I’ve been a little stunned—and delighted—by the sudden popularity of one of my favorite pastimes, a game with a funny name and strange terminology, such as, “dink,” “kitchen,” and “skinny singles.”

Largely confined to the Pacific Northwest for decades, it has now emerged as America’s fastest-growing sport.

I’m talking about pickleball.

It’s best described as a mash up of tennis, badminton, and ping-pong. And if you haven’t heard of it, I expect you soon will.

I’ve been a “Pickler,” as people obsessed with the game like me are known, for more than 50 years.

And if you and your family are bored and looking for something to do this summer, I encourage you to become one too.

Boredom was what got this sport started in 1965.

Three dads living on Bainbridge Island, near Seattle, came home one summer evening to find their children complaining that there was nothing for them to do. So, they found a net, a Wiffle ball, some ping-pong paddles, and created a game on an old badminton court that the entire family could play together.

It was a hit.

Over the next year, the three friends worked together to develop a set of rules, formalize the court layout, and introduce a larger plywood paddle that was good for striking the ball. And they decided to call it pickleball. (The name’s origins remain a matter of debate. Some believe it was named after a dog. Others say it’s a reference to a “pickle boat,” a thrown together boat made from the leftover rowers in crew races. I don’t know. I prefer to just play the game and stay out of the fray.)

Meanwhile, word slowly spread in Seattle of this odd new pastime.

My dad was friends with the game’s inventors, Joel Pritchard, a state legislator and later Washington’s lieutenant governor, Barney McCallum, and Bill Bell. He learned about their creation and by the late 1960s, he got inspired to build a pickleball court at our house. I’ve been playing ever since.

At the time, the pickleball community was very small. I doubt there were more than a thousand people in the Seattle area who had ever seen the sport when my family picked it up. And I don’t think anyone expected it would ever become a national phenomenon.

Today, there are more than 4.8 million players nationwide, a growth of nearly 40 percent over the last two years. And I expect it will only get bigger. (I knew things had gotten serious for pickleball when I opened up The Economist and found a story about the game’s newfound fame.)

I don’t know exactly what’s driven this recent surge in interest in pickleball, but I think the fact that it’s so easy to play is one big reason. People like to say a lot of sports—even hard ones like golf—are “easy to play,” but in the case of pickleball, it’s true. Everyone from the super young to the super old can take part. It takes minutes to learn the basics, games are short, and all you need is a net, paddle, and ball to get started. It doesn’t take much skill to hit the ball, either, because it doesn’t move as fast as a tennis ball. The best thing about pickleball, however, is that it’s just super fun.

I look forward to playing a pickleball game with friends and family at least once a week and more often during the summer. I’m also a lifelong tennis player, and for me, the games complement one another. Pickleball has helped me become a better tennis player and tennis has done the same for my pickleball game.

Still, I’ve spent a lot of time explaining and defending pickleball to newcomers, especially tennis players. Many people are confused by the unfamiliar court and a little skeptical of the strange terminology. There’s an area of the court within 7 feet on either side of the net called “the kitchen” or non-volley zone. And a key to being a top player is to master something called the “dink shot,” a soft shot that arcs over the net and lands within the opposing team’s kitchen. While playing doubles is most popular, singles games, including a version played crosscourt, called “skinny singles,” is another option.

Despite its silly terms and funny name, pickleball is actually quite a sophisticated game. I enjoy watching YouTube videos where I can learn about tactics and strategies from the best players. It’s amazing to see pros like Ben Johns play the game. Given all the rage about pickleball, I expect someday soon it may end up as an exhibition sport at the Olympics.

Nearly everyone in my family plays and we’ve had great fun in matches against one another over the years. We’ve all played so much that we can sometimes get very competitive. If we ever lose a game to visiting players, we’re always a little surprised and vow to take the next match more seriously.

Win or lose, I can’t think of a better way to spend a summer day than as a Pickler.

If you decide to give pickleball a try, I hope it brings you as much joy as it has my family and me.

I was twenty when I gave my first public speech. It was 1976, Microsoft was almost a year old, and I was explaining software to a room of a few hundred computer hobbyists. My main memory of that time at the podium was how nervous I felt. In the half century since, I’ve spoken to many thousands of people and gotten very comfortable delivering thoughts on any number of topics, from software to work being done in global health, climate change, and the other issues I regularly write about here on Gates Notes.

One thing that isn’t on that list: myself. In the fifty years I’ve been in the public eye, I’ve rarely spoken or written about my own story or revealed details of my personal life. That wasn’t just out of a preference for privacy. By nature, I tend to focus outward. My attention is drawn to new ideas and people that help solve the problems I’m working on. And though I love learning history, I never spent much time looking at my own.  

But like many people my age—I’ll turn 70 this year—several years ago I started a period of reflection. My three children were well along their own paths in life. I’d witnessed the slow decline and death of my father from Alzheimer’s. I began digging through old photographs, family papers, and boxes of memorabilia, such as school reports my mother had saved, as well as printouts of computer code I hadn't seen in decades. I also started sitting down to record my memories and got help gathering stories from family members and old friends. It was the first time I made a concerted effort to try to see how all the memories from long ago might give insight into who I am now.

The result of that process is a book that will be published on Feb. 4: my first memoir, Source Code. You can order it here. (I’m donating my proceeds from the book to the United Way.)

Source Code is the story of the early part of my life, from growing up in Seattle through the beginnings of Microsoft. I share what it was like to be a precocious, sometimes difficult kid, the restless middle child of two dedicated and ambitious parents who didn’t always know what to make of me. In writing the book I came to better understand the people that shaped me and the experiences that led to the creation of a world-changing company.

In Source Code you’ll learn about how Paul Allen and I came to realize that software was going to change the world, and the moment in December 1974 when he burst into my college dorm room with the issue of Popular Electronics that would inspire us to drop everything and start our company. You’ll also meet my extended family, like the grandmother who taught me how to play cards and, along the way, how to think. You’ll meet teachers, mentors, and friends who challenged me and helped propel me in ways I didn’t fully appreciate until much later. 

Some of the moments that I write about, like that Popular Electronics story, are ones I’ve always known were important in my life. But with many of the most personal moments, I only saw how important they were when I considered them from my perspective now, decades later. Writing helped me see the connection between my early interests and idiosyncrasies and the work I would do at Microsoft and even the Gates Foundation.

Some of the stories in the book were hard for me to tell. I was a kid who was out of step with most of my peers, happier reading on my own than doing almost anything else. I was tough on my parents from a very early age. I wanted autonomy and resisted my mother’s efforts to control me. A therapist back then helped me see that I would be independent soon enough and should end the battle that I was waging at home. Part of growing up was understanding certain aspects of myself and learning to handle them better. It’s an ongoing process.

One of the most difficult parts of writing Source Code was revisiting the death of my first close friend when I was 16. He was brilliant, mature beyond his years, and, unlike most people in my life at the time, he understood me. It was my first experience with death up close, and I’m grateful I got to spend time processing the memories of that tragedy.

The need to look into myself to write Source Code was a new experience for me. The deeper I got, the more I enjoyed parsing my past. I’ll continue this journey and plan to cover my software career in a future book, and eventually I’ll write one about my philanthropic work. As a first step, though, I hope you enjoy Source Code.

I was an extremely lucky kid. I was born to great parents who did everything to set me up for success. I grew up in a city I love and still call home, at the dawn of the computer age. And I went to one of two schools in my state—one of a handful in the country—that actually had computer access. These were all strokes of luck that helped shape my future.

But equally important, maybe most important, were the teachers I was fortunate enough to learn from along the way. In my new book, Source Code, I write about many of them. From grade school through college, I had teachers who saw my potential (even when it was buried under bad behavior), gave me real responsibilities, let me learn through experience instead of lectures, and created space for me to explore my passions.

These five brilliant teachers didn’t just teach me subjects; they taught me how to think about the world and what I might accomplish in it. Looking back, I realize how rare this was—and how lucky I was to find it over and over again. 

Blanche Caffiere

Blanche Caffiere entered my life twice—first as my first-grade teacher, and later as my first “boss,” when I was in fourth grade at View Ridge Elementary and she was the librarian. At the time, I was a handful in (and out of) class: energetic, disruptive, constantly lost in my own thoughts. Most teachers and administrators saw me as a problem to be solved. But Mrs. Caffiere saw a problem-solver in me instead. When one of my teachers struggled with how to challenge me and channel my energy, she stepped in and gave me a job as her library assistant. 

“What you need is kind of like a detective,” I said when she tasked me with finding missing books that were lost somewhere in the library. I warmed to the work immediately, roaming the stacks until I found each one. Then Mrs. Caffiere taught me the Dewey Decimal system by having me memorize a clever story about a caveman, so I could figure out where each book belonged. For a kid who loved reading and numbers, it was a dream job. I felt essential. I stayed through recess that first day, showed up early the next morning, and ended up working in the library for the rest of the year.

When my family moved and I had to leave View Ridge Elementary, I was most devastated about leaving my library job. “Who will find the lost books?” I asked. Mrs. Caffiere responded that I could be a library assistant at my new school. She understood that what I needed wasn’t just busy work, but a sense of being valued and trusted with real responsibility. She’d been teaching for nearly forty years when we met, which meant she’d seen every kind of student imaginable. But she had a particular gift for helping those at the extremes—the ones who were struggling or excelling—find their way. I was a little of both, and she certainly helped me find mine.

Paul Stocklin

Paul Stocklin’s eighth-grade math class at Lakeside changed my life in two profound ways, though I couldn’t have known it at the time. First, it was where I met Kent Evans, who would become my best friend and earliest “business” partner before his tragic death in a mountain climbing accident at age 17. Like me, Kent didn’t easily fit into the established cliques at Lakeside. Unlike me, he had a clear vision for his future, which inspired me to start thinking about my own.

It was also in Mr. Stocklin’s class that I first saw a teletype machine—an encounter that would shape my entire future. One morning, Mr. Stocklin led our class down a hall in McAllister House, a white clapboard building at Lakeside that was home to the school’s math department, where we heard an unusual “chug-chug-chug” sound echoing from inside a room. There, we saw something that looked like a typewriter with a rotary telephone dial. Mr. Stocklin explained that it was a teletype machine connected to a computer in California. With it, we could play games and even write our own computer programs—something I’d never thought I’d be able to do myself. That moment opened up a whole new world for me.

There’s a lot more I’ve come to appreciate about Mr. Stocklin, including how much he encouraged an early love of math in me. But it’s undeniable that he changed my life by facilitating two of the most important relationships of my early years: my friendship with Kent, and my introduction to computing. These were gifts from him that I’ll appreciate forever, even though one would end in heartbreak.

Bill Dougall

Bill Dougall embodied what made Lakeside special—he was a World War II Navy pilot and Boeing engineer who brought real-world experience to teaching. Beyond his degrees in engineering and education, he had even studied French literature at the Sorbonne. He was the kind of Renaissance man who took sabbaticals to build windmills in Kathmandu.

