Looking back at 2018 after one day into 2019, one word comes to mind, tumultuous. I started a new job, read more books in a year than ever before, and got back into writing and recording original music. Picked up some new life lessons that I'll be trying to implement in 2019. We'll see how that goes.
2018 included some Nordic highlights. I finally got to live the dream of seeing Finnish rock vocalist (ex Nightwish singer) Tarja Turunen sing a medley of Nightwish songs. Her concert was one of the best live shows I saw in 2018. Thanks to a friend I was also introduced to the Finnish rock group Sturm und Drang. Although the band is unfortunately no longer together, their 2012 album "Graduation Day" is one of the best rock albums I've heard in a long time (here is one the singles from the album). I also found out from 23andme that I'm 2.4% Finnish! Hence my affinity for everything Nordic.
As an avid podcast listener I've added a new section to this year-in-review, "Current Podcast Subscriptions". It's a snapshot of the podcasts I'm subscribed to right now. Curious to see how this list evolves in years to come.
I wanted to also surface this wonderful Scott Forstall interview from 2017. Scott was the software leader for the first iPhone, and this was his first public interview since he had left Apple. The interview is inspirational and includes some fantastic lessons and stories.
- Bruce Lee: A Life by Matthew Polly
- Chaos Monkeys: Obscene Fortune and Random Failure in Silicon Valley by Antonio García Martínez
- City of Thieves by David Benioff
- Dirty Genes: A Breakthrough Program to Treat the Root Cause of Illness and Optimize Your Health by Ben Lynch
- Black Privilege: Opportunity Comes to Those Who Create It by Charlamagne Tha God
- Machine Learning Yearning by Andrew Ng
- How Does The Oura Ring Work by Ben Greenfield
- Productivity by Sam Altman
- How Airbnb Democratizes Data Science With Data University by Jeff Feng
- The Big Business of Becoming Bhad Bhabie by Jamie Lauren Keiles
Movies & Documentaries
- War Of The Worlds, Pt. 1 by Michael Romeo
- Sleepwalking by NINA
- Equinoxe Infinity by Jean-Michel Jarre
- Songs About People Including Myself by The Bad Dreamers
- Life Is Not Beautiful by Arion
- Kids by The Midnight
Current Podcast Subscriptions
- Jocko Podcast
- Recode Decode, hosted by Kara Swisher
- The Ben Shapiro Show
- The Bill Simmons Podcast
- The Daily
- The Joe Rogan Experience
- The Kevin Rose Show
- The Lowe Post
- The Tim Ferriss Show
- This Week in Startups
wait just start Posts
Biohacking, while still underground, is steadily making it's way to the mainstream:
I describe Biohacking as utilizing technology to produce data that you use to make lifestyle decisions in order to optimize your health. For example, you may have done a 23andme genetic test that indicated based on your genetics, you are likely to drink slightly less caffeine than the average person. Thus you now make the lifestyle decision to no longer have afternoon coffee so the caffeine doesn't impact your sleep. Congratulations, you're a biohacker.
I've recently acquired an OURA ring. It's made by a startup in Finland and is marketed to be the "most accurate sleep and activity tracker". This past week I was puzzled in that although I was getting 7 hours of sleep, I was still feeling tired the next day. Here is what my OURA ring showed for Thursday night:
You'll notice that my deep sleep was quite low. According to 23andme, my genetic profile makes me "less likely to be a deep sleeper", so I'm already starting at a disadvantage. Thus I need to optimize both my lifestyle and sleep environment in order to maximize the amount of deep sleep I get.
The ideal sleep environment for the average person has two obvious traits: quiet and dark. What may not be as obvious is the environment needs to be cool. Research has shown that humans sleep better in cooler environments. So for me, when any of these three elements are not ideal, my deep sleep suffers. There are many other lifestyle factors that can impact deep sleep (large meal before eating, too much screen time just before sleep, etc.), but the foundation is: quiet, dark, and cool.
In the winter season in New York City my apartment (whose heat I do not control) gets warm. Leaving a window open when it's 30 degree outside results in a freezing apartment. So I have two options for sleep environments: Siberia or Cancun. I've opted for Cancun by keeping my windows closed and that's been impacting my deep sleep. So I attempted a Biohacking solution.
Using a ChiliPad I was able to cool my bed to a brisk 62 degrees F. And I received instant gratification:
Both my REM and deep sleep improved and OURA now gave me an 88% sleep score. Clearly I still can do better across the board, but one change already has clear benefits.
