Antifragile, by Nassim Nicholas Taleb

March 4th, 2014

Amazon link

Taleb is known for his book The Black Swan, which I own and have read but apparently never wrote a review for. While his writing style is a little annoying, the central concepts of nonlinearity and power-law distributions are worth remembering (described in a Long Now talk here if you want the short version).

His latest book, Antifragile, is about how to live in a world with black swans and nonlinear outcomes. His writing style was even more annoying in this one, as he insults everybody that dares to disagree with him, and wanders off on irrelevant tangents as he apparently fired his editor. So I’m writing this post to summarize the few interesting ideas I got out of the book so you don’t have to actually read it.

The core concept is that in a world of volatility, where black swans can explode out of nowhere unexpectedly, there are three ways to deal with change – Taleb uses examples from financial investing to illustrate:

  • Fragile – unstable equilibriums where volatility is bad because it is likely to tip you into a worse state – in other words, you have limited upside and unlimited downside. A fragile investment strategy would be one where you borrow money to invest in something with a slightly higher return – if you are overleveraged and something goes wrong (and something always goes wrong), you will be bankrupt many times over, and even if you are successful, you didn’t make that much money.

  • Robust – stable states which don’t change under volatility. A robust investment strategy would be one where you don’t invest in the market at all – just stick it in your bank account and do nothing – you can’t get hurt by change but you can’t benefit from it either.
  • “Antifragile” – states that are at the bottom of the state space, so they benefit from volatility (or as the subtitle says “Things that gain from disorder”). He uses a lot of fancy concepts like convexity and concavity and references to abstruse options theory, but the basic idea is that you have limited downside and unlimited upside. An antifragile investment strategy would be what Taleb describes as a “barbell” strategy, with 90% of your wealth in robust investments that are rock-solid, and the last 10% spread around a number of highly speculative investments that have big upsides (e.g. angel investing, big options bets, etc) so that if a black swan does take off, you have a piece of it. The reason the strategy is antifragile is that your downside is limited (only 10% of your wealth), but the upside is large – even a small piece of a positive black swan like a Google or Facebook is hugely valuable.

One important aspect to Taleb’s mindset is that he believes that prediction is impossible in a non-linear world. If things can blow up unexpectedly (as he described in The Black Swan), and if very small differences in initial conditions can lead to wildly disparate results (as he described in Fooled by Randomness), then any strategy that depends on accurately predicting the future is doomed to failure. Hence the focus on creating antifragile states which have limited downside and let you keep the upside – in such states, you don’t have to predict the future, as most volatility will benefit you. Forecasting the future only matters if you are in a fragile state, and leads to your downfall when you get the forecast wrong, as Wall Street did in 2006-2007 – Taleb points out that Wall Street was taking the fragile bet of limited upside (ongoing subprime mortgage payments at a higher interest rate) and unlimited downside (holding the option if the mortgage defaulted).

That’s basically the entire message of the book: don’t think you can predict the future, and put yourself in an antifragile state where you limit your downside and keep the upside (in case you get lucky with a black swan).

Taleb also goes off on all sorts of other rants that are sometimes amusing but only marginally relevant to his central argument:

  • When investing in anything, don’t assume you can forecast the future and predict what will pay off – better to spread your investments around than make big bets. As he says, “Small amounts per trial, lots of trials, broader than you want. Why? Because in Extremistan, it is more important to be in something in a small amount than to miss it.”