As head of Lakeside’s math department, Mr. Dougall was instrumental in bringing computer access to our school, something he and other faculty members pushed for after taking a summer computer class. Even though it was expensive—over $1,000 a year for the terminal and thousands more in computer time—he helped convince the Mothers’ Club to use the proceeds from their annual rummage sale to lease a Teletype ASR-33.

The fascinating thing about Mr. Dougall was that he didn’t actually know much about programming; he exhausted his knowledge within a week. But he had the vision to know it was important and the trust to let us students figure it out. His famous camping trips, a sacred tradition at Lakeside, showed another side of his belief in experiential learning. These treks took students through whatever weather the Pacific Northwest could throw at forty boys and a few intrepid teachers. They taught resilience, teamwork, and problem-solving in a way that no classroom ever could. That was the essence of Mr. Dougall’s teaching philosophy.

Fred Wright

Fred Wright was exactly the kind of teacher we needed in the computer room at Lakeside. He had no practical computer experience, though he’d studied the FORTRAN programming language. But he was relatively young (in his late twenties) and only recently hired, and he intuitively understood that the best way to get students to learn was to let us explore on our own terms. There was no sign-up sheet, no locked door, no formal instruction.  

Instead, Mr. Wright let us figure things out ourselves and trusted that, without his guidance, we’d have to get creative. At some point, a student taped a sign above the door that said “Beware of the Wrath of Fred Wright”—a tongue-in-cheek nod to his laissez-faire oversight of the computer room. Some of the other teachers argued for tighter regulations, worried about what we might be doing in there unsupervised. But even though Mr. Wright occasionally popped in to break up a squabble or listen as someone explained their latest program, for the most part he defended our autonomy.

Officially, he was the adult sponsor of our work at Lakeside. Unofficially, Mr. Wright gave us something invaluable: the space to discover our own potential. That was also his approach to geometry class, where I was his student in tenth grade. I remember him watching with amusement as I powered through problems using algebra instead of geometry. Rather than force me to do it the right way, he let me forge my own path, knowing I’d eventually figure out the more efficient (geometric) solution. 

Daniel Morris 

Dr. Daniel Morris was different from most high school science teachers. With a PhD from Yale and a patent for isolating tryptophan, he was a former industrial chemist who brought real-world expertise to our chemistry classroom. Some might have found it pretentious that he wore a lab coat and drank coffee from a glass beaker, but he earned those rights. I think he also earned the label that I’ve long used to describe him: the world’s greatest chemistry teacher. 

What made Dr. Morris so memorable was his ability to transform the rote memorization that most people associate with chemistry into unifying concepts that explain the world around us. He demystified complex processes by using everyday examples—to teach, for example, why soda stays fizzy if you put the cap back on, or what makes super glue that sticky. The introduction he wrote to his own chemistry textbook captures his teaching style perfectly: “We seem to forget the true foundation stone of science: the belief that the world makes sense.”

Before him, the sciences were subjects I did well in analytically but didn’t much care to practically understand or apply. That wasn’t good enough for Dr. Morris, who gave me a hard time for just getting by with what I already knew. Instead, he forced me into the lab to do experiments; to this day, I trace my love of science back to the demands he put on me to really get chemistry. He’s the reason I decided to take organic chemistry at Harvard—even though the class was mostly pre-med students, and I had no plans to become a doctor. (I got a C, my lowest grade in college, but I don’t think I ever told him.)

Tom Cheatham 

Looking back on my time at Harvard, I’m grateful for Professor Tom Cheatham’s hands-off approach to some of the most hands-on learning I’ve ever done. As director of the Aiken Computation Lab, he made an extraordinary exception by granting me access to the school’s PDP-10 computer—a privilege typically reserved for graduate students and other professors. Back then, Harvard didn’t even have an undergraduate computer science major.  

When we first met, I was an overconfident freshman, practically jumping out of my chair as I pitched him on all my ideas; I remember him taking drags on his Parliament cigarettes as I spoke, seeming pretty uninterested. I later learned that administrative tasks—signing students’ study cards and managing the day-to-day of the lab—were Cheatham’s least favorite parts of his job. Having come to Harvard after years working in industry and government, he was a programmer at heart, designing new computer languages when he wasn’t off meeting with the Department of Defense and securing more funding for the lab.

But he must have seen (and liked) something in me—either my technical experience, my teenage enthusiasm, or both. In my sophomore year, he made another exception and agreed to be my advisor for an engineering independent study to write a computerized baseball game. While I regret that we never formed a closer relationship, Cheatham was clearly in my corner. I knew that then and was reminded of it again recently, when I saw my old college records and learned how he’d defended me when I got in trouble for bringing friends into the lab without permission: It would be a “travesty of justice” if I were forced to withdraw from Harvard, Cheatham told the university’s Administrative Board, adding that he “would be delighted to have BG computing at the Center next year.”

I don’t think I ever properly thanked any of my teachers, including Professor Cheatham, for seeing something in me that I didn’t always see in myself. So many of them passed away before I had the chance. But I am who I am today because of their influence. So in Source Code, I’m sharing their stories and giving credit where it’s due. After all, one brilliant teacher, one mind-blowing class, is enough to change a person’s life. I’m so lucky and grateful to have had many.  

I loved how the computer forced me to think. It was completely unforgiving anytime I showed mental sloppiness. It demanded that I be logically consistent and pay attention to details. One misplaced comma or semicolon and the thing would crash.

It felt like solving mathematical proofs. Programming doesn’t require math skills (beyond the basics), but it does demand the same kind of rigorous logical approach to problem-solving. In both math and programming, I liked the process of breaking problems down into smaller, more manageable parts. And like solving a problem in algebra, there are different ways to write programs that work—some more elegant and efficient than others — but infinite ways to make a program that crashes. And mine crashed all the time.

I had to solve how a player moved the lander left and right, up and down, how much fuel it had, how fast it burned. I also had to describe what it looked like and how to display the ship in dashes and asterisks on the screen.

Unfortunately, I don’t have the code I wrote back then, but below you can play a text-only Lunar Lander based on the one written by Jim Storer in 1969—the same game that inspired me to write my own.

The Problem

You’re 120 miles above the surface of the moon, and your automated landing system has failed! You’re now in freefall and must take manual control to land safely within two minutes.

To avoid crashing, slow your descent by firing your engines. But use your fuel wisely: You only have 16,000 pounds, and if you run out before landing, you could crash.

Safely touch down a lunar lander on the moon without crashing and before you run out of fuel.

I am deeply saddened to learn of the passing of former president Jimmy Carter, and my heart is heavy for the whole Carter family. For more than two decades, I’ve had a chance to work with Jimmy, Rosalynn, and the Carter Center on several global health efforts, including our mutual work to eliminate deadly and debilitating diseases.

The Carters were among my first and most inspiring role models in global health. Over time, we became good friends. They played a pretty profound role in the early days of the Gates Foundation. I’m especially grateful that they introduced us to Dr. Bill Foege, who once helped eradicate smallpox and was a key advisor for our global health work.

Jimmy and Rosalynn were also good friends to my dad. One of my favorite photographs of all time shows Jimmy Carter, Nelson Mandela, and my dad in South Africa holding babies at a medical clinic. I remember my dad coming back from that trip with a whole new appreciation for Jimmy’s passion for helping people with HIV. At the time, then-President Thabo Mbeki was refusing to let people with HIV get treatment, and my dad watched Jimmy almost get into a fist fight with Mbeki over the issue. As Jimmy said in a 2012 conversation at the Gates Foundation hosted by my dad, “He was claiming there was no relationship between HIV and AIDS and that the medicines that we were sending in, the antiretroviral medicines, were a white person’s plot to help kill black babies.” At a time when a quarter of all people in South Africa were HIV positive, Jimmy just couldn’t accept Mbeki’s obstructionism.

As with HIV, Jimmy was on the right side of history on many issues. During his childhood in rural Georgia, racial hatred was rampant, but he developed a lifelong commitment to equality and fairness. Whenever I spent time with him, I saw that commitment in action. He had a remarkable internal compass that steered him to pursue justice and equality here in America and around the world.

After Jimmy “involuntarily retired” (his term) from the White House, he reset the bar for how Presidents could use their time and influence after leaving office. When he started the Carter Center, he gave a huge shot in the arm to efforts to treat and cure diseases that rich governments were ignoring, like river blindness and Guinea worm. The latter once devastated an estimated 3.5 million people in Africa and South Asia every year. That total dropped to just 14 cases in 2023, thanks to the incredible efforts of the Carter Center.

When the world eradicates Guinea worm, it will be a testament to Jimmy’s dedication—and yet another remarkable achievement to add to his list of accomplishments. He won the United Nations Human Rights Prize and the Nobel Peace Prize. He wrote 30 books. He helped monitor more than 100 elections in countries with fragile democracies—and did not pull and punches about the ways America’s own democracy was being undermined from within.

He worked to erase the stigma of mental illness and improved access to care for millions of Americans. He taught at Emory University. He built hundreds of homes with Habitat for Humanity. And, as I saw when I visited with Jimmy and Rosalynn in Plains a few years ago, he also painted, built wooden furniture, and took the time to offer his intellect and wisdom to people from all walks of life. As he once told my dad, tongue in cheek, “I have Secret Service protection, so I can pretty well do what I want to!”

Whenever I have struggled with a global health challenge, I knew I could call him and ask for his candid advice. It’s just starting to sink in that I can no longer do that.

But President Carter’s example of moral leadership will inspire me for as long as I’m able to pursue philanthropy—just as it will the hundreds of millions of people whose lives he touched through peacemaking, preaching, teaching, science, and medicine. James Earl Carter Jr. was an incredible statesman and human being. I will miss him dearly.

My dad passed away peacefully at home yesterday, surrounded by his family.

We will miss him more than we can express right now. We are feeling grief but also gratitude. My dad’s passing was not unexpected—he was 94 years old and his health had been declining—so we have all had a long time to reflect on just how lucky we are to have had this amazing man in our lives for so many years. And we are not alone in these feelings. My dad’s wisdom, generosity, empathy, and humility had a huge influence on people around the world.

My sisters, Kristi and Libby, and I are very lucky to have been raised by our mom and dad. They gave us constant encouragement and were always patient with us. I knew their love and support were unconditional, even when we clashed in my teenage years. I am sure that’s one of the reasons why I felt comfortable taking some big risks when I was young, like leaving college to start Microsoft with Paul Allen. I knew they would be in my corner even if I failed.

As I got older, I came to appreciate my dad’s quiet influence on almost everything I have done in life. In Microsoft’s early years, I turned to him at key moments to seek his legal counsel. (Incidentally, my dad played a similar role for Howard Schultz of Starbucks, helping him out at a key juncture in his business life. I suspect there are many others who have similar stories.)

My dad also had a profound influence on my drive. When I was a kid, he wasn’t prescriptive or domineering, and yet he never let me coast along at things I was good at, and he always pushed me to try things I hated or didn’t think I could do (swimming and soccer, for example). And he modeled an amazing work ethic. He was one of the hardest-working and most respected lawyers in Seattle, as well as a major civic leader in our region.

