15. AI Misuse and Laziness

Email: bidemiologunde@gmail.com

In this episode, host Bidemi Ologunde examines a modern paradox: how the misuse of AI can make laziness look productive. What happens when polished outputs replace real thinking? When speed starts to masquerade as substance? And how can ambitious professionals, builders, leaders, athletes, performers, students, and diaspora listeners use AI in ways that support sustainable excellence rather than hollow performance? Through recent real-world examples, Bidemi explores how to use powerful tools without outsourcing judgment, ownership, or craft. Listeners are also invited to take part in this week's challenge and continue the conversation inside the show's private WhatsApp Community.

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Transcript

SPEAKER_00 0:47

Imagine this. It's a Sunday morning. Someone is holding a fresh newspaper, coffee in one hand, hope in the other. They turn to a summer reading list, circle a few promising titles, maybe even text a friend. I'm picking this up this week. And then hours later, they discover that several of those books do not exist. Real authors, but fake titles, clean formatting, confident summaries, polished nonsense. In May 2025, that is exactly what happened when a syndicated summer supplement carried by the Chicago Sun Times and the Philadelphia Inquirer included AI-generated recommendations for books that were never written. The freelancer behind it admitted he used AI in developing the piece and failed to fact-check it. The fallout was immediate. Public embarrassment, broken trust, the supplements removed, and the writer fired. So that story matters because it captures a modern danger in one scene. Something can look finished, sound intelligent, and still be completely unserious. That is the paradox I want to talk about today. The misuse of AI can make laziness look productive. Not laziness in the childish sense, not laziness as in doing nothing. I mean a more sophisticated kind of laziness, outsourcing the hard parts of work while keeping the appearance of work. Skipping the thinking but keeping the formatting. Avoiding the rep but delivering the summary. Handing off the judgment, but still taking credit for the output. And that is where this gets dangerous. Because AI is incredibly good at producing the signals of effort. AI is incredibly good at producing the signals of effort. It can generate text, slides, summaries, emails, captions, proposals, scripts, research notes, customer replies, and code suggestions at speed. So if we're not careful, we stop measuring work by depth, truth, usefulness, or ownership. We start measuring it by volume, polish, and speed. And once that happens, laziness no longer looks like laziness, it looks like efficiency. But sustainable excellence is not built on that. Sustainable excellence is not hustle culture. It's not do more, sleep less, post harder. It is not frantic output just for applause. Sustainable excellence is doing work you can stand behind at a pace you can repeat with standards that do not collapse the moment the pressure rises. Sustainable excellence is doing work you can stand behind at a pace you can repeat with standards that do not collapse the moment the pressure rises. It is excellence with lungs, excellence with integrity, excellence that does not require you to become a machine in order to compete with one. The last two years have given us multiple warnings. Take Air Canada. In a case that became a global example, a customer named Jake Moffat relied on information from Air Canada's website chatbot about a bereavement fare. The chatbot gave him the wrong answer. When he followed that guidance and later sought the discount, the airline refused. In February 2024, the British Columbia Civil Resolution Tribunal found Air Canada liable for negligent misrepresentation. The tribunal rejected the idea that the chatbot was somehow a separate legal entity and said the company remained responsible for what its AI2 told customers. Now notice what happened there. The company saved time at the front end by automating a customer interaction. But on the back end, the cost was trust, legal exposure, and reputational damage. That is one of the defining features of AI misuse. It borrows speed from the future and sends the bill back later. Then there is a legal world where precision is not optional. In February 2025, a federal judge sanctioned three lawyers in a lawsuit against Walmart after a filing included fake case citations generated by AI. One attorney was fined $3,000 and removed from the case. Two others were fined $1,000 each for failing to ensure the filing was accurate. Think about that for a second. In a profession built on verification, people used a machine to manufacture the appearance of research and then submitted fiction with legal formatting. That is not productivity, that is decorative irresponsibility. And then there is politics. In the run-up to the New Hampshire 2024 Democratic Primary, voters received robocalls using an AI-generated voice imitating former President Joe Biden, telling them to save their votes for November instead of voting in the primary. Federal regulators later finalized a $6 million fine against political consultant Steve Kramer, saying the deep fake robocalls used spoofed colour ID and targeted potential voters two days before the election. This is the same pattern in a more dangerous form. Technology used to scale deception while preserving the illusion of authenticity. And even in business, where AI is often sold as a clean productivity win, the lesson has become more complicated than the headlines suggest. Clarina announced in early 2024 that its AI assistant, powered by OpenAI, was handling two-thirds of customer service charts and doing the equivalent work of 700 full-time agents. But later reporting from AP showed the results were mixed and that the company still needed higher skilled human support for more complex issues such as identity theft and had brought some people back in to handle those cases. Faster is not always better. Sometimes faster only means the easy part got automated. The hard part, empathy, edge cases, accountability, discernment, was still waiting for a human being. So here is the core message for this episode. AI is a powerful tool, but when people use it to avoid effort instead of upgrading effort, it creates counterfeit productivity. Counterfeit