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If you search for your city on a new map and zoom in, you can see pollution drifting from factories, power plants, and ports into your neighborhood. The mapa first-of-its-kind air quality tool from Climate TRACE, a nonprofit coalition cofounded by former Vice President Al Goreshows how pollution moves through cities. The new interactive tool, launching September 24, is powered by a sophisticated model that tracks local air pollution and weather data and feeds the map. It shows PM 2.5 pollution (responsible for nearly 9 million deaths each year globally) in more than 2,500 cities. Orange dots indicate sources of pollution, with a stream of smaller dots showing how it moves over the city, shifting course with the wind. Right now, the map presents snapshots of average and bad air days in each city. But it will later offer data in near real time. [Image: Climate TRACE] Eventually, we will have it on a daily basis, so that if you have a child with asthma or if you have family members with lung and heart conditions that make them sensitive to air pollution, you can go to your favorite weather app and see exactly what the pollution flows have been through your neighborhood that particular day, Gore says. Health researchers can use the data to see how pollution is linked to disease at the neighborhood level. Louisiana’s Cancer Alley, for example, has one of the highest levels of air pollution in the world. One community in the area, called Reserve, has a cancer rate 50 times higher than the U.S. average. [Image: Climate TRACE] The tool’s visualizations can aid policymakers in making the case for more state regulation and help the worst-polluting sites transition to cleaner tech. (As the Environmental Protection Agency moves to stop collecting some emissions data, Climate TRACE, which stands for tracking real-time atmospheric carbon emissions, can also help partially fill that data gap.) Companies can use its data to identify and replace the worst polluters in their supply chains. Because the same sources are responsible for both climate emissions and air pollution, highlighting the health impacts also helps build support for climate action. “Connecting those two streams of pollution, and tracing them back to the same combustion process, makes it easier to understand exactly why we have to accelerate the transition away from fossil fuels,” says Gore. [Image: Climate TRACE] The coalition launched in 2020 to track greenhouse gas emissions using satellite images, other data, and machine learning to estimate the pollution emitted by industrial sites. Last year, the group added co-pollutants like particulate matter and sulfur dioxide to its database, using data on the size and type of each polluting site. The new tool can help make the issue of air pollution seem more immediate and personal. “My experience with everyone I’ve showed this to is that it feels abstract until they see themselves in the story,” says Gavin McCormick, cofounder of Climate TRACE. “You can show people on a map where their house is, they can show you where their kid goes to school, and you can see the pollution. I think that’s just kind of making people realize this is happening to them.
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E-Commerce
When using AI, most of us worry about the technology hallucinatingtelling us lies, misinformation, or nonsense that it presents as fact. But legendary fashion designer Norma Kamali has no such fear. Over the past two years, Kamali has been using AI extensively in her work. Kamali, who recently celebrated her 80th birthday, partnered with computer scientists to create an AI platform based on her five decades of work as a designer, and she also took an AI course at MIT to better understand how the technology works. “These scientists asked if they could download my brain,” she says. “They would isolate my intellectual property, brand history, and archive. At first I said, “No way.” But I’ve come to see the possibilities for my brand.” Kamali has used her AI platform to design pieces for her own collection, including variations of her famous Sleeping Bag Coat. But she says that as she interacts with the AI, some of her favorite moments are when it hallucinates, generating bizarre images that explode with a strange kind of creativity. “The image is always a surprise,” she says. “If I say something like, I’d like to put a fishtail on this swimsuit worn with a sleeping bag coat, the AI goes crazy. It’s beyond gorgeous in the most art tech, fashion way.” As AI companies continue to refine the technology with the aim of eliminating mistakes, Kamali believes its only a matter of time before hallucinations no longer occur. But she says she’ll be sad when that time comes. In many ways, her open-minded approach to AI is a microcosm of her openness as a designer, which has paved the way to all kinds of unconventional, creative collaborations. “AI, for me, has been a really joyous experience,” she says. “We’re