As mentioned there are many other factors that influence sleep, but in my example I started to address a foundational one. And that is the essence of Biohacking. Like a technology hacker, you collect data, analyze it, identify the metric(s) you want to move, implement a solution, measure, optimize, repeat.
There are certain skills citizens should develop in school and nurture throughout their careers. Skills such as empathy, grit, wonder, and growth-mindset. These are often referred to as non-cognitive, twenty-first century, or intangible skills. They can empower an individual to live a fulfilling and prosperous life.
I've recently started to believe that dealing with ambiguity is another critical non-cognitive skill. This skill requires an individual to be comfortable with committing to an answer when there is no right answer. To be able to take in multiple inputs (perspectives, facts, etc.) and make a decision. To not only strive to make the best decision that can be made, but to be aware of the impact that decision may have. And to use that awareness of potential impact(s) to make an even more optimal decision.
Learning to deal with ambiguity is the antithesis of a multiple-choice test. The latter has one correct answer. Many situations in the real-world have no clear right answer. For example as new technologies emerge, regulations for those technologies can rarely be organized into a A, B, C, or D answer. The answer is there is no right answer. And we will need citizens that are capable of making decisions that are ethical and value driven. Decisions that if audited, show that the citizen made the best decision they could given the information available.
While certain questions and decisions will have narrow consequences, others will be far-reaching. In the article "Tech Giants Join Forces to Score AI Chips", the author describes how tech companies need to align around a benchmark for measuring how well computer chips perform artificial intelligence tasks:
While esoteric, the process of devising benchmarks can be surprisingly contentious, involving fierce technical battles and corporate politics. Participants are often the same companies that have heavy stakes in the results of the tests—namely, chip makers and cloud computing providers who use the scores to publicly boast about the advantages of their products and services. It is a bit like inviting students to craft the questions for an exam they’re about to take.
If you're the mediator, or a representative of a company building such chips, how do you navigate this situation? How do you deal with the ambiguity? How do you approach understanding the perspectives and goals of the other parties? How do you take a stance and recognize when it's more productive to shift your stance even if it comes with a negative cost to you.
In a white paper by Senator Mark Warner, he describes potential policies for regulating social media and tech firms. In one of the sections he talks about "dark patterns":
Dark patterns are user interfaces that have been intentionally designed to sway (or trick) users towards taking actions they would otherwise not take under effective, informed consent. Often, these interfaces exploit the power of defaults - framing a user choice as agreeing with a skewed default option (which benefits the service provider) and minimizing alternative options available to the user.
One drawback of codifying this prohibition in statute is that the law may be slow to address novel forms of these practices not anticipated by drafters.
He gives the example of Facebook asking users to provide access to their address book, and not giving the user a clear YES / NO option. The product design skews the passive user to selecting the YES option.
And thus how do you regulate this? As a free product that users have the choice to not use, should Facebook be regulated in how they build their product? How will such regulation impact other companies ability to innovate? How would you introduce regulation for something that seems clear today, but may become ambiguous in the future? Although your stance may make sense today, tomorrow a new company or technology may break it. Would you be able to adapt? As Mark Warner writes, can a law be written in such a way that it anticipates future problem areas?
As new technologies emerge the level of ambiguity around how those technologies impact our societal infrastructure increases. And as these technologies impact a majority of citizens, the decisions made around these ambiguous questions will have a far-reaching impact. And thus I hope that the citizens in positions to answer ambiguous questions are comfortable and confident in dealing with ambiguity.
How do you form an opinion on a complex topic such as climate change, immigration, or the gender pay gap? Do you read research papers by experts? Articles by news publishers? Watch the news? Listen to podcasts? Read tweets?
Are you quick to discount information outside your trusted sources? Do you actively seek alternate perspectives? Are you quick to jump to conclusions or get riled up? How often do you question the integrity of the information you're receiving? In your quest to quell your information hunger or FOMO (fear of missing out), do you find time to pause and reflect on what you're processing?
Today we have access to an unparalleled amount of information. And thus we seek more. More articles to read. More feeds to swipe. More information to digest. As we rush from one thing to the next, our opinions become susceptible to being deceived by the information presented to us. We become susceptible to misleading facts.
A misleading fact is a statement that is factually accurate, but overgeneralizes the issue. This may be for an ulterior motive, a way to sensationalize the issue, or the author has no motive and feels they are stating a fact.