  • Taleb has a long rant against iatrogenics, which is preventable harm due to medical intervention. His point is that medical intervention in cases where the patient is not imminently dying is a fragile intervention, with limited upside (in most cases the patient will get better if the doctor does nothing), and unlimited downside (unexpected side effects leading to death). Obviously, the opposite is true in cases where the patient is dying which makes that an antifragile intervention – there is limited downside (they are dying anyway), and unlimited upside (intervention might save them). That all makes sense (and I already had a policy of never going to the doctor for anything routine), but I think he goes too far with his contention that the best way to kill somebody is to get them a personal physician who will feel compelled to intervene.
  • I agree with his larger point that when we are uncertain of the consequences (and we should generally be uncertain), we should bias towards inaction. Many people bias towards action to make them look like they are contributing and doing their job, but it often contributes to a worse result e.g. active fund managers are generally outperformed by index funds.
  • I don’t agree with his bias that natural selection is always correct. He believes that nature has done a perfect job of crafting our bodies to fix themselves, but I think he is missing the point that natural selection only works on situations where reproduction is affected. Cancer is a problem because it happens after reproduction, and generally beyond the life expectancy of anybody before the 20th century – there is no way for natural selection to have dealt with cancer, so expecting our bodies to deal with it naturally doesn’t make sense.
  • He has a nice discussion of comparative advantage – the idea in economics that it is best to specialize and only do one thing as everybody gets better goods at cheaper prices in that theoretical world. His point is that the world changes, and if you put all of your effort into one thing, you are in a fragile state with the unlimited downside if that thing is made worthless for some reason (e.g. being an expert in Cobol was great for years, until it was worthless).
  • Another nice observation is that the best way to predict what technologies will last into the future is to look at how old the technology is. A technology that has been around for a hundred years (e.g. the car) is more likely to be around for another hundred years than a technology that has only existed for a year (e.g. Snapchat). This is consistent with my long-standing bias against technological determinism – technology does not drive social change – technology is adopted when it serves a social need. Technology that has been around for decades has been shown to serve a social need, and is thus likely to stick around.

All in all, I can’t recommend the book as it is really terribly written, but I think the core ideas are worth considering. If you’ve read it, I’d love to get your take, and if you haven’t, let me know if this summary is useful.

P.S. I’m hosting a salon in SF this Wednesday evening with this as a potential discussion topic – contact me for details if you’re interested in attending.

2013 review

January 6th, 2014

I’m a little late to this, but a 2013 review is an easy post to kick off my theoretically renewed commitment to blogging in 2014.

For the first time since joining Google in September of 2008, I wasn’t completely swamped by work, and thus had time to invest in the rest of my life as well as in my job.

At work, I started a new role in November of 2012 as the chief of staff to the product VP of AdWords. Instead of the fire drills and processes of finance (month close P&Ls, budget planning cycles, etc), my role was more open-ended, helping out on whatever concerned my boss, whether it was strategic questions, coordinating with sales or finance, or nailing down operational processes. The lack of structure was both wonderful (I wasn’t working like crazy) and terrifying (it was up to me to get the right stuff done without much direction). I’m still figuring out how best to focus on the big questions and issues facing Google, and convert my hand-waving ramblings into concrete actions and forward progress, but it’s a great opportunity to use my generalist tendencies and meld my finance and technology and product management perspectives.

Outside of work, I decided that 2013 was the year of Yes – whenever I heard about something that sounded intriguing, I said yes and did it, even if it wasn’t something I would normally do (with confidence built by my India trip last December and my bike tour last July).

  • I went to both Overlap and Yes By Yes Yes despite knowing nothing about either “conference” beforehand, and actually talked to people I didn’t know (which is terrifying for introverts like me) and made new friends that had no connection to my existing circles.

  • I went backpacking in the Ansel Adams Wilderness despite not having done a backpacking trip in 10 years.
  • I went to a wedding in Milwaukee where I only knew the bride and groom, and I was nervous that I’d be that weird guy off by himself all weekend, but I was welcomed with open arms by their friends and had a fantastic time (we went trap shooting and saw the Fonz!).
  • I went to Tulum, Mexico, even though I didn’t think beach vacations were for me.
  • I took a helicopter ride to the Grand Canyon!
  • I volunteered for the MIT Venture Mentoring Service despite not having been an entrepreneur myself and not being sure what I could add. It turns out I have plenty of thoughts to offer the company I’m advising (I don’t know how useful it is to them, but I’m having fun so far :) ).
  • I started mountain biking, which I’d never really done despite having a mountain bike for ten years – it had always been my commuting bike, but after buying a dedicated commuter bike a couple years ago, it was time to actually use my mountain bike on the trails. I’m still terrified of hurting myself, but I’m gaining confidence slowly.
  • I even made a real effort at dating, going on ~50 dates with ~20 women. While that effort did not result in a relationship, I considered it a success in getting more comfortable with putting myself out there, talking to people I didn’t know, and building my social confidence.

