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Charlotte Blease is an associate professor in the medical faculty at Uppsala University in Sweden. She is also a researcher in the Digital Psychiatry Program at Harvard Medical School. Whats the big idea? Humans are fallible . . . and unfortunately, that applies to doctors too. Misdiagnosis and error lead to a considerable number of deaths. Medical professionals have their own biases and limited bandwidth and time to keep up with the latest research developments. Doctors are doing their best, but its possible that AI could do even better. As eerie as it is to consider entrusting your healthcare to a bot, it could be a lifesaver. Below, Charlotte shares five key insights from her new book, Dr. Bot: Why Doctors Can Fail Usand How AI Could Save Lives. Listen to the audio versionread by Charlotte herselfbelow, or in the Next Big Idea App. 1. Medicine is failing us more than we think Every four to five days, a tragedy on the scale of 9/11 strikes, yet hardly anyone notices. On a weekly basis, the equivalent of four airplanes (each carrying 170 people) falls out of the sky, killing all the passengers onboard. These figures dont make the 24-hour news cycle, but the inconceivable is happening. Medical error is one of the leading causes of death in the United States and is responsible for over a quarter of a million fatalities annually. Around one-third of this death toll is due to misdiagnosis. Globally, most people will face a diagnostic error at least once in their lifetime. In Europe, 22 million patients with rare diseases dont have a diagnosis and 8 million wait an average of a decade to get one. In low- or middle-income countries, the misdiagnosis rate is likely to be considerably higher. Errors and misdiagnoses are not the only problems. Modern medicine prides itself on being scientific, yet, studies show that evidence-based treatments are offered only about half the time. And when it comes to accessing medical expertise, healthcare is upside down: Those most in needthe sickest, poorest, the elderly, and the most marginalized in societyare more likely to be left behind. People with disabilities, parents, and part-time workers (including those with gig economy jobs) often struggle to attend checkups. American Time Use Survey data show patients sacrifice an average of two hours for a 20-minute doctors visit, with low-income and unemployed people facing up to 28% longer burdens. Even when we manage to put a foot in the doctors office, patients are not treated equitably. Hippocratic Oaths are sometimes hypocritical oaths, leaving some of us at a disadvantage in the clinic. 2. Doctors are medicines second victims Underneath the commanding professional garb, physicians face realities that patients seldom see. In the U.S., half of all doctors say they are burned out, with 20% reporting they are depressed. An estimated 300 to 400 doctors in the U.S. take their own lives every year. Thats the equivalent of one medical school graduating class dying by suicide annually. By graduation, half of what medical students learn is already outdated. As patient numbers surge, these pressures are only mounting. Doctors are officially a scarce resource. We are not producing enough of them to meet patients needs. The UN forecasts that by 2037, we will share the planet with a billion more people. Longer life and more people carry consequences for doctors and our healthcare systems. In the U.S., by 2050, most people aged 50 or older will live with one or more chronic illnesses. Making matters worse, medical knowledge moves faster than doctors can keep up. It takes approximately 17 years for research to transition from the bench to practice. By graduation, half of what medical students learn is already outdated. And with a new biomedical article published every 39 seconds, even skimming 2% of summaries would take more than 22 hours a day. Nor is the knowledge treadmill shrinking. There are over 7,000 rare diseases, with around 250 more identified each year. Viewed from another angle, its remarkable that doctors get it right as often as they do. 3. AI is resilient Digital tools defy traditional doctor stereotypes. They dont don classic white coats with stethoscopes draped around silicon necks. But they are remarkably resilient. Being devoid of brows and brains, bots dont sweat or stress. They are not hostage to circadian rhythms, low blood sugar, or distractibility. AIs brute computational power means it isnt limited by fleshy constraints. Physicians have barely any time to read, never mind acquire the latest research. They are deprived of their sleep daily. But machines can crunch their way through open-source data at breakneck speed without needing to stop for a breath, a break, or even to take a pee. Like speed-freak bookworms, AI has a stunning capacity to ingest medical publications and data in seconds, 24/7. Where doctors vary in unwanted ways, AI can be more consistent. AI chatbots make errors, too, but the question is, who or what makes fewer mistakes? While much more research is needed, tantalizing studies are proving hard to ignore. Studies demonstrate that some AI tools vastly outperform human doctors in clinical reasoning, including for complex medical conditions. A particular AI superpower is spotting patterns humans miss. In one recent study, researchers fed 50 clinical cases (including 10 rare conditions) into a popular chatbot. It accurately identified 90% of the rare disease diagnoses within eight suggestions, routinely outperforming the doctors in the study. For the one in 10 people worldwide who live with a rare disease, AI could be a lifeline. 