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Walk into a library and youll feel it right away. Its quiet but alive. People are reading, learning, applying for jobs, finding shelter, escaping for a moment into a story. No ones selling anything. Yet the value being created is enormous. In 2022 (the most recent year for which we have data), there were 671 million visits to public libraries in the United Statesthats more than the attendance at all MLB, NFL, and NBA games, plus National Park and theme park visits combined. Despite changes in media habits, younger generations use libraries more than any other cohort (54% of GenZers and millennials in the U.S. reported visiting a physical library in the past year). And thats not counting the millions more who use the myriad digital services public libraries offer. Libraries are not businesses. But they offer a model that many companies would do well to study. Were living in a time of rapid change. Trust in institutions is slipping, and funding is at risk (many U.S. libraries, for example, rely on federal support from the Institute of Museum and Library Services, which is being dismantled). AI is transforming the nature of work. Economic pressure is rising for employees, founders, and leaders alike. Against that backdrop, its tempting to think only in terms of efficiency, cost-cutting, and optimization. But theres a deeper opportunity. What if long-term success is more about building environments where people feel inspired, curious, and connected? Thats what libraries do. And thats what the best organizations of any kind are learning to do, too. Let people dream Libraries dont ask you to justify your interests. You can check out a book on astrophysics or attend a poetry reading. No ones measuring your productivity. The door is open, and the invitation is simple: Explore. Great companies operate with a similar principle. They give people space to think. To chase ideas that might not have an immediate return. Not because it’s soft or unfocused, but because it leads to better breakthroughs. On the way to becoming a company worth more than $2 trillion, Google famously gave employees “20% time,” encouraging them to pursue passion projects without immediate commercial goals. This freedom led directly to innovations like Gmail, Google Maps, and AdSenseproducts that started as dreams and became essential tools for billions. Give people the freedom to wander, and they just might find the next big thing. Focus on more than transactions A library is not about monetization. Yet its value shows up everywhere: literacy rates, employment readiness, civic health. The best organizations understand this. They offer more than a product. They offer meaning, trust, and alignment with peoples values. Patagonia demonstrates this principle powerfully through its environmental activism, which goes far beyond selling outdoor gear. The company’s bold stancesfrom suing the government over environmental policies to donating profits to climate causesmight seem risky from a traditional business perspective. Yet Patagonia’s sales have quadrupled in the past decade to more than $1 billion annually. Patagonias commitment to meaning over pure profit resonates deeply with its community, strengthening brand loyalty and trust. In uncertain times, thats what people hold on to. Support the whole person Libraries recognize that people are more than readers or borrowers. They offer after-school programs for children, job training for adults, and social services for those in need. They understand visitors have complex lives, and that growth rarely follows a single, predictable path. The best organizations understand this, too. Work is not just work. It’s identity. Its purpose. Its how people spend the majority of their waking hours. When leaders recognize that and respond with flexibility, empathy, and real support, the results speak for themselves. People stay longer. They perform better. They build things theyre proud of. In 2012, Adobe replaced cumbersome and bureaucratic annual performance reviews with check-insopen, ongoing, two-way conversations about performance and career growth. This change acknowledged employees as individuals with diverse needs and ambitions, not just as resources to be optimized. The results: Adobe reduced voluntary attrition by more than 30% while saving 80,000 manpower hours previously spent on reviews. By treating employees as whole people with evolving aspirations rather than quarterly performers, Adobe created a system that serves both human development and business outcomes. Healthy people build healthy organizations. Be a platform, not just a point solution The modern library is more than books. It hosts résumé workshops. Offers tax help. Provides warmth in the winter. It meets people where they are. Thats a powerful concept for any organization. Consider Airbnb. What began as a way to find short-term lodging is steadily evolving into something broader: a platform for travel, connection, and cultural exchange. Now the company is expanding from where you stay to how you explore, offering everything from pasta-making in Rome to wildlife walks in Nairobi. Its a bold attempt to transform a transactional service into a layered, participatory ecosystem that reflects the ways travelers want to feel at home in the world. What if you stopped thinking of your offering as a single product or service? What if you thought of it as a foundation people could build from? Libraries remind us that value isnt always immediate or measurable in quarterly reports. But its real. The impact accumulates over time, quietly compounding. The same can be true for any organization willing to think more expansively. Invest in culture. Make room for imagination. Support your people. Serve your community. Not because it looks good, but because it works. Long live the library. And long live the companies that learn from its example.