My dad’s influence on our philanthropy was just as big. Throughout my childhood, he and my mom taught me by example what generosity looked like in how they used their time and resources. One night in the 1990s, before we started our foundation, Melinda, Dad, and I were standing in line at the movies. Melinda and I were talking about how we had been getting more requests for donations in the mail. Dad simply said, “Maybe I can help.”

The Bill & Melinda Gates Foundation would not be what it is today without my dad. More than anyone else, he shaped the values of the foundation. He was collaborative, judicious, and serious about learning. He was dignified but hated anything that seemed pretentious. (Dad’s given name was William H. Gates II, but he never used the “II”—he thought it sounded stuffy.) He was great at stepping back and seeing the big picture. He was quick to tear up when he saw people suffering in the world. And he would not let any of us forget the people behind the strategies we were discussing.

People who came through the doors of the Gates Foundation felt honored to work with my dad. He saw the best in everyone and made everyone feel special.

We worked together at the foundation not so much as father and son but as friends and colleagues. He and I had always wanted to do something concrete together. When we started doing so in a big way at the foundation, we had no idea how much fun we would have. We only grew closer during more than two decades of working together.

Finally, my dad had a profoundly positive influence on my most important roles—husband and father. When I am at my best, I know it is because of what I learned from my dad about respecting women, honoring individuality, and guiding children’s choices with love and respect.

Dad wrote me a letter on my 50^th birthday. It is one of my most prized possessions. In it, he encouraged me to stay curious. He said some very touching things about how much he loved being a father to my sisters and me. “Over time,” he wrote, “I have cautioned you and others about the overuse of the adjective ‘incredible’ to apply to facts that were short of meeting its high standard. This is a word with huge meaning to be used only in extraordinary settings. What I want to say, here, is simply that the experience of being your father has been… incredible.”

I know he would not want me to overuse the word, but there is no danger of doing that now. The experience of being the son of Bill Gates was incredible. People used to ask my dad if he was the real Bill Gates. The truth is, he was everything I try to be. I will miss him every day.

My family worked together on a wonderful obituary for my dad, which you can read here.

Warren Buffett turns 90 years old today. It’s hard to believe that my close friend is entering his tenth decade. Warren has the mental sharpness of a 30-year-old, the mischievous laugh of a 10-year-old, and the diet of a 6-year-old. He once told me that he looked at the data and discovered that first-graders have the best actuarial odds, so he decided to eat like one. He was only half-joking.

Here’s a short birthday video in honor of his dietary preferences:

Warren is still so youthful that it’s easy to forget he was once an actual young man, just starting out in his career. Here he is with his first wife, Susan, and their first two children, Susie and Howard. (Peter hadn’t been born yet.) This photo was taken in 1956, around the time Warren started the Buffett Partnership, the investment firm that eventually morphed into Berkshire Hathaway.

If you’ve ever been to a Dairy Queen, you’re probably familiar with one of their most popular menu items, the Blizzard, soft serve ice cream mixed with sundae toppings, cookies, brownies, or candy. You might also be aware that every Blizzard is served upside down—a surprising piece of fast food performance art to prove that each treat is so thick it will defy gravity.

“Thinking differently and celebrating an upside-down philosophy runs deep in the DQ system,” is how one Dairy Queen executive once explained the practice.

The same could be said of the genius of Dairy Queen’s owner, Warren Buffett, whose Berkshire Hathaway empire acquired the restaurant chain in 1998. (A frequent Dairy Queen customer, Warren explained at the time that he and his business partner, Charlie Munger, “put our money where our mouth is.”)

Every time I get to see Warren, I’m struck by his surprising, insightful, “upside-down” view of the world. He thinks differently—about almost everything. For starters, he credits his amazing success to something anyone could do. “I just sit in my office and read all day,” he explained.

In a time when instant gratification is craved in all aspects of life, Warren is one of the most patient people I know, willing to wait to get the results he wants. As he once said, “Someone’s sitting in the shade today because someone planted a tree a long time ago.”

And, as I’ve learned again and again during my visits with him even his diet is oddly upside down. Instead of ending his day with dessert, that’s how he likes to begin the day. He counts Oreos and ice cream among his breakfast foods!

During my visit to Berkshire Hathaway’s annual meeting in Omaha last month, I learned more about Warren’s sweet tooth. Warren and I broke away from the meetings to visit a Dairy Queen for some lunch and to get some restaurant training. We learned how to work the cash register, greet guests, and make a Blizzard (including the proper way to serve it, “Always upside down with a smile!”) I think I may have been a quicker study than Warren in the Blizzard department but watch the video above and you can judge for yourself.

Now that Warren knows how to make a Blizzard, I suspect it will be on his breakfast menu too. (Warren, just be careful turning it upside down!)

Whenever I hang out with Warren Buffett, I feel like a kid in a candy store. And not just because of his famous sweet tooth (one of the first times he came to visit in Seattle, our kids were stunned when they saw him chowing down Oreos for breakfast). We’ve been close friends for more than 25 years, and we have just as much fun together now as we did when we first met. In all that time we have never run out of things to talk about and laugh about.

So when we got together in Omaha during this year’s Berkshire Hathaway shareholder meeting, we decided to check out a real candy store. Actually, although the Fairmont Antiques & Mercantile has just about every kind of sweet you can imagine, it is much more than a candy store. It’s also an old-fashioned soda shop, used record store, vintage memorabilia shop, and pinball museum. We had a blast reminiscing about our favorite treats, Melinda’s and my special history with Willie Nelson, why pinball machines were the best business Warren ever had, and a lot more. Take a look:

When the weather turns warm, some people head to the beach. Some like a picnic in the park. Personally, there is one place I visit every spring no matter what: Omaha, Nebraska, the site of Berkshire Hathaway’s annual shareholders weekend with the company’s CEO and chairman (and my friend) Warren Buffett.

“Woodstock for Capitalists” is always a magical weekend, and this year’s was no exception. Tens of thousands of people came to buy stuff from Berkshire companies, check out the local steakhouses, and most of all, soak up the wit and wisdom of Warren and his partner, Charlie Munger. I would go even if I weren’t on the company’s board of directors. Despite all the changes in the business landscape during Warren’s 52-year tenure, he has lived by the same principles of integrity and creating business value since day one. He sets a wonderful example, and even though I have known him well for more than 25 years, I have never stopped learning from him.

Although the Berkshire weekend is always busy, Warren and I usually find time to goof off with a few games of bridge or a golf-cart ride around the showroom. (See my posts from 2012, 2013, 2014, and 2015. I didn’t post anything last year, but we goofed off then too.)

This year, Warren took me on a tour of Nebraska Furniture Mart, a super-successful megastore owned by Berkshire. We tried out some lounge chairs, played with remote-controlled mattresses, and somehow managed to get lost. Take a look:

I still love software as much today as I did when Paul Allen and I started Microsoft. But—even though it has improved a lot in the decades since then—in many ways, software is still pretty dumb.

To do any task on a computer, you have to tell your device which app to use. You can use Microsoft Word and Google Docs to draft a business proposal, but they can’t help you send an email, share a selfie, analyze data, schedule a party, or buy movie tickets. And even the best sites have an incomplete understanding of your work, personal life, interests, and relationships and a limited ability to use this information to do things for you. That’s the kind of thing that is only possible today with another human being, like a close friend or personal assistant.

In the next five years, this will change completely. You won’t have to use different apps for different tasks. You’ll simply tell your device, in everyday language, what you want to do. And depending on how much information you choose to share with it, the software will be able to respond personally because it will have a rich understanding of your life. In the near future, anyone who’s online will be able to have a personal assistant powered by artificial intelligence that’s far beyond today’s technology.

This type of software—something that responds to natural language and can accomplish many different tasks based on its knowledge of the user—is called an agent. I’ve been thinking about agents for nearly 30 years and wrote about them in my 1995 book The Road Ahead, but they’ve only recently become practical because of advances in AI.

Agents are not only going to change how everyone interacts with computers. They’re also going to upend the software industry, bringing about the biggest revolution in computing since we went from typing commands to tapping on icons.

A personal assistant for everyone

Some critics have pointed out that software companies have offered this kind of thing before, and users didn’t exactly embrace them. (People still joke about Clippy, the digital assistant that we included in Microsoft Office and later dropped.) Why will people use agents?

The answer is that they’ll be dramatically better. You’ll be able to have nuanced conversations with them. They will be much more personalized, and they won’t be limited to relatively simple tasks like writing a letter. Clippy has as much in common with agents as a rotary phone has with a mobile device.

An agent will be able to help you with all your activities if you want it to. With permission to follow your online interactions and real-world locations, it will develop a powerful understanding of the people, places, and activities you engage in. It will get your personal and work relationships, hobbies, preferences, and schedule. You’ll choose how and when it steps in to help with something or ask you to make a decision.

To see the dramatic change that agents will bring, let’s compare them to the AI tools available today. Most of these are bots. They’re limited to one app and generally only step in when you write a particular word or ask for help. Because they don’t remember how you use them from one time to the next, they don’t get better or learn any of your preferences. Clippy was a bot, not an agent.

Agents are smarter. They’re proactive—capable of making suggestions before you ask for them. They accomplish tasks across applications. They improve over time because they remember your activities and recognize intent and patterns in your behavior. Based on this information, they offer to provide what they think you need, although you will always make the final decisions.

Imagine that you want to plan a trip. A travel bot will identify hotels that fit your budget. An agent will know what time of year you’ll be traveling and, based on its knowledge about whether you always try a new destination or like to return to the same place repeatedly, it will be able to suggest locations. When asked, it will recommend things to do based on your interests and propensity for adventure, and it will book reservations at the types of restaurants you would enjoy. If you want this kind of deeply personalized planning today, you need to pay a travel agent and spend time telling them what you want.

The most exciting impact of AI agents is the way they will democratize services that today are too expensive for most people. They’ll have an especially big influence in four areas: health care, education, productivity, and entertainment and shopping.

Health care

Today, AI’s main role in healthcare is to help with administrative tasks. Abridge, Nuance DAX, and Nabla Copilot, for example, can capture audio during an appointment and then write up notes for the doctor to review.

The real shift will come when agents can help patients do basic triage, get advice about how to deal with health problems, and decide whether they need to seek treatment. These agents will also help healthcare workers make decisions and be more productive. (Already, apps like Glass Health can analyze a patient summary and suggest diagnoses for the doctor to consider.) Helping patients and healthcare workers will be especially beneficial for people in poor countries, where many never get to see a doctor at all.

These clinician-agents will be slower than others to roll out because getting things right is a matter of life and death. People will need to see evidence that health agents are beneficial overall, even though they won’t be perfect and will make mistakes. Of course, humans make mistakes too, and having no access to medical care is also a problem.

Mental health care is another example of a service that agents will make available to virtually everyone. Today, weekly therapy sessions seem like a luxury. But there is a lot of unmet need, and many people who could benefit from therapy don’t have access to it. For example, RAND found that half of all U.S. military veterans who need mental health care don’t get it.

