Youyang Gu Data scientist and creator of covid19-projections.com
Auren Hoffman CEO of the geospatial data company SafeGraph
Hollis Robbins Dean of Arts & Humanities, Sonoma State University
Eliot Peper Author of nine science-fiction novels
Fadeke Adegbuyi Writer of the Cybernaut newsletter
Andy Bromberg CEO of the digital wallet startup Eco
Matt Clifford Cofounder and CEO of Entrepreneur First
David Lang Executive Director of the Experiment Foundation
Tomer Hanuka Award-winning illustrator
Patrick Wyman Host of the Tides of History podcast
Tamara Winter Editor at Stripe, previously Charter Cities Institute
Packy McCormick Writer of the Not Boring newsletter
Jacob Mchangama Creator of the podcast Clear and Present Danger
Andy Coravos Cofounder and CEO of HumanFirst, formerly EiR FDA
Nikhyl Singhal Writer of The Skip newsletter, VP of Product at Facebook
Holly Liu Cofounder of the mobile gaming company Kabam
Hamish McKenzie Cofounder of Substack
Lindsay Howard Head of Community at digital art platform Foundation
Gabby Dizon Cofounder of play-to-earn gaming guild Yield Guild Games
Sotonye Jack Creator of the written interview platform Time Well Spent
Nadia Eghbal Independent researcher and writer
“Science is the belief in the ignorance of experts,” as Nobel Prize-winning physicist Richard Feynman once said. Right now, we’re either witnessing a golden age of expertise or a crisis of expertise, depending on who you ask. It’s undeniable that technology has democratized access to high-quality information, data, and tools for research, creation, and distribution. But how do we separate the contrarians from the cranks, the signals from the noise, the skills we need and the skills we don’t? More broadly, how is expertise being redefined in the modern era?
We posed that question to 20+ experts. The line-up includes those that society might traditionally categorize as such — academics, scientists, researchers — as well as authorities in their own domains: a sci-fi novelist, an award-winning illustrator, gamers, prominent and emerging newsletter writers, and startup builders. Their answers are far from unequivocal, but do provide insights across education, science funding, healthcare, and more. The contributors offer advice for both organizations and individuals (“Here’s something I wish I had learned in my 20s…”) as well as what they consider essential skills for building expertise.
In March 2020, I googled the word “epidemiology” and read the Wikipedia page on “mathematical modeling of infectious diseases.” With COVID-19 arriving in full force in the U.S., I was anxious about the future (along with countless others), and I set out to build a machine learning model to predict the direction of the pandemic. One month later, my model at covid-projections19.com was included by the CDC as one of five COVID-19 models forecasting deaths. It soon was considered to be one of the most accurate, and the site I built would go on to receive millions of visitors throughout the pandemic.
I was an untrained data scientist with zero prior experience in infectious diseases, but I became known as an “expert” in COVID-19. Not that I did it alone — my model was a crowdsourced effort, because I received help and advice from countless individuals on social media. Advancements in technology and dismantling barriers to communication have enabled access to, and the ability to build on, tons of information and knowledge that were previously inaccessible. With a few keystrokes and mouse clicks, I was able to receive real-time responses from experts and non-experts alike. For a time-sensitive topic like COVID-19, this pace and approach of quick iteration was critical for adjusting to fast-changing dynamics.
Solidarity in opinions may be seen as desirable among some in the scientific community, sometimes at the expense of intellectual debates and scientific discourse … There is a very fine line between questioning the science and being anti-science. I’ve found it quite difficult to walk this line, not only for myself but for the individuals who misrepresent my work to ‘prove the experts wrong.’
In a way, the biggest advantage I had was not knowing anything. Starting with a “blank slate” approach was extremely valuable, as many prior conceptions of how a virus operates did not necessarily apply in the case of this novel coronavirus. And since I had no prior conceptions, I based my results only on what the data was telling me — this turned out to be the right approach more often than not. I’ve seen many instances where experts were unwilling to change their beliefs because the results disagreed with their priors, and it wasn’t until they were presented with overwhelming evidence that they were forced to abandon their assumptions.
As a result of this experience, my own perception of expertise has changed. I believe there exists a modicum of groupthink in an established expert community; solidarity in opinions may be seen as desirable among some in the scientific community, sometimes at the expense of intellectual debates and scientific discourse. However, this is understandable given the high volume of anti-science rhetoric throughout this pandemic, leading to a need to “consolidate” opinions to counter this rhetoric. I try to avoid this line of thinking, as my goal has always been to seek and present the truth, no matter how inconvenient it may be.
That said, there is a very fine line between questioning the science and being anti-science. I’ve found it quite difficult to walk this line, not only for myself but for the individuals who misrepresent my work to “prove the experts wrong.” I often must clarify that I am not interested in proving the experts wrong, but rather in presenting an unbiased, data-driven analysis that others can build upon in their work. Sometimes this requires me to question the prevailing expertise, especially when new data does not support the existing theories.
When I think about expertise in today’s world — how to claim it and how to understand it — I think that speed is a key skill. Research in academia is generally a slow process — papers take months and sometimes years to go from start to publication. COVID-19 has hastened this timeline, but results still often lag by several months. People who can adapt to fast iterations and release real-time analyses will inevitably have an advantage in producing the latest insights. As long as these individuals possess the ability and resolve to continuously search for scientific truth and create testable hypotheses (such as by making future forecasts), they will be able to give traditional experts a run for their money.
It used to be that “who you know” — not “what you know” — held the most value. But in the last 15 years, it has become much more important to build something than to know people: The “what-you-knows” are ascendent.
The hard thing is figuring out who those real experts are. Here’s something I wish I had learned in my 20s: The “experts” that most people agree on are usually only experts on a very narrow subject. We should listen to them on that one subject, then, and disregard almost everything else they say.
In order to make your own sound decisions rather than blindly following such “experts,” it’s often argued that we need to use first principles — reducing something down to its basic, foundational assumptions and building them from the bottom up, or creating the knowledge from scratch. But we don’t have time to go to first principles on everything. So when do you dive into the data yourself?