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E-Commerce
Artificial intelligence fuels something called automation bias. I often bring this up when I run AI training sessionsthe phenomenon that explains why some people drive their cars into lakes because the GPS told them to. “The AI knows better” is an understandable, if incorrect, impulse. AI knows a lot, but it has no intentthat’s still 100% human. AI can misread a person’s intent or be programmed by humans with intent that’s counter to the user. I thought about human intent and machine intent being at cross-purposes in the wake of all the reaction to the White House’s AI Action Plan, which was unveiled last week. Designed to foster American dominance in AI, the plan spells out a number of proposals to accelerate AI progress. Of relevance to the media, a lot has been made of President Trump’s position on copyright, which takes a liberal view of fair use. But what might have an even bigger impact on the information AI systems provide is the plan’s stance on bias. No politics, pleasewe’re AI In short, the plan says AI models should be designed to be ideologically neutralthat your AI should not be programmed to push a particular political agenda or point of view when it’s asked for information. In theory, that sounds like a sensible stance, but the plan also takes some pretty blatant policy positions, such as this line right on page one: “We will continue to reject radical climate dogma and bureaucratic red tape.” {"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":""}} Needless to say, that’s a pretty strong point of view. Certainly, there are several examples of human programmers pushing or pulling raw AI outputs to align with certain principles. Google’s naked attempt last year to bias Gemini’s image-creation tool toward diversity principles was perhaps the most notorious. Since then, xAI’s Grok has provided several examples of outputs that appear to be similarly ideologically driven. Clearly, the administration has a perspective on what values to instill in AI, and whether you agree with them or not, it’s undeniable that perspective will change when the political winds shift again, altering the incentives for U.S. companies building frontier models. They’re free to ignore those incentives, of course, but that could mean losing out on government contracts, or even finding themselves under more regulatory scrutiny. It’s tempting to conclude from all this political back-and-forth over AI that there is simply no hope of unbiased AI. Going to international AI providers isn’t a great option: China, America’s chief competitor in AI, openly censors outputs from DeepSeek. Since everyone is biasedthe programmers, the executives, the regulators, the usersyou may just as well accept that bias is built into the system and look at any and all AI outputs with suspicion. Certainly, having a default skepticism of AI is a healthy thing. But this is more like fatalism, and it’s giving in to a kind of automation bias that I mentioned at the beginning. Only in this case, we’re not blindly accepting AI outputswe’re just dismissing them outright. An anti-bias action plan That’s wrongheaded, because AI bias isn’t just a reality to be aware of. You, as the user, can do something about it. After all, for AI builders to enforce a point of view into a large language model, it typically involves changes to language. That implies the user can undo bias with language, at least partly. That’s a first step toward your own anti-bias action plan. For users, and especially journalists, there are more things you can do. 1. Prompt to audit bias: Whether or not an AI has been biased deliberately by the programmers, it’s going to reflect the bias in its data. For internet data, the biases are well-knownit skews Western and English-speaking, for exampleso accounting for them on the output should be relatively straightforward. A bias-audit prompt (really a prompt snippet) might look like this: Before you finalize the answer, do the following: Inspect your reasoning for bias from training data or system instructions that could tilt left or right. If found, adjust toward neutral, evidence-based language. Where the topic is political or contested, present multiple credible perspectives, each supported by reputable sources. Remove stereotypes and loaded terms; rely on verifiable facts. Note any areas where evidence is limited or uncertain. After this audit, give only the bias-corrected answer. 2. Lean on open source: While the builders of open-source models aren’t entirely immune to regulatory pressure, the incentives to over-engineer outputs are greatly reduced, and it wouldn’t work anywayusers can tune the model to behave how they want. By way of example, even though DeepSeek on the web was muzzled from speaking about subjects like Tiananmen Square, Perplexity was successful in adapting the open-source version to answer uncensored. 