AI agents that are well trained in mental health will make therapy much more affordable and easier to get. Wysa and Youper are two of the early chatbots here. But agents will go much deeper. If you choose to share enough information with a mental health agent, it will understand your life history and your relationships. It’ll be available when you need it, and it will never get impatient. It could even, with your permission, monitor your physical responses to therapy through your smart watch—like if your heart starts to race when you’re talking about a problem with your boss—and suggest when you should see a human therapist.

Education

For decades, I’ve been excited about all the ways that software would make teachers’ jobs easier and help students learn. It won’t replace teachers, but it will supplement their work—personalizing the work for students and liberating teachers from paperwork and other tasks so they can spend more time on the most important parts of the job. These changes are finally starting to happen in a dramatic way.

The current state of the art is Khanmigo, a text-based bot created by Khan Academy. It can tutor students in math, science, and the humanities—for example, it can explain the quadratic formula and create math problems to practice on. It can also help teachers do things like write lesson plans. I’ve been a fan and supporter of Sal Khan’s work for a long time and recently had him on my podcast to talk about education and AI.

But text-based bots are just the first wave—agents will open up many more learning opportunities.

For example, few families can pay for a tutor who works one-on-one with a student to supplement their classroom work. If agents can capture what makes a tutor effective, they’ll unlock this supplemental instruction for everyone who wants it. If a tutoring agent knows that a kid likes Minecraft and Taylor Swift, it will use Minecraft to teach them about calculating the volume and area of shapes, and Taylor’s lyrics to teach them about storytelling and rhyme schemes. The experience will be far richer—with graphics and sound, for example—and more personalized than today’s text-based tutors.

Productivity

There’s already a lot of competition in this field. Microsoft is making its Copilot part of Word, Excel, Outlook, and other services. Google is doing similar things with Assistant with Bard and its productivity tools. These copilots can do a lot—such as turn a written document into a slide deck, answer questions about a spreadsheet using natural language, and summarize email threads while representing each person’s point of view.

Agents will do even more. Having one will be like having a person dedicated to helping you with various tasks and doing them independently if you want. If you have an idea for a business, an agent will help you write up a business plan, create a presentation for it, and even generate images of what your product might look like. Companies will be able to make agents available for their employees to consult directly and be part of every meeting so they can answer questions.

Whether you work in an office or not, your agent will be able to help you in the same way that personal assistants support executives today. If your friend just had surgery, your agent will offer to send flowers and be able to order them for you. If you tell it you’d like to catch up with your old college roommate, it will work with their agent to find a time to get together, and just before you arrive, it will remind you that their oldest child just started college at the local university.

Entertainment and shopping

Already, AI can help you pick out a new TV and recommend movies, books, shows, and podcasts. Likewise, a company I’ve invested in, recently launched Pix, which lets you ask questions (“Which Robert Redford movies would I like and where can I watch them?”) and then makes recommendations based on what you’ve liked in the past. Spotify has an AI-powered DJ that not only plays songs based on your preferences but talks to you and can even call you by name.

Agents won’t simply make recommendations; they’ll help you act on them. If you want to buy a camera, you’ll have your agent read all the reviews for you, summarize them, make a recommendation, and place an order for it once you’ve made a decision. If you tell your agent that you want to watch Star Wars, it will know whether you’re subscribed to the right streaming service, and if you aren’t, it will offer to sign you up. And if you don’t know what you’re in the mood for, it will make customized suggestions and then figure out how to play the movie or show you choose.

You’ll also be able to get news and entertainment that’s been tailored to your interests. CurioAI, which creates a custom podcast on any subject you ask about, is a glimpse of what’s coming.

A shock wave in the tech industry

In short, agents will be able to help with virtually any activity and any area of life. The ramifications for the software business and for society will be profound.

In the computing industry, we talk about platforms—the technologies that apps and services are built on. Android, iOS, and Windows are all platforms. Agents will be the next platform.

To create a new app or service, you won’t need to know how to write code or do graphic design. You’ll just tell your agent what you want. It will be able to write the code, design the look and feel of the app, create a logo, and publish the app to an online store. OpenAI’s launch of GPTs this week offers a glimpse into the future where non-developers can easily create and share their own assistants.

Agents will affect how we use software as well as how it’s written. They’ll replace search sites because they’ll be better at finding information and summarizing it for you. They’ll replace many e-commerce sites because they’ll find the best price for you and won’t be restricted to just a few vendors. They’ll replace word processors, spreadsheets, and other productivity apps. Businesses that are separate today—search advertising, social networking with advertising, shopping, productivity software—will become one business.

I don’t think any single company will dominate the agents business--there will be many different AI engines available. Today, agents are embedded in other software like word processors and spreadsheets, but eventually they’ll operate on their own. Although some agents will be free to use (and supported by ads), I think you’ll pay for most of them, which means companies will have an incentive to make agents work on your behalf and not an advertiser’s. If the number of companies that have started working on AI just this year is any indication, there will be an exceptional amount of competition, which will make agents very inexpensive.

But before the sophisticated agents I’m describing become a reality, we need to confront a number of questions about the technology and how we’ll use it. I’ve written before about the issues that AI raises, so I’ll focus specifically on agents here.

The technical challenges

Nobody has figured out yet what the data structure for an agent will look like. To create personal agents, we need a new type of database that can capture all the nuances of your interests and relationships and quickly recall the information while maintaining your privacy. We are already seeing new ways of storing information, such as vector databases, that may be better for storing data generated by machine learning models.

Another open question is about how many agents people will interact with. Will your personal agent be separate from your therapist agent and your math tutor? If so, when will you want them to work with each other and when should they stay in their lanes?

How will you interact with your agent? Companies are exploring various options including apps, glasses, pendants, pins, and even holograms. All of these are possibilities, but I think the first big breakthrough in human-agent interaction will be earbuds. If your agent needs to check in with you, it will speak to you or show up on your phone. (“Your flight is delayed. Do you want to wait, or can I help rebook it?”) If you want, it will monitor sound coming into your ear and enhance it by blocking out background noise, amplifying speech that’s hard to hear, or making it easier to understand someone who’s speaking with a heavy accent.

There are other challenges too. There isn’t yet a standard protocol that will allow agents to talk to each other. The cost needs to come down so agents are affordable for everyone. It needs to be easier to prompt the agent in a way that will give you the right answer. We need to prevent hallucinations, especially in areas like health where accuracy is super-important, and make sure that agents don’t harm people as a result of their biases. And we don’t want agents to be able to do things they’re not supposed to. (Although I worry less about rogue agents than about human criminals using agents for malign purposes.)

Privacy and other big questions

As all of this comes together, the issues of online privacy and security will become even more urgent than they already are. You’ll want to be able to decide what information the agent has access to, so you’re confident that your data is shared with only people and companies you choose.

But who owns the data you share with your agent, and how do you ensure that it’s being used appropriately? No one wants to start getting ads related to something they told their therapist agent. Can law enforcement use your agent as evidence against you? When will your agent refuse to do something that could be harmful to you or someone else? Who picks the values that are built into agents?

There’s also the question of how much information your agent should share. Suppose you want to see a friend: If your agent talks to theirs, you don’t want it to say, "Oh, she’s seeing other friends on Tuesday and doesn’t want to include you.” And if your agent helps you write emails for work, it will need to know that it shouldn’t use personal information about you or proprietary data from a previous job.

Many of these questions are already top-of-mind for the tech industry and legislators. I recently participated in a forum on AI with other technology leaders that was organized by Sen. Chuck Schumer and attended by many U.S. senators. We shared ideas about these and other issues and talked about the need for lawmakers to adopt strong legislation.

But other issues won’t be decided by companies and governments. For example, agents could affect how we interact with friends and family. Today, you can show someone that you care about them by remembering details about their life—say, their birthday. But when they know your agent likely reminded you about it and took care of sending flowers, will it be as meaningful for them?

In the distant future, agents may even force humans to face profound questions about purpose. Imagine that agents become so good that everyone can have a high quality of life without working nearly as much. In a future like that, what would people do with their time? Would anyone still want to get an education when an agent has all the answers? Can you have a safe and thriving society when most people have a lot of free time on their hands?

But we’re a long way from that point. In the meantime, agents are coming. In the next few years, they will utterly change how we live our lives, online and off.

The risks created by artificial intelligence can seem overwhelming. What happens to people who lose their jobs to an intelligent machine? Could AI affect the results of an election? What if a future AI decides it doesn’t need humans anymore and wants to get rid of us?

These are all fair questions, and the concerns they raise need to be taken seriously. But there’s a good reason to think that we can deal with them: This is not the first time a major innovation has introduced new threats that had to be controlled. We’ve done it before.

Whether it was the introduction of cars or the rise of personal computers and the Internet, people have managed through other transformative moments and, despite a lot of turbulence, come out better off in the end. Soon after the first automobiles were on the road, there was the first car crash. But we didn’t ban cars—we adopted speed limits, safety standards, licensing requirements, drunk-driving laws, and other rules of the road.

We’re now in the earliest stage of another profound change, the Age of AI. It’s analogous to those uncertain times before speed limits and seat belts. AI is changing so quickly that it isn’t clear exactly what will happen next. We’re facing big questions raised by the way the current technology works, the ways people will use it for ill intent, and the ways AI will change us as a society and as individuals.

In a moment like this, it’s natural to feel unsettled. But history shows that it’s possible to solve the challenges created by new technologies.

I have written before about how AI is going to revolutionize our lives. It will help solve problems—in health, education, climate change, and more—that used to seem intractable. The Gates Foundation is making it a priority, and our CEO, Mark Suzman, recently shared how he’s thinking about its role in reducing inequity.

I’ll have more to say in the future about the benefits of AI, but in this post, I want to acknowledge the concerns I hear and read most often, many of which I share, and explain how I think about them.

One thing that’s clear from everything that has been written so far about the risks of AI—and a lot has been written—is that no one has all the answers. Another thing that’s clear to me is that the future of AI is not as grim as some people think or as rosy as others think. The risks are real, but I am optimistic that they can be managed. As I go through each concern, I’ll return to a few themes:

• Many of the problems caused by AI have a historical precedent. For example, it will have a big impact on education, but so did handheld calculators a few decades ago and, more recently, allowing computers in the classroom. We can learn from what’s worked in the past.
• Many of the problems caused by AI can also be managed with the help of AI.
• We’ll need to adapt old laws and adopt new ones—just as existing laws against fraud had to be tailored to the online world.

In this post, I’m going to focus on the risks that are already present, or soon will be. I’m not dealing with what happens when we develop an AI that can learn any subject or task, as opposed to today’s purpose-built AIs. Whether we reach that point in a decade or a century, society will need to reckon with profound questions. What if a super AI establishes its own goals? What if they conflict with humanity’s? Should we even make a super AI at all?

But thinking about these longer-term risks should not come at the expense of the more immediate ones. I’ll turn to them now.

Deepfakes and misinformation generated by AI could undermine elections and democracy.

The idea that technology can be used to spread lies and untruths is not new. People have been doing it with books and leaflets for centuries. It became much easier with the advent of word processors, laser printers, email, and social networks.

