator, a prospect which may never transpire. When those projects fall through, the local community is left holding the bag. Build a more sustainable approach Its possible for data centers to access the energy they need without driving up energy costs for everyone. To achieve this, the industry needs to work with utilities in a collaborative way to close the gap between supply and demand. Data centers can and should take on more of the risk (and costs) of building infrastructure and transmission, which will require regulatory support. Data center developers generally have easier access to capital, fewer restrictions when it comes to buying land and faster decision-making capabilities than regulated utilities. That means, were able to contribute financially to the development of transmission lines and substations. Complex regulatory processes often stand in the way of this today. Paving the path for microgrids, which enable data centers go off grid power and even return power to the grid during peak demand periods, can turn data centers into a grid resource rather than a drain on supply. The path forward AI represents unprecedented potential for human advancement. Whats always been done wont work in the era of AI and electric-everything. American utilities are going to need to invest $50 billion to build new generation capacity for data centers alone by 2030. To achieve this, energy leaders are going to need to think out of the box and explore ways to closely collaborate with industry. Its the only path forward for long-term, resilient growth and a more equitable AI-powered future. Chris Crosby is CEO of Compass Datacenters.
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E-Commerce
The modern international food trade currently plays a significant role in breaking food insecurity in parts of the world. Although innovative, the downsides are the high expense of transit, supply chain vulnerability, and potential for environmental harm. The alternative? Helping farmers worldwide to successfully and sustainably overcome crop stressors such as insects that take a toll on crops grown to feed the populations close to them. AI can help make a positive difference. There are an estimated 570 million farms of varying sizes globally, a number not expected to expand significantly. The worlds population, however, is predicted to grow (from almost 8 billion to nearly 10 billion by 2050) requiring farmers to produce 50% more food on those 570 million farms, a significant problem, unless there is change. Farmers already lose 20-40% of their crops annually to weeds, pests, and disease; changing pressures caused by climate change and resistance are exacerbating the situation. Many current treatments to fight weeds, pests, and disease were developed over 30 years ago and today struggle against resistance. Farmers are resourceful and eager to find solutions but pests are nimble and persistent. North Americas corn rootworm, for example, has adapted to crop rotation. And Asias barnyard grass mimics rice plants to evade hand-weeding. Innovation is desperately needed to provide solutions. So, how can we ensure there is sustainable, more localized, food production in a world where farmers face these challenges? Artificial intelligence (AI) is emerging as a promising tool to address these challenges by efficiently turning data into actionable recommendations and solutions. Take a page from pharmas AI book AI is revolutionizing many industries, from education to energy. While its still early in its impact, improving crop yields and bringing agriculture into the future is shaping up to be another industry AI is poised to disrupt. AI can help with on-field tasks like efficiently powering a sprayer. It can also help with in-lab tasks like accelerating the discovery of safer, more effective crop protection solutions. Consider the pharmaceutical industry. AI is set to transform drug discovery by enabling the rapid development of vaccines and treatments to protect global health. Today, scientists can create annual vaccines for evolving viruses like COVID-19 and influenza while also advancing therapies for other common and rare diseases. AI is beginning to equip scientists with tools to navigate the vast diversity of chemical space, prescreening them for efficacy and then rapidly identifying the most promising molecules in the fight against disease. By analyzing data from sources like DNA-encoded chemical libraries, AI helps scientists pinpoint potential candidates from billions of options. Machine learning models further expand this exploration, unlocking chemical diversity from ultra-large, make-on-demand libraries. Now, apply that approach to agriculture, because crops get sick too. In humid regions, fungi threaten yields, while in arid climates, insect infestations can destroy fields within days. AI-driven innovation in crop protection can help address these challenges with the same urgency and precision as in pharma research and discovery. Sifting through genetic and chemical datasets can help farmers tackle evolving threats faster and more accurately. Traditional crop protection discovery is slow and expensive, typically taking more than 13 years to bring a product to market. AI-informed research can likely cut discovery time in half and ultimately generate higher quality leads. A better way to support farmers Beyond crop protection discovery benefits, the responsible use of AI in agriculture has the potential to transform global food systems, making them more sustainable and resilient in the face of challenges. With AI, farmers gain powerful tools to not only safeguard their crops but also to enhance overall productivity and sustainability. AI can help farmers anticipate and respond to the effects of climate change, such as altered growing seasons, pest invasions, and extreme weather events. With predictive tools, farmers can make informed decisions about crop rotation, pest control, and irrigation, leading to improved outcomes while navigating unpredictable conditions. Farmers can also harness AI to improve productivity while minimizing environmental impacts. AI-driven solutions can allow for precise monitoring of soil health, real-time weather analysis, and efficient resource use, ensuring that farmers apply water, fertilizers, and pesticides only where and when they’re needed most. This reduces waste, lowers costs, and mitigates the negative effects of overuse on the environment. The long-term potential of AI in agriculture lies in its ability to boost productivity for farmers and foster more sustainable food systems that can feed a growing global population while preserving the health of the planet. Looking to the future AI is already making meaningful strides in revolutionizing agriculture and the potential is enormous. Enhancing crop protection and boosting productivity without the need for farmland expansion is only the beginning. The potential for breakthroughs is vast, with new solutions on the horizon that could significantly transform agriculture and drive further progress. By continuing to innovate and integrate AI into agricultural practices, well reach new levels of sustainability and efficiency, ultimately creating a more resilient and productive food system to support the world. As these technologies develop, ongoing research, ethical considerations, and farmer education will be critical to ensure AIs responsible integration into agriculture. Jacqueline Heard,PhD, MBA is cofounder and CEO of Enko.
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E-Commerce
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