It used to be that “who you know,” not “what you know,” held the most value. But in the last 15 years, it has become much more important to build something than to know people: The “what-you-knows” are ascendent.
The first rule of thinking: At any given point in time, you should be working on at least one thing via first-principles thinking. It might take you the rest of your life. But having at least one thing to go deep on is a life well lived.
The second rule of thinking: When relying on proxies — which is likely the case for over 99% of what you believe — vary your proxies. Variation increases the likelihood that the proxies end up disagreeing with each other on important truths.
This brings us to the third rule: Make sure that the proxies you use conflict with each other at least some of the time, giving you ample opportunity to question your assumptions. And at least some of your proxies should be heretics in their field.
The internet has exposed teaching and lecturing across the world to public view, both via formal online courses and informal video recordings of lectures. Most people focus on the vast reserves of content now available online, but few people ask: “Is this a good teacher?”
Likewise, many education technologies focus on information delivery, not teaching, or focus on networks of people who know people, not subject matter expertise. The best scholars are those who have a single-minded focus, strive to learn everything about that thing, and change how we see it. To paraphrase the famed Swiss psychologist Jean Piaget: If you work to become an expert in one thing, however narrow, you gain the ability to be an expert in anything — you’ve trained your brain to organize knowledge effectively.
Many education technologies focus on information delivery, not teaching, or focus on networks of people who know people, not subject matter expertise … Too few people inside and outside the education sector talk about what makes a great teacher and what makes great teaching.
The best way to recognize an expert is to be one. The best way to become an expert is to learn from experts who are themselves brilliant teachers. The challenge is that people are not experts in what makes a great teacher. A few years ago, a fascinating study suggested that students like entertaining lecturers that make them think that they’re learning. I’d put most TED Talks in this category — everyone goes home full, thinking they’ve learned a lot, when active learning environments where you are seen and engaged by the teacher are much more conducive to actually learning.
Unfortunately, gatekeeping for great professors has not yet been disrupted; the college admission system still limits who can study with whom. Thus, truly great teachers are often known only by a select community: other experts in the field and former students. Too few people inside and outside the education sector talk about what makes a great teacher and what makes great teaching. What we need is future thinking that focuses not only on what makes a great teacher, but what will make that great teaching available to all.
Nobel Prize-winning physicist Richard Feynman had a trick for seeking out truths clouded by expertise. He was always talking to experts in diverse fields — mathematicians, artists, geologists — but most of the time they couldn’t articulate their ideas in a way that anyone but their colleagues could understand. As a result, their ideas rarely influenced the larger culture. Feynman, meanwhile, developed a reputation as a polymath. Experts in many different fields were stunned by how quickly he grokked their hardest problems, zeroed in on key questions, and offered constructive insights.
How did he do it? Simple. Whenever an expert was describing a complex idea, Feynman asked for a concrete example. Then he followed the example along in his mind as they built back up to the idea itself. Not infrequently, the example would reveal obvious flaws or gaps in the idea, and he would interrupt. Even if the idea was sound, the example clarified it. By moving from the concrete to the abstract instead of the other way around, Feynman excised insight from unnecessary complexity. He unlocked the value expertise was supposed to offer, even when it didn’t.
The more I learn, the more concrete experiences I accumulate, the more I see that if you can’t explain an idea with simple, clear, precise language, you probably don’t yet have an idea worth explaining.
I write thrillers about the near future, and each novel has speculative elements woven through it: what-if questions about how the world is changing that drive the story forward. Like Feynman’s trick, these questions often emerge from trawling the internet for concrete examples that spark my curiosity. Maybe I read a tweet that leads me to a blog post which leads me to a subreddit and then a newsletter and then a podcast and then a few articles in scientific journals and then a series of YouTube videos and then a book and then another dozen books and then I start emailing and DMing people and Zooming with them and maybe even meeting a few in person. If, instead of answers, I’m left with a sufficiently compelling question, then I begin to suspect that it might become the seed for a new novel.
The internet is a shadow city with billions of residents. Everyone has a voice, even if nobody listens. Yes, there are assholes and authoritarians. But there are also good samaritans, beautiful nerds, brilliant poets, and every other kind of human you could possibly imagine.
People have wandered the intellectual garden of forking paths for thousands of generations, but the internet is a profound accelerant for such cultural exploration. It is a shadow city with billions of residents. Everyone has a voice, even if nobody listens. Yes, there are assholes and authoritarians. But there are also good samaritans, beautiful nerds, brilliant poets, and every other kind of human you could possibly imagine. The more long-tail blog posts, niche newsletters, and scientific papers I read, the more I realize how desperately we need more stories that bridge important ideas into the larger culture. Humanity has so much profound understanding locked inside expert silos, and narrative is a crowbar that can pry them open for the rest of us. And here’s the kicker: The internet is just getting started. It’s easy to forget how new this whole wonky, dazzling, contradictory place is. We haven’t even begun to figure it out yet.
The command and deep understanding of a subject has been decoupled from credentialism. Experts can be born and brought up on the internet, bypassing post-secondary institutions and other centralized forms of education and knowledge dissemination. One example: An independent researcher can challenge the work of a renowned UC Berkeley professor’s book with a single, well-researched blog post (and a social media account to share it).
Additionally, the rate at which the internet allows for information to be generated and spread means new fields are emerging at lightning speed, with academic and government institutions unable to keep pace. In these new domains, people are not turning to universities or federal departments to learn — instead, they’re often looking to individuals who are taking an internet-first approach to acquiring and sharing expertise.
The generative intellectual environments that academic institutions house and foster are being recreated or entirely rethought online, outside of the brick walls of a university. Internet salons, writer collectives, open-source software, fellowships, and cohort-based courses are providing modern alternatives to those institutions. You don’t need an MSc or PhD to join, just HTTP.
