- The book argues regenerative agriculture could feed the U.S. – while being better for the long-term environment (p. 232):'Do we have the land for it? Diana consulted with a few experts to run the numbers, including Dr. Allen Williams, an ecosystem and soil health consultant, farmer, and former agriculture professor ... [List of many other people consulted]... One critical piece of information to keep in mind is to remember that we’re comparing industrial monocropping to regenerative agriculture, which have drastically different impacts on the land. Even though it takes more land to produce well-managed grass-finished beef, it could be argued that the regenerative solution is a smarter one for our future than the chemical one. At a recent conference about grass-fed beef, Rowntree said in his presentation, “I’d rather have 2.5 acres of regenerative agriculture than 1 acre of extractive agriculture.” [And that regenerative agriculture leads to more utilisable land]‘let’s dive into what sort of acres we’d need in the US to finish all our beef herd on grass… the numbers are rough and could certainly be challenged, but… If we look at the current amount of idle grassland, underutilized pasture, and cropland that would be freed up from grain production in an all-grass-finished scenario, the short answer to our question is yes. We do have the land to finish all our current beef cattle on pasture in the US.‘If we are now grass-finishing all beef cattle produced annually in the US, we can reduce the ninety to ninety-four million acres of corn planted. Approximately 36–40 percent of today’s corn crop actually goes into livestock feed (cattle, pigs, and chickens)…‘If we take just fifteen million acres of cornfields and consider these productive (after all, they once were thriving grasslands), each of them can finish 1.25 steers per acre. Altogether, these acres finish 18.75 million cattle. In addition to converting some of our corn acres back to grassland, there are over five hundred million acres of privately owned pastureland in the US, and many experts we’ve spoken to estimate it’s only being utilized at 30 percent capacity. This leaves enormous potential for better grazing management.‘And again, these acres will be a net gain to our agricultural land because they would be beneficial to our ecosystems instead of destroying them… soil, water cycles, and mineral cycles, and more wildlife.’

In general, more people need to let go of the idea of creating some kind of omniscient (second) superbrain that remembers everything and subsequently makes you do everything right. The things we're really performing well at are the things we did (and repeatedly failed at) 1000 times before. Think about how you learnt to ride a bicycle. Did you read a book about riding bicycles and took notes on it? I don't think so.Do you really want to take away something from reading all of those books and articles? Think about what you are going to (lastingly) change that represents the ideas presented in the text. Most of the time, that will be just one or two things; everything else will be lost until you pick up that book again, perhaps. But that's okay. Life is too short to spend it on personal knowledge management.

Historically speaking, knowledge meant power. In the middle ages, anyone who knew more or was better informed than his/her peers had a considerable advantage. Today we are bombarded with new information every day and the challenge is a different one: Separating the wheat from the chaff. And naturally, personal knowledge management seems like a promising coping strategy.However, most of the stuff I read about personal knowledge management is about systems, apps, setups or plugins, and never really about its purpose. Why bother doing all this? Although it feels really good, creating organisational systems and collecting notes for the sake of retaining the information itself is a huge waste of time and will leave you hoarding useless data.

We’ve reached the point where search is so good, effectively the whole document is made up of tags, and the cognitive load of meticulously tagging every note becomes truly unforgivable.

So you shock yourself for eight hours a day, because you know if you don’t everyone else will kill you, because if they don’t, everyone else will kill them, and so on. Every single citizen hates the system, but for lack of a good coordination mechanism it endures. From a god’s-eye-view, we can optimize the system to “everyone agrees to stop doing this at once”, but no one within the system is able to effect the transition without great risk to themselves.

"I saw how you struggled to finish your degree, and you did it with grace and poise. I know what it feels like to struggle. I am so proud of you for staying with it to the finish, you are amazing!""I know that you work so hard to fit in at the office. Being a first-generation professional is challenging because we don't have parents to shepherd us through the office politics, the nuances of being a professional, and how to act. I may not have guidance, but I see you working so hard. I really respect everything that you are doing."And if you look at some of my responses to others here, you'll find a range of additional validations and encouragements. Our childhoods' had little, if any of that, it was always, "do better" or just a blank stare when we wanted to celebrate an achievement or accomplishment. No acknowledgments, no encouragements, no validations.

Another point to consider when designing the Outline hierarchy is the inheritance feature of the Outline. Each line in the Outline can take a number of properties. These properties normally cascade down. So, if you group tasks of similar nature, you can only set the properties at the parent level and all lines under this parent line will inherit these properties.