4. Bots could be less prejudiced than people Bots are sometimes biased because AI reflects individual and societal prejudices. Its training can embed unwanted biasesgiving rise to the slogan garbage in, garbage out. When unwanted biases are baked into machines, leading to unfair recommendations, this is called algorithmic discrimination. In medicine, there is a huge scope for machines to perpetuate unfair treatment via coded biases. In a 2024 study of ChatGPT 4, researchers found the model was far more likely to diagnose men than women with equally common conditions like COVID-19 and colon cancer. It also recommended fewer CT, MRI, or ultrasound scans for Black patients versus white patients, and it judged white men as more prone to exaggerating pain than any other group. Examining the scope for bias, errors, and safety with AI is crucially important. But this focus often comes with a selective amnesia about the creaking, inherited systems we already rely on. It assumes the status quo of human doctors working in a traditional way is inherently superior. Unfortunately, a wealth of research demonstrates that doctors are biased, too. De-biasing AI is likely a more achievable goal than debiasing doctors split-second decisions in high-pressure clinics. Were better at spotting bias in others than in ourselves. Thats why its a game changer to train AI to do some heavy lifting in healthcare: to flag missing demographics, expose skewed findings, and identify prejudice. AI studies have, at scale, identified discriminatory language embedded in electronic medical records for patients with chronic pain, diabetes, and addictions. AI also shows us that doctors are more likely to use negative descriptors for Black versus white Americans. As uncomfortable as it sounds, de-biasing AI is likely a more achievable goal than debiasing doctors split-second decisions in high-pressure clinics. Pain, too often dismissed in clinical settings, is especially problematic for marginalized patients. In one study, AI was used to read knee x-rays to predict arthritis pain, capturing 43% of the differences across race, income, and education, compared to just 9% by radiologists. That five-fold jump shows AI could finally give every patients pain the attention it deserves. 5. People pour their hearts out to machines You know, doctor, I really like this computer better than the physicians upstairs. So proclaimed the very first person to talk to a computer about their health. The year was 1966, the location was a hospital at the University of Wisconsin, and the physician was Warner Slack. On hearing the patients candid admission, Dr. Slack was not insulted. He recognized something unique was unfolding. Dr. Slack later reflected in an academic article, The physician presents an authoritarian figure, and yet, the patient was very comfortable with the machine and criticized it freely. Many doctors still believe that AI can never replace them when it comes to face-to-face interactions. In multiple international surveys of doctors, I have asked them their opinions on what technology might do. Most tend to believe that AI can handle the routine chores, but when it comes to genuine human connection, doctors will always be indispensable. However, since Dr. Slacks first study, nearly 60 years ago, a wealth of research has demonstrated that patients tend to be more talkative with machines. Theyre more likely to disclose sensitive or embarrassing symptoms, challenge opinions, and ask questions. Sitting in front of a physician can sometimes meddle with our time-crucial medical disclosures, including red-flag cancer symptoms and our mental health. The very humanness of our doctors can undermine the delivery of healthcare. This article originally appeared in Next Big Idea Club magazine and is reprinted with permission.
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In April, when Duolingos CEO, Luis von Ahn, announced the company was going AI-first,” he wasnt just making a strategic decision. He was stepping into a spotlight few leaders envy. The decision was bold. The backlash was immediate and unexpected. Critics called the rollout tone-deaf. Users deleted the app. Commentators flooded social media with post-mortems on what the CEO should have done differently. But heres what most people missed: They werent in the room when the decision was made. They didnt carry the weight of the trade-offs. They didnt face the timeline, the internal debates, or the reputational risk. And they didnt have to answer to stakeholders while trying to lead through ambiguity. Every high-stakes leader faces this dichotomy. A pharmaceutical executive greenlighting a drug trial. A retail chief ending hybrid work. A startup founder accepting an acquisition and pivoting past the point of no return. The specifics change, but the test