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Below, co-authors Barry Schwartz and Richard Schuldenfrei share five key insights from their new book, Choose Wisely: Rationality, Ethics, and the Art of Decision-Making. Barry spent 45 years teaching psychology at Swarthmore College. Now he holds a visiting position at the Haas School of Business, University of California, Berkeley. Richard held a similarly long tenure at Swarthmore College, 42 years, as a philosophy professor. Whats the big idea? There is no such thing as a calculator for lifes decisions. Try as we might to quantify, count, and calculate in search of the right choice, that is simply not how wise decision-making happens. Qualitative judgment and consideration of preferences and values are required when identifying the best option before us. Listen to the audio version of this Book Biteread by Barrybelow, or in the Next Big Idea App. 1. Sorting through the possibilities Imagine waking up on a beautiful Saturday morning and asking yourself, What should I do today? You consider the possibilities: get some exercise, go for a hike, go to a lovely park with a serious book under your arm, catch up on work, veg out, and watch sports on television. Or maybe, instead of thinking about what you might do, think about what we might do. What social activities might you engage in? Get in touch with friends, visit your mother at the assisted living facility, or help your adult daughter pack for her apartment move. Lots of possibilities. Is there a right way to think through your options for the day? Is there a right way to choose which of these things to do? 2. Rational choice theory In economics, according to rational choice theory, there is a rational way to make decisions, which requires thinking about two things: How valuable are the options youre deciding between? How likely is it that the option you pick will be as good as you expect? We live in an uncertain world, and so you assess the value and probability of your options, then multiply them. What you get is expected utility. The rational choice should be the option that provides the greatest amount of expected utility. This framework analogizes the decisions we make in life to the decisions you might make in a gambling casino. Whats the best strategy in a blackjack hand? What are the odds and payoffs at the roulette table? In situations like this, it only matters how much you could possibly win and how likely you are to win. Rational choice theory suggests that we should think about most of our decisions in these terms. In figuring out how good it will be if I choose this option, and how likely it is to be that good, you must quantify the relevant information. Create a spreadsheet of all the factors that might matter in making a choice. List how good a particular option is with respect to all these factors, and enter a value for both how good it is and how probable it is. Fill out the spreadsheet with all the options, push a button that does the math, and youve made a rational decision. This framework analogizes the decisions we make in life to the decisions you might make in a gambling casino. Rational decisions are quantitative. You need to attach quantities and magnitudes to both the value of the options and the likelihood that you will achieve that value. Rational choice theory has nothing to tell us about what your preferences among options should be, what your values should be, or what set of options you should consider. In this economic framework, you have whatever values you have, your options are whatever options the world presents, you create the spreadsheet, do the math, and pick the best option. Thats the model of rational decision making. 3. Framing the options Do we behave as rational decision makers? Definitely not. About 50 years ago, psychologists Daniel Kahneman and Amos Tversky started studying how people make decisions. They did some beautiful and extremely important research, but unfortunately, Tversky died prematurely. Kahneman survived to win the Nobel Prize in Economics and published a book called Thinking Fast and Slow, which has been on the bestseller lists for almost 10 years. His work helped create the field of behavioral economics. Behavioral economics research has illustrated the ways in which people fail to meet the standards of rational choice theory. People are bad at thinking about probability. People are heavily influenced by the way in which options are framed. People divide their decisions into different accounts and often dont aggregate the potential consequences of those decisions into one big account. People are highly influenced by anchors. A $500 suit seems inexpensive on a rack full of $1000 suits but seems quite expensive on a rack of $200 suits. These aspects of decision-making get us to more or less the right place, but they can also lead us seriously astray. The way Kahneman came to regard human decision making is that there are two processes happening: Conscious process: Thinking through the pluses and minuses of various options when asking yourself what choice to make. This is effortful, slow, and demanding. Automatic process: This system delivers answers to you even before you frame the question. It is fast, efficient, and operating whether you want it to or not. These two systems interact, and sometimes the automatic system leads the more deliberate, rational system astray. Even if we end up making rational decisions, its not through the processes that rational choice theory tells us we should follow. 