Importantly, the generative intellectual environments that academic institutions house and foster are being recreated or entirely rethought online, outside of the brick walls of a university. Internet salons, writer collectives, open-source software, fellowships, and cohort-based courses are providing modern alternatives to those institutions. You don’t need an MSc or PhD to join, just HTTP. This is not all to say that there’s no value in academic environments and their mechanisms for building and propagating expertise. Formal institutional mechanisms for building and creating expertise can be complementary. But the internet has become an institution of its own that’s reshaping who can become an expert, how they share their expertise, and the ways they can earn a living from it.
Without the academic formality and pressure to uphold institutional reputation, experts now share their knowledge in ways that are decidedly more engaging and even non-academic — say, humorous memes or storytelling devices to explain concepts — across podcast episodes, newsletters, YouTube videos, TikTok clips, and Twitter threads. It’s a change not just in medium, but in mode. An expert in cancer and aging breaks down the science of longevity and health on a YouTube channel with over 375,000 subscribers; a former options trader and investment partner uses TikTok videos to humorously explore subjects like the space economy and the history of ExxonMobil; an investor and expert on China provides long-form tech analysis on the country through a Substack newsletter.
Without the academic formality and pressure to uphold institutional reputation, experts now share their knowledge in ways that are decidedly more engaging and even non-academic … It’s a change not just in medium, but in mode.
And as experts increasingly use the same online channels as content creators, they can be compensated the same way: through an audience. Experts can now go direct using subscription platforms like Substack or Patreon to make a living, bypassing (or combining) traditional mechanisms for being paid for expertise, such as institutional salaries, grants, book deals, and media appearances.
Knowledge-holders thus become “public experts” instead of “institutional experts,” trading a higher level of visibility for a greater degree of scrutiny. By maintaining a constant dialogue with the public rather than a closed discussion within institutions, experts can learn from audiences, sharpen their ideas from critique, and update more quickly based on new information. “Expert” becomes a title that has to be continuously earned, rather than a moniker that is permanently bestowed. A thousand true fans (and a thousand true haters) can spawn a legion of fact-checkers.
The wisdom of crowds is giving way to the “wisdom of communities.” In a world of ever-greater complexity, no one person can possibly make sense of all the signals and all the noise — from a single, static vantage point. A networked group is required to adapt to this new world. It’s evolution: Domains of knowledge historically governed by leading “experts” are being shaken up as the inadequacy of individuals at this new scale of complexity is revealed.
The wisdom of crowds — the idea that groups of people assessing the same possibilities but from different vantage points might have superior insights than “experts” — offered an alternative approach. This approach controls for the flaws of a single interpreter by sampling disparate perspectives and coordinating them into a median viewpoint. Whether in stock exchanges, betting, or prediction markets, the wisdom of crowds has been consistently validated, and even more so in internet times.
But it can’t do everything. Although a wise crowd can observe a system and discern its trajectory, it still can’t build an airplane or write a decent novel. That’s where the wisdom of communities comes in.
If the wisdom of crowds is a form of ‘averaging out’ each person’s abilities, then the wisdom of communities is a way to compound them.
The key difference is that community members coordinate with one another, while crowd members act and predict independently. New communication technologies have made it possible for individuals to globally coordinate their knowledge, leading to expertise growing in places where it would previously have been geographically impossible.
People are no longer being polled in isolation but rather are pooling their individual capabilities. If the wisdom of crowds is a form of “averaging out” each person’s abilities, then the wisdom of communities is a way to compound them. Pretty soon you’ve got something that’s more like an orchestra than a mob, every individual playing their specialized role and building on one another. This is how expertise will come to be defined: less and less by what any one individual knows, and more by the (compounded) insights of broad, distributed communities who may also have vested stakes in their shared ambitions. The ivory tower is giving way to the village.
The internet prizes showing, not telling, whether via a GitHub profile, YouTube channel, a Substack newsletter, or even a timestamped tweet that makes a prediction. Don’t tell me you’re an expert, show me. Beyond being a democratizing force — fewer gatekeepers, more participants — this has had a subtler, but even more important impact: It provides an alternative to traditional expertise that deals better with weirdness, and the world is becoming weirder.
Beyond being a democratizing force — fewer gatekeepers, more participants — the internet has had a subtler, but even more important impact: It provides an alternative to traditional expertise that deals better with weirdness, and the world is becoming weirder.
Traditional expertise is as much about belonging to a community of experts as it is about knowledge. The emerging field of network epistemology is the study of how groups generate and propagate beliefs. One of its lessons is that if having a particular belief is correlated with being well-connected, then soon everyone within a social network will believe that everyone else shares that belief. Deviating from such beliefs is to step outside the network — and thus to surrender the claim to expertise. This is one of the best explanations for why (some) non-specialists on the internet were able to make better predictions about the COVID-19 pandemic than the global public health establishment. By being outside the traditional network of expertise, they were better able to entertain “weird” beliefs—and reality turned out to be very weird indeed.
This won’t be our last weird crisis. From Wall Street bets to climate change to AI, we’re going to need to interpret and respond to more and more outlier events.
This raises two important questions for the future of expertise: First, how do we build better intuitions and norms around when to rely on traditional expertise and when to look further afield? Second, how do we build better tools and institutions for distinguishing “contrarian and correct” from “crank”? The two will often look similar, but the former might sometimes (literally) save the world. Prediction markets and superforecasting communities are good starting points, but there is much more to be built. Developing an epistemology that takes unusual ideas seriously without falling for all of them will be one of the great challenges of this century.
The current distrust of experts is part of a broader breakdown in the social contract between science and society. Science is stuck in its Napster moment — just as the music industry fought the coming disruption of technology, the science establishment is one of the last institutional holdouts to the reality of a digital, connected world. In the same way that early members of the Royal Society, the U.K.’s natural academy of sciences, could not conceive of a scientific project at the scale or scope of the industrial science we know today, current institutions are failing to imagine a bigger and better future for science. For a working academic scientist or administrator, it’s a fixed pie — and a fierce competition — to grab the biggest slice. Science is being played as a finite game when it could, and should, be infinite.