To balance all the new things, I returned to a couple old familiar activities. Over the summer, I started playing volleyball regularly for the first time in years, finding a group of coworkers to play doubles with on the sand volleyball court at Google a couple times a week. And in the fall, I started singing again, joining the Collage Vocal Ensemble, a small chamber group in Los Altos. Plus there was the occasional pickup ultimate frisbee game at Google or weekend road bike ride (like this overnight trip to the Pigeon Point Lighthouse).

It was a good year. Now I have to figure out what my focus will be for 2014. Since 2013 was an outward year, this might be an inward year – thinking and reading and writing more. I’d like to update this blog more regularly with “Deep Thoughts I Have Thunk” (™ Jofish) and read more challenging books. I also want to more regularly have challenging conversations with people that stretch my mind – it might be time for me to restart SF salons for that purpose. We shall see.

Regardless, happy new year! Hope y’all have a great 2014.

Inequality, Globalization and Technology

November 26th, 2013

There has been a discussion about economic inequality on an email list I’m on. It started with a link to this CNN summary of “must reads” on inequality, and has continued over a few other threads the past couple months. I’ve written a few thoughts in those threads, and thought I would assemble them here to see what others have to say.

My main theory is that the rise in inequality is linked to the rise in globalization. Capitalism (theoretically) links income to the impact that a company has. When that company can operate globally instead of locally, they (a) can make more money because they are having a bigger impact with more customers and (b) are out-competing local providers who are losing their customers. So the successful companies get richer while the local providers get driven out of business, which increases inequality. Within the US, you can see this in Amazon and Walmart rising to dominance at the expense of local shopping.

This dynamic of greater competition from globalization is also playing out in the labor market. A manual laborer is now competing with billions of people worldwide, and with that greater supply of people, demand has gone down and thus the price for their labor has gone down. At the same time, highly skilled software engineers can now be employed worldwide, and with companies from around the world bidding for their services, incomes for those engineers have gone up. Again, globalization is increasing inequality. The best in the world at their professions, whether they are a CEO, athlete, or engineer, are reaping the benefits of their expertise while those without similar skills are losing out.

One other effect that is happening is that technology is enabling more work to be done by less people. For instance, the graph at http://inequality.is/expensive shows average productivity going up without wages going up, with the implicit statement that these should go up in parallel. But suppose an engineer creates a machine that increases productivity by 10x, such that one person can now do what 10 people did before on the factory floor. 9 people are now out of a job, and if the engineer gets paid, say, 50% of that difference, the difference between average productivity and wages will have increased while also increasing inequality. A similar story is in play when a technology company is willing to give away a product for free (e.g. “Android may be the greatest legal destruction of wealth in history”).

If those inequality trends are linked to globalization and technology, as I posit, then I don’t see how efforts to decrease inequality by mandating pay caps (e.g. this Swiss law proposing that executives can make no more than 12x their lowest-paid employees) are going to work without also breaking the market economy. Under such caps, somebody is not getting paid “fairly” – either the executives or engineers are not getting paid enough, or the janitor is getting overpaid.

“Fair” has two meanings here, which is also part of the confusion. I am using “fair” in the sense of “people should earn what they are paid”, and so people who have more impact should get paid more, and that people who aren’t contributing don’t deserve anything (shades of the Protestant work ethic). But many liberals believe that it is unfair for one person to earn orders of magnitude than another because we are all humans and all interconnected. (thanks to Jonathan Haidt’s book The Righteous Mind for identifying this interesting split on the meaning of “fair”)

So is the rise in inequality intrinsically a bad thing? Many liberals, using the second definition of fair in the previous paragraph, take the stance of “Inequality is growing. That is unfair. QED.” I disagree and believe that inequality is “fair” in and of itself, as it is a reflection of the greater impact that people and companies can have in a world of rising globalization and increasingly powerful technology. But that’s not the whole story.