in this little moment in history that will eventually disappear. But then we’ll find other things to excite us.” [Photo: Eugene Gologursky/Getty Images for Fast Company] Kamali launched her label in 1976 and became an overnight sensation when Farrah Fawcett wore one of her red bathing suits in a poster that same year. It’s ironic to Kamali that she first made her name with a swimsuit because she really didn’t like the version that Fawcett had purchased. “I would use my shop as a lab, making six of a new style to test and see what sold,” she recalls. “I had no idea she had come in and bought that one. I really hated it: I didn’t like the fit or anything about it, and quickly took it out of the shop.” Kamali is proudest of the moments when she’s been willing to innovate and explore ideas that to others may have seemed unconventional. She’s often proven to be far ahead of her time. In the early 1970s, for example, she created the Sleeping Bag Coat, inspired by a camping trip. The coat became iconic (its on display at MoMA), at a time when most coats were made of wool. It ended up being a precursor to the puffer coats that are now ubiquitous around the world in cold weather. Another cutting edge-design was her line of Sweats sportswear, which she launched in the 1980s. It was designed to be worn outside of the gym, three decades before the “athleisure” trend would take over modern life. Kamali hasn’t just been willing to take risks with design, she’s also been willing to try new things at retail. In 2003, Target began collaborating with designers to create more affordable versions of their clothing, starting with Isaac Mizrahi and Michael Graves. Walmart, on the other hand, was not known for being particularly design-oriented. But in the early 2000s, Kamali met with a Walmart buyer who proposed a partnership. Much like with AI, Kamali took a minute to think about it before she embraced it. “I was like, Oh my God, I’ve never been to Walmart,” she recalls thinking. Then she realized there was a need for smart, fashion-forward clothes at an affordable price point. She grew up going to public schools in New York City, and she knew there were many parents who didnt attend parent-teacher meetings because they didn’t have the right clothes. There were also teachers who couldnt afford to buy professional-looking clothes on their salaries. “I felt that teachers should dignify the position, and look amazing in front of the kids in their class,” she says. So Kamali created a wardrobe that was everything an adult would need to walk into a school and look polished: a trench coat, a white collared shirt, black trousers, ballet slippers, and pumps. She also worked hard to find manufacturers who could create these products at the best possible quality given the price point, which was less than $20 per item. The popularity of the collection became clear when Kamali noticed that people were reselling these products on eBay for upwards of $200 apiece. Ultimately, Kamali believes the success of her business has been all about being open to going in unconventional directions, and not following the status quo within the industry. This is another moment when she can redefine her work, and Kamali doesn’t want to miss the chance to engage in new creative outlets. There’s a lot of fear, but there’s so much more opportunity,” she says. “I’m having a wonderful time playing around with [AI] and asking it to play with my ideas.”
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E-Commerce
Your company has rolled out AI like its a new office uniform. Everyones using it. And unlike most uniforms, people are using it even when they are told not to. As a result, your inbox clears itself, your reports write themselves, and meetings collapse into neat little summaries at the click of a button. You may be even be fantasizing about sending your digital clone to those pointless meetings, and perhaps your colleagues have done so already (which may explain their perfect attendance record). And yet, theres a difference between outsourcing pointless tasks to AI, and making work better (which also requires you to figure out what to do with the time you save). Plainly put, if you are running faster in the wrong direction you will only get to the wrong place faster. This may explain the recent resurgence of an old paradox, Robert Solows law, which in the late 1980s noted that You can see the computer age everywhere but in the productivity statistics.” What are you really using AI for? Right now, most companies treat AI like an espresso shot for knowledge workers. A jolt to help fire off emails, draft decks, or summarize meetings. It feels like magic, but magic tricks dont grow the bottom line. Saving a few minutes here and there is like sweeping the kitchen when the roof is leaking. Part of AIs seduction is its smooth, conversational interface. Ask, and you shall receive. But business value doesnt appear by asking polite questions: It usually requires hard structural change. And so far, AIs