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In Aesops fable “The North Wind and the Sun,” the two forces of nature argue over who is stronger. To settle the debate, they test their power on a passing traveler by trying to remove his cloak. The North Wind blows fiercely, but the traveler only clutches his cloak tighter. But the Sun shines gently, gradually warming the man until he willingly takes it off. The story illustrates that persuasion is often more effective than force, but theres also a lesson about leadership tucked inside it. When you lead with pressure, you create an environment of resistance and insecurity. But when you lead with empathy and humility, others are more likely to follow your direction. Thats been my experience as CEO for nearly two decades. I often look to an unlikely team as a model for great leadership: our customer service team. Their work is grounded in empathy, responsiveness, and relationship-buildingqualities that earn customer loyalty. When leaders apply the same principles, they foster more engaged, motivated teams, and that benefits the company at every level. Heres a closer look at what customer service taught me about leadership. Empathy leads to better results At my company, we carefully track customer service calls to continually improve the user experience. Im consistently impressed by the complexity of these conversations and by how our team handles them with both tact and empathy. We know that no one (well, almost no one) wants to spend their time calling customer service. So the team makes it a priority to truly understand a users needs and resolve issues as efficiently and thoughtfully as possible. Leaders who take a similar approachlistening closely, responding empathetically, and aiming to meet employees needsset the tone for a more engaged workplace with a greater sense of wellbeing. A recent review of studies on empathetic leadership found that its linked to higher employee engagement, lower turnover, and better performance, particularly during uncertain times. Even more compelling, the research showed a pay it forward effect: Empathy from leadership tends to inspire empathy throughout the organization. Just like a great customer service team, strong leaders make it a practice to listen carefully and respond thoughtfully. Transparency builds trust Clear, transparent communication is essential to efficient customer service. It starts with active listening: Representatives must tune in to the root of a user’s question or concern, then summarize it to ensure both parties are on the same page. Then, they can resolve the issue or escalate it appropriately. Leaders should cultivate this same dynamic with employees. Communication should be a two-way dialogue, where both sides ask questions, listen deeply, and aim for mutual understanding. The old modelwhere employees operate in the dark while leaders hoard informationis no longer effective. Especially in times of rapid, unpredictable change, open communication is critical to employee wellbeing and performance. Take the advent of AI. In a recent YouGov survey, 49% of U.S. respondents said they felt concerned about AI, while 22% said they were scared. Transparent communication, like explaining the best ways to leverage the technology and continually checking in to see how theyre adapting to it, is a powerful way to quell ongoing concerns. Adaptability isnt optional When we interview candidates for customer service roles, one of the top traits we look for is the ability to think on their feet. These employees face novel issues daily and must adapt in real time, finding creative solutions on the fly. So we might ask them to walk us through a conversation regarding a tricky issue. For example, a frustrated user is demanding a refund; the company policy says refunds are only given after 14 days, and its only been 7. How do you proceed? Adaptability is likewise a requisite trait for todays most effective leaders. Try this adaptability mantra from Olympic gold medalist Lindsey Vonn: first, stay focused on your goal. Then, when facing a challenge, ask yourself, how can I reframe this situation as an opportunity to get closer to my goal? This reframefrom adversity to an opportunity to growgives a window into becoming more adaptable. Its one thing to think quickly in the moment; its another to pause, zoom out, and reframe problems when the pressure mounts. For leaders, both skills are necessary. Its easy to get lost in the minutiae of daily issues, especially when juggling the concerns of others. But keeping your broader mission in focusyour own North Starcan help reframe challenges as opportunities. By channeling the mindset of a great customer service rep, leaders can stay on their toes while guiding their teams through uncertainty.