Data in a misleading fact is unfairly curated to amplify the author's position. On the surface the misleading fact presents a clear problem, but the scale of the problem changes depending on how the underlying data is interpreted. Take the 2013 State of the Union address as an example. President Obama raised a statistic that on average women earn 23 cents on the dollar less than men.  Here is the quote from the addresses supporting document:
Securing equal pay for equal work: Women make up nearly half of the U.S. workforce and two thirds of our families rely on a mother’s wages for a significant portion of their income. Yet on average women generally make 23 cents on the dollar less than men.
The Washington Post, in its State of the Union fact checking article, replied:
There is clearly a wage gap, but differences in the life choices of men and women — such as women tending to leave the workforce when they have children — make it difficult to make simple comparisons.
The administration’s back-up document for this statement asserted that “on average women generally make 23 cents on the dollar less than men.” But the White House is using a figure (annual wages, from the Census Bureau) that makes the disparity appear the greatest. The Bureau of Labor Statistics, for instance, shows that the gap is 19 cents when looking at weekly wages. The gap is even smaller when you look at hourly wages — it is 14 cents — but then not every wage earner is paid on an hourly basis, so that statistic excludes salaried workers.
On the surface, this fact appears to state (and many interpreted it this way) that a woman doing the same job as a man makes 23 cents less per dollar earned. And, as the Washington Post concluded, this is just not true.  If one were to look at the data through a different lens, they may learn that each dataset tells a different story. 
Am I saying that there is no such thing as a gender pay gap? Absolutely not. Looking at a US Department of Labor 2016 report, out of the 22 selected occupations in this data set not one has women's earnings as a percentage of men's above 91.3%. Yet, as the Department of Labor writes in the report:
These comparisons of earnings are on a broad level and do not control for many factors that may be important in explaining earnings differences.
I believe such "23 cent per dollar earned" misleading facts are more prevalent today than ever before. These facts fuel the business models of social and news media platforms. They are convenient to package into tweets, eye-catching articles, and 5 minute long news debate segments. They spark controversy, rile us up, and engage us.
In a world where there is more content than attention, misleading facts are a powerful tool to capture your attention. As your attention jumps from one piece of content to the next, you're susceptible to taking the misleading fact at face value and may miss out on a deeper understanding of the issue. An understanding that could potentially empower you to do something to address an underlying problem of the issue.
Here is another example of how easy it can be to overlook and accept a misleading fact. "The Gender Pay Gap Is Largely Because of Motherhood" is an article published in the New York Times in May 2017. The tweet worthy title is clear and conclusive. It stirs emotions and may reinforce for some women their sense of unfairness and hopelessness in seeing change in the gender pay gap. A pessimistic interpretation of the title could be: "Good Luck Changing Biology. As the Bearer of Children Your Destiny is to Earn Less".
As you read through the article, you'll find links to other articles written by this author and research studies. If you're in a rush to get to the next piece of content in your queue, you're not likely to examine these additional sources. You may assume that because this is a New York Times piece, and because the author provided links to studies, the conclusion reached in this article is definitive. And yet if you did explore the linked articles and studies, would you reach the same conclusion as the author?
Here is a quote from the article:
The big reason that having children, and even marrying in the first place, hurts women’s pay relative to men’s is that the division of labor at home is still unequal, even when both spouses work full time. That’s especially true for college-educated women in high-earning occupations: Children are particularly damaging to their careers.
The first link is to another article written by this author in 2015, "Stressed, Tired, Rushed: A Portrait of the Modern Family". This article relies on evidence from a Pew Research Center report to conclude that the division of labor at home is unequal and that women more often share that burden.
Note that the report's findings came from survey data. Here is who was surveyed:
The analysis in this report is based on telephone interviews conducted from Sept. 15 to Oct. 13, 2015, among a nationally representative sample of 1,807 parents, 18 years of age or older, with children under 18, living in all 50 U.S. states and the District of Columbia.
Therefore, the findings are based on the perceptions of those interviewed. One of the prompts in the telephone interviews was "household chores and responsibilities". 787 fathers and 651 mothers were interviewed with this prompt. 50% of the mothers perceived that they do more household chores, while 57% of the fathers stated the responsibility was shared equally.
You could use this study to make the conclusion that women have taken on more household responsibilities but, from my perspective, additional data would be needed before I can accept this as a fact. 