4. Not everything canor shouldbe calculated Rational choice theory is a terrible model of what it means to be a rational decision maker. Are most of our decisions really like casino gambles? Can everything that matters in a decision be quantified? Whats good about doing strenuous exercise on a hike? And whats good about helping your daughter pack? What is the common scale of value? Can everything that matters in a decision be quantified? If youre choosing a job, you might be interested in knowing the salary, benefits, who your colleagues will be, whether the work will be interesting, the location, opportunities for advancement, and other relevant details. Its preposterous to attach numbers to all those factors and then use those numbers in a spreadsheet to figure out which job is best for you. Similarly, if youre deciding where to go to college, you might be interested in quantifiable things like graduation rate and average salary after graduation, but what about the qualitative features of the education, social life, food, and housing? Can thes things be arrayed on a spreadsheet using a common scale for assigning value? When you follow rational choice theory, instead of thinking about decisions, you count. Calculation substitutes judgment. In some areas of life, that could be a good thing, but in many others, shutting down your ability to subjectively reflect will lead to worse, impoverished, pinched decisions. 5. A rational decision requires rational judgment Rational choice theory is dangerous as a normative standard. It narrows our thinking by encouraging us to invent quantifications of things that cant be quantified. During the Vietnam War, the U.S. government was facing pushback from citizens and wondering how to generate popular support for the war. It was concluded that if the public saw that the U.S. was winning, then more people would favor involvement. But it was a guerrilla war, so can someone know whos winning? It was decided to use body counts and casualties as an indicator. If the enemy had higher numbers of wounded or dead than our side, then we must be winning. This affected our fighting strategy. Instead of seeking strategic advantages, we made decisions designed to maximize casualties because it meant we could tell folks back home that the U.S. was winning the war. As a result, we didnt win the war, and thousands of people died needlessly. Rational deciding requires rational judgment and not just counting. You can see the danger of rational choice theory decisions, like where to go to college, too. People are heavily influenced by the ratings of U.S. News & World Report, so universities have learned how to game those ratings by making themselves look good with respect to the dimensions that U.S. News cares about. Does that make them better institutions? Maybe sometimes, but mostly it does not. Rational choice theory forces us to focus on things that can be easily compared and quantified while leaving out the rest. Rational deciding requires rational judgment and not just counting. We dont want our ability to think and judge rationally to atrophy because we think that the rational approach to decisions is essentially mechanical and algorithmic. Enjoy our full library of Book Bitesread by the authors!in the Next Big Idea App. This article originally appeared in Next Big Idea Club magazine and is reprinted with permission.
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Over the last five years, artificial intelligence has shifted from a fringe interest to one of the most important drivers of global economic growth. So important has the technology become that the United Nations Security Council held its first open debate on artificial intelligence last month. While little of substance was achieved, a General Assembly resolution authorizing the creation of an independent scientific panel on AI may have a more enduring impact. One of the core questions this panel will seek to answer is how AI can support sustainable economic development without entrenching inequality. The potential dangers here have deep historical parallels. AI runs on compute, cloud capacity, and dataresources that are concentrated in the hands of countries in the Global North. Africa, for example, hosts less than 1% of global data center capacity, leaving the continent reliant on expensive infrastructure abroad. Even an IT powerhouse like India hosts just 3% of global capacity, despite being home to nearly 20% of the worlds population. Meanwhile, workers across the Global South are earning as little as $2 an hour creating, cleaning, and labeling data for use in Western models. A new digital colonialism? To some, this looks like a digital version of the kind of resource extraction associated with the age of empires: labor and data flow inexorably north, where they create economic value, but little of this value finds its way back into the pockets of developing nations. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity?","dek":"Faisal Hoques books, podcast, and his companies give leaders the frameworks and platforms to align purpose, people, process, and techturning disruption into meaningful, lasting progress.","ctaText":"Learn More","ctaUrl":"https:\/\/faisalhoque.com","theme":{"bg":"#02263c","text":"#ffffff","eyebrow":"#9aa2aa","buttonBg":"#ffffff","buttonText":"#000000"},"imageDesktopId":91420512,"imageMobileId":91420514}} The reality is that these patterns are driven by market forces rather than imperial ideology, but the historical echoes are troubling nonetheless. Whatever the motivations, we know that this kind of concentration of power can do long-term economic and social damage. In some cases, the results are felt only in the underserved countries. AI systems trained to deliver healthcare to Western patients, for instance, can be dangerously inaccurate when working with other populations, limiting the transferability of the advances made in the West. Similarly, researchers at Columbia University have found that Large Language Models are less able to understand and represent the societal values of countries that have limited digital resources available in local languages. These limitations are just the tip of the iceberg. AI is not just a productivity toolits a force multiplier for innovation. It will