AI takes this problem of fake text and extends it, allowing virtually anyone to create fake audio and video, known as deepfakes. If you get a voice message that sounds like your child saying “I’ve been kidnapped, please send $1,000 to this bank account within the next 10 minutes, and don’t call the police,” it’s going to have a horrific emotional impact far beyond the effect of an email that says the same thing.

On a bigger scale, AI-generated deepfakes could be used to try to tilt an election. Of course, it doesn’t take sophisticated technology to sow doubt about the legitimate winner of an election, but AI will make it easier.

There are already phony videos that feature fabricated footage of well-known politicians. Imagine that on the morning of a major election, a video showing one of the candidates robbing a bank goes viral. It’s fake, but it takes news outlets and the campaign several hours to prove it. How many people will see it and change their votes at the last minute? It could tip the scales, especially in a close election.

When OpenAI co-founder Sam Altman testified before a U.S. Senate committee recently, Senators from both parties zeroed in on AI’s impact on elections and democracy. I hope this subject continues to move up everyone’s agenda.

We certainly have not solved the problem of misinformation and deepfakes. But two things make me guardedly optimistic. One is that people are capable of learning not to take everything at face value. For years, email users fell for scams where someone posing as a Nigeran prince promised a big payoff in return for sharing your credit card number. But eventually, most people learned to look twice at those emails. As the scams got more sophisticated, so did many of their targets. We’ll need to build the same muscle for deepfakes.

The other thing that makes me hopeful is that AI can help identify deepfakes as well as create them. Intel, for example, has developed a deepfake detector, and the government agency DARPA is working on technology to identify whether video or audio has been manipulated.

This will be a cyclical process: Someone finds a way to detect fakery, someone else figures out how to counter it, someone else develops counter-countermeasures, and so on. It won’t be a perfect success, but we won’t be helpless either.

AI makes it easier to launch attacks on people and governments.

Today, when hackers want to find exploitable flaws in software, they do it by brute force—writing code that bangs away at potential weaknesses until they discover a way in. It involves going down a lot of blind alleys, which means it takes time and patience.

Security experts who want to counter hackers have to do the same thing. Every software patch you install on your phone or laptop represents many hours of searching, by people with good and bad intentions alike.

AI models will accelerate this process by helping hackers write more effective code. They’ll also be able to use public information about individuals, like where they work and who their friends are, to develop phishing attacks that are more advanced than the ones we see today.

The good news is that AI can be used for good purposes as well as bad ones. Government and private-sector security teams need to have the latest tools for finding and fixing security flaws before criminals can take advantage of them. I hope the software security industry will expand the work they’re already doing on this front—it ought to be a top concern for them.

This is also why we should not try to temporarily keep people from implementing new developments in AI, as some have proposed. Cyber-criminals won’t stop making new tools. Nor will people who want to use AI to design nuclear weapons and bioterror attacks. The effort to stop them needs to continue at the same pace.

There’s a related risk at the global level: an arms race for AI that can be used to design and launch cyberattacks against other countries. Every government wants to have the most powerful technology so it can deter attacks from its adversaries. This incentive to not let anyone get ahead could spark a race to create increasingly dangerous cyber weapons. Everyone would be worse off.

That’s a scary thought, but we have history to guide us. Although the world’s nuclear nonproliferation regime has its faults, it has prevented the all-out nuclear war that my generation was so afraid of when we were growing up. Governments should consider creating a global body for AI similar to the International Atomic Energy Agency.

AI will take away people’s jobs.

In the next few years, the main impact of AI on work will be to help people do their jobs more efficiently. That will be true whether they work in a factory or in an office handling sales calls and accounts payable. Eventually, AI will be good enough at expressing ideas that it will be able to write your emails and manage your inbox for you. You’ll be able to write a request in plain English, or any other language, and generate a rich presentation on your work.

As I argued in my February post, it’s good for society when productivity goes up. It gives people more time to do other things, at work and at home. And the demand for people who help others—teaching, caring for patients, and supporting the elderly, for example—will never go away. But it is true that some workers will need support and retraining as we make this transition into an AI-powered workplace. That’s a role for governments and businesses, and they’ll need to manage it well so that workers aren’t left behind—to avoid the kind of disruption in people’s lives that has happened during the decline of manufacturing jobs in the United States.

Also, keep in mind that this is not the first time a new technology has caused a big shift in the labor market. I don’t think AI’s impact will be as dramatic as the Industrial Revolution, but it certainly will be as big as the introduction of the PC. Word processing applications didn’t do away with office work, but they changed it forever. Employers and employees had to adapt, and they did. The shift caused by AI will be a bumpy transition, but there is every reason to think we can reduce the disruption to people’s lives and livelihoods.

AI inherits our biases and makes things up.

Hallucinations—the term for when an AI confidently makes some claim that simply is not true—usually happen because the machine doesn’t understand the context for your request. Ask an AI to write a short story about taking a vacation to the moon and it might give you a very imaginative answer. But ask it to help you plan a trip to Tanzania, and it might try to send you to a hotel that doesn’t exist.

Another risk with artificial intelligence is that it reflects or even worsens existing biases against people of certain gender identities, races, ethnicities, and so on.

To understand why hallucinations and biases happen, it’s important to know how the most common AI models work today. They are essentially very sophisticated versions of the code that allows your email app to predict the next word you’re going to type: They scan enormous amounts of text—just about everything available online, in some cases—and analyze it to find patterns in human language.

When you pose a question to an AI, it looks at the words you used and then searches for chunks of text that are often associated with those words. If you write “list the ingredients for pancakes,” it might notice that the words “flour, sugar, salt, baking powder, milk, and eggs” often appear with that phrase. Then, based on what it knows about the order in which those words usually appear, it generates an answer. (AI models that work this way are using what's called a transformer. GPT-4 is one such model.)

This process explains why an AI might experience hallucinations or appear to be biased. It has no context for the questions you ask or the things you tell it. If you tell one that it made a mistake, it might say, “Sorry, I mistyped that.” But that’s a hallucination—it didn’t type anything. It only says that because it has scanned enough text to know that “Sorry, I mistyped that” is a sentence people often write after someone corrects them.

Similarly, AI models inherit whatever prejudices are baked into the text they’re trained on. If one reads a lot about, say, physicians, and the text mostly mentions male doctors, then its answers will assume that most doctors are men.

Although some researchers think hallucinations are an inherent problem, I don’t agree. I’m optimistic that, over time, AI models can be taught to distinguish fact from fiction. OpenAI, for example, is doing promising work on this front.

Other organizations, including the Alan Turing Institute and the National Institute of Standards and Technology, are working on the bias problem. One approach is to build human values and higher-level reasoning into AI. It’s analogous to the way a self-aware human works: Maybe you assume that most doctors are men, but you’re conscious enough of this assumption to know that you have to intentionally fight it. AI can operate in a similar way, especially if the models are designed by people from diverse backgrounds.

Finally, everyone who uses AI needs to be aware of the bias problem and become an informed user. The essay you ask an AI to draft could be as riddled with prejudices as it is with factual errors. You’ll need to check your AI’s biases as well as your own.

Students won’t learn to write because AI will do the work for them.

Many teachers are worried about the ways in which AI will undermine their work with students. In a time when anyone with Internet access can use AI to write a respectable first draft of an essay, what’s to keep students from turning it in as their own work?

There are already AI tools that are learning to tell whether something was written by a person or by a computer, so teachers can tell when their students aren’t doing their own work. But some teachers aren’t trying to stop their students from using AI in their writing—they’re actually encouraging it.

In January, a veteran English teacher named Cherie Shields wrote an article in Education Week about how she uses ChatGPT in her classroom. It has helped her students with everything from getting started on an essay to writing outlines and even giving them feedback on their work.

“Teachers will have to embrace AI technology as another tool students have access to,” she wrote. “Just like we once taught students how to do a proper Google search, teachers should design clear lessons around how the ChatGPT bot can assist with essay writing. Acknowledging AI’s existence and helping students work with it could revolutionize how we teach.” Not every teacher has the time to learn and use a new tool, but educators like Cherie Shields make a good argument that those who do will benefit a lot.

It reminds me of the time when electronic calculators became widespread in the 1970s and 1980s. Some math teachers worried that students would stop learning how to do basic arithmetic, but others embraced the new technology and focused on the thinking skills behind the arithmetic.

There’s another way that AI can help with writing and critical thinking. Especially in these early days, when hallucinations and biases are still a problem, educators can have AI generate articles and then work with their students to check the facts. Education nonprofits like Khan Academy and OER Project, which I fund, offer teachers and students free online tools that put a big emphasis on testing assertions. Few skills are more important than knowing how to distinguish what’s true from what’s false.

We do need to make sure that education software helps close the achievement gap, rather than making it worse. Today’s software is mostly geared toward empowering students who are already motivated. It can develop a study plan for you, point you toward good resources, and test your knowledge. But it doesn’t yet know how to draw you into a subject you’re not already interested in. That’s a problem that developers will need to solve so that students of all types can benefit from AI.

What’s next?

I believe there are more reasons than not to be optimistic that we can manage the risks of AI while maximizing their benefits. But we need to move fast.

Governments need to build up expertise in artificial intelligence so they can make informed laws and regulations that respond to this new technology. They’ll need to grapple with misinformation and deepfakes, security threats, changes to the job market, and the impact on education. To cite just one example: The law needs to be clear about which uses of deepfakes are legal and about how deepfakes should be labeled so everyone understands when something they’re seeing or hearing is not genuine

Political leaders will need to be equipped to have informed, thoughtful dialogue with their constituents. They’ll also need to decide how much to collaborate with other countries on these issues versus going it alone.

In the private sector, AI companies need to pursue their work safely and responsibly. That includes protecting people’s privacy, making sure their AI models reflect basic human values, minimizing bias, spreading the benefits to as many people as possible, and preventing the technology from being used by criminals or terrorists. Companies in many sectors of the economy will need to help their employees make the transition to an AI-centric workplace so that no one gets left behind. And customers should always know when they’re interacting with an AI and not a human.

Finally, I encourage everyone to follow developments in AI as much as possible. It’s the most transformative innovation any of us will see in our lifetimes, and a healthy public debate will depend on everyone being knowledgeable about the technology, its benefits, and its risks. The benefits will be massive, and the best reason to believe that we can manage the risks is that we have done it before.

Is it harder for machines to mimic the way humans move or the way humans think? If you had asked me this question a decade ago, my answer would have been “think.” So much of how the brain works is still a mystery. And yet, in just the last year, advancements in artificial intelligence have resulted in computer programs that can create, calculate, process, understand, decide, recognize patterns, and continue learning in ways that resemble our own.

Building machines that operate like our bodies—that walk, jump, touch, hold, squeeze, grip, climb, slice, and reach like we do (or better)—would seem to be an easier feat in comparison. Surprisingly, it hasn’t been. Many robots still struggle to perform basic human tasks that require the dexterity, mobility, and cognition most of us take for granted.