One thing that came out of the email discussion is that the effects of inequality serve to perpetuate inequality. In particular, highly concentrated wealth uses the existing system to reinforce itself. There are two ways in which this happens:

  • Money buys access in our political system, such that those who make a lot more money can change the rules to preserve their advantage in a de facto plutocracy.

  • Money buys access to education. For children, parents need money to afford private schools or to afford houses in great school districts. For college students, the best universities cost an absurd amount of money, but I still think those elite universities are worth it. So having more money gives a huge advantage to the next generation also, making it more difficult for people outside the wealthy class to get a “fair” chance to break into that class.

These are both problems that need to be addressed, but I don’t think that the problem is inequality per se. A cap on how much people can earn does not feel right to me, as it is attacking inequality directly, when I think it is these effects that are the problem. And trying to cap how much people or companies can earn via laws feels like it will be a game of Whack-a-Mole, as people will find loopholes in the laws, and other countries (e.g. tax havens) will write their own laws to attract such people and companies.

For political access, I’d prefer to address that with Lawrence Lessig’s efforts to attack the money problem in politics directly. Let’s figure out how to get money out of politics and out of campaigns, and then it won’t matter as much if companies make a lot of money. They will have the same access everybody else does

For educational access, we need to break the connection between money and education. I don’t know if the right answer is better public schools (particularly preschools), funding public schools from the state level rather than the district level (to break the connection between property taxes and school quality), or just finding ways to pay our teachers more so that our best students can make a good living by teaching (I know several people who loved teaching but eventually give it up, because they can get paid so much more as an engineer). It’s a tough problem, but it’s the right problem to solve – not how to stop inequality from happening.

What do you think? Is rising inequality a problem in and of itself? Or is it in the effects of inequality perpetuating itself through political and educational access? And what should we do about it?

Consistency

October 30th, 2013

As I mentioned in my previous post, I’ve gotten back into playing volleyball this summer at Google, and have been really enjoying it. The sand court on Google’s main campus is in regular use, and I’ll occasionally stop by and watch to pick up some pointers. One Wednesday at lunch, I was watching the really good game with players that are probably AA-rated (one notch below the top beach players). One of my coworkers sat down next to me and asked me what was the difference between me and them.

He asked “Can you hit it like that?” and I said “Sometimes” and he asked “Can you make a defensive play like that?” and I said “Sometimes”, and so he didn’t understand why I said those guys were at a whole different level than I was.

Of course, the difference is that I said “Sometimes”. When I go up for a hit, I can hit it down hard 10-20% of the time – these guys were doing it 90% of the time. When my opponent spikes the ball down, I can dive for it and return a playable ball maybe 5-10% of the time – these guys were doing it 30% of the time. So watching them is amazing because one of them will go up and pound the ball past the blocker, and the defender will have read the hit and pop it up, and it’ll go back and forth a few times. Whereas when I play, half the time I screw up the initial pass and get a weak hit at best.

A similar situation arose when I was playing in a pickup ultimate frisbee game last week. I had the best game I’ve had all year – I was jumping over two defenders to catch the disc, I was throwing hucks for scores, etc. The frustrating thing is that I know I can play like that, but it is rare when I can put it all together – at the previous week’s game, I couldn’t get open and missed several throws.

And that’s the difference between the intermediate player and the advanced player: consistency. Anybody athletic can have an occasional great play, but being a great player means being able to make that play every single time. I am stuck at a certain level in these sports where I have moments of greatness, but am mediocre most of the time, because I can’t consistently play at that higher level.

To take the next step requires the patience of deliberate practice. It’s not just about doing the activity more – it’s about breaking the activity down to its component parts and practicing each of those parts so much that they become second nature. So rather than just playing volleyball, I need to do drills to practice passing over and over again, and then drills on setting, hitting and digging, to focus on each individual skill. But that requires effort and organization, so I just play instead and have to therefore be content with my current level of inconsistency.