The second link (for the point that children are particularly damaging to college-educated women in high-earning occupations) goes to a landing page for a 340 page book. As the author of the Time's piece does not mention any specific passages from the book, here are two paragraphs from the book's summary:
Unequal Time shows that the degree of control that workers hold over their schedules can either reinforce or challenge conventional gender roles. When male doctors work overtime, they often rely on their wives and domestic workers to care for their families. Female nurses are more likely to handle the bulk of their family responsibilities, and use the control they have over their work schedules to dedicate more time to home life.
Surprisingly, the authors find that in the working class occupations, workers frequently undermine traditional gender roles. Male EMTs often take significant time off for child care, and female nursing assistants sometimes choose to work more hours to provide extra financial support for their families.
I selected these paragraphs to showcase how the narrative of gender roles may change as different segments are analyzed. For example, it's in working class occupations where workers frequently undermine traditional gender roles. A finding that was omitted from the Times article.
The two studies that the author of the Times piece used as the basis of her article are described here:
But even married women without children earn less, research shows, because women are more likely to give up job opportunities to either move or stay put for their husband’s job. Married women might also take less intensive jobs in preparation for children, or employers might not give them more responsibility because they assume they’ll have babies and take time off.
“One person focuses on career, and the other one does the lion’s share of the work at home,” said Sari Kerr, an economist at Wellesley College and an author of both papers. One will be published in the American Economic Review this month; the other was published this month as a working paper by the National Bureau of Economic Research. The other researchers were Claudia Goldin of Harvard, Claudia Olivetti of Boston College and Erling Barth of the Institute for Social Research in Oslo.
The first study was published in the American Economic Review. It utilized data from the 2000 Census linked to the LEHD database (a data set that combines federal, state, and Census Bureau data on employers and employees). The study was a statistical study that looked at the wage gap from multiple data angles. As the concluding paragraph of the study states, the research was not about explaining the wage gap. The data cannot answer that question. However, the authors could use the data to theorize some of the likely causes (e.g. family responsibility) of the wage gap:
Our bottom line is that the widening is split between men’s greater ability or preference to move to higher paying firms and positions and their better facility to advance within firms. Given industry and occupation, far more is due to men’s better advancement within firms. Women’s greater family responsibilities appear to be largely responsible for both the between and within firm differences. These data cannot tell us what part of the differences are due to women’s choice to work in less demanding, and thus lower paying, industries, firms and occupations when they have greater family responsibilities. But they hint to that as an important explanation.
The second study is a working paper issued in May 2017 that used the same dataset (2000 Census data linked to the LEHD database).
Like in the previous study, the researchers did not examine the reasons for why the gender pay gap exists. They used statistical data to show that the gap exists, and then theorized as to the likely factors causing the gap:
The researchers point out that women may face both between- and within-establishment gaps. Due to family and caretaking obligations, women may be less able to put in the long hours required to score a big promotion at their employer, or to invest in the networking and job search activities that facilitate financially advantageous job changes. These effects may be compounded if employers believe that women are less likely to remain in the labor force over the long term, or if women are less likely to seek promotions and raises within and across firms in anticipation of needing more time flexibility or because of family location decisions in which the career of the primary earner, usually the husband, takes precedence.
The quotes above illustrate that the definitive conclusions presented in the Times article are misleading. The research can be interpreted in various ways and if you didn't take the time to dive into the data you'd be left with the one perspective the author chose to present.
Should President Obama have been clearer in his State of the Union address about what we do and do not know about the 23 cent figure? Should the Times author been more upfront that the researchers she quoted theorized about the likely causes of the gender pay gap, but did not study why it exists?
I view humanity as a collective group striving to improve society through shared knowledge. There are more research papers and studies published each day than each of us can read in a lifetime, yet if I read one, and you read one, and we find a format to share our knowledge without bias - we collectively benefit. But, if my intent is to get you to adopt my perspective, I'll present misleading facts that support my position and deprive you of the alternative perspective(s).
I believe that people must strive to develop their inquisitiveness. To be vigilant and curious as to how messengers reach their conclusions and what those conclusions imply. People must hold messengers to a high standard and not blindly follow them because of some underlying loyalty.
Messengers that present a misleading fact should be clear about the limitations of that fact and why they chose to present it in such a way. Break down your sources, point out their strengths and flaws. Be explicit about the assumptions you made and where the evidence was inconclusive. Don't leave it for your audience to guess what the conclusion is. A link to a study does not absolve you from the responsibility of analysis and examination.