Pursuing multiple independent paths reduces risks more when the failure modes of each path are different. Recently we wanted to build a multi-lumen subsystem. We contracted with two different vendors to make multi-lumen extrusions, each using slightly different materials. This reduces the risk of a vendor-specific problem (e.g. they can’t dial in the right settings) but doesn’t reduce the risk that the design may not work.

Working hard is not just a dial you turn up to 11. It's a complicated, dynamic system that has to be tuned just right at each point. You have to understand the shape of real work, see clearly what kind you're best suited for, aim as close to the true core of it as you can, accurately judge at each moment both what you're capable of and how you're doing, and put in as many hours each day as you can without harming the quality of the result. This network is too complicated to trick. But if you're consistently honest and clear-sighted, it will automatically assume an optimal shape, and you'll be productive in a way few people are.

There is some technique to it: you have to learn not to lie to yourself, not to procrastinate (which is a form of lying to yourself), not to get distracted, and not to give up when things go wrong.

As a kid, you get the impression that everyone has a calling, and all they have to do is figure out what it is. That's how it works in movies, and in the streamlined biographies fed to kids. Sometimes it works that way in real life. Some people figure out what to do as children and just do it, like Mozart. But others, like Newton, turn restlessly from one kind of work to another.

Are you really interested in x, or do you want to work on it because you'll make a lot of money, or because other people will be impressed with you, or because your parents want you to? [8]

Many problems have a hard core at the center, surrounded by easier stuff at the edges. Working hard means aiming toward the center to the extent you can. Some days you may not be able to; some days you'll only be able to work on the easier, peripheral stuff. But you should always be aiming as close to the center as you can without stalling.

You can't solve this problem by simply working every waking hour, because in many kinds of work there's a point beyond which the quality of the result will start to decline.

I can't be sure I'm getting anywhere when I'm working hard, but I can be sure I'm getting nowhere when I'm not, and it feels awful. [2]

There are three ingredients in great work: natural ability, practice, and effort. You can do pretty well with just two, but to do the best work you need all three: you need great natural ability and to have practiced a lot and to be trying very hard. [1]

You can try to invent specific things that make extinction less likely, like (in the case of pandemic preparedness) better personal protective equipment and wastewater surveillance. You can identify things that make extinction more likely, such as nuclear proliferation, and combat them. These are still thorny problems that reach across domains and in some respects confuse even the full-time experts who study them, but there are achievable near-term technical goals, and longtermists have some genuine accomplishments to point to in achieving them. In the short term, persuading people to adopt your values is also concrete and doable. Effective altruists do a lot of it, from the campaign against cruelty to animals on factory farms to the efforts to convince people to give more effectively. The hard part is determining whether those changes durably improve the long-term future — and it seems very hard indeed to me, likely because my near-term future predictions differ from MacAskill’s.

Broadly, current methods of training AI systems give them goals that we didn’t directly program in, don’t understand, can’t evaluate and that produce behavior we don’t want. As the systems get more powerful, the fact that we have no way to directly determine their goals (or even understand what they are) is going to go from a major inconvenience to a potentially catastrophic handicap.

Hormesis: A low dose of something can have the opposite effect of a high dose. A little bit of stress wakes you up, but a lot of stress is bad for you. Lifting weights for 30 minutes per day is good for you, but lifting weights for 6 hours per day will destroy your muscles. Stress yourself, but not too much.

Hickam’s Dictum: The opposite of Occam’s Razor. In a complex system, problems usually have more than one cause.

Hock Principle: Simple, clear purpose and principles give rise to complex and intelligent behavior. Complex rules and regulations give rise to simple and stupid behavior.

Gall’s Law: A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working simple system.

Goodhart’s Law: When a measure becomes a target, it ceases to be a good measure.

Table Selection: This idea comes from poker, where you’re advised to choose your opponents carefully. That means you shouldn’t compete against the best people. You don’t need to get good at doing difficult things if you get good at avoiding difficult things. If you want to win, pick an easy table and nail your execution.

Planck’s Principle: Science doesn’t progress because people change their views. Rather, each new generation of scientists has different views. As old generations pass away, new ideas are accepted and the scientific consensus changes.

Russell Conjugation: Journalists often change the meaning of a sentence by replacing one word with a synonym that implies a different meaning. For example, the same person can support an estate tax but oppose a death tax — even though they are the same thing.