biggest impact has been making existing processes leaner, often by replacing the interns and juniors who used to do that work. Think of it as corporate liposuction: It trims the fat, but it doesnt build new muscle. To be sure, as the great Peter Drucker noted, there is nothing so useless as to make more efficiently what should not be done at all, which may explain why, in a resurgence of Solows law, AI is everywhere except in the productivity stats. Cutting costs makes humans twitch Behavioral economists call it loss aversion: We hate losing more than we enjoy winning. Announce that AI will eliminate jobs, and people panic, even when the math adds up. History, though, shows a different pattern: As old tasks disappear, new ones emerge. Just as the rise of spreadsheets created a need for finance analysts, AI will create demand for data governance, ethics, and human oversight. The long arc of technology bends toward job growth, but the bumps along the way are brutal. The real promise of AI isnt subtraction, its addition Netflix recently used generative AI to add an impossible scene to a show, something too costly and complex with traditional methods. Thats the story leaders should chase: holding baseline costs steady and producing something better. AI at its best is not a fancier calculator; its a time machine that lets you create what yesterday was impossible. So what makes a great AI project? Right now, too many organizations are wandering around with a hammer, mistaking everything for a nail. A CEOs blanket mandate, everyone must use AI, is like ordering an army to march without telling them where the battle is. Great AI projects share three ingredients: Volume: Attack the most common, repetitive activities that drive your business. Shave seconds off the thing done a million times, and youve found your goldmine. Variability: Raise the floor. Get average performers closer to your best. Its like tightening a symphony so fewer notes are off-key. Human Glue: Fix the broken joints between systems. AI shines when it eliminates the soul-crushing cut-and-paste that holds organizations hostage. But heres the kicker: speeding up one cog in a broken machine doesnt make the whole machine run better. Unless you reimagine end-to-end processes (often across teams and departments) youre just moving bottlenecks around, and should really not expect great results. Data: the ceiling that caps your ambitions AI is like a gourmet chef: It can cook only with the ingredients you give it. If your data is stale, inconsistent, or scattered across warring silos, dont expect a Michelin-starred meal. Most firms have exquisite data in a few areas (finance, operations), but HR and talent data? Thats like a pantry filled with mystery cans. You know who got promoted, but not why. You feel when a team clicks, but cant quantify it in machine-readable terms. Without proprietary, well-structured data, your competitive advantage is just reheating the same meal as everyone else. Culture: the silent killer Even the sharpest AI project can crash into an organizations immune system. A culture obsessed with cost-cutting breeds fear. Misaligned incentives choke collaboration. A weak communication culture makes change management impossible. Remember, 80% of change projects fail, and AI doesnt get a free pass (it is still a change management task, and very much led by humans). Layoffs may feel like the obvious shortcut, but decades of research show that slashing headcount first is like burning the furniture to heat the house. It buys a little time, but undermines long-term survival. Leaders need to show courage, humility, and clarity. Employees, meanwhile, can choose to be architects of change instead of passive victimsreimagining work, learning new skills, and using AI as a career lever rather than a threat. Doin Better Right now, too many firms are playing the corporate equivalent of toddler soccer: everyone chasing the ball, no strategy, lots of shouting. Winning with AI depends on three foundations: The right technology, deployed against the right problems The right data, accurate and unique The right culture, aligned and prepared for change Everything else is noise. The lesson is clear: AI is not the main course, it is the fire. It can burn the house down, or it can cook a feast no one thought possible. What separates the two outcomes is not the cleverness of the algorithms, but the imagination of the people deploying them. If leaders see AI only as a knife for trimming costs, they will eventually cut into the bone of their own organizations. But if they see it as a telescope (an instrument that lets us glimpse horizons we couldnt see before) then AI becomes a catalyst for growth, innovation, and human potential. The future wont be won by those who use AI most quickly, but by those who use it most wisely: to create new value, to elevate human talent, and to turn technological possibility into strategic reality.
Category:
E-Commerce
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