productivity is when the output grows but the person does not. Counterfeit productivity is when your drafts improve but your judgment weakens. Counterfeit productivity is when your inbox gets cleared, but your thinking gets outsourced. Counterfeit productivity is when you look efficient to other people while becoming more fragile in private. That is the paradox. When used well, AI can reduce waste. When used poorly, AI removes the very friction through which competence is built. And that matters whether you are an operator early in your career, a mid-career professional carrying real responsibility, a founder making decisions with imperfect information, a freelancer trying to protect your reputation, a creator trying to protect your voice, a student launching a career, a manager trying to lead fairly, an athlete reviewing performance, a performer sharpening craft, or someone in the diaspora balancing ambition across multiple worlds, multiple obligations, and in most cases, several time zones. So what does healthy use actually look like? I want to give you a simple operating system. First, start with your own brain before you start with the machine. Before you open ChatGPT or Cloud or Gemini or Copilot or any other AI assistant, write three simple bullets. First one, what is the problem? Second one, what does good look like? Third one, what must be true when I'm done? That small pause matters because if you don't define the work, the tool will define it for you. And when the tool defines the work, you usually get something fluent instead of something fitted. Second, divide every task into three buckets. Generate, verify, decide. AI is excellent for generating options. Humans must verify what is true, and humans must decide what is wise. Use AI to brainstorm subject lines, summarize notes, draft a first pass, generate alternatives, organize raw material, or surface blind spots. Do not let it be the final judge of facts, the final owner of strategy, or the final voice in moments that affect trust. Third, protect your red zones. There are some areas where delegation to AI should be limited, slow, and supervised, such as high-stakes emails, client promises, legal claims, financial commitments, performance reviews, public statements, health decisions, and basically any communication where tone, truth, and consequence are tightly connected. If it can damage a relationship, a reputation, a livelihood, or a community, it deserves more than autocomplete. Fourth, never use AI to escape the raps that make you good. If you are a writer, don't outsource all of your writing. If you are a strategist, don't outsource first principles thinking. If you are a manager, don't outsource difficult conversations. If you're a student, don't outsource comprehension. If you're an athlete or a performer, don't mistake analysis for training. Use AI to support practice, not to replace practice. Because the skill you stop exercising is the skill you eventually lose. Last but not least, measure quality, not just speed. Ask better questions. Did this save time without lowering truth? Did this reduce friction without reducing ownership? Did this make the work clearer, kinder, sharper, or more useful? Would I still be proud to attach my name to this if everyone knew exactly how it was made? So that last question is powerful. Would I still be proud of this if the process were visible? If the answer is no, that is not smart leverage. That is concealed weakness. Now I also want to say this clearly. That would be unserious. The answer is to refuse lazy adoption. The future does not belong to the people who use AI most recklessly. The future belongs to the people who can combine tools with standards, speed with truth, scale with judgment, assistance with ownership. In other words, the winners will not simply be the fastest, they will be the most trustworthy under acceleration. And that is a very different ambition from Hospital. Horse culture tells people to produce endlessly. Sustainable excellence asks people to produce deliberately. Hossoculture glorifies visible grind. Sustainable excellence values durable capacity. Horse culture says, How can I do more? Sustainable Excellence asks, how can I do meaningful work well, consistently, without hollowing myself out? That is a healthier question. And honestly, it is a more elite question too. Because anyone can be noisy for a season. What is rare is being useful for a long time. So here is this week's challenge for our private WhatsApp community. For the next seven days, practice the human first AI challenge. Before every meaningful use of AI, do these four things. 1. Write your own three bullets first. The problem, the goal, and the non-negotiable. 2. Use AI only for one of these purposes. Generate, organize, or refine. 3. Manually verify one important claim, one key assumption, or one sensitive detail. 4. Share one short reflection in our private WhatsApp community using this format. Here is what I used AI for. Here is what I refused to outsource, and here is what improved. Keep it simple: a text post, a screenshot, or even a 30-second voice note. If you are an operator, tell us where AI saved you time without lowering your standard. If you are a founder or creator, tell us where you kept your voice instead of borrowing one. If you are a student or early career professional, tell us where you used AI to learn instead of merely submit. If you're a manager, tell us where you chose presence over automation. If you're an athlete or performer, tell us where you used AI for review, but still honored the reps. If you're navigating life in the diaspora, tell us how you use these tools without letting convenience flatten your identity, judgment, or relationships. At the end of the week, do not ask only how much faster was I. Ask, did I become sharper? Did I become more responsible? Did my work remain mine? Because that is the real goal. The goal is not to prove that you can make a machine produce something. The goal is to prove that you can remain a serious human being in a world drowning in synthetic competence. And that to me personally is the work ethic that will matter now. Not panic, not posturing, not hustle culture for the camera. But disciplined ownership, clear standards, calm excellence, and the wisdom to use powerful tools without becoming weak from using them. That is the difference between looking productive and becoming exceptional. And that is the work.