Science is stuck in its Napster moment — just as the music industry fought the coming disruption of technology, the science establishment is one of the last institutional holdouts to the reality of a digital, connected world.
I took an unorthodox path into science through tool-building, not academia. (I co-founded an ocean technology company and an open-source underwater drone company, among other things.) That backdoor gave me a unique perspective into the blindspots of “The Academy.” Most poignantly, I learned that most efforts that fall outside the format of a peer-reviewed, published paper — tools, science communication, or long-term experimentation, for example — are woefully underappreciated. Most scientists are under tremendous pressure to constantly publish. That realization caused me to view scientific expertise through the lens of incentives. I’m nervous to use that language, because it’s the same line that conspiracy theorists use to deny and obfuscate facts, but I do think it’s the fault line. The meaningful fixes will happen there.
The emerging interest in “metascience” — applying a scientific rigor and lens to the processes of science itself — is exactly the right idea, but the body of research there still feels incomplete. We need new ideas and experimentation. We need applied metascientists, people who build new tools and models, in addition to just studying the current systems. I recently attended the Science of Science Funding conference, and the highlight was Katalin Karikó’s recounting of her uphill battle trying to attract funding for her mRNA research. She struggled to secure grants, attract corporate funding, and shore up institutional support throughout the 1990s. She helped save the world in spite of the system, not because of it.
Art used to be a heaven for hermits, a meritocracy: Put a strong portfolio out there, and the rest would happen by itself. Now, being an expert just doesn’t cut it; the field has been leveled in terms of knowledge and skills. The promise of the internet was less human friction. Instead, we got constant networking on every platform.
Expertise would certainly be the first step in this ladder. But there are so many exceptionally great experts with extremely varied education and backgrounds, and so many can deliver on the highest level. What moves an artist forward is defining a professional trajectory and then making human connections toward these targets. It’s called many things — grit, ambition, tenacity — a primal survival instinct in a jungle of talent.
My advice for young illustrators and cartoonists is to be irresponsible and create your own intellectual property or IP … if you have something to say, do your own thing.
My advice for young illustrators and cartoonists is to be irresponsible and create your own intellectual property or IP. The challenge is making a living in the meantime — you’re likely going to be working as a freelancer for, and often blinded by, other IPs. Some of the projects out there are terrific and harness the best talents on earth. But if you have something to say, do your own thing. It will create a space with a different set of metrics, defined solely in service of your artistic vision.
We’re not dealing with a crisis of expertise itself as much as a crisis of explanation. Far too many disciplines (most notably, epidemiology and public health over the last year) have run face-first into their inability to make the general public understand what they’re saying and why.
Part of this is simply a matter of training, but it’s also the effect of a hubristic institutional worldview. Trust has to be earned and reinforced rather than simply assumed. In the absence of forceful and persuasive explanation, trust will inevitably dwindle. This goes for everything from disease control to journalism. Treating any field as a black box whose inner workings are opaque is a terrible idea in an era of mass mistrust.
We’re not dealing with a crisis of expertise itself as much as a crisis of explanation. Far too many disciplines have run face-first into their inability to make the general public understand what they’re saying and why … Treating any field as a black box whose inner workings are opaque is a terrible idea in an era of mass mistrust.
All disciplines have their own technical languages and ways of doing things; however, these norms often have the effect of closing off expertise from outside understanding and inspection. Without the ability to speak that technical language or navigate the norms of a field, how can a layperson hope to understand even the terms of the debate, much less its content or relevance? It’s incumbent on these fields to develop not just their specific expertise, but also the ability to communicate that expertise in terms the general public can grasp. Amid a crisis of public trust in experts, the only path forward is to make massive investments to renew that trust through open and effective explanation of why experts are “right.”
The average city resident often has a better understanding of how a city should feel, of what would make them feel safe and content, than planners these days. Today, living in many cities feels more like playing a (perverse!) game of sidewalk Tetris — with hostile architecture for pedestrians, and streets that are impossible to navigate if you’re not in a car (and sometimes even if you are).
While most experts acknowledge the importance of seeking input from people like this — that is, those with skin in the game — when making decisions, it happens so rarely in practice. It’s not hard to think of examples of this phenomenon across very different industries, from education to healthcare, to city planning and administration.
The average city resident often has a better understanding of how a city should feel, of what would make them feel safe and content, than urban planners today … It’s clear that “expertise” needs to be more about practical, ground-up insights than just top-down planning or research.
During my time working on charter cities — new cities that are granted special jurisdictions to accelerate economic growth — I partnered with a number of people who were developing cities from the ground up. Initially I assumed that devouring World Bank reports about “best practices” for development, or absorbing the histories of charter city forebears like Singapore and Shenzhen, would provide the best intellectual foundation for how to build new, dynamic cities that served the needs of residents. But each trip to meet builders and bureaucrats in Lusaka, Nairobi, and beyond disabused me of that notion.
On my last trip to Zambia, I met an entrepreneur who wanted to locate her factory in a new special economic zone, the Lusaka East Special Economic Zone, to take advantage of favorable tax and banking laws. Special economics zones, which are regulated differently than other areas as a way to support innovation, are a popular development tool among governments, largely due to the fact that China’s SEZs, established in the 1980s, eventually helped lift 800 million people out of poverty.
The problem? This zone lacked electricity.
Had the officials taken a more bottom-up approach and consulted potential residents instead of solely focusing on getting the regulations right on paper, they might have prioritized more practical concerns. Lack of access to reliable infrastructure is among the biggest challenges for aspiring entrepreneurs in developing countries.
When I asked multiple residents on a trip to Johannesburg which single change would most improve their lives, I got the same answer every time: a safer environment. But instead, gated communities and private security are the norm across the city (for those who can afford it, anyway). It clearly wasn’t a priority for the city officials.
It’s clear that “expertise” needs to be more about practical, ground-up insights than just top-down planning or research. But this isn’t to say that only those with clear “skin in the game” should be making decisions in a given domain. Overcorrecting in the other direction could also produce suboptimal results; just try applying to build anything new in San Francisco, where veto power is inexplicably granted to those with the extra time and motivation to show up at planning hearings.