Mimetic Theory of Desire

Faustian Bargain

It’s a simple framework but it takes a lot to apply it: you’ve got to diagnose the elements that make up a task; map your diagnosis onto an assessment of another person’s skills and motivation for accomplishing the elements of that task; intervene successfully to provide support based on that diagnosis; and adjust along the way for both how well/poorly you diagnosed both the task and your colleague, and how well/poorly you succeeded in your intervention.

As it is, my books are bought by enough people to provide me with a sort of middle-class lifestyle, but not enough to hire employees, and so I am faced with a stark choice between being a bad correspondent and being a good novelist. I am trying to be a good novelist, and hoping that people will forgive me for being a bad correspondent.

The productivity equation is a non-linear one, in other words. This accounts for why I am a bad correspondent and why I very rarely accept speaking engagements. If I organize my life in such a way that I get lots of long, consecutive, uninterrupted time-chunks, I can write novels. But as those chunks get separated and fragmented, my productivity as a novelist drops spectacularly. What replaces it? Instead of a novel that will be around for a long time, and that will, with luck, be read by many people, there is a bunch of e-mail messages that I have sent out to individual persons, and a few speeches given at various conferences.   That is not such a terrible outcome, but neither is it an especially good outcome. The quality of my e-mails and public speaking is, in my view, nowhere near that of my novels. So for me it comes down to the following choice: I can distribute material of bad-to-mediocre quality to a small number of people, or I can distribute material of higher quality to more people. But I can’t do both; the first one obliterates the second.

There’s no way I ever would have gotten my thesis proposal written without Beeminder. The important thing to note is that the goal was based on page count rather than time spent. (The “Odometer” goal type is useful for this sort of thing.) This forced me to actually get real writing done, rather than frittering time away adjusting the kerning or whatever.

it’s so easy to assume those who disagree with you aren’t as smart or informed as you are. A lot of good ideas are ignored, or intentionally rejected, because they are said by people you don’t admire.

You always find these people where you’re like, “Oh, I thought this was a Steve Jobs idea.” No, no. It’s an [Sony founder] Akio Morita idea, or an Edwin Land idea. Watch the presentations that Steve Jobs gives where he says, “We’re building at the intersection of technology and liberal arts.” Edwin Land said those exact words! You’re never going to find anybody who gets to the top of the profession without studying the people that came before them and learning from them and admiring them.

Ridley once explained this further: I’m not interested in the debate about whether some groups have higher I.Q.s than other groups. It’s completely irrelevant. What’s relevant to a society is how well people are communicating their ideas, and how well they’re cooperating, not how clever the individuals are.

It’s ideas combining, joining, and merging, that create the modern world.

The question is: Did George Wheelwright know that he would influence Edwin Land, who would then influence Steve Jobs, who would then design a phone that 2.5 billion people would use? Did Michael Faraday, who died in 1867, know that his ideas would directly influence the light bulb, which effectively led to the creation of everything from the modern power grid to nightlife? Did Ben Graham know that his 1950s finance class would lead to 45,000 trekking to Omaha every year to hear his student speak? Of course not. It’s so hard to know what an idea, or an invention, or a philosophy, will influence, and what a person who’s influenced by it will go on to create.

What’s more, becoming a trusted community member who’s fully up to speed can easily take several years, and this makes it harder than it looks to absorb new specialists. It also seems like we’re going to need a lot of specialists, at least in certain areas and skills.

we’ve sketched three types of community:Single-player communities — where other people’s actions are (mostly) treated as fixed, and the benefits of coordination are mainly ignored.Market communities — which use markets and price signals to facilitate trade, but are still vulnerable to market failures and coordination failures.Shared aims communities — where members share a common goal, potentially allowing for trade+ and even more resilience to coordination failures, which may allow for the greatest degree of coordination.

shared aims communities should also in theory be the most resistant to coordination failures.

However, what about if the agents also care about each others’ wellbeing, or share a common goal? We call these ‘shared aims’ communities. The effective altruism community is an example, because at least to some degree, everyone in the community cares about the common goal of social impact, and our definitions of this overlap to some degree. Likewise, environmentalists want to protect the environment, feminists want to promote women’s rights, and so on. How might cooperation be different in these cases?This is a question that has received little research. Most research on coordination in economics, game theory and computer science, has focused on selfish agents. Our speculation, however, is that shared aims communities have the potential to achieve a significantly greater degree of cooperation.