remains: Will you default to data alone? Cave to the loudest voice? Or, when no playbook exists, cultivate the discernment to judge your own judgment first? The Easy Trap: Judging by Outcome We tend to assume that a good decision-making process leads to a good result. But leadership doesnt work that way. Outcomes are shaped by countless factors, many outside the leaders control. The more helpful question is this: Was the process for making the decision sound? Research by Daniel Kahneman describes outcome bias as the tendency to evaluate decisions based on their results, rather than on the logic and context that produced them. In high-stakes environments, this bias is magnified. Most people dont realize how lonely leadership can be at the top. Especially when youre making irreversible calls. You can gather advice. You can run models. But eventually, someone has to decide. And that someone is often you. Thats why judgment before the judgment matters. Its not about getting it right. Its about being able to live with how you chose. The process becomes your compass when the outcome is uncertain. What leaders need is a decision framework that creates space to pause, before the final judgment. It might not guarantee a perfect outcome, but it ensures a process you can stand behind. And in high-stakes leadership, thats what separates reactive choices from principled ones. Leadership isnt about predicting the future. Its about preparing your judgment before it arrives. The Judgment Before the Judgment Framework Most people dont realize how lonely leadership can be at the top. Especially when youre making irreversible calls. You can gather advice. You can run models. But eventually, someone has to decide. And that someone is often you. Thats why judgment before the judgment matters. Its not about getting it right every time. Its about being able to live with and justify how you made a decision. The process becomes your compass when the outcome is uncertain. It might not guarantee a perfect outcome, but it ensures a process you can stand behind. As an executive coach working closely with CEOs and senior leaders I often support decision-making moments. This framework helps sharpen that process by focusing on the three dimensions that matter most: perspectives, pressure, and integrity. 1. Perspectives: Whos in the room? When pressure builds, leaders often default to voices they know and trust. But this can breed blind spots and echo chambers. The absence of tension often signals the absence of perspective. A McKinsey study on decision-making found that teams with diverse perspectives were significantly more likely to avoid costly strategic errors. And yet, under pressure, many executives unintentionally exclude dissent, not because they fear disagreement, but because they crave certainty. Goal: Expand your inputs before narrowing your options. Example: When Microsoft was considering its dramatic shift to cloud computing, Satya Nadella deliberately included dissenting voices from across the organization. “We needed the skeptics at the table,” he later recalled in his memoir Hit Refresh. Cognitive friction and diverse thinking reduces blind spots. Leaders who intentionally invite challenges gain a wider field of vision and fewer regrets. Ask: Who am I listening to? Whose voice am I unconsciously excluding? Have I actively invited challenges, not just alignment? Try this: Assign someone the role of “Shadow Stakeholder.” Have a team member argue from the perspective of someone not in the room, a customer, contractor, regulator, critic, or press. This activates empathy and anticipates real-world backlash. Open decision-making meetings with this question: What are we not saying that might matter later? It gives people permission to speak up, before discomfort shows up in side channels or quiet resistance. 2. Pressure : Whats driving my urgency? Urgency can become a form of self-deception. Leaders often borrow pressure from investors, media cycles, and competitors, and internalize it as their own. What starts as external noise can quietly shape timelines, tone, and trade-offs without anyone naming it. By slowing down to examine the source of urgency, leaders reclaim the ability to choose rather than react. When you name the source of pressure, you reclaim your authority. The pace of technology these days is incredibly fast. And research shows that rushed technological decisions often bypass deeper analysis, leading to choices that optimize immediate outcomes rather than the benefit of customers and society in the long term. Slowing down to assess pressure creates space for deliberate thinking. Leaders need to manage tempo as much as they manage outcomes. Goal: Name the pressure so it doesnt dictate the decision Example: When the pandemic hit in 2020, Zoom saw daily participants jump from 10 million to over 200 million. The pressure to scale was high. But CEO Eric Yuan recognized that the real urgency lay not in scaling, but in trust. He paused new feature rollouts, declaring a fature freeze, to focus on security and privacy, naming the true pressure drive. He named the pressure accurately and responded with disciplined context, not reaction. Ask: Is this deadline fixedor self-imposed? Am I feeling external pressure, or emotional pressure? Whats the real cost of pausing Try this: Ask 3 trusted colleagues to evaluate the decision independently. Dont brief them together. This surfaces noise reveals blind spots and gives you a clearer signal. As Daniel Kahneman suggests, comparing independent inputs reduces judgment bias before consensus pressures kick in. Map the pressure chain. Identify whos behind the urgency, board, media, competitors, and internal stakeholders, and ask: Whose pressure am I absorbing? This turns urgency into a diagnostic tool instead of a trigger. 