Still, experts should be careful not to underrate personal stakes in their decision-making. I love the idea of “method acting”, but for experts, to consistently marry academic expertise and practical, local knowledge by regularly immersing themselves within the communities they seek to serve. My personal planning hero, Jane Jacobs, was a journalist by trade, and her dedication to seeking input not only from planners, but from the very people who were most affected by their decisions, made her a powerful advocate for ordinary cities. Hers was a model that blended the best of the bottom up with the best of the top down. I hope that over time, this will increasingly become standard operating procedure in how we build things, from cities to schools and beyond.
I generally trusted experts. Sure, I knew that some of the information passed through the author’s personal lens, and that things that were once thought true often get proven wrong, but typically, I thought that experts were a good guidepost. When I joined a startup — which operates very differently than many big companies — it took me a few years to internalize the fact that expertise isn’t uniformly applicable. Contexts change, knowledge isn’t always generalizable, and the people who project the most expertise often have the least. Now I tend to question prevailing expertise most on the subjects I know the most about, which makes me question how trusting I am of experts in subjects I know less about.
To reach a healthy, balanced place with experts, you can use a method that I use: Take their expertise as an input. Test it against your own thoughts. Test it against other experts’ ideas. Then mix and match and blend and throw out and remix until you come up with your own ideas.
Now that everyone has a voice, weaving together facts, figures, and information into a clear, coherent, and compelling narrative is the only repeatable way to stand out.
It’s more art than science, but I’ve been applying it to build a growing newsletter and now as an investor, too. It’s hard to imagine two fields — writing and investing— that have been more impacted by open access, democratized distribution, and the diminished power of centralized gatekeepers. The fact that I could come out of left field and build a direct line of communication with tens of thousands of people just by sitting in front of a keyboard writing, day after day, is a beautiful thing.
It also means that the pressure is on to keep quality, accuracy, and judgment running at a high level. We live in a world where expertise can be justly claimed by anyone who can continue to prove it. Synthesis and storytelling are the keys to navigating that world. In a world with so much information available and fewer unquestioned experts, the ability to let large amounts of information wash over you, figure out where to dive deep, pull out the most compelling bits, and tie them all together is key.
Once synthesized, the ability to then turn that information into a good story has never been more valuable. Unquestioned experts didn’t really have to tell a compelling story. They were the experts, and their word was law. Now that everyone has a voice, weaving together facts, figures, and information into a clear, coherent, and compelling narrative is the only repeatable way to stand out. Obviously, stories can be used for good and bad. They can be full of truths or lies or some combination of the two. That’s where synthesis kicks back in.
Hand-wringing about the evils of an increasingly egalitarian public sphere is often driven by “elite panic,” in which traditional gatekeepers seem at least as concerned with the eroding authority and relevance of their own privileged access to the public than with concerns about the common good. This is not to say that social media is a uniquely benign phenomena — real harms occur, and huge challenges must be overcome — but the picture is far more nuanced than the prevailing discourse suggests and, in my opinion, the benefits of a more unmediated access for everyone to share and access information instantly and across the globe significantly outweigh the harms (so far).
Future generations will marvel at the new perspectives, voices, and knowledge that have come to light in the digital era and simply weren’t possible (or deemed desirable) in the age of analog. People will recognize that with a few digital tools, dedicated journalists and researchers are able to shine a critical light on authoritarian states and their dark practices (impossible when totalitarian states were able to mostly hide the existence of Gulags and concentration camps). New decentralized and organic ways of using the digital sphere can help to spread trust and belief rather than distrust and apathy in institutions.
Where does all this leave expertise? Expertise remains crucial to knowledge production, but it must reflect genuine excellence in a given field, rather than mere affiliation with institutional authority. This of course makes it difficult to navigate and discern experts from prolific tweeps, bloggers, and bullshit merchants. Genuine experts must be willing to engage horizontally with the masses and the public as active participants — defending and interacting around their expertise — rather than treating the public as mere passive recipients of their knowledge production.
Expertise remains crucial to knowledge production, but it must reflect genuine excellence in a given field, rather than mere affiliation with institutional authority.
These related trends naturally lead to a new set of skills that will become crucial to navigating the modern world and becoming a genuine expert in a new paradigm: Intellectual humility (rather than know-it-all-ism); genuine curiosity (rather than reflexive, orthodox thinking); and the willingness to openly admit error (rather than defensive stubbornness or dismissiveness that masks insecurity of one’s own fading authority). All this, and an acute and constantly refined bullshit detector.
When someone asks, “What do you do?” I find it curious that our social norm is to focus the answer on the nouns — “I am a doctor at MD Anderson,” “I am a biologist at the FDA,” “I am a VC-backed healthtech entrepreneur” — instead of on the verbs: “I care for cancer patients,” “I evaluate regenerative medicines,” “I build products for at-home clinical trials.” When people ask what you do, they really seem to be asking who you are, putting the attention on people’s credentials within institutions (the nouns) rather than on their actions and contributions (how they live, work, and cultivate knowledge in their fields). Expertise is equated with the former, when it should be more about the latter.
In the healthcare industry, there are plenty of disagreements about establishment expert credentialism and expert institutions, and we saw many of these play out in real time during the pandemic. Calls are mounting to deregulate and weaken institutions like the FDA, as well as diminish the role of academic research, because, the critics claim, the expert classes of bureaucrats and academics are more interested in maintaining power, avoiding risk, and preserving their elite status. But what is missing in the absolutist regulation-is-bad and research-is-compromised rhetoric is that regulation and research can be useful in building a much-needed foundation of trust in a society. For instance, we don’t all need to sponsor our own multibillion-dollar clinical trials before filling a prescription at CVS; our system can borrow and build on that expertise and trust.
What is missing in the absolutist ‘regulation-is-bad and research-is-compromised’ rhetoric is that regulation and research can be useful in building a much-needed foundation of trust in a society.