But if we get the technology right, the uses for robots will be almost limitless: Robots can help during natural disasters when first responders would otherwise have to put their lives on the line—or during public health crises like the COVID pandemic, when in-person interactions might spread disease. On farms, they can be used instead of toxic chemical herbicides to manually pull weeds. They can work long days lugging hundred- or thousand-pound loads around factory floors. A good enough robotic arm will also be invaluable as a prosthesis.

I understand concerns about robots taking people’s jobs, an unfortunate consequence of almost every new innovation—including the internet, which (for example) turned everyone into a travel agent and eliminated much of the vacation-planning industry. If robots have a similar impact on employment, governments and the private sector will have to help people navigate the transition. But given present labor shortages in our economy and the dangerous or unrewarding nature of certain professions, I believe it’s less likely that robots replace us in jobs we love and more likely that they’ll do work people don’t want to be doing. In the process, they can make us safer, healthier, more productive, and even less lonely.

That’s why I’m so excited about the companies across the country and around the world that are at the forefront of robotics technology, working to usher in a robotics revolution. Some of their robots are humanoid or human-like—constructed so they can interact easily in environments built for people. Others have super-human traits like flight or extendable arms that can supplement an ordinary person’s abilities. Some move around on legs. Others have wheels. Some navigate using sensors. Others are operated by remote controls.

Despite their differences, though, one thing is certain: In healthcare, hospitality, agriculture, manufacturing, construction, and even our homes, robots have the potential to transform the way we live and work. In fact, a few of them already are.

Here are some of the cutting-edge robotics start-ups and labs that I’m excited about:

Agility Robotics

If we want robots to operate in our environments as seamlessly as possible, perhaps those robots should be modeled after people. That’s what Oregon-based Agility Robotics decided when creating Digit, what they call the “first human-centric, multi-purpose robot made for logistics work.” It’s roughly the same size as a person—it’s designed to work with people, go where we go, and operate in our workflows—but it’s able to carry much heavier loads and extend its “arms” to reach shelves we’d need ladders for.

Tevel

For farmers in some rich countries, around 40 percent of costs can come from labor—with workers spending entire days out in the hot sun and then stopping at night. But given the labor shortage in agriculture, farms often have to throw away fruit that’s not harvested in time. That’s why Tevel, founded in Tel Aviv, has created flying autonomous robots that can scan tree canopies and pick ripe apples and stone fruits around the clock, while simultaneously collecting comprehensive harvesting data in real time.

Apptronik

What’s more useful: multiple robots that can each do one task over and over, or one robot that can do multiple tasks and learn to do even more? To Apptronik, an Austin-based start-up that spun out of the human-centered robotics lab at the University of Texas, the answer is obvious. So they’re building “general-purpose” humanoid bi-pedal robots like Apollo, which can be programmed to do a wide array of tasks—from carrying boxes in a factory to helping out with household chores. And because it can run software from third parties, Apollo will be just a software update away from new functionalities.

RoMeLa

Building a robot that can navigate rocky and unstable terrain, and retain its balance without falling over, is no small task. But the Robotics and Mechanisms Lab, or RoMeLa, at UCLA is working on improving mobility for robots. They may have cracked the code with ARTEMIS, possibly the fastest “running” robot in the world that’s also difficult to destabilize. ARTEMIS actually competed at the RoboCup 2023, an international soccer competition held in France in July.

Field AI

Some robots don’t just need great “bodies”; they need great brains, too. That’s what Field AI—a robotics company based in Southern California that doesn’t build robots—is trying to create. Instead of focusing on the hardware of these machines, Field AI is developing AI software for other companies’ robots that enables them to perceive their environments, navigate without GPS (on land, by water, or in the air), and even communicate with each other.

I’ve always been a car guy. When I was younger, I used to love driving fast (sometimes too fast). Now, I look forward to my daily commute to work. There’s something so fun yet meditative about driving a car.

Despite that, I’m excited for the day I get to hand over control of my car to a machine.

That day is coming sooner rather than later. We’ve made tremendous progress on autonomous vehicles, or AVs, in recent years, and I believe we’ll reach a tipping point within the next decade. When it happens, AVs will change transportation as dramatically as the PC changed office work. A lot of this development has been enabled by the progress made in artificial intelligence more broadly. (I recently shared my thoughts about AI on this blog. You can read them here.)

Some background for those who might not know a lot about AVs: The best way to understand where we are today is by looking at the Society of American Engineers, or SAE, classification system. This is widely used to describe how autonomous a vehicle is.

In levels 0-2, a human driver is in full control of the car, but the vehicle can provide assistance through features like adaptive cruise control and lane centering. Level 3 is when the technology starts to move from the driver being in control to the vehicle being in control. By the time you reach the highest level, the car can be fully autonomous at all times and under all conditions—the level 5 vehicles of the future might not have steering wheels at all.

Right now, we’re close to the tipping point—between levels 2 and 3—when cars are becoming available that allow the driver to take their hands off the wheel and let the system drive in certain circumstances. The first level 3 car was recently approved for use in the United States, although only in very specific conditions: Autonomous mode is permitted if you’re going under 40 mph on a highway in Nevada on a sunny day.

Over the next decade, we’ll start to see more vehicles crossing this threshold. AVs are rapidly reaching the point where almost all of the technology required has been invented. Now, the focus is on refining algorithms and perfecting the engineering. There have been huge advances in recent years—especially in sensors, which scan the surrounding environment and tell the vehicle about things it needs to react to, like pedestrians crossing the street or another driver who swerves into your lane.

There are a lot of different approaches to AVs in development. Many vehicle manufacturers—like GM, Honda, and Tesla—are working on models that look like regular cars but have autonomous features. Then there are companies entirely focused on AVs, some of whose products are pushing the boundaries of what a vehicle can be—like a perfectly symmetrical robotaxi or public transit pods. Many others are developing components that can be installed to give an existing vehicle autonomous capabilities.

I recently had the opportunity to test drive—or test ride, I guess—a vehicle made by the British company Wayve, which has a fairly novel approach. While a lot of AVs can only navigate on streets that have been loaded into their system, the Wayve vehicle operates more like a person. It can drive anywhere a human can drive.

When you get behind the wheel of a car, you rely on the knowledge you’ve accumulated from every other drive you’ve ever taken. That’s why you know what to do at a stop sign, even if you’ve never seen that particular sign on that specific road before. Wayve uses deep learning techniques to do the same thing. The algorithm learns by example. It applies lessons acquired from lots of real world driving and simulations to interpret its surroundings and respond in real time.

The result was a memorable ride. The car drove us around downtown London, which is one of the most challenging driving environments imaginable, and it was a bit surreal to be in the car as it dodged all the traffic. (Since the car is still in development, we had a safety driver in the car just in case, and she assumed control several times.)

It’s not clear yet which approaches will be the most successful, since we’re only starting to reach the threshold where cars become truly autonomous. But once we get there, what will the transition to AVs actually look like?

For one thing, passenger cars will likely be one of the last vehicle types to see widespread autonomous adoption. Long-haul trucking will probably be the first sector, followed by deliveries. When you finally do step into an AV, it will likely be a taxi or a rental car. (Rental car companies lose a lot of money every year to driver-caused accidents, so they’re eager to transition to an AV fleet that is—at least in theory—less accident-prone.)

As AVs become more common, we’re going to have to rethink many of the systems we’ve created to support driving. Car insurance is a great example. Who is responsible when an autonomous vehicle gets in an accident, the person riding in the car or the company that programmed the software? Governments will have to create new laws and regulations. Roads might even have to change. A lot of highways have high-occupancy lanes to encourage carpooling—will we one day have “autonomous vehicles only” lanes? Will AVs eventually become so popular that you have to use the “human drivers only” lane if you want to be behind the wheel?

That type of shift is likely decades away, if it happens at all. Even once the technology is perfected, people might not feel comfortable riding in a car without a steering wheel at first. But I believe the benefits will convince them. AVs will eventually become cheaper than regular vehicles. And if you commute by car like me, just think about how much time you waste driving. You could instead catch up on emails, or read a good book, or watch the new episode of your favorite show—all things that are possible in fully autonomous vehicles. More importantly, AVs will help create more equity for the elderly and people with disabilities by providing them with more transportation options. And they’ll even help us avoid a climate disaster, since the majority in development are also electric vehicles.

Humanity has adapted to new modes of transportation before. I believe we will do it again. For most of our existence, we relied on natural ways of getting around: We walked, or rode on horseback, or traveled in a boat pushed by wind. Then, in the 1700s, we entered the locomotion age when mobility was powered by steam engines and internal combustion. Now, we find ourselves in the early days of the autonomous age. It’s an exciting time, and I can’t wait to see what new possibilities it unlocks.

I’ve been fascinated by the artist and inventor Leonardo da Vinci for decades. He had one of the most innovative minds ever. Next year is the 500^th anniversary of his death, and I thought I would share a short video about a project I’ve worked on that is helping to mark the occasion.

The project is called the Codescope. It’s an interactive kiosk with a touch screen that lets you explore the Codex Leicester, a notebook of Leonardo’s that I bought in 1994. Using the Codescope, you can learn about the history of the notebook, see every page of Leonardo’s original writing, get a translation, and even watch animated versions of his drawings.

The Codex and Codescope are traveling together to various museums in Europe as part of the celebration. (They’re at the Uffizi in Florence through January 20.) Since you can’t touch the Codex itself—it’s preserved behind glass—the Codescope is the next best thing to flipping through the pages that the great man wrote on.

Can Alzheimer’s disease be funny? I was skeptical, especially given the devastating experience my family had watching my dad suffer from it. So, I asked two experts in using humor to raise awareness—Seth Rogen and Lauren Miller Rogen—to help me see the light. We had a great conversation about their organization Hilarity for Charity, hope for the future of Alzheimer’s research, the importance of a good night’s sleep, and why Seth started a cannabis lifestyle company. 

Sal Khan is a true pioneer of harnessing the power of technology to help kids learn. So, when I wanted to learn more about how artificial intelligence will transform education, I knew I had to talk to the founder of Khan Academy. I loved chatting with Sal about why tutoring is so important, how his new service Khanmigo is making the most of ChatGPT, and how we can keep teachers at the center of the classroom in the age of AI. We even found time to talk about our favorite teachers and the subject we wish we’d studied in school.

Ahmir “Questlove” Thompson is the ultimate multi-hyphenate: He’s a musician, filmmaker, author, entrepreneur, and more. The Grammy and Oscar winner is also a plant-based foods advocate, so when I had some questions about the future of food, I knew I had to sit down with him. We had a blast talking about why he made a meatless Philly cheesesteak, how we make healthy food accessible to more people, Questlove’s insane record collection, how we got our nicknames, and our Wordle strategies.

I recently started learning French, and the process has made one thing clear to me: There’s a lot I don’t understand about how languages work. So, I turned to John McWhorter, a linguist who has dedicated his career to demystifying the roughly 7,000 languages spoken around the world. When he isn’t busy writing books, John is a professor at Columbia University, host of his own podcast, and frequent lecturer for Great Courses. He helped me understand why English is so irregular, what the ideal language would look like, why all dialects are created equal, and more.