3. Integrity:Will I stand by this if it fails? The real test of leadership isnt whether a decision works out. Its whether the process can hold under scrutiny, even when the outcome doesnt go your way. When strategy, reputation, and speed collide, and if values are not integrated into the transformation decision, the result can feel hollow. Anchoring your decision on a values-aligned process ensures you’re explaining, not regretting, your choices.Decisions made with integrity build internal trust and external credibility. They allow leaders to course-correct without losing moral footing. When people trust your process, theyre more likely to stay engaged even through failure. Goal: Make the call in a way your future self can defend. Example: When Patagonias founder transferred his ownership of the company to a trust dedicated to fighting climate change, the move reflected decades of values-aligned decision-making, even at personal financial cost. His goal? To ensure the companys profits and governance align permanently with its environmental mission, what Chouinard called going purpose rather than going public.” Ask: Would this decision align with our values if it were scrutinized, not just by shareholders, but by employees? Did I lead with clarity, courage, and transparency? Would I make the same call againknowing what I know now? Try this: Write the “failure postmortem” in advance. It makes the stakes real and forces you to confront blind spots before they blind you. If you’re not proud of the logic that led you here, thats a signal. Conduct a data friction audit. Ask your team what data they hesitate to share, and why. This reveals cultural dynamics, misaligned incentives, or unspoken fears that distort decision-making upstream. What Duolingos CEO Got Rightand What It Reveals Back to Duolingos CEO. His AI-first announcement hit a nerve. But if you strip away the internet outrage, youll see a leader trying to navigate a fast-changing landscape. Trying to position the company for long-term success. Trying to do what the role requires: make the call. Could the communication have been better? Absolutely. Could the tone have more directly acknowledged the human and emotional cost? Yes. But behind the missteps, you can see the signs of a decision made under pressure, uncertainty, and in service of a larger vision. Thats a position many CEOs will find themselves inif they havent already. Thus, the question shouldnt be, am I making a decision that will lead to the right outcome but rather, what process do I need to make the decision so I can stand behind it with confidence regardless of what happens? Because sooner or later, your Duolingo moment will come. Your Duolingo moment is inevitable. Not because youll face the same choice, but because every leaders judgment gets tested when the stakes are high and the path is unclear. The question isnt whether youll make the call, its whether your process will stand when others start asking why. Because in the end, people will judge your decisions. Before you make the call, strengthen the judgment that will live with it.
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If youve ever used an iPhone, you know the magic of an ecosystem. Your phone unlocks your Mac, syncs your photos, connects to your AirPods, and mirrors to your TVeffortlessly. Each device on its own is useful, but together they create a seamless experience that feels greater than the sum of its parts. Once you experience that level of integration, its almost impossible to go back to juggling disconnected tools. Apple showed us what happens when products work seamlessly together: Integration builds loyalty, trust, and efficiency. Real estate finance is entering a similar moment. For too long, investors have managed rental operations in silos. They collected paper rent checks. They tracked maintenance in spreadsheets. And they chased financing through traditional banksoften with months of paperwork and uncertainty. Each function worked, but nothing worked together. Thats beginning to change. By connecting operational data, tenant management, and financing into a single ecosystem, investors can reduce friction. They can also stabilize returns. The connections make smarter, more informed decisions. Intelligent ecosystems are emerging that tie together capital access and operations, along with data, into one continuous loop. That reshapes how investors grow and sustain their portfolios. THE PROBLEM WITH FRAGMENTATION When real estate investors rely on fragmented systems, it leads to unpredictable cash flow. It can also lead to delayed property improvements. At the market level, it slows portfolio growth and