But where the critics are right to push institutions is in considering (and better absorbing into the system) novel methods for medical product development. Historical precedent should not stop us from pursuing new and potentially beneficial treatments. For instance, there’s emerging research that plant medicines have the potential to reduce suffering for those struggling with major depressive disorder, anxiety disorders (e.g., end-of-life with cancer), addictions (e.g., alcohol dependence), and more. The gold standard for many clinical trial designs — a double-blind, randomized controlled trial (RCT) — may not be possible for these therapeutics. (Double-blinding a plant medicine clinical protocol is hard; it becomes clear very quickly which cohort got niacin and which cohort got a psychedelic drug!)
We need a more balanced view of expertise here: one where prevailing expertise, scientific research methods, and regulatory processes can serve as a guide, not the only way. And we need one that can better support novel medical product development — more real-world evidence, faster, more proportional in applying risk vs. one size fits all — in service of the humans who could receive those life-altering treatments.
We need a view of expertise that can better support novel medical product development — more real-world evidence, faster, more proportional in applying risk vs. one size fits all.
Even the technology startup ecosystem has its own battleground in the expertise wars: Emerging leaders and outsiders less beholden to traditional viewpoints are the heroes we need to disrupt conventions and build the future, the thinking goes. Yet artificially fitting these leaders into the “expert vs. novice” framework creates an infertile environment for collaboration, connection, and creation across our system. The goal of people with less traditional experience shouldn’t be to check those with more experience in hopes of proving them wrong. We should instead entertain two contradictory ideas simultaneously: that both existing expertise and an openness to new methods with unexpected outcomes can, and should, coexist on a truth-seeking journey.
So what is the core of those new methods? While developing expertise, I seek to cultivate shoshin (a philosophy popularized by the Sōtō school of Zen Buddhism), which involves cultivating an orientation toward wonder, openness, and lack of preconceptions when studying a subject. It means doing so even when studying at an advanced level, just as a beginner would — aka the “beginner’s mind.”
I’ve seen through my work in healthcare how technology-based information-sharing has led to incredible scientific breakthroughs as well as exacerbating disparities in health and healthcare. The path forward is to cultivate shoshin — even if the idea may seem naive to the credentialed — because the world is researched and built by optimists who may not realize that what they are building was at one point deemed impossible by the established classes. My breakthroughs occur when my mind is engaged, open, and curious; I find joy and a sense of wonder building in healthcare because there is room for *both* scientific rigor and playful curiosity. It is possible to both revere the scientific method and to develop novel approaches — especially when existing methods no longer serve the question or need at hand.
I used to believe that corporate managers, especially in technology, were skilled professionals who were able to balance teaching and coaching along with execution. They became managers because they had proven they were able to lead. But I’ve come to believe that most senior people aren’t actually skilled managers. They succeeded due to their domain expertise, tenure, or ability to execute on well-defined projects. And then as top performers, they are rewarded with more responsibility and a team to manage. However, they don’t necessarily have expertise in growing talent and building teams.
Instead of training managers before they are given responsibility, sectors like technology, which are relatively new, skip this crucial step. The industry often relies on collaborative tools, or trial by fire, as substitutes for good management practices. Over time, the cycle repeats itself, within and across companies, diluting the skill of management. This makes it more difficult to actually create expertise around what good, experience-driven management looks like.
The tech industry often relies on collaborative tools, or trial by fire, as substitutes for good management practices. Over time, the cycle repeats itself, within and across companies, diluting the skill of management.
What happens when an entire industry has weak management? For one thing, it’s harder to innovate or change a company’s culture, process, or product. Timing is everything, after all; in life and as leaders, we are often asked to identify and execute big changes. Yet we accept a constant rotating workforce in technology where tenures last only a couple of years until a person gets frustrated with the company, or the company gets frustrated with the individual—neither side taking the time to really manage larger, bolder changes within the individual nor to manage change as an organization.
But organizations and people are inherently change-averse, so knowing how to manage change is arguably a more crucial type of expertise than knowing how to execute (creatively or technically) on the change itself. Because it’s easier to know what to do than how and when to do it — and much, much harder to know how to help others do it. In my view, coaching — and with it, talent management — is the new and most valuable expertise in and across organizations in this current and coming era. And this can be broken down into a few key skills: Expertise such as (1) knowing when to time a change; (2) how to scale oneself; (3) how to break a larger effort into smaller pieces; and (4) how to bring people along and build a coalition.
Though taking the time to train our leaders is crucial, I don’t think it requires organizations to slow down or raise the bar on when to become a manager. The expertise of coaching successful individual contributors, even early in their careers, on these core basics will ensure a future not just of commenters but of builders.
As game makers, our content once lived inside a platform. If you didn’t own the platform, the platform owned you. Then, in the aughts, the shift to the cloud — coupled with the growth of the free-to-play business model — ushered in a wave of new game developers, some of whom built titanic companies and games: Zynga with Farmville, Riot with League of Legends, and Kabam with Marvel Contest of Champions. That shift moved our industry from a craft practiced by a small body of people to one rich with new talent — new experts — coming from web-based and service backgrounds. Because those fields were new to everyone, expertise could be acquired by those daring to go to the edge.
The shift to cloud and free-to-play moved the games industry from a craft practiced by a small body of people to one rich with new talent coming from web-based and service backgrounds.
But such changes are not without their challenges. As makers of free-to-play games, the entire economy was both centralized and owned by us. Once land ownership was redistributed and privatized, the GDP began to grow, so we developers began building for the two percent of the population that spent money in our games. We toed the line between making a fun game for everyone and designing pay-to-win strategies that, in effect, created premium experiences for only a small sliver of players.
But then blockchain technology, by solving the basic problem of provenance (a record of ownership) for digital items, meant the economy could now live outside of the game creators’ control. However, since blockchain had no liquidity, it still forced all the ownership and its consequences back to the game developer (without any of the ownership benefits).