As usual, this doesn’t just apply to sports. Every activity requires practice to embed it deeply into our unconscious expertise, whether it’s cooking or project managing or data analysis. If you have to use your limited conscious bandwidth to examine something, it will take too long. So if you’re stuck at a level of inconsistency, are you willing to take a step back and practice individual skills assiduously? If not, you’re going to be inconsistent for a lot longer.

P.S. I’ve written about this topic before, in posts on what it takes to achieve mastery and the importance of coaching and feedback in improving and getting results, but I decided to write about it again, given my recent inconsistent play in sports.

Being a good teammate

September 4th, 2013

As those of you who follow me on Facebook know, I have gotten back into playing volleyball this summer, specifically sand doubles volleyball. I have been playing with a variety of folks on the main Google court. We typically get 4 people together to play, and then rotate through teammates, so everybody plays with everybody else over the course of 3 games.

There have been a few times when I have jumped in with the advanced players because they needed a fourth. And whenever I play with them, I feel totally bad-ass because I play so well – I hit better and set better than I ever do in the intermediate games where I normally play.

It was only recently that I realized that my higher skill level when playing with better teammates wasn’t necessarily me stepping up my game.

Both teammates are typically involved in every point in doubles volleyball, with one teammate passing the ball to the other, who sets it up for the first teammate to hit the ball over. The teammates have to work together to be successful (and I love being part of a team).

So what happens when I play with a better teammate? If I pass off target, they can recover and still give me a great set to hit – it’s placed perfectly for me to swing away. And when I am setting, my set doesn’t have to be perfect for them to be successful in hitting the ball down. When I was playing better, I was really just being made to look better by my teammate, because they could do more with my bad plays than my intermediate teammates normally could (which was in their interest because it made the team more successful).

And I realized that what is true on the volleyball court is also applicable to being a good teammate in general:

  • A good teammate sets you up with the inputs you need to be successful.
  • A good teammate takes your input and figures out how to apply it to make everybody look good.
  • A good teammate does both of those things without you realizing that you’re being helped so that you think you’re more badass than you necessarily are.

So I learned something about team building and management out on the court – that means volleyball counts as work, right?

P.S. I have now completed the restoration of blog posts from the Wayback Machine, and think I’ve gotten all of them. Unfortunately, I don’t have any way to recover comments, so I apologize to those of you that added insightful comments. I will be backing up more frequently (including after this post is up), especially since Textdrive has given me no indication that they are alive other than the server still being up (no email, no Twitter, no answering of service tickets).

Restoration in progress

August 18th, 2013

In case you hadn’t noticed, the server where nehrlich.com is hosted had a catastrophic meltdown a few months ago, and my hosting provider (Textdrive) was not able to recover files or backups. This is sad, because I’d last backed up my blog in 2009, so I’m going to be using the Wayback Machine to try to at least get some of the posts back, if not the comments.

But at least I still have the content back from when I was posting more regularly (once or twice a week) vs. the last four years when it’s been more like once a month (~40-50 posts lost).

I’m still annoyed at myself for not having kept my backups current and putting too much trust in my provider. Textdrive did terribly, and then didn’t have the courage to respond to any of my repeated status requests. Learning lesson. I should look into another hosting provider – after spending the few hours to get myself up and running on the textdrive blank slate server, transferring wouldn’t be that bad. Recommendations welcome.

Then maybe once I’ve done all that recovery, I can start posting again about the new thoughts I’m having.

I went to India!

January 1st, 2013

I just got back from a trip to India and thought I’d share my thoughts and some pictures.

I had only 17 days in India itself, as getting there and back took a couple days out of the three weeks of vacation that I had available. My itinerary evolved throughout the trip as I made adjustments on the fly, but I ended up flying into Delhi, then to Kerala, the tropical area in the south of India, then to Aurangabad to see the Ellora and Ajanta caves, then to the region of Rajasthan, where I traveled from Jodhpur to Jaisalmer to Udaipur to Sawai Madhopur (tiger safari!) to Agra (Taj Mahal) back to Delhi for my flight out. I packed way too much in, as I just barely saw the tourist highlights of each city (like coming to SF and only seeing Fisherman’s Wharf), and I wore myself out, but I feel like I got a nice flavor of India.