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E-Commerce
If you want to understand how even modern American cities became hostile to human life, dont start with the political conspiracies; look at the way city planners and road engineers calculate success. Every day, public agencies across the country greenlight projects that cost millions of dollars, destroy neighborhoods, and ultimately kill peopleall in the name of saving drivers a few seconds. This is standard operating procedure, justified by a single, dangerous metric: vehicular delay. In transportation bureaucratese, its called Level of Service (LOS). Think of it as a report card with grades A to F describing how freely cars move. But this grade has nothing to do with safety, quality of life, economic productivity, or human flourishing. Its entirely about how long a vehicle waits at an intersection or slows down during rush hour. The built environment is shaped around that metric. {"blockType":"creator-network-promo","data":{"mediaUrl":"","headline":"Urbanism Speakeasy","description":"Join Andy Boenau as he explores ideas that the infrastructure status quo would rather keep quiet. To learn more, visit urbanismspeakeasy.com.","substackDomain":"https:\/\/www.urbanismspeakeasy.com\/","colorTheme":"salmon","redirectUrl":""}} Take a look at this table that status quo planners and engineers use to measure an intersections performance. [Image: courtesy of the author] Experts give a failing grade to an intersection where people wait a little over a minute before going about their business. Taxpayers are forced to chip in for road expansion projects that cost hundreds of millions of dollars to buildprojects justified by the impatient nature of drivers. It gets worse. The intersections are graded during the busiest hour of the busiest day of a week. If the experts were honest about their analysis, theyd tell you the following: During the busiest hour of the day, the average driver waits 30 seconds at the stop sign. We give that a grade of D. The other 23 hours of the day dont matter. The average person attending a public hearing has been trained since early childhood that A is good and F is bad. So even if they dont like the idea of the local government seizing their front yard in order to widen a street to improve LOS, normies assume road expansions are for the greater good. Such is the treacherous nature of LOS. But wait, it gets even worse. Fortune-telling replaces advanced education and engineering judgment as the experts responsible for designing transportation systems use manuals that are the equivalent of Magic 8 Balls to ask if we need more space for car traffic decades into the future. The answer, of course, is always Signs point to yes. Again, if they were honest, the forecasting analysis would be described like this: The transportation department is guessing that 20 years from now, the average driver might have to wait an entire minute at the stop sign. We give that a grade of F. The other 23 hours of the day wont matter. With the prophecy of more traffic in hand, engineers not only design todays streets to earn good grades on the pseudoscience report card, they design for a future they cant possibly predict. With infrastructure designed for high-volume, high-speed, low-delay motor vehicles, anyone wanting to walk or ride a bike is put into a lethal game of Frogger. When a city does create bus and bicycle infrastructure to shift trips from vehicles to other modes, the traffic report cards dont reflect the fact that people have options. Its solely focused on cars. Theres no redeeming quality to LOS. This obsession with delay has had disastrous effects. When your only metric is vehicle throughput, you end up designing highways through neighborhoods, not places worth living in. A traffic engineer will tell you its more efficient to eliminate street parking and narrow sidewalks to make room for a dedicated right-turn lane. The spreadsheet says so. But that same design makes it harder to cross the street, harder to linger, harder to be a human being. The math checks out, the morality doesnt. A status quo success story is when a road expansion allows a driver to get home 18 seconds sooner but makes it impossible for a child to safely bike to the library. Every single intersection is analyzed and graded based on seconds of delay for drivers. So every single intersection needs more lanes to pump as much car traffic as quickly as possible through an intersection. Anything else (moms pushing strollers, grandparents with canes, kids on bicycles) interferes with LOS. Here are three important questions for experts to ponder: Is slow-moving car traffic ever safer than fast-moving traffic? Do we have any obligation to provide safe and convenient access for people when they arent inside cars? What are the economic downsides of wider, faster streets in the central business district? When planners and engineers truly wrestle with those questions, they can choose to remain a conformist who ignores the damage of traffic metrics, or become an outlier in the industry and make a positive impact that might be felt for generations to come. Things can get better in the end. {"blockType":"creator-network-promo","data":{"mediaUrl":"","headline":"Urbanism Speakeasy","description":"Join Andy Boenau as he explores ideas that the infrastructure status quo would rather keep quiet. To learn more, visit urbanismspeakeasy.com.","substackDomain":"https:\/\/www.urbanismspeakeasy.com\/","colorTheme":"salmon","redirectUrl":""}}
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The AI copyright courtroom is heating up. In back-to-back rulings last week, the ongoing legal war between AI companies and content creators has significantly shifted, ostensibly favoring the former. First, Anthropic got the better outcome of a case that examined whether it could claim “fair use” over its ingestion of large book archives to feed its Claude AI models. In another case, a federal judge said Meta did not violate the copyright of several well-known authors who sued the company for training its Llama models on their books. At a glance, this looks bad if you’re an author or content creator. Although neither case necessarily sets a precedent (the judge in the Meta case even went out of his way to emphasize how narrowly focused it was), two copyright rulings coming down so quickly and definitively on the side of AI companies is a signalone that suggests “fair use” will be an effective shield for them, potentially even in higher-stakes cases like the ones involving The New York Times and News Corp. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}} As always, the reality is a little more complicated. The outcomes of both cases were more mixed than the headlines suggest, and they are also deeply instructive. Far from closing the door on copyright holders, they point to places where litigants might find a key. What the Anthropic ruling says about AI inputs vs. outputs Before I get going, I need to point out that I’m not a lawyer. What I offer here is my analysis of the cases based on my experience as a journalist and media executive and what I’ve learned following this space for the past two years. Consider this general guidance for those curious about what’s going on, but if you or your company is in the process of arguing one of these cases or thinking about legal action, you should consult a lawyer, preferably one who specializes in copyright law. Speaking of, here’s a little refresher on that: Copyright law is well defined in the U.S., and it provides for a defense for certain violations, known as fair use. Almost all of the AI companies at the forefront of building models rely on this defense. Determining whether a fair-use defense holds water comes down to four factors: The purpose of the use, or whether it was for commercial or noncommercial purposes. Courts will be more forgiving for the latter, but obviously what the AI companies are doing is a massively commercial exercise. This also covers whether the allegedly violating work is a direct copy or “transformative.” Many have said that AI outputs, because they aren’t word-for-word copies and usually rely on many different sources, are transformative. The nature of the copyrighted work: More protection usually goes to creative works than factual ones. AI systems often deal with both. How much of the original work was copied: Reproducing short excerpts is usually OK, but AI companies typically ingest entire works for training. Courts have sometimes tolerated full copying as long as the output doesnt reproduce the entire work or big chunks verbatim. Whether the violation caused market harm: This is a large focus in these cases and other ongoing litigation. The outcome of the Anthropic case drew some lines between what was OK and what wasn’t. The fact is, anyone can buy a book, and for the books that were legally obtained, the judge said that training its AI on them qualified as fair use. However, if those books were illegally obtainedi.e. piratedthat would amount to a copyright violation. Since many of them undoubtedly were, Anthropic might still pay a price for training on the illegally copied books that happened to be in the archives. An important aspect of the Anthropic case is that it focuses on the inputs of AI systems as opposed to the outputs. In other words, it answers the question, “Is copying a whole bunch of books a violation, independent of what you’re doing with them?” with “No.” In his ruling, the judge cited the precedent-setting case of Authors Guild, Inc. v. Google, Inc. from 2015. That case concluded Google was within its rights to copy books for an online database, and the Anthropic ruling is a powerful signal that extends the concept into the AI realm. However, the Google case came out in favor of fair use in large part because the outputs of Google Books are limited to excerpts, not entire books. This is important, because a surface-level reading of the Anthropic case might make you think that, if an AI service pays for a copy of something, it can do whatever it wants with it. For example, if you wanted to use the entire archive of The Information, all you’d need to do is pay the annual subscription. But for digital subscriptions, the permission is to access and read, not to copy and repurpose. Courts have not ruled that buying a digital subscription alone licenses AI training, even though many might read it that way. The missing piece in the Meta case: harm The Meta case has a little bit to say about that, and it has to do with the fourth point of fair-use defense: market harm. The reason the judge ruled in favor of Meta was because the authors, which include comedian Sarah Silverman and journalist Ta-Nehisi Coates, weren’t able to prove that they had suffered a decline in book sales. While that gives a green light for an AI to train on copyrighted works as long as it doesn’t negatively affect their commercial potential, the reverse is also true: content creators will be more successful in court if they can show that it does. In fact, that’s exactly what happened earlier this year. In February, Thomson Reuters scored a win against a now-defunct AI company called Ross Intelligence in a ruling that rejected Ross’s claims of fair use for training on material derived from Thomson Reuters’ content. Ross’s business model centered around a product that competed directly with the source of the content, Westlaw, Thomson Reuters’s online legal research service. That was clear market harm in the judge’s eyes. Taken together, the three cases point to a clearer path forward for publishers building copyright cases against Big AI: Focus on outputs instead of inputs: It’s not enough that someone hoovered up your work. To build a solid case, you need to show that what the AI company did with it reproduced it in some form. So far, no court has definitively decided whether AI outputs are meaningfully different enough to count as “transformative” in the eyes of copyright law, but it should be noted that courts have ruled in the past that copyright violation can occur even when small parts of the work are copiedif those parts represent the “heart” of the original. Show market harm: This looks increasingly like the main battle. Now that we have a lot of data on how AI search engines and chatbotswhich, to be clear, are outputsare affecting the online behavior of news consumers, the case that an AI service harms the media market is easier to make than it was a year ago. In addition, the emergence of licensing deals between publishers and AI companies is evidence that there’s market harm by creating outputs without offering such a deal. Question source legitimacy: Was the content legally acquired or pirated? The Anthropic case opens this up as a possible attack vector for publishers. If they can prove scraping occurred through paywallswithout subscribing firstthat could be a violation even absent any outputs. The case for a better case This area of law is evolving rapidly. There will certainly be appeals for these cases and others that are still pending, and there’s a good chance this all ends up at the Supreme Court. Also, regulators or Congress could change the rules. The Trump administration has hardly been silent on the issue: It recently fired the head of the U.S. Copyright Office, ostensibly over its changing stance on AI, and when it solicited public comment on its AI action plan, both OpenAI and Google took the opportunity to argue for signing their interpretation of fair use into law. For now, though, publishers and content creators have a better guide to strengthening their copyright cases. The recent court rulings don’t mean copyright holders can’t win, but that the broad “AI eats everything” narrative won’t win by itself. Plaintiffs will need to show that outputs are market substitutes, the financial harm is real, or that the AI companies used pirated sources in their training sets. The rulings aren’t saying dont suethey show how to sue well. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}}
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