shape how we farm, teach, heal, and govern in the future. If the Global South remains a passive consumer of imported AI systems, it risks losing not just economic opportunity but digital sovereignty. The Industrial Revolution brought extraordinary wealth to Europe and North America while locking much of the world into dependency for generations. AI could repeat that cyclemore rapidly and at an even greater scale. Why this should worry every global business The irony is that this approach hurts everyone, including the companies driving it. In terms of population, India has overtaken China while Nigeria and other African nations are enjoying booming birthrates. These countries represent tomorrows largest markets. Yet multinationals that treat them as data factories without trying to situate that data in its local context will find that they dont understand the customers they will desperately need tomorrow. A model that misunderstands how most of the world thinks about family, risk, or trust is a model doomed to fail. We have already seen how this trend can play out. The mobile money transfer company M-Pesa revolutionized banking in Kenya while Western banks were still trying to penetrate the market with credit cards. Today, Indian companies are developing chatbots that can speak to the hundreds of millions who communicate daily in so-called low resource languages. Unless multinationals begin to think intentionally about how they can serve these underserved populations, they will find themselves looking in from the outside once these markets mature. The path forward Avoiding the dangers of algorithmic colonialism and earning a position in emerging markets for AI products and services requires deliberate action from governments, businesses, and global institutions. Data centers, power supply, and research capacity should be financed like roads and ports, with blended capital from development banks and sovereign funds. Without local compute capacity, nations will inevitably remain digital renters, not owners. Governments should also establish data trusts to negotiate how their citizens information trains global models, including setting benefit-sharing and transparency requirements. AI annotation work should pay living wages with proper labor protections. And critically, we need investment in open-source models, multilingual datasets, and local developers, so solutions are built with communities, not just for them. Some companies are already changing course. They are investing in local infrastructure, creating genuine partnerships, and recognizing that sustainable profits come from creating value with communities, not extracting it from them. They understand that todays data creators and workers will be tomorrows consumers, and, potentially, tomorrows innovators as well, if they are given the chance. AI has the potential to be a great global equalizeror it could become the most powerful driver of inequality in human history. We have seen what happens when transformative technology is hoarded: inequality deepens, resentment grows, and instability follows. If we want to write a different storyone in which the Global North and South cocreate the future and share the benefits of artificial intelligencewe must act now, before the gap becomes unbridgeable. 4 things leaders can do today to start bridging the AI divide 1. Audit your AIs eographic blind spots today. Map where your training data comes from and which populations it represents. If more than 80% comes from Western sources, you run the risk of not being able to represent or communicate effectively with consumers from much of the world. Work to diversify your data if that is feasible, or develop localized AI systems that are trained or tuned with local data. 2. Create transparent data-sharing agreements. Develop a framework for using local data to train your models, including benefit-sharing provisions and audit rights for local data providers. Companies that move first will become preferred partners when governments start to mandate these arrangements. 3. Pay fair wages for AI workand let your target markets know you are putting your money where your mouth is. Commit to paying local sustainable living wages plus a mark-up for data annotation and AI training work. Make this commitment public. You will attract better talent, improve the quality of your data, and build brand equity in emerging markets. 4. Launch an open-source initiative in at least one emerging market. Pick a specific challenge in a growth markethealthcare in Nigeria, agriculture in India, education in Indonesiaand commit to building an open-source solution with local developers. The relationships and market intelligence you gain will be worth more than any proprietary advantage you might give up. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity?","dek":"Faisal Hoques books, podcast, and his companies give leaders the frameworks and platforms to align purpose, people, process, and techturning disruption into meaningful, lasting progress.","ctaText":"Learn More","ctaUrl":"https:\/\/faisalhoque.com","theme":{"bg":"#02263c","text":"#ffffff","eyebrow":"#9aa2aa","buttonBg":"#ffffff","buttonText":"#000000"},"imageDesktopId":91420512,"imageMobileId":91420514}}
