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The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. In a world increasingly shaped by the potential of artificial intelligence, the life sciences industry may be one of the largest beneficiaries of its transformative potential. Artificial intelligence (AI) has already revolutionized elements of the drug discovery and development process, redefined research methodologies, enhanced disease detection and diagnosis, and paved the way for personalized medicine. Knowing that we have just begun to scratch the surface of AIs potential, I am excited to see how its continued evolution will accelerate our collective mission of bringing novel medicines to patients in need. But I am also cognizant of its limitations. While we can outsource human tasks to AI, we simply cannot outsource humanity. AI is not intelligent when it comes to emotion, imagination, empathy, or qualities critical to creating and leading. Similarly, the spark of ingenuity and the recognition of serendipity exists solely within the bounds of the human experience. AI also lacks context and nuancea critical component when considering the myriad factors needed to be successful in drug development, such as evaluating patient needs, defining new white spaces in an increasingly competitive environment, and other macro considerations. A case study for humanity In founding Tarsus, we set out to develop a treatment for a large, underdiagnosed eyelid disease, Demodex blepharitis (DB). Both the literature and our discussions with many eye care providers validated early on that this was a highly prevalent disease, with very low disease awareness, and no FDA-approved therapies. We needed to prove how significant the unmet need was and build a market that would support an entirely new category in eye careand there were no benchmarks to assist us in establishing a path forward. Our early clinical trials were conducted in Mexico City. I recall sitting in a large eye hospital, packed with hundreds of patients and family members of all ages, while we worked with the eye care team to find patients with visible signs of DB. After many hours searching individual clinics for DB patients with very little return, we questioned our initial prevalence modeling and wondered whether this disease was, in fact, as large as we predicted. Recognizing a potential lost opportunity in front of me, our clinical team used the microphone for the waiting area. In Spanish, we asked if anyone in the waiting roomwhether they were there to see a doctor or notwas experiencing eyelid irritation, redness, crusting, and itching (all signs of DB). To our surprise, a couple dozen people stood up and got in line to be seen by an eye care provider, and roughly half of them were diagnosed with DB during a routine exam. This serendipitous moment changed everything, and it would not have occurred without several very human elements: instinct, informed risk taking, and an inherent sense of how to connect and engage with other humans. After seeing hundreds of people line up over the next few months, we knew we had uncovered a unique opportunity to potentially serve millions of patients living with DB. Active listening and human connections Our Mexico City experience further reinforced that AI is no match for the type of insights and perspectives that can be gained from human-centric approaches like active listening and empathy. These very personal interactions inform the work we do every day across every aspect of our businessfrom clinical development to strategic marketing to building an award-winning culture, and so much more. More recently, as we listened carefully to the thousands of doctors now prescribing our treatment for DB and doing careful eyelid exams, we identified another large, underdiagnosed eye disease, ocular rosacea, that now presents a promising opportunity in our pipeline to potentially serve millions more. The human ability to adapt, relate, and emotionally connect with other humans, and our aptitude to make ethical and rational decisions has ensured that people come first in medicine and science. And that will not change. It is clear we are on the cusp of a technology-enabled revolution that will improve howand how quicklywe can deliver innovative new treatments to patients. And we are finding numerous ways to strategically leverage AI. But our collective success as an industry will be dictated by our ability to maintain a nimble, empathetic, and uniquely human-centered approach. Bobak Azamian, MD, PhD is CEO and chairman of Tarsus Pharmaceuticals.
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E-Commerce
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. Tariffs, trade, imports, exports, prioritization, energy, and dominance are all words that have been flooding the headlines lately. In this world of globalization, it is an equilibrium of exchanges, ensuring we have enough of something but not too much. We see this balance come to life in supply and demand graphs of critical minerals, often in the context of batteries or energy dominance. The supply and demand of materials required to support growing energy-related technology and sectors, such as energy storage needs, plays a crucial role in the critical minerals market, both in the United States and globally. Today, the U.S. imports a large number of batteries that are used in consumer devices, vehicles, military, and grid storage. And the demand for batteries is set to continue growing quickly based on current policy settings, estimated to rise by more than four times by 2030 and by at least seven-fold by 2035. This growth is a clear sign that the owner of the critical minerals source will hold more control over the supply chain. This is why a diversified approach to critical minerals is vital. Battery recycling is a key to that strategybecoming a major source of domestically manufactured critical materials. Chinas control in the lithium-ion battery manufacturing industry is expected to decline between now and 2034, which can be attributed to cell manufacturing operations coming online in other regions. To further highlight this shift in the global marketplace, the U.S. battery recycling market size was estimated at $374.28 million in 2023, and is estimated to grow at a compound annual growth rate of 38.1% from 2024 to 2030. Diversify and stabilize domestic supply chains Original equipment manufacturers and battery cell manufacturers are not slowing down their production timelines and the global demand for large-format batteries will continue to rise. The U.S. must capitalize on these opportunities to diversify and stabilize domestic supply chains, all while becoming a leading producer of critical minerals. Materials from recycled content will play an increasingly important part in meeting this demand, with predictions that battery recycling could meet 20-30% of lithium, nickel, and cobalt demand by 2050. Reuse of critical minerals is necessary to diversify and domesticate our supply chains and is work that is already being done. To further the need for increasing battery recycling capacity, the critical minerals market will begin to experience an undersupply in the form of black mass (the output of end-of-life and scrap batteries that have been recycled and processed that is put back into the supply chain), as early as 2026. For example, by 2030, lithium will see a supply and demand gap that is considered high risk, according to the International Energy Agency, due to price volatility and high geopolitical risk factors in the countries its currently sourced from. The expected growth, combined with supply gaps, is why the U.S. needs to continue its focus on enhancing our domestic critical minerals supply chains, with a heavy emphasis on recycled content. Recycling is important The U.S. has developed a large battery recycling capacity in anticipation of the large number of end-of-life batteries predicted to enter the market. Fueled by public and private investments, the United States battery recycling and critical mineral refinement sectors are fundamental to becoming a divergent player and seriously competing with those in Asia for the limited supplies of black mass. To encourage the build-out of battery recycling capacity, we must recognize that it aligns with domestic priorities related to the sourcing of critical materials. Strengthening our domestic supply chains will position the U.S. as a leading producer of critical minerals; it furthers the National Defense Stockpile sources to reduce the nations mineral reliance on foreign entities of concern; and it accelerates access to domestically sourced critical minerals, enhancing national security and global competitiveness. The largest operating mine of critical minerals is in our pockets, offices, garages, on the roads, and supplying energy to data centers and power grids.Recycling these materials at their end-of-life is a must. David Klanecky is CEO and president of Cirba Solutions.