Udaipur PalaceWhile I was there, I decided to skip Delhi and Mumbai from my original itinerary, as other travelers said that they were more globalized cities and less specific to India – I disagree based on the two evenings I spent in Delhi, as I enjoyed observing the specifics of Indian interactions as an amateur anthropologist, but it was definitely not as scenic as the rest of my visit.

Kailash temple at Ellora CavesThe most amazing thing I saw was the Ellora caves – these are temples and monasteries carved out of the side of a mountain in 500-700 AD (1500 years ago!) that have amazing sculptures carved into almost every available surface. It was jaw-dropping to think of them doing all of these carvings perfectly, as they couldn’t start over with a fresh piece of stone if they made a mistake.

I'm on a camel!I also really enjoyed the camel trek I went on in Jaisalmer – we rode camels out to the sand dunes, ate dinner over an open fire while watching an amazing sunset, slept under the stars (more stars than I’ve ever seen in my life!), woke to an amazing sunrise, and rode back in the morning.

The different forts I saw were a highlight of the trip as well – the picture below is from Kumbalgarh, but I also saw Jaisalmer Fort, Meherangarh Fort in Jodhpur, and Daulatabad Fort near Aurangabad, of which Meherangarh Fort was probably my favorite (partially because it had the best audio tour).

Detailed journal posts I made to Google+ while I was over there below, along with hundreds of pictures, in case you want to read or see more:I'm at Kumbalgarh

Big Data isn’t the answer

November 16th, 2012

I was talking to somebody last week who had recently moved to San Francisco, and she randomly interjected Big Data into the conversation. She said she’d learned that’s what you do in SF – Big Data is a buzzword that can be used at any time on any topic. I found this amusing, because Big Data is becoming almost messianic – all of our problems will be solved once we have Big Data! Everybody should become a statistician or economist or data analyst!

My response? Don’t believe the hype.

The trends are unmistakable – humans are creating and capturing more data than ever before. IBM estimates that 90% of the data in the world today was created in the last two years. And the tools we have to sift through data are becoming ever more powerful, with open-source packages like Hadoop for map/reduce, and R for statistical computing.

This flood of data and the tools to analyze it are creating market opportunities for businesses and career opportunities for individuals – the story of Target identifying a pregnant teenager from her purchases is a founding myth of Big Data. And some credit Obama winning the presidency to data analysis. So why am I skeptical?

There is a belief that if we could only quantify everything, we would be in control. The management saying is “You can’t manage what you don’t measure.” So if we have more data, and can measure everything, we should be able to manage everything! Except that the world is not that simple. Just because something has been quantified doesn’t mean that it is good or meaningful data – how the data is collected can introduce biases or trends that render it useless for making decisions. And just because an analysis gives a numerical output does not make it into useful knowledge or wisdom.

What I am seeing in the rush to Big Data is the urge to quantify things before understanding them. Recording 600 metrics and tossing them all into a database creates a ton of data, and analysts can spend weeks or months looking through the data. But is that really driving value for an organization? Similarly, I’ve seen situations where an analyst uses a standard ARIMA model to forecast a trend with confidence (because it’s data-driven!), and later being surprised that the forecast is wrong because they never really understood the underlying data. Another example is when a consultant creates a 500-line Excel spreadsheet, where every possible variable is quantified and every change ripples through the spreadsheet… but of those 500 lines, 490 are assumptions, so it’s impossible to tell which variables really matter.