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In 2025, Amazon, Dell, Apple, Google, IBM, Meta, Salesforce, and dozens more have doubled down on demands for employees to return to the office (RTO) at least three days a week, if not all five. And theyre getting exactly what they want. Now, when I say exactly what they want, you might be expecting me to paint a picture of workers happily returning to their daily commutes, overcrowded highways, cavernous or claustrophobic offices, constant interruptions, and extra expenses, and all of it resulting in massive productivity gains. Thats not happening, the productivity-gains part. And the longer we play this out, the sillier the performances of productivity theater have become. The truth is, the science on productivity is still out. So you have to go with your gut. Or your experience. And what 30 years of gut and experience tells me is that the real question isnt whether people are more productive at homeits whether companies can afford to lose their best talent over this. Right now, tech workers are desperate. Companies know it. Thats why Amazon can demand five days in the office and get compliance instead of resignations. But the labor market isnt static; it never was. In fact, it tends to whipsaw back and forth every few years. Remember 2022? Companies were begging people to take jobs. Signing bonuses, remote work, unlimited PTOwhatever it took. Candidates were ghosting interviews. That shoe was totally on the other foot, and it was a Doc Marten. But if we look at history, even recent history, a lot of companies that are mandating RTO now are writing the future resignation letters for their best employees, to be delivered the nanosecond the tech job market stops being the worst in history. Let me tell you how common sense foreshadows a reckoning for RTO. How did we get here? I dont want to defend remote work. I really dont. But Im a huge fan of common sense. Its a little ironic that remote work accelerated with another mandatethat we all stay home for most of 2020 and a lot of 2021. I, for one, still cant believe that happened. But its what happened next that mattered. As the pandemic restrictions lifted almost universally by 2022, the natural calls by employers for their employees to return to the office were met with an unexpected backlash. No, thanks. Were more productive, our work-life balance is much better, we feel better, and anyway you said we could do this. That backlash peaked in 2024, when a bunch of Dell employees, shockingly, chose to take the hit to their company future rather than come back to the office. Thats fine. Wed rather do a better job in a more comfortable environment. By the way, weve moved to New Zealand. Yeah, it got silly. And corporate tech did not take that silliness lying down. Employees needed to return to the office because . . . well, because its always been that way. Does it matter that in a post-pandemic internet business world, that physical proximity no longer matters? That doesnt matter. As employers started stamping their feet over the mandates, I started talking about common sense. For one, the long-term hits these companies were taking to their talent candidate pool, their employee morale, and their productivity when measured from the employees perspective, were costs that were going to far outweigh their sunk real estate costs in the short term. But then corporate tech got smart. Sort of. Employers started making the misguided assumption that the employees who were most dead set against returning to the office were the ones that the company could live without. RTO became a natural, if completely illogical, weeding-out mechanism. And that kinda worked. But kinda didnt. Sure, the troublemakers all found the door and gave the finger on the way out, but the go-along-to-get-along crowd stopped performing and got performative, and the rest of the tech workforce got ready to revolt. Then the employers got bailed out by the worst tech labor market in history. When there are more job seekers than jobs, tech companies can mandate a company loyalty sing-along every morning, and the entire workforce will start warming up their vocal cords. Whats next for the labor market and RTO? Well, what does common sense tell us? Productivity is in the eye of the beholder. In any position where creativity, innovation, or even decision-making matters, Id argue that there is no stable metric for productivity that goes beyond correlation to causation where employee performance is concerned. So you have to go with simple, common-sense concepts. Evolution doesnt come wit introductory pamphlets. There is no title card for the next phase of the future of work. It just happens, and you evolve or die. And if we couldnt connect the dots that the internet had made physical proximity irrelevant in every case where it wasnt mandatory (i.e., surgery, construction, airline pilot), the pandemic lockdowns ironically hammered that point home. As an evolutionary concept, the productivity argument no longer even matters. Its the same productivity argument that was being made when we were deciding whether everyone still had to wear suits and skirts to work. But if that kind of common sense doesnt sway the naysayers, I can make the argument even common-sensier. Yo. 2022. The job market was supposed to have recovered by now. It hasnt, and that has emboldened a lot of employers to lean into their leverage with their supply of scarce and valuable jobs. But the market will recover. When it does, the first questions that are going to need to be answered are: Why am I on a Zoom with the person down the hall? Why can we only hire within a two-hour commute of some of the most expensive real estate in the country? Why am I wearing this three-piece suit with matching fedora and a pocket watch? Im a database administrator. Because when an employee has leverage, questions like that no longer make any sense. And the very same companies demanding RTO now will likely be forced to offer remote work again to compete for scarce, valuable talent. Theyll be right back where they started, while their talent heads to those smart companies that see remote work as an evolutionary concept, and are creating solutions that accommodate both remote and in-office employees. If you are also a fan of common sense, please join my email list and Ill shoot you a quick heads-up when I spout something close to it. Joe Procopio This article originally appeared on Fast Companys sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
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