Few people are better at explaining the science of artificial intelligence than Yejin Choi. She’s a computer science professor at the University of Washington, senior research director at the Allen Institute for AI, and the recipient of a MacArthur Fellowship. I thought her recent TED talk was terrific, and I was thrilled to talk to her about how you train a large language model, why it’s so hard for robots to pick tools out of a box, and why universities must play a key role in the future of AI research.

If you ask people to name leaders in artificial intelligence, there’s one name you’ll probably hear more than any other: Sam Altman. His team at OpenAI is pushing the boundaries of what AI can do with ChatGPT, and I loved getting to talk to him about what’s next. Our conversation covered why today’s AI models are the stupidest they’ll ever be, how societies adapt to technological change, and even where humanity will find purpose once we’ve perfected artificial intelligence.

When I start to feel overwhelmed by the climate challenges we face, I turn to Hannah Ritchie, a researcher at Our World in Data. Her data-driven approach is an essential antidote to environmental doomsday-ism and provides some much-needed optimism about humanity’s ability to tackle big problems. I recently sat down with Hannah to talk about her terrific new book Not the End of the World, why it’s so hard to wrap our minds around human progress, what we would ask a time traveler about the future, and more.

Several huge global setbacks over the past few years have left many people discouraged and wondering whether the world is destined to keep getting worse. The pandemic and the invasion of Ukraine are just two examples. These setbacks are causing significant suffering.

But it is important to remember that they are happening in the context of two decades’ worth of historic progress. I believe it is possible to mitigate the damage and get back to the progress the world was making. In this post I will enumerate the progress and the setbacks, explain how the world can respond, and discuss how I and others can do our part.

Melinda and I started our foundation in 2000 to advance our vision that every person should have the chance to live a healthy and productive life. That same year, the world set an ambitious vision for improving people’s lives when it adopted the United Nations Millennium Development Goals and agreed to measurable targets for meeting those goals.

Over the next 20 years—thanks to efforts by governments, the private sector, non-profits, and philanthropies like ours—the number of children who died before their fifth birthday dropped by half, from 12 million per year to 6 million per year. The fraction of people living in extreme poverty also dropped by half. More children enrolled in school than ever. Deadly diseases such as HIV, TB, and malaria went into retreat, as the number of people who died from these diseases continued to fall. This progress was not limited to one region or to wealthy countries. It happened in dozens of countries all over the world from Bangladesh to Ethiopia to Ghana.

Against this backdrop, the pandemic is one of the biggest setbacks in history. The world was poorly prepared, so the damage is widespread. In addition to more than 20 million excess deaths caused by COVID— exacerbated by the inequity in vaccine distribution between high- and low-income countries—childhood deaths from all causes are going up because of disruptions to health systems. Polio eradication was set back several years. Students have lost as many as two years of learning in most countries. Emergency spending on the COVID response has left governments with large debts that will have to be paid off. Many countries are experiencing significant job losses, particularly among women. Women have had to bear most of the burden of taking care of children who were not in school.  

The war on Ukraine is a gigantic tragedy for the entire world. Ukraine itself is experiencing the death and destruction of an intense war. The country will have to be rebuilt. The reduction in the supply of natural gas is driving up costs, such as the cost of electricity, particularly in Europe. The reduction in the supply of food—particularly wheat and edible oils—and the supply of fertilizer is driving up food prices, which will increase malnutrition and instability in low-income countries.

The world economy is entering a low-growth cycle, with rising interest rates and high inflation. Deficit spending will have to be reined in to reduce inflationary pressure. Government income will go down and more will be spent on interest payments, which will reduce the amount of money available for programs and make trade-offs necessary. Aid budgets will be stretched, and the poorest countries may see support cut at the time when they need it most. Many low- and middle-income countries have unsustainable levels of debt, particularly as their currencies weaken against the currencies they have borrowed in. Reducing these debts will be particularly hard because a significant portion of them is owed to China and the private sector, rather than traditional development banks, which makes it much more challenging to negotiate debt relief.

The damage from climate change is already worse than most models predicted. We are seeing a lot of bad weather events, including heat waves and lower agricultural output, particularly in countries near the Equator. Most countries are falling short of the climate commitments they have made. Hard-to-reduce emissions from agriculture/deforestation, buildings, and industrial production including cement and steel continue to go up, more than offsetting the reductions from electric cars and renewable energy. Low-income countries are hurt the most, even though they are responsible for only a small portion of the historical emissions.

We are facing all these global crises at a time of deep political polarization in the United States. The political divide limits our political capacity for dialogue, compromise, and cooperation and thwarts the bold leadership required both domestically and internationally to tackle these threats. Polarization is forcing us to look backwards and fight again for basic human rights, social justice, and democratic norms. I believe the reversal of abortion rights in the U.S. is a huge setback for gender equality, for women’s health, and for overall human progress. The potential for even further regression is scary. It will put lives at risk for women, people of color, and anyone living on the margins.

Response to setbacks

How can I possibly still be optimistic? I see incredible heroism and sacrifice all over the world. Medical workers put in unbelievable hours at great risk to themselves to help people infected with COVID. Incredible efforts are taking place to help refugees from the Ukrainian war and to help those caught in battle zones. Activists are courageously protesting and often risking their lives to protect people’s rights. People on the front lines inspire me to do whatever I can. Although each of us can only do so much, when lots of people join in we will resume progress.

We need all sectors of society—government, the private sector, and the non-profit sector including philanthropy—to engage on these issues. Philanthropy is the smallest of these sectors, but it is unique in its ability to try risky ideas that can have a large impact if they succeed and are scaled up.

I wish I knew how to help bring the war to a quicker end or to shorten the economic downcycle or improve our political capacity. I have an open mind to helping anyone who proposes how to improve these areas.

Personally, I am putting a lot of my energy and resources into innovators working on pandemic prevention, global health, climate mitigation (including getting rid of dependence on hydrocarbons) and adaptation, education improvement (including remediation), and food costs. When I say “innovation,” I’m referring to new products and services as well as new ways of delivering them to those in need—including by strengthening local leaders and institutions. These innovations will not come in time to avoid the problems altogether, but the faster we move, the less people will suffer. For many people including myself this is the most concrete way of contributing, even when it seems modest compared to the scale of the problems. Focusing on being part of the solution is better than giving up in despair.

Innovation areas

These are some of the areas where I think innovation can make a big difference with new tools and new ways of delivering them. These are areas where the groups I am involved with—the Bill & Melinda Gates Foundation and Breakthrough Energy (for climate mitigation)—are working with partners to come up with solutions, and the innovations I describe are all in the pipeline.

Preventing pandemics. Eventually, we will have vaccines that prevent infection (as opposed to reducing only the risk of getting severely ill or dying) and last for at least a decade. A vaccine that prevented infection would cut cases over half in countries with good vaccine coverage. (These vaccine advances will also allow scientists to make vaccines for TB and HIV.) A drug that blocks respiratory infection will be able to be deployed even faster than a new vaccine. The world should fund and staff a global group connected to the WHO doing monitoring so that outbreaks are stopped before they become pandemics.

Reducing childhood deaths. The world can get back to and even exceed the vaccine coverage levels we had before the pandemic, when 80 percent of children were being reached. There will be new vaccines for respiratory diseases and other conditions that threaten the lives of infants and children in low-income countries. A new generation of malaria-preventing bednets will help overcome the resistance that mosquitos have developed to the current generation. Researchers need to invent transformative tools, including more-effective vaccines and new ways of reducing mosquito populations to allow for eventually eradicating malaria. Because of COVID and other setbacks, the United Nations’ goal to cut childhood deaths in half again to 3 million by 2030 will be missed, but it can still be achieved the following decade.

Eradicating diseases. Polio is nearly eradicated—the number of cases has dropped 99.9 percent since 1988. Some countries have recently benefited from innovations such as better mapping capabilities to make sure that all children are reached with vaccines. Mobile money is being used to make sure vaccinators get paid. An improved polio vaccine was given an emergency license during the pandemic and is now being used in 20 countries. The last places with endemic cases of wild polio are Pakistan and Afghanistan, and with the right level of funding and stability, eradication has a strong chance of succeeding in 3 to 4 years—which will make it only the second disease after smallpox to be eradicated. Recent cases in Malawi and Mozambique—after decades with no wild polio—and recent detection of poliovirus in sewage in London remind us that it will spread back globally if we don’t get rid of it completely.

Improving food security and climate adaptation. Low- and middle-income countries are already by far the most affected by climate change, given that they depend on agriculture that is being put at risk by more frequent droughts and floods. Africa is currently a large net importer of food, including grains and edible oils. More than 30 percent of African and South Asian children are so malnourished that they don’t fully develop their mental and physical potential. With population growth and climate change, Africa will have less food per person unless agricultural productivity is increased. A new generation of seeds along with using cell phones to advise farmers on better farming practices will allow a doubling of agricultural productivity in Africa despite climate change. This will turn Africa from a net food importer to a net food exporter and reduce pressure to deforest. This is an important piece of climate adaptation that requires far more investment.

Achieving gender equality. Melinda has helped me and many others see how improving women’s access to health care and contraceptives, empowering girls with better education, giving women access to savings and credit, and creating leadership opportunities for them can lift up societies. This is not only an equity issue but a way of making progress for everyone. There is still a lot to do in improving maternal health and providing access to family planning, especially for women in low- and middle-income countries. Innovations include better contraceptive choices, new ways of reducing anemia, and inexpensive tools for reducing maternal mortality. Increasing the use of mobile phones by women can create economic opportunities for them and give them access to digital financial services.

Improving educational outcomes. Just equipping students with computers only improves education outcomes modestly. By adding personalized, engaging curriculum and systems to detect when students need advice and support, the foundation’s partners have seen substantial gains. This work covers everything from structured pedagogy in lower-income countries to improving math instruction in the American K-12 system to preparation for key classes in college. Getting this right has turned out to be far harder than I expected, but it is clearly achievable.

Mitigating climate change. We can invent new ways of making products that eliminate emissions while not costing much more. I call this reducing the Green Premiums, and the toughest areas include making zero-emissions steel and cement. Several companies funded by my Breakthrough Energy group and others in the past few years have made more progress than I expected. Policies in rich countries can drive demand for these products, helping to bring the Green Premiums down to zero. It is still daunting since it requires replacing large parts of the physical economy in all the high- and middle-income countries. As more people witness the progress here, I think a sense of real possibility will emerge, which will help get the policies and urgent action necessary to succeed.

I am very proud of the Gates Foundation’s role in these areas. (I fund climate mitigation through Breakthrough Energy, not the foundation.) We have been able to help bring together other foundations, non-profits, governments, multilateral agencies, and the private sector as partners to solve big problems. We were central to the creation of GAVI and the Global Fund, both of which created innovative ways to deliver lifesaving tools like vaccines and anti-retrovirals to people who need them most. Together these two groups have saved 60 million lives so far. Along with Rotary International, we have been a key partner in reviving the effort to eradicate polio. We supported the creation of a new vaccine for rotavirus that has reduced the number of children who die of this disease every year by 75 percent, from 528,000 annually in 2000 to 128,500 in 2016. And we are just at the beginning of the work that is needed to ensure that women have the access and power to use these innovations.