Another potential peril is when analysts start their work with a preconceived notion of the result they want to get. With Big Data, you have enough data to support almost any conclusion if you slice the data in the right way. One of my favorite stories about the perils of data analysis came from my time as an intern at CERN – a grad student was looking for a particular energy resonance from the L3 detector data, and displayed this beautiful graph showing that resonance. Dr. Sam Ting, Nobel Prize winner, smelled a rat – the result looked _too_ clean. He told the grad student to show the data with all of the filters removed, and the raw data showed nothing but noise. The student had applied the filters to show what he wanted to see. Note that I’ve seen similar things happen at Google – as a coworker commented to me recently, if even Google (and MIT grad students) can’t consistently get data analysis right, can anybody?

I worry that the quantification of the world in the form of Big Data is being seen by businesspeople as an end in itself, rather than as the tool it is. Like any tool, data analysis can be used well by those who have trained in its use, or it can be used poorly and cause damage by those without experience. Understanding data is hard. It takes time and effort, and while a well-constructed tool can accelerate that process, it doesn’t replace the need to sit and work with the data to understand its quirks and characteristics. After really understanding the data, you may discover that only 3 metrics out of 600 really matter, and so you don’t need Big Data to run your organization – just a dashboard with the 3 things that matter.

Big Data isn’t a silver bullet that will fix everything with your organization. It is a powerful tool that can help you better understand what is going on, but only if you spend the time to use it properly. Just because your analysts create output that is quantitative doesn’t mean it’s right. Trust, but verify. Use your judgment and all of your tools including walking around to figure out what to do, because in the end, you are the one responsible, no matter what the data says.

Career development in the 21st century

October 30th, 2012

It’s performance review time at Google, and that means that I am reassuring the young’uns in their mid-20s that it’s all going to be fine. They have been at the top of their class their entire life, they got into the best colleges, and they plan on continuing to ace every test they’re given. And so they come to me to ask me whether they are on the right track with their career development. I have given out the same advice to several people in their mid-20s recently, so I figured I may as well share it here as well. And that advice is: Chill!

It is a ridiculous concern to be worried about being on the right career path in your mid-20s. Your career is not like the Milton Bradley Game of Life, where everybody is on the same path, and it’s a race as to who gets there first. It’s about figuring out the right path for you to achieve the results that you desire. I suppose I should stop here to caveat that I have an unconventional career path that influences my viewpoint, but so far it seems to be working for me – I keep finding interesting jobs and convincing companies to hire me.

Here is the situation in the 21st century:

  • The world is changing faster and faster. World-famous companies are appearing and disappearing in years, if not months. The old model of going to work for a company and retiring 40 years later is not realistic in this fast-changing world.

  • More possibilities for careers exist than ever before. We are not constrained in our choice of professions by what exists in the world – we can create our own professions by combining existing skill sets in new ways.
  • Because the world is changing faster and because the possibilities are growing exponentially, the one thing you can guarantee is that the skills you have today are not the skills you will need in ten years. Developing an aptitude and zest for learning will be key to staying relevant.

Unfortunately, most career development advice is still based in 20th century thinking.

  • Work your way up the career ladder.

  • Do what you have to do to get promoted, jumping through the hoops.
  • Visualize your dream job in ten years, and develop the skills to have that job.

These all assume a static world, and I just don’t think that’s a reasonable assumption. My last four jobs (three at Google) didn’t exist before I took them, so there was no way I could have planned to get those jobs in advance – they existed on no career ladder. And I think that’s the direction we’re heading, where more ad hoc positions will be created to bridge gaps in the state of things.

So how should a college grad face this new world? What does it mean to develop your career in the 21st century?

  • Always be learning (ABL?). Learning is the key to keeping up with a rapidly changing world, so developing that skill at every opportunity will put you in the best position to succeed.

  • Also, make sure that you are learning useful skills – skills at managing people, building influence, and domain-specific knowledge are transferable skills that you can keep in your toolbox, skills on how to play the politics at a dysfunctional company are not transferable.
  • When you’re in a job, solve problems and build relationships. These are often related – you don’t build relationships by schmoozing – solving people’s problems is what earns you respect and ensures that you are remembered.

So pick jobs where you are learning useful skills, and where you can have an impact and build relationships. If you do that repeatedly, you will find new positions and careers being created for you, rather than trying to climb over other people on a ladder that others built.