Going one level further, we get ‘indirect trade.’ For instance, in some professional networks, people try to follow the norm of ‘paying it forward.’ Junior members get mentoring from senior members, without giving the senior members anything in return. Instead, the junior members are expected to mentor the next generation of junior members. This creates a chain of mentoring from generation to generation. The result is that each generation gets the mentoring they need, but aid is never directly exchanged.

We call one of these mechanisms ‘preemptive trade.’ In a preemptive trade, if you see an opportunity to benefit another community member at little cost to yourself, you take it. The hope is that they will return the favour in the future. This allows more trades to take place, since the trade can still go ahead even when the person isn’t able to pay it back immediately and when you’re not sure it will be returned. Instead the hope is that if you do lots of favours, on average you’ll get more back than you put in.

Communities that coordinate have developed mechanisms to spread this knowledge in a trusted way.

In some coordination failures, a better outcome exists for everyone, but it requires everyone to switch to the better option at the same time. This is only possible in the presence of ‘common knowledge’ — each person knows that everyone else is going to take the better option.

These mechanisms don’t only allow us to understand how to better work with others, but are also relevant to many global problems, which can be thought of as coordination failures.

The paradox is that tight-knit communities are fundamentally more inclined to maintain agreement than explore disagreement. For debate-mapping to work in the context of a tight-knit community, the community must also invest in fostering a culture of respectful disagreement alongside any formal process.

EA's comparative advantage is altruism, not solidarity

diversity does not cause intellectual diversityStandpoint epistemology does not outperform expertise, study, measurement. Standpoint epistemology is the false value prop of demographic diversity. When you run into a black person at EAG you don't assume that they know a lot about OpenPhil's CJR portfolio just because incarceration disproportionately effects black people, black EAs are free to care about whatever cause areas they want. The alternative (assuming that a minority at EAG isn't as impartial in their prioritization as a majority) is equal parts rude and absurd, but I feel like I've seen weak versions of this insinuation around, kind of a lot.

A spectrum with an overly-whiggish "if capitalism isn't working, try more capitalism" view on poverty abolition on the one side and the unabomber on the other side is a frame. What if it's not a polarity thing, what if it's a triangle because of a third thing that we dismiss as anomalous when we put on that frame's blinders? What if the best path forward isn't splitting the difference between the extremes somehow, but has nothing to do with those extremes?

High performance, in terms of fixing things that are broken, should remain the EA priority. Not fairness or being a movement people feel good to be a part of. Instrumental value of fairness or the movement being a fun place to hang out is a separate argument, one that should probably stay in the overton window, because I think it's probably true! But what I want is for diversity advocates to make their claims falsifiable. I want calls for diversity (both kinds) to be judged by ITN forecasts/evaluations and then by reality, in that order, like anything else.

A century or two ago, the word community “seemed to connote a specific group of people, from a particular patch of earth, who knew and judged and kept an eye on one another, who shared habits and history and memories, and could at times be persuaded to act as a whole on behalf of a part.” In contrast, the word has now become fashionable to describe what are really networks, as in the “business community”—“people with common interests [but] not common values, history, or memory.”3

If you want to understand the difference between a network and a community, ask your Facebook friends to help paint your house. Networks connect; communities care.

(Low fidelity of information transmission isn’t the only reason truth-seeking spaces are PR hazards for the movements in whose ecology they grow. Most outlandish ideas considered will be somewhere between neutral and awful through sheer statistics, and someone who hasn’t yet sufficiently trained their memetic antibodies might end up endorsing some of them or even acting on them. This means a PR hazard exists even if all information were transmitted with perfect fidelity.)

Memorising the most common/intelligent/whatever refutations of yesterday’s Horrible Ideas is not very useful if you want to be on guard against the Horrible Ideas of tomorrow. Chances are they will not have enough superficial resemblance for a simple pattern-matching algorithm to detect them. Think of it this way: our culture already has strong antibodies against nazism, communism, etc. It doesn’t have nearly as many antibodies against whatever the Most Horrible Idea of the 21st century will be. But that amount is not zero. And they disproportionately come from the truth-seeking spaces, where people are allowed to do their outlandish thought experiments even if they lead to repugnant conclusions.