Fast forward to this past year. decentralized finance has provided liquidity — and a renaissance of sorts — to the entire crypto industry. Liquidity is powerful: Having property rights (tokens/currency), proving those property rights (blockchain), and re-selling those rights (liquidity) were the missing pieces to create entirely new gaming economies, as well as new gameplay strategies (like play-to-earn).
By changing the economics of expertise in gaming, virtual game worlds today can impact the real world, for the first time. With trends such as play-to-earn games, the rise of livestreaming, and the growing contingent of esports pros, players — not just game publishers! — can now create value for the entire community and get paid. Expertise has evolved dramatically. It now comes from the edge — from bold creators and players.
Lots of people claim to be experts because they’re richly rewarded by a spectacle-oriented information ecosystem that runs on attention. On social media, posers are often given the most status points, and so we’re left with a misleading idea of authority; it seems the people who are loudest in their claims to be experts — the ones we hear from most on Twitter, Facebook, and YouTube — are the ones to be most wary of. When self-proclaimed experts are ultimately revealed to be, at best, vulnerable to overreach or, at worst, outright charlatans, the whole concept of expertise is undermined. Many of us are living in an alternate reality in which actual insight matters less than the noisy claim to it.
When self-proclaimed experts are ultimately revealed to be, at best, vulnerable to overreach or, at worst, outright charlatans, the whole concept of expertise is undermined. Many of us are living in an alternate reality in which actual insight matters less than the noisy claim to it.
Today, clear-mindedness has become a learned skill that is essential to navigating media, both social and traditional. It’s something to be worked on, developed, and mastered. In practice, that means the ability to pause and think, rather than reflexively accepting what the machine is shouting at you; the ability to seek and interrogate alternative viewpoints through reading widely; and the ability to defer judgment until you have absorbed competing arguments via introspective consideration. At its best, the internet has given writers the superpower of influence and readers the ability to discover the most informed and interesting examinations on any imaginable topic.
I do believe in the importance of genuine experts — those who have distinguished themselves in their fields by spending thousands of hours attempting to understand a particular subject and then publishing their findings, not just asserting themselves widely in public. But I am also more attuned than ever to experts’ fallibility, and to our own faulty belief that to find ultimate wisdom, we just have to hear it from the anointed ones who “know the way.”
The paradox is that the best kinds of leaders we can hope for are the ones who accept their ignorance — and publicly share their best attempts to overcome it.
When we think of expertise, we should think expansively. This is not to say that experts themselves should no longer be valued, but instead that value should be determined through the consensus of many. Consider the vital forms of social and economic organization that have developed through distinct cultures passing down traditions, histories, and generational knowledge. These forms of collective expertise don’t rely on pedigree or exclusivity, nor do they require an individualist philosophy or spokesperson. Group resiliency and peer-to-peer knowledge — often shared between families, neighborhoods, indigenous cultures, and friends — have long been capable of manifesting futures that would have been impossible to achieve alone.
Today, crypto promises to provide the building blocks for a web that will be equipped to address the many challenges of our networked culture. In the crypto community, “decentralization” often means self-sovereignty, or community sovereignty — the distribution of power, knowledge, and resources away from a central point. Artists, for instance, have already been putting the internet to good use for decades by making it a space for decentralized expertise and resource sharing, whether through renegade collectives (Free Art and Technology Lab) or open source toolkits for creative work (openFrameworks) or other initiatives.
With the introduction of NFTs, we’re already seeing seismic shifts in what constitutes art and who can participate in the art market.
In practice, groups like these have destabilized taxonomies of knowledge, discourse, and participation established by those who try to allocate what is deserving of merit and recognition. Decentralization should also entail that we reconfigure traditional hierarchies of expertise, so that we can construct more meaningful frameworks and models for communication, valuation, and exchange. Where web2 users don’t retain value from their creative labor, web3 offers us the type of expertise we need today, a collaborative one — one that can be shared throughout digital communities via decentralized technologies such as peer-to-peer networks, decentralized autonomous organization (DAOs), and community tokens. Ideally, these tools will help us cultivate communities that share resources and make space for experimentation — refusing and reshaping the presupposed expertise of a few, in the favor of many.
With the introduction of NFTs, we’re already seeing seismic shifts in what constitutes art and who can participate in the art market. Now, visual artists, meme creators, musicians, and many others have the ability to generate their own markets through decentralized technologies. Shared expertise is capable of catalyzing cultural movements, resulting in greater opportunities for all. We have a chance to create a different kind of container for what “expertise” is intended to do altogether, by promoting expertise without necessarily centering the expert. Imagine the creative potential of operating according to this principle: a collective redefinition of expertise that could also represent a collective redefinition of value.
As a Filipino-born founder running a startup in the Philippines, right now I have access to the best resources, funding, and the most formidable partners that the world — not just my local region — has to offer. Before COVID, these opportunities were slowly building but still largely closed to me. With the breakthrough of remote communication technologies, along with the prevailing attitude and culture of virtual collaboration in the crypto space, it became possible for me to showcase my talent on a global stage without ever leaving my home in the Philippines.
This shattering of the “geographic lottery” — where you win the location lottery merely by being born where you are, as opposed to showing your expertise from where you are — is now being helped along by the ongoing construction of crypto infrastructure. This can improve access to income-generation opportunities — jobs that people can thrive in, feel passionate about, make good money from. NFT-based games, for example, are allowing anyone with a smartphone and an internet connection to earn cryptocurrency rewards from contributing their time and skill. This play-to-earn model represents a dramatic shift in the way we think about in-game economies and who gets to benefit from them, as traditionally, it was only the game developers, publishers, and platform owners that were able to tap into the financial value that gaming communities bring to these platforms.
This shattering of the “geographic lottery” — where you win the location lottery merely by being born where you are, as opposed to showing your expertise — is now being helped along by the ongoing construction of crypto infrastructure.