limits investment opportunities. RentRedis own survey data highlights the stakes: 35% of landlords report plans to spend more than $20,000 on property upgrades this year, yet a substantial number of these projects have been delayed due to funding constraints. Many cite limited access to capital as a key reason. Capital access is one of the most common growth barriers. This bottleneck reverberates across the housing market, slowing down renovations and leaving tenants with fewer quality housing options. An ecosystem-driven approach to finance, with capital directly connected to operational data, can address these gaps. It can better align with real-world rental economics and accelerate funding. ECOSYSTEMS: ENGINES OF TRUST AND TRANSPARENCY Trust is the foundation of both finance and housing. For investors, its knowing they can secure capital when needed, on terms that make sense. For tenants, its stability, timely repairs, and confidence in their housing situation. Integrated ecosystems naturally foster that trust. Rent collection data can inform financing decisions, ensuring investors are judged on real performance instead of just projections. Maintenance systems warrant that properties remain livable and competitive. Accounting tools create transparency around income and expenses. When the pieces connect, investors gain confidence. Tenants also benefit from better housing conditions, with the market as a whole becoming more resilient. WHAT AN INTELLIGENT ECOSYSTEM LOOKS LIKE The clearest benefit of an ecosystem approach is that every part of the investment cycle reinforces the others. Rent collection, tenant screening, financing, and reporting arent separate stepsthey feed into one another. Take rent payments, for instance. RentRedi data shows that autopay led to 99% on-time rent payments as opposed to an 88% on-time rate without autopay. This mirrors broader renter behavior. A recent PYMNTS study found that more than half of renters now prefer to pay online, and 77% of those renters report being satisfied with the experiencemore than double the satisfaction rate for traditional methods like paper checks. Renters benefit from digital, integrated payments while stabilizing investor returns. That reliability cascades through the entire investment strategy: Predictable income means investors can more confidently manage expenses or pursue new acquisitions. Capital access can now be built into this ecosystem. When investors prequalify for financing within the rental management platform, it accelerates access to funds. The outcome is clear: Investors experience smoother operations, stabilized cash flow, and better market positioning, while tenants benefit from improved housing quality and responsiveness. ACCESS TO CAPITAL IS A MARKET GAME-CHANGER Traditional financing is often slow, rigid, and disconnected from real-time portfolio performance. Ecosystem-driven models change this by tying capital availability to operational data. Funds can be delivered in days rather than weeks, allowing investors to act on opportunities or handle urgent repairs without delaying projects. Flexible repayment models are central to this innovation. In a pay-as-you-earn approach, repayments automatically adjust to a percentage of rent collected until the full balance is paid, and investors can make additional or early payments without penalty. By aligning financing with actual cash flow, investors maintain liquidity. They protect their properties and stabilize portfoliosall while supporting the broader rental market. THE BROADER SHIFT IN REAL ESTATE FINANCE The real estate industry is moving from isolated products to interconnected, intelligent systems. Just as Apple built its ecosystem around the iPhone, rental investors are beginning to centralize operations and financing around rent and property data, because investors and tenants alike are expecting smarter systems that reward consistency and trust. One of the clearest signs of this trend is the rapid adoption of rent reporting. A TransUnion report found a 33% year-over-year increase in property managers reporting rent payments to credit bureaus. For tenants, the payoff is real84% of renters who had payments reported said their credit scores improved. Its a clear win-win born from ecosystem thinking: Investors gain higher-quality tenant pools, while renters gain a pathway to financial growth. Embedded financing is the next step in this evolution. Transparency and fairness (clear terms, flat fees, and performance-based repayment) become standard. They reduce friction and align incentives. Intelligent ecosystems do more than improve convenience. They professionalize real estate investing, enabling portfolios to scale efficiently and withstand market volatility. THE ECOSYSTEM ADVANTAGE The future of real estate finance lies in connected, intelligent systems that build trust over time. Investors leveraging these ecosystems gain speed, clarity, and control. They position themselves to grow and compete in an increasingly complex rental market. In real estate, as in technology, the smartest players arent just using toolstheyre operating within ecosystems. Ryan Brone is cofounder and CEO of RentRedi.
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