Whatever is learned from systems mapping exercises tends not to be shared democratically. In fact, more often than not, when a consultant is hired, the knowledge sits externally with them rather than with the system agents themselves who require it to effect any meaningful change and who can add contextual nuance to it.

This is where Systems Innovation is so different. It is symbiotic with democracy. If you require a large number of agents to drive transformation, then the innovation capacity has to be as micro as possible and agency has to be established at that particular level. In the decentralised, distributed, and coordinated model that System Innovation enables, agency to change is preserved by all.

Over the past 12 months I have spoken with many people and organizations across the world who are also trying to tackle or measure complex systems challenges and it turns out that most of them are grappling with these same challenges. Some are much further ahead than UNDP while others are just beginning their journey. For instance, the Bill and Melinda Gates Foundation is investing in building an evidence-base around how to document systems change in areas such as food and agriculture and Co-Impact has developed a learning, measurement, and evaluation guidebook for systems change. Meanwhile, the Cynefin Centre and Climate-KIC offer useful thoughts on developing transformative theories of change for complex systems, while the Small Foundation has developed a framework for measuring and managing impact networks. Blue Marble Evaluation is rethinking the role and approach of evaluators when it comes to global systems change, and organizations such as UNFPA and the Open Government Partnership are deploying developmental evaluation approaches to help them continuously learn and adapt in the wake of complexity. Furthermore, the adaptive management community has built a solid evidence base and practice, while a variety of publications such as CEDIL’s Methods Briefs and work by Aston and Colnar discuss complexity appropriate evaluation methods. Lastly, outfits such as the Transformative Innovation Policy Consortium, the Rockwool Foundation’s System Innovation Initiative, and FSG’s Water of Systems Change work offer useful conceptual frameworks for thinking about what to measure when documenting systems change.

Capture impact in the aggregate: We cannot evaluate individual interventions in isolation because we usually tackle systems challenges through portfolios of interconnected interventions.

The system consists of one long list of everything that you have to do, written in a ruled notebook (25-35 lines to a page ideal). As you think of new items, add them to the end of the list. You work through the list one page at a time in the following manner: Read quickly through all the items on the page without taking action on any of them. Go through the page more slowly looking at the items in order until one stands out for you. Work on that item for as long as you feel like doing so Cross the item off the list, and re-enter it at the end of the list if you haven’t finished it Continue going round the same page in the same way. Don’t move onto the next page until you complete a pass of the page without any item standing out Move onto the next page and repeat the process If you go to a page and no item stands out for you on your first pass through it, then all the outstanding items on that page are dismissed without re-entering them. (N.B. This does not apply to the final page, on which you are still writing items). Use a highlighter to mark dismissed items. Once you’ve finished with the final page, re-start at the first page that is still active.

The Abilene paradox describes this unfortunately common situation where a group of people agree to an idea, despite most of them not fully believing that it is the best decision.

The “equation” would work only if the North Vietnamese leaders were calm, rational actors who would “calculate costs and benefits to the extent that they can be related to different courses of action, and make choices accordingly,” as one paper put it.

Secretary of Defense Robert McNamara viewed the world as a big math problem. He wanted everything quantified, and based his career on the idea that any problem could be solved if you obeyed the cold truth of statistics and logic.

For me, much of the anxiety around following-up and keeping in touch centre on being a burden, and bothering other people. A mindset I find helpful is reframing it all as providing a public good. Taking social initiative is hard and most people aren’t very good at it. But most people do value fun social interactions. And, for some reason, people often enjoy interacting with me. This means that by taking social initiative, I am creating more opportunities for both of our lives to be better, which is something I find deeply motivating.

Another key insight about friendship is that it’s all about upside risk. I will meet many, many more people in my life than I could ever sustain friendships with, let alone close friendships. Thus, if I am meeting new people and want to find potential close friends, I want to filter fast for compatible people. Further, compatibility is heavy-tailed - I won’t really vibe with most people, but some people are awesome. I want to explore and optimise for information. This pushed towards high-variance strategies. If I meet 100 people, and want to pursue a friendship with just a handful, this is great! This is a very, very different mindset from standard social norms, which push me towards being bland and inoffensive, and minimising the probability of bad interactions. A bad interaction (so long as it doesn’t damage my reputation) is just as useless as a mediocre interaction for finding potential friends. Instead I want to maximise the probability that, if someone is compatible with me, we have an awesome interaction. This is a key part of why I push for excitement and vulnerability - many people won’t vibe with that, but it makes it much more likely that I hit it off with the right kind of person.