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E-Commerce
As artificial intelligence gets smarter, a growing number of companies are increasing its implementation in their operations or more heavily promoting their own AI offerings. The buzzword for this is “AI first.” Duolingo is among the latest to adopt an AI-first approach. The company’s CEO Luis von Ahn announced the change in an all-hands email Monday, saying it would stop using contractors to do work AI can handle and only increase headcount when teams have maximized all possible automation. The way we work is fundamentally shifting. AI is becoming the default starting point,” said Duolingos Chief Engineering Officer Natalie Glance in an internal Slack message she shared on LinkedIn. “Start with AI for every task. No matter how small, try using an AI tool first. It won’t always be faster or better at first – but that’s how you build skill. Don’t give up if the first result is wrong.” Von Ahn, in his email, said the AI-first approach was already paying dividends, helping the company with its content creation process. Without AI, it would take us decades to scale our content to more learners,” he wrote. Earlier this month, Shopifys CEO told workers at that company that using AI was now a fundamental expectation in daily tasks. Our task here at Shopify is to make our software unquestionably the best canvas on which to develop the best businesses of the future, Tobi Lütke wrote. We do this by keeping everyone cutting edge and bringing all the best tools to bear. . . . For that we need to be absolutely ahead. AI’s rise in business has been forecast for years, of course, but as more companies make it a priority, there are other impacts to be considered. A scientific paper released by Cornell University late last year titled The Unpaid Toll: Quantifying the Public Health Impact of AI said the pollution from data centers powering the AI industry could lead to up to 1,300 premature deaths each year by 2030. It further estimated, public health costs related to the air pollution those centers put out are already at $20 billion per year. Data centers are nothing new. They’ve been around since the 1940s, when the University of Pennsylvania built one to support the first general-purpose digital computer, the ENIAC. But as generative AI has grown, so too has the demand for newer, more powerful centers. The power requirements of data centers in North America increased from 2,688 megawatts at the end of 2022 to 5,341 megawatts at the end of 2023, according to MIT. And demand is only growing. (Energy Secretary Chris Wright, in February, called for more nuclear power plants to meet the growing demands of AI companies.) The demand for new data centers cannot be met in a sustainable way, said Noman Bashir, a Computing and Climate Impact Fellow at MIT’s Climate and Sustainability Consortium. “The pace at which companies are building new data centers means the bulk of the electricity to power them must come from fossil fuel-based power plants.” This is all occurring as concerns about the environment have been deemphasized at many Big Tech firms. Companies like Walmart, Siemens and Apple all opted against signing an open letter earlier this year reaffirming commitment to the Paris Agreement. (Duolingo, which released an environmental statement last March, did not reply to questions about how the AI-first approach might impact the company’s environmental footprint.) Meanwhile, the Trump administration has dismantled dozens of climate programs in its first 100 days. And the Environmental Protection Agency (EPA) is considering overturning previous findings that classify greenhouse gas pollution as harmful, which could impact its ability to regulate carbon emissions. By 2030, Cornell forecasts, the public health burden of AI data centers will be double that of the U.S. steelmaking industry. And it could be on par with all of the cars, buses, and trucks in California. Shopify and Duolingo are hardly the only companies adopting an AI-first approach. Many companies large and small are racing to incorporate AI into all levels of their services and workflows. Financial services firm Lettuce leans into AI to assist with tax solutions. Findigs lets property managers use AI to screen rental applicants. And a real estate brokerage in Portugal is using an AI interactive real estate agent, which has already booked $100 million in sales. In the grand scheme, though, corporate use of AI is still in its infancy. ServiceNow’s Enterprise AI Maturity Index last year measured AI maturity at 4,500 businesses in 21 countries on a scale of 0 to 100. The average score was 44, with only one in six companies topping 50. Part of what’s keeping that score low is the newness of the technology. Another factor is cost. (Does using AI, especially one that’s developed in house, actually save money given the cost of data centers, for instance?) But in the coming months and years, more companies are likely to move to an AI-first approach. And that will likely increase emissions, pumping more CO2 and pollution into the atmosphere, raising even more health concerns.
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E-Commerce
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