Accelerating investment

Over the past two decades, the Gates Foundation has gone from spending around $1 billion per year to spending nearly $6 billion per year. During the pandemic, Melinda and I approved spending an additional $2 billion so we could help with the COVID response without taking money away from other important work that we fund. (Of this commitment, $1.5 billion had been spent by the end of 2021, with remaining commitments of up to $500 million that have not been disbursed.) At the time, we expected the extra spending to stop once the acute phase of the pandemic was over. But it is now clear that the need in all the areas where we work is greater than ever. The great crises of our time require all of us to do more.

For this reason, rather than returning the foundation’s budget to pre-pandemic levels, we will continue to expand it. With the support and guidance of our board, the Gates Foundation intends to increase spending from nearly $6 billion per year before COVID to $9 billion per year by 2026. Our focus will remain the same—but at this moment of great need and opportunity, this spending will allow us to accelerate progress by investing more deeply in the areas where we are already working. To help make this spending increase possible, I am transferring $20 billion to the foundation’s endowment this month.

Biggest gift ever given

There is one not-very-well-known but incredibly important reason why the foundation has been able to be so ambitious. Although it is named the Bill & Melinda Gates Foundation, basically half of our resources to date have come from Warren Buffett’s gifts. Since 2006, Warren has gifted the foundation $35.7 billion, including his most recent gift of $3.1 billion in June. The actual value of these gifts is about $45 billion if you include the appreciation of the Berkshire Hathaway stock after it was given. Warren’s advice and thinking influenced the foundation in a profound way even before he made any gifts. Warren, I can never adequately express how much I appreciate your friendship and guidance as well as your generosity.

Future plan

As I look to the future, my plan is to give all my wealth to the foundation other than what I spend on myself and my family. I do some giving and investing in U.S. health care issues, including Alzheimer’s, outside the foundation. Through Breakthrough Energy, I will continue to invest and give money to address climate change. Overall I expect that the work in these areas will make money, which will also go to the foundation. I will move down and eventually off of the list of the world’s richest people. My giving this money is not a sacrifice at all. I feel privileged to be involved in tackling these great challenges, I enjoy the work, and I believe I have an obligation to return my resources to society in ways that have the greatest impact for improving lives.

I hope others in positions of great wealth and privilege will step up in this moment too.

Part 1 of the Netflix documentary series Inside Bill’s Brain tells the story of the Gates Foundation’s quest to rethink sanitation for the world’s poorest. First step: reinvent the toilet! This belief in the power of innovation has been a constant in my life, starting from the time I fell in love with software in high school to my work today at our foundation. What follows is the story of a moment of clarity for me on that path and the influence of someone who’s been a critical guide along the way.

If you’d have asked me in my twenties if I’d ever retire early from Microsoft, I’d have told you that you were crazy. I loved the magic of software, and the ever-rising learning curve that Microsoft provided. It was hard for me to imagine anything else I’d rather do.

By my mid-forties my perspective was changing. The U.S. government’s antitrust suit against Microsoft had drained me, sucking some of the joy out of my work. Stepping down as CEO in early 2000, I hoped to focus more on building software products, always the best part of my job.

Also, my world view was broadening. Both Melinda and I were feeling a strengthening pull toward our young foundation and its work in U.S. education and the development of drugs and vaccines for diseases in poor countries. For the first time in my adult life I allowed myself space for non-Microsoft reading, soaking up books on the immune system, malaria and the history of plagues just as I had once scoured The Art of Computer Programming.

With our commitment to philanthropy growing, Melinda and I transferred $20 billion of Microsoft stock to our foundation, making it the largest of its kind in the world. Within a year I’d taken my first overseas trip for the foundation, to India, where I squeezed drops of polio vaccine into babies’ mouths. Melinda traveled to Thailand and India to study how those countries were handling AIDS.

Our good friend Warren Buffett was curious about this new journey we were on. So in the fall of 2001, he invited me to a resort in West Virginia and asked me to speak to a group of business leaders about what Melinda and I were learning.

I’m not a natural public speaker. But at Microsoft, speech after speech, year after year, I learned to step out on a stage and paint a vision of technology for our customers, partners and the media. It helped that people wanted to hear about the white-hot software industry. I grew to enjoy it.

I felt like I was starting over with our foundation. At big global meetings, like the World Economic Forum, people flocked to hear me detail some cool piece of software, but the crowd and the energy would be gone when later that day I’d announce an innovative plan to get vaccines to millions of children.

At the time, many people I met thought health problems in low-income countries were so big and intractable that no amount of money could make any significant difference. I could see why. It was easy to ignore death and disease happening so far away. And so much of what we read in the news about global health focused on doom and gloom. This frustrated me. The problems were real enough, but so is the power of human ingenuity to find solutions. Melinda and I felt a strong sense of optimism, but we didn’t see that reflected in these stories.

Right around the time Warren asked me to give the talk, Melinda and I were trying to figure out how we might use our voices to raise the visibility of global health. Would anyone listen?

My speech to Warren’s friends was a chance to practice. If I could stir them, it would be a step towards persuading the people with the power to make the biggest difference: the legislators and heads of countries who decide how much money flows into foreign aid and global health.

I was a little nervous heading to the conference room where Warren’s group was gathered—but more than that, I was exhausted. We were in the midst of negotiations over the antitrust case, and I’d been on the phone with lawyers deep into the night. I hadn’t had time to write a full speech. I’d just jotted notes between calls, trying to simplify all we had learned into the clearest possible story.

I started talking, haltingly at first. Our big revelation, I explained, had come in the mid-1990s when Melinda and I realized how much misery in poor countries is caused by health problems that the rich world had stopped trying to solve because we’re no longer affected by them. That incensed us. The cost of that inequity at the time was three million children dying ever year, I said.

Those deaths, we realized, weren’t caused by a bunch of runaway diseases, but by a handful of illnesses that are largely treatable. Diarrhea and pneumonia alone were responsible for half of the deaths among children. Many of those children could be saved with medicines and vaccines that already existed. All that was lacking were incentives and systems to get those life-saving technologies to the people and places where they were needed—and some new inventions to speed the change.

Our philanthropy, I explained, followed the same philosophy that guided Microsoft: relentless innovation. The right vaccine can wipe a deadly virus off the planet. A better toilet can help stop diarrheal disease. Investments in science and technology can help millions to survive their childhood and lead healthy productive lives—potentially the greatest return in R&D spending ever.

As I spoke, the legal tangles that had consumed me the night before vanished. I was energized. When ideas excite me, I rock, I sway, I pace—my body turns into a metronome for my brain. For the first time, all the facts and figures, anecdotes and analyses cohered into a story that was uplifting—even for me. I was able to make clear the logic of our giving and why I was so optimistic that a combination of money, technology, scientific breakthroughs, and political will could make a more equitable world faster than a lot of people thought.

I could tell from the nods and laughs and caliber of questions that the group got it. Afterward, Warren came over with a big smile. “That was amazing, Bill,” he said. “What you said was amazing, and your energy around this work is amazing.” I grinned back at him. Three ‘amazings’—a first.

The confidence I found that day encouraged me to take a more public role on global health issues. Over the next year, I refined my message at events and in interviews. I spent more time talking about health with government leaders. (That’s now a big part of my job.)

But something else had happened, too. The speech helped me see more clearly a life for myself after Microsoft, centered on the work that Melinda and I had started. Software would remain my focus for years and I will always consider it the thing that most shaped who I am. But I felt energized to get further along this new path we were traveling, to learn more and to apply myself to the obstacles in the way of more people living better lives. Eventually, I would retire from Microsoft almost a decade earlier that I had planned. The 2001 speech was a step, a private moment, on the way to that decision.

Now I get to focus every day on trying to deliver the vision I outlined in that conference room almost two decades ago. The world is more equitable now than it was then. But we’ve still got a long way to go. By letting Netflix’s cameras in, I hope you can see the joy I get from my work and why I am so optimistic that with ingenuity, imagination, and determination, we can make even more progress towards that goal.

I grew up in a family where giving back to society—whether through volunteer time or financial resources—was just part of what you did. At the dinner table, both of my parents talked frequently about their volunteer work with non-profits and their advocacy work for children and the less fortunate in our community.

Community service was also an important part of Melinda’s upbringing; so even when we were still just engaged to be married, we talked about our responsibility to give back the great majority of our wealth—even though at that point we didn’t know exactly how or when we’d do it.

Anyone who wants to seriously engage in giving faces two important questions: where can you make the biggest impact, and how do you structure your giving so it’s effective.

Our viewpoint evolved over time, but there was a real turning point when we read an article about rotavirus, a disease that was pretty much a non-event in the United States, but which still killed a half-million children a year in the developing world. It seemed impossible to us that it was receiving so little worldwide attention. And so we dug in, learnt a lot more about the problem, and eventually began a serious effort to reduce childhood mortality worldwide.

Today, the framework that guides our giving is based on the simple premise that everyone deserves the chance to live a healthy, productive life. Given the resources at our disposal, we believed we could make the biggest difference by concentrating in three areas: global health, global development, and in the US, education.

Half our foundation’s funds are spent addressing global health problems, with a focus on malaria, tuberculosis, AIDS, diarrheal and respiratory diseases.

Twenty-five per cent of the foundation’s funds assist the poorest people in the world in ways other than healthcare through development projects. And the other 25% is devoted to improving public education in the US, where, in spite of our nation’s great wealth, our education system continues to fail too many of our children.

A few basic principles guide the way in which we give. Our approach emphasizes partnerships, and looks to foster innovation, often pursuing new technologies or delivery schemes.

We try to apply new thinking and approaches to solving big problems, which sometimes means taking calculated risks on promising ideas. We set goals and are quite serious about measuring our results. Often, this means attempting to be a catalyst by investing in areas where governments can’t or won’t invest, or where there is a vacuum or failure in the marketplace.

Diseases that affect the poor are a great case in point. Rich-world diseases attract research investments that dwarf the money going to problems like rotavirus. (Think of how much more money goes to curing male pattern baldness than malaria!) As a foundation, we have the chance to help address that inequality.

The question of risk is something we think about a lot. Warren Buffett, our good friend and the third trustee of our foundation, reminds us that failure will be part of any bold approach. “You can have a perfect batting average by not doing anything too important. Or you’ll bat something less than that if you take on the really tough problems.”

We’re willing to accept failure at times in the name of trying new things to solve old and difficult problems.

At the end of the day, what draws people to philanthropy is something universal—the connection to other human beings and the desire to make a difference. This is what tugs at people and that makes them want to get involved, to imagine how they can help create a better world.

For me, philanthropy is a responsibility, a passion, and an honor. And so far as I can tell—after being a parent—it’s the most gratifying job on earth.

Note – An edited version of this post was published as part of the ‘Doing Good’ series on livemint.com.