But I was pretty terrible at being vulnerable and forming emotional connections. These friendships rarely went beyond the surface level. In hindsight, I expect these could have been far richer (and I’ve formed much stronger friendships with some of these friends since!), but I never really tried.

40. Empty Name:We can be convinced that a concept is real by the mere fact that it has a name, but the world is full of names for things that aren't real (e.g. Batman). As such, assume nothing is true just because it has a name (including every concept in this megathread!)

39. Principle Of Humanity:Every single person is exactly what you would be if you were them. This includes your political opponents. So instead of dismissing them as evil or stupid, maybe seek to understand the circumstances that led them to their conclusions.

38. Tilting At Windmills:An online stranger doesn't know you; all they have are a few vague impressions of you, too meager to form anything but a phantasm. So when they attack "you", they're really just attacking their own imagination, and there is no need to take it personally.

35. Information-Action Ratio:The mark of useful info is that it makes us act differently. Most info we consume doesn't make us act differently; we just passively graze on it like cattle before defecating it undigested.Stop mindless scrolling and seek out info that changes you.

34. Promethean Gap:Technology is outpacing wisdom; we're changing the world faster than we can adapt to it. Lagging ever more behind accelerating progress, we're increasingly unable to foresee the effects of what we create. We're amassing the power of gods, yet we remain apes.

31. Algorithmic Blindspots:We find growth while searching for other things. Algorithms give us exactly what we want on demand, so we never need to search, and never find what we never knew we needed.If you wish to grow, defy the robots' recommendations.

21. Law of Triviality:A company needs a nuclear reactor and a bike shed. Few workers understand reactors, but all understand sheds, so the shed becomes the focus of debate as everyone tries to enact their vision.Projects that require the least attention tend to get the most.

Blog About Shared Future SOS Currency Public Blog About Shared Future SOS Currency Public Blog Follow @collabfund The Optimal Amount of Hassle May 19, 2021 SHARE ↓ by Morgan Housel @morganhousel Copy Link Steven Pressfield wrote for 30 years before publishing The Legend of Bagger Vance. His career leading up to then was bleak, at one point living in a halfway house because it had cheap rent. He once spoke about the people he met living there: The people in this halfway house, we used to hang out in the kitchen and talk all night long, were among the smartest people that I ever met and the funniest and the most interesting. And what I concluded from hanging out with them and from others in a similar situation was that they weren’t crazy at all. They were actually the smart people who had seen through the bullshit. And because of that, they couldn’t function in the world. They couldn’t hold a job because they just couldn’t take the bullshit, and that was how they wound up in institutions. The greater society thought, “Well these people are absolute rejects. They can’t fit in.” But in fact they were actually the people that really saw through everything. This may not have been Pressfield’s point, but it reminds of something I’ve long believed. If you recognize that BS is ubiquitous, then the question is not “How can I avoid all of it?” but, “What is the optimal amount to put up with so I can still function in a messy and imperfect world?” If your tolerance is zero – if you are allergic to differences in opinion, personal incentives, emotions, inefficiencies, miscommunication and such – your odds of succeeding in anything that requires other people rounds to zero. You can’t function in the world, as Pressfield says. The other end of the spectrum – fully accepting every incidence of nonsense and hassle – is just as bad. The world will eat you alive. The thing people miss is that there are bad things that become bigger problems when you try to eliminate them. I think the most successful people recognize when a certain amount of acceptance beats purity. Theft is a good example. A grocery store could eliminate theft by strip-searching every customer leaving the store. But then no one would shop there. So the optimal level of theft is never zero. You accept a certain level as an inevitable cost of progress. BS, in all its forms, is similar. A unique skill, an underrated skill, is identifying the optimal amount of hassle and nonsense you should put up with to get ahead while getting along. Franklin Roosevelt – the most powerful man in the world whose paralysis meant the aides often had to carry him to the bathroom – once said, “If you can’t use your legs and they bring you milk when you wanted orange juice, you learn to say ‘that’s all right,’ and drink it.” Every industry and career is different, but there’s universal value in that mentality, accepting hassle when reality demands it. Volatility. People having bad days. Office politics. Difficult personalities. Bureaucracy. All of them are bad. But all have to be endured to some degree if you want to get anything done.

I procrastinate because I’m afraid what I’ll produce won’t be good enough. My imposter syndrome makes a great perfectionist out of me.