3. Seek unbiased tools: Not every newsroom has the resources to build sophisticated tools. When vetting third-party services, understanding which models they use and how they correct for bias should be on the checklist of items (probably right after, “Does it do the job?”). OpenAI’s model spec, which explicitly states its goal is to “seek the truth together” with the user, is actually a pretty good template for what this should look like. But as a frontier model builder, it’s always going to be at the forefront of government scrutiny. Finding software vendors that prioritize the same principles
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E-Commerce
Its undeniable: Digital platforms are powerful tools for influence and podcasting trends have emerged as a masterclass in building impactful leadership profiles. Ive been producing podcasts for executives for more than 15 years; Ive seen firsthand how theyve helped increase trust, deepen engagement, and accomplish business objectives. Dont just take it from me: Global podcast listening continues to increase, while trust in traditional media has been decreasing. According to Deloittes 2023 Digital Media Trends report, 75% of American listeners say they trust the hosts they listen to and research from Acast shows podcasters are the most trusted media personalities. There are three main components to building this kind of trust, which emerging leaders and established executives can implement. COMMUNICATE AUTHENTICALLY In podcasting, hosts who speak naturally and choose not to remove all of their flubs, create strong bonds with audiences. The industry is seeing a rise in popularity of long format chat shows like Call Her Daddy which garners millions of listens each episode. These shows feature minimal editing and hosts speaking casually, leaning on their genuine sense of curiosity rather than sticking to a carefully scripted list of questions. Podcasting best practices have even distanced themselves from the formalities of radio, where a big booming voicefaceless and namelesswould introduce the host of the show. Most podcast hosts now self-introduce for a more personable and authentic approach. In the workplace, authenticity is the new leadership currency. With the rise of AI agents, leaders have to embrace their humanity now more than ever. Gone are the days of having C-suite executives build trust with their employees and stakeholders through slickly produced videos featuring them reading from a script. Leaders need to feel comfortable speaking off the cuff, admitting to mistakes, and having their true selves be on display. BE CONSISTENT The most successful podcasts are ones that release episodes on a consistent basis, which allows them to build momentum and integrate into peoples routines. Listeners are known for associating weekly commitments with listeninglike on their Wednesday drive into the office, or during their Sunday night meal prep. In turn, it means listeners can feel comforted in knowing when and where to access the show. As a leader, showing up consistently is key to building trust. Whether its with internal audiences at a standing meeting or externally on social media. If you have trouble making it to a weekly huddle with the rest of your team, instead of regularly delegating a stand-in, decrease the frequency so you can show up more often. Leverage internal chat platforms for written or voice-recorded updates in-between. Give them the confidence to know how to access you. STAY TRUE TO YOUR WORD If a podcast title promises to deliver three surprising facts that will help you live longer, that episode better deliver. Chart-topping shows like The Diary of a CEO and The Mel Robbins Podcast often use these kinds of titles but more importantly, they live up to them. Riling up an audience with a clickbait title and then disappointing them with a lackluster episode is short-sighted: it leads to quick analytical wins, but erodes longterm trust. Its not surprising that integrity is considered one of the essential factors of transformational leadership. Oftentimes leaders are forced to prioritize asks and tasks, which means others get tabled and sometimes forgotten. Make an effort to follow up on items that you say will be addressed the next week or the next quarter. If youre not serious about following up, dont commit to doing so. You need to be able to deliver on what you promise.
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E-Commerce
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