We are reaching an inflection point. Misleading facts and outrage culture are among us. And yet we have an opportunity to rise above it through collective information. For if we collectively bring our knowledge and findings together we can rise together, and overcome the challenges facing our society.
The costly alternative is more anger, more outrage, and more divide.
Thanks to my long time friend Courtney Diamond for reading and providing feedback on a draft of this.
 If you're curious as to how the 23 cent figure was calculated, start with the 2015 Income and Poverty data tables from the US Census Bureau. Download Table A-4. Number and Real Median Earnings of Total Workers and Full-Time, Year-Round Workers by Sex and Female-to-Male Earnings Ratio: 1960 to 2015. Select year 2012, and look at the last column (Female-to-male earnings ratio), the value is 0.765 (or 77%), or $0.77 to $1.
 Is it possible that in some cases a woman is paid less than a man for doing the same job? Absolutely. Does this happen in 51% or more employment situations? Very unlikely. And, it's also just as possible that a man may be paid less than another man for doing the same job.
 The filters through which you look at the data impact the conclusion. For example, take a look at the Q1 2018 Weekly Earning Report by the US Department of Labor. The report found that "white women earned 81.2 percent as much as their male counterparts, compared with Black women (92.8 percent), Asian women (78.5 percent), and Hispanic women (85.1 percent)".
 Given that in 2015 there were 42.5 million Married Men employed and 32.9 million Married Women, is a sample survey size of 787 and 651 enough to make a definitive conclusion on the division of labor at home?
There is a group of individuals I'll label as "wake up early individuals" (WUEIs). People that get an early start in order to tackle goals before the day begins.
For some it's waking up early and exercising. Jocko Willink consistently posts photos starting his day at 4:30 AM. The book "How Children Succeed" gives an example of a middle school chess prodigy who woke up early to practice chess. Joe Satriani, electric guitar extraordinaire practiced in the mornings before school:
When I was a kid, I’d get up and practice guitar for an hour before school, and during that hour I’d do all the boring stuff just to get it over with. That way I could come home, do my homework and then jam with my friends.
How are they able to do it? In a world of distractions (mobile phones, YouTube, etc.) WUEIs find a way to go to sleep early and pull themselves out of bed to get after it. Jocko in his book "Disciple Equals Freedom" argues that discipline is the enabler:
Discipline: The root of all good qualities. The driver of daily execution. The core principle that overcomes laziness and lethargy and excuses.
And that waking up early is the starting point:
Discipline starts with waking up early. It really does. But that is just the beginning; you absolutely have to apply it to things beyond waking up early.
Discipline is one common trait WUEIs share. Fuse the desire to achieve a goal with discipline and you get an individual that will wake up at 4:30 AM. Someone that will do whatever it takes.
Yet discipline is only an enabler. It's a starting point. Showing up isn't enough.
Before discipline you set a goal(s). I want to be a: entrepreneur, author, musician, fit individual, etc. This broad goal (musician) may start to become a bit more specific: 80s shred guitar player.
And thus with your goal you channel discipline to show up and put in time towards reaching your goal. This alone will not be enough. For you can show up everyday at 6 AM and practice guitar, but if the practice isn't focused and the goal is open-ended, one year later you may have not made the progress you imagined.
You must set yourself up for success. So when you do show up you take full advantage.
Break down your goal by setting mini-goals with deadlines. This month I'll learn three 80s metal guitar riffs and will write three original ones. I'll also learn to play one full song. Even more specific: by the end of this week I'll learn one riff and the first 2 sections of the song. With clear goals you now have a roadmap towards where you want to be.
To fulfill the roadmap you'll need a system. The system may even impact how you define the roadmap (the path to reaching your goal(s)). Once you define the path your system is how you divide your time. If I have 90 minutes in the morning, my system may be 20 minutes guitar exercises, 30 minutes learning the song, and 40 minutes composing.
Your focus and attention must be deliberate. It's easy to fall into a habit of repeating the same system everyday. But you're showing up so it must be enough right? Just put in the time and results will follow. This is dangerous and you'll likely stagnate. Today you may need to spend 45 minutes learning the song and 45 minutes composing. Tomorrow it may need to shift again.
With deliberate focus you are constantly aware of the goal, your system, and the progress you are making. You make adjustments as necessary so you don't fall into a mindset that just showing up is enough.
If you combine discipline, goals, deadlines, systems, and deliberate focus, you will significantly increase the likelihood of achieving your goals.