Now, access to these global, online economies means more people around the world can become “experts.” But expertise is not a static thing; it must evolve over time. Those who are revered for their expertise today must continually refresh themselves and their knowledge, or their perspectives will expire. Rather than giving credence to people who achieved expert status in the past — much like old gaming systems rewarded the whales only — we should be looking to those who are constantly renewing their skills, and revisiting their own competencies, to see their ongoing adaptability as credible instead.
In new gaming models, players devote significant energy and effort to mastering these complex games and the crypto-based economies that feed them. Most of the players are coming from outside the crypto sphere — and some wouldn’t even call themselves avid gamers. But these new experts all share a deep desire to learn something new, “level-up,” and bring others in their communities along and up with them.
Access and expertise (they are often the same thing) shouldn’t be about a college degree, or a job title, or even how many years of experience you have in a given field. It should be about curiosity, learning, and being able to share what you learn with others and build up others. Today, we are seeing this open up opportunities for new innovation and new leaders.
The Big Three prestige-generating institutions — academia, news media, and publicly held government offices — have been the American Mint for Expertise over the last 200 years, conferring status and gravity to any individual who satisfies their barriers to entry. But the Legacy Mint is only feasible in an environment where information is expensive, costing either time or money to acquire it and distribute it with high fidelity. Now, the open, scintillating, beautiful internet has resolved this scarcity of information and information distribution in one fell swoop.
Anyone who cares to be an expert can be (with, for example, nearly 13,000 open-access databases being reported in the Directory of Open Access Journals in 2019), and anyone empowered in this fashion by the internet who wants an audience can now have one. This parallel “institution” of the internet has arisen at the same time that legacy sense-making institutions have struggled with errors and botched predictions (that X or Y never happened or could happen), or have foregone their core mission to speak truth to power for less clear, more partisan aims.
The ‘institution’ of the internet has arisen at the same time that legacy sense-making institutions have struggled with errors and botched predictions.
The eroding information quality seen over the last decade in mainstream sense-making may result from diminishing returns on traditional frameworks. When an unschooled YouTuber can exceed an entire traditional publishing entity’s average daily viewership, traditional institutions begin to enter a face-saving, self-preservational mode of operating, instead of a more constructive pursuit of truth.
For the first time in history, the power to pursue truth and make up your own mind is backed by the decentralized sum of all human knowledge, which changes the game of expertise from the bottom up. But that in turn requires a new lens to parse its dynamics — a writer on a newsletter platform, for example, doesn’t face the same editorial limits or incentives as a columnist for a paper of note. When the qualifications to write about a topic change from formal training or specialization to basic interest, writing as a whole becomes more democratic, expanding the number of both good and bad ideas and, in turn, creating a larger market to sort them both. It can also incentivize competition, which may have the added benefit of increasing content quality (and maybe even improve the quality of legacy institutions if they follow the same idea!).
A writer on a newsletter platform doesn’t face the same editorial limits or incentives as a columnist for a paper of note. When the qualifications to write about a topic change from formal training or specialization to basic interest, writing as a whole becomes more democratic, expanding the number of both good and bad ideas and creating a larger market to sort them both.
The New Expert, empowered by the internet, has a nearly infallible editor at her fingertips in the form of Search and sprawling Social Networks. The New Expert can be transformed into a polymath after the fashion of Newton, Locke, Rousseau, etc., as a consequence of having no upper bounds to what she can learn and having audiences hungry for the same infinite knowledge horizons made available to anyone with wi-fi, which is pretty cool. With only a few essential keys to keep on hand, anyone can be transformed into a New Expert. These keys are fourfold and include keeping in mind that:
- Replication is the gold standard in science;
- Nonpartisanship is the key to understanding partisan issues;
- The social media accounts of business leaders tell more about a business-oriented mind than contrived, PR-directed talks and appearances; and
- The idea that the “latest is the greatest” when it comes to finding quality information and staying up to date on almost any subject matter.
The New Experts of tomorrow are different from the pundits, the think-tankers, the analysts and commentators of yesterday. They are a new breed unhindered by differences in privilege and opportunity. They are a voice raised in harmonious accord speaking truth to institutional power, and they have the whole world in the palm of their hand.
Technology has expanded the system of knowledge production, maintenance, and distribution that’s historically been reserved for academic institutions, religious organizations, and the media. From open source developers to online creators, we are rapidly reinventing not just the nature of our knowledge systems, but how individual agents come to associate with them.
It’s not just the discovery of knowledge (i.e., learning new things) that’s easier now, but also the validation (where your peers, rather than an accredited institution, decide whether your insights are worth discussing) and distribution of knowledge. Sharing new ideas previously required working with centralized gatekeepers, like a university or a newspaper. But today, a popular blog post can reach many more readers, and possibly the right readers, versus publishing an academic paper.
For some types of research, it’s now possible to pursue PhD-level work outside of formal academic institutions. You don’t need a title to demonstrate expertise: you just need to show your work. It’s astounding how many hard research questions still haven’t been explored in depth; someone who’s taken the time to deeply understand a murky, underexplored niche, whether that’s through interviews, reading primary material, or connecting ideas from other fields — then sharing what they’ve learned in public — can get much further than someone with a fancy-sounding title but little practical experience.
For some types of research, it’s now possible to pursue PhD-level work outside of formal academic institutions. You don’t need a title to demonstrate expertise: you just need to show your work … Someone who’s taken the time to deeply understand a murky, underexplored niche — then sharing what they’ve learned in public — can get much further than someone with a fancy-sounding title but little practical experience.
It’s also easier (though not as easy as it should be!) for a researcher to get the resources they need to pursue their work, whether that’s connecting with a like-minded patron or funding their research with a growing host of creator-oriented services. Information is easier to Google, but people are more accessible as well, via Twitter, blogs, and public email addresses. From a field-building perspective, it’s possible to find and attract a cohort of peers who share your research interests.
Expertise isn’t going anywhere: we’re just finding new ways to measure and signal it. There’s a lot more noise in expertise today. Easy access to information means everyone is a superficial expert on everything. But if you’ve put in the hours to understand your topic and can demonstrate what you know, no amount of credentialing, outgrouping, or gatekeeping can take that away from you.
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