One other point – people early in their careers often worry that a given position is the wrong choice and that it will put them “behind”. I tell them that there are no wrong choices at that stage, as they will learn something from every position they take. Comparing themselves to peers who may be “advancing” faster is not useful since careers are no longer comparable given the multiplicity of options – we are each creating our own path.

So, yeah. Keep learning, get things done, build relationships, and then learn how to package together your unique skill set to find or create your next opportunity. That’s my advice – what do you think?

The Idea Factory, by Jon Gertner

October 7th, 2012

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In light of my last post on the Anthropology of Innovation, it was apropos that I was just finishing The Idea Factory, by Jon Gertner, a history of Bell Labs and its impact on 20th century innovation. I actually also saw Gertner at the Computer History Museum in March, but had to wait a few months for the book to get through the hold queue at the library.

The book itself is a well-told story of the creation of Bell Labs and its rise to pre-eminence, mostly focusing on the 1930s to the 1950s. Bell Labs started off as just an R&D lab for AT&T, developing technology and materials to better enable phone calls. But in the 1930s, the director started to expand its mandate by hiring physicists and chemists to do basic research. During World War II, the lab was essential to the war effort, contributing to radar among other projects, and after the war, they were given the freedom to work on whatever they wanted. This led to the invention of the transistor in 1947, but also the conception of information theory by Claude Shannon in 1948 – two amazing leaps forward in how we think about the world.

The most interesting part of the book to me was how Mervin Kelly engineered a culture of innovation at Bell Labs that will probably never be rivaled. The idea that an industry lab would do research leading to thirteen Nobel Prizes is inconceivable today. To be fair, AT&T had a government-granted monopoly, so they could do research that wouldn’t pay off for 20 years, and know that they would still be in business to benefit. And to keep on earning that monopoly, they had to demonstrate that their research was contributing to the basic good of humanity – I was surprised to learn that they were required to license out all of their innovations for low cost, including the transistor. So that combination of monopoly-protected resources and a requirement to do good was a key factor in enabling Bell Labs to go beyond any other lab.

But Bell Labs wouldn’t be Bell Labs if it was just a monopoly-driven research lab. Kelly designed Murray Hill, the New Jersey home of Bell Labs, to be a building where people had to run into each other going back and forth. This is now pretty common (e.g. at Google, they have a micro-kitchen on every floor to encourage such congregation), but at the time was very unusual. He then populated that building with the smartest people he could find, regardless of their field of expertise – physics, chemistry, mathematics, materials science, electronics – every field was relevant to something AT&T was doing (e.g. going from the vacuum tube to the transistor required inputs from all of those fields). Another aside: the scope of what they had to create included all sorts of things I wouldn’t have thought of but were an essential part of building for the long term – the book talked about burying wood logs in swamps to see how they would hold up to 20 years of service as a telephone pole, or designing materials that could handle seawater so they could insulate their underwater cables.

Kelly also instituted a culture where these bright minds could work on what they wanted, and ask anybody anything – so if you wanted to ask Shockley (the inventor of the transistor) a question about semiconductor physics, you just went and did it. This created a cross-pollination of ideas, where you might have a cockamamie idea, but could go ask the world expert on it, who was just down the hall, and that might lead you together to think of a more reasonable idea, so you’d stroll down the hall some more to talk to an engineer who could build a prototype. And the challenges of running a nationwide communication network meant that there were always new problems to think about. This combination of challenges and bright minds and the need to turn ideas into real products led to an enormous number of breakthroughs.

It’s interesting that nearly a century later, the same principles are still at the forefront of creating innovation. The Anthropology of Innovation panel talked about breaking down silos between fields, and about focusing on the user (Bell Labs was always grounded by the mission of delivering the best possible service to somebody making a phone call). The principles are straightforward, but it’s hard to really apply them, and so it’s impressive to read about an institution that did so and was pre-eminent as a result for decades. I don’t think such a lab could exist today (again, the monopoly-protected revenue stream was a key component), but it’s an inspiring example of how to take those principles and create a beacon of innovation.

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