We might want to read more … but we abandon that when we’re feeling stressed about a project and decide to fill our available time with work.

Let’s say you have a goal like, “Spend more time with family (or friends)” … why do you need a goal like that in the first place? Without any judgment, it’s worth asking, Why aren’t you already doing that? Or another way to ask it: What will likely pull you away from that goal?

Everything’s been done before. The scenes change but the behaviors and outcomes don’t. Historian Niall Ferguson’s plug for his profession is that “The dead outnumber the living 14 to 1, and we ignore the accumulated experience of such a huge majority of mankind at our peril.” The biggest lesson from the 100 billion people who are no longer alive is that they tried everything we’re trying today.

Everyone belongs to a tribe and underestimates how influential that tribe is on their thinking. There is little correlation between climate change denial and scientific literacy. But there is a strong correlation between climate change denial and political affiliation. That’s an extreme example, but everyone has views persuaded by identity over pure analysis.

Mark Twain said kids provide the most interesting information, “for they tell all they know and then they stop.” Adults lose this skill and falsely associate the number of words with the amount of insight.

Consider a “no meeting” day every week (case for, case against).

When I first started out reading papers, I approached this the wrong way. One day, I’d suddenly decide “hmm, complexity theory is pretty interesting, let’s go on arXiv and look at some recent complexity theory papers“. Then, I’d open a few, attempt to read them, get confused, and conclude I’m not smart enough to read complexity theory papers. Why is this a bad idea? A research paper exists to answer a very specific question, so it makes no sense to pick up a random paper without the background context.

Using this information, you may choose not to read fur-ther.

Q. Why do we use bones to make chicken stock? A. They’re full of gelatin, which produces a rich texture.

actively seek industry and academic partners across clinical and research processes

Coordinate and support multiple workgroups and guide towards common strategic vision by identifying and collecting relevant data, providing data analysis, soliciting and incorporating key stakeholder feedback, and scheduling, organizing, creating materials for, and facilitating recurring meetings

Schedule, organize, create materials for, and facilitate coordinating committee meetings Collate and distribute meeting minutes and action items as warranted

best practices/lessons learned across workgroups to improve process going forward

support ongoing change management efforts based on guidance from coordinating committee and faculty

consulting role in cross-disciplinary projects

maintain a portfolio of projects

signal is a method of conveying information among not-necessarily-trustworthy parties by performing an action which is more likely or less costly if the information is true than if it is not true. Because signals are often costly, they can sometimes lead to a depressing waste of resources, but in other cases they may be the only way to believably convey important information

if every other company in your industry is buying Super Bowl commercials, then none of them have a comparative advantage and they're in exactly the same relative position as if none of them bought Super Bowl commercials - throwing money away just as in the diamond example.

Nikolai Roussanov's study on how the dynamics of signaling games in US minority communities encourage conspicuous consumption and prevent members of those communities from investing in education and other important goods.

if they ask me to read and I don't want to I might say "I don't feel like reading right now." This lets them know it's ok to try to convince me. If there's a deeper reason I try to give that: "sorry, I can't read to you right now because I need to cook dinner" gives them more information about how I'm thinking about it

Working hard is not just a dial you turn up to 11. It's a complicated, dynamic system that has to be tuned just right at each point. You have to understand the shape of real work, see clearly what kind you're best suited for, aim as close to the true core of it as you can, accurately judge at each moment both what you're capable of and how you're doing, and put in as many hours each day as you can without harming the quality of the result. This network is too complicated to trick. But if you're consistently honest and clear-sighted, it will automatically assume an optimal shape, and you'll be productive in a way few people are.

Are you really interested in x, or do you want to work on it because you'll make a lot of money, or because other people will be impressed with you, or because your parents want you to?

Many problems have a hard core at the center, surrounded by easier stuff at the edges. Working hard means aiming toward the center to the extent you can. Some days you may not be able to; some days you'll only be able to work on the easier, peripheral stuff. But you should always be aiming as close to the center as you can without stalling.

You can't solve this problem by simply working every waking hour, because in many kinds of work there's a point beyond which the quality of the result will start to decline.

I can't be sure I'm getting anywhere when I'm working hard, but I can be sure I'm getting nowhere when I'm not, and it feels awful

So I want to close this piece by generally discouraging people from "taking advice," in the sense of making a radically different decision than they would otherwise because of their interpretation of what some particular person would think they should do.