Keynote: Lucky You

by Sandi Metz

In her keynote address titled "Lucky You" at RubyConf 2019, Sandi Metz explores the concept of luck and its correlation to success, particularly in the context of programming and socioeconomic factors. The talk highlights how individuals can cultivate their own luck through a mindset shift based on research by psychologist Richard Wiseman, who identified four key components of luck. Metz elaborates on these components, emphasizing the importance of paying attention, being open to experience, expecting luck, and positively interpreting events.

Key points discussed include:

The Nature of Luck: Metz describes luck as something that can be harnessed by individuals through conscious effort and a positive mindset.
Statistical Insights on Income: She presents data indicating that programmers typically earn significantly higher than the average US worker, with median salaries around $93,000.
Diversity in Tech: Metz addresses ongoing issues regarding gender and ethnic representation in tech roles, noting a concerning trend in the decreasing number of women in programming despite improvements in income equality.
Impact of Neighborhood on Outcomes: Drawing from Raj Chetty's research, she illustrates how the neighborhood one is born into can dramatically affect socioeconomic mobility, with contrasting outcomes based on community wealth and segregation.
Historical Context of Inequality: The history of redlining and its long-lasting effects on racial wealth gaps is discussed, showcasing how systemic barriers continue to hinder progress for certain demographics.
The Role of Family Structure: Metz emphasizes that neighborhoods with supportive family structures and high social capital yield better outcomes for children.
Call to Action: In her conclusion, Metz urges attendees to acknowledge their privilege, engage in reform, advocate for systemic change, and address issues like climate change, ensuring equitable opportunities for all.

The talk emphasizes that while individual effort is important, understanding and acting on systemic issues is crucial for creating lasting equity in society. Metz encourages everyone to take responsibility for promoting social change and addressing the historical injustices that continue to impact communities today.

00:00:11.990 Alright, so my talk really just barely fits in my time slot, so I can't take much time to gab with you. I do, first, want to thank the sponsors; this couldn't happen without them.

00:00:18.029 You know how many times this week you've been told, 'If you have a problem, talk to someone in a red shirt?' If you haven't talked to someone in a red shirt yet, before you leave today, find one of them, shake their hand, and thank them. They do a lot of work to make these conferences happen.

00:00:35.460 I’ve been sitting here all week watching the hat.

00:00:51.000 Let's thank Stacy! Yay!

00:00:57.859 Alright, so here I am. It's so unlikely that I would be here; I mean, I've been incredibly lucky—it's astonishing! What about you? Are you lucky?

00:01:15.290 Fortunately, luck is smiling on you. Do you think of it this way? I think about how I drove when I was sixteen, and I remember thinking how lucky I am to be alive. Look how well everything turned out! Or perhaps not so much; maybe you're unlucky. Maybe you were born under an evil sign, dragging that bad luck around like the flu, infecting everyone with it.

00:01:39.410 If you're unlucky, I have good news for you. It turns out that you can hack luck. This guy's name is Richard Wiseman. He's a psychologist at a university in the UK, and he did a 10-year study on luck. He wrote a paper about it.

00:01:53.910 What he did was solicit volunteers who thought of themselves as either lucky or unlucky, and he tried to figure out what differentiated those two groups. He found just four components to luck. The first is that lucky people pay attention; they're not caught up in their own stuff, so they look around and see opportunities for luck. The next is that they're open to experience; they listen to their intuition.

00:02:19.730 The third component is quite oddly self-referential: they expect to be lucky. They assume they're going to be lucky—there's a way in which they practice luck in their heads. Finally, lucky people tend to interpret the things that happen to them as if they were lucky.

00:02:38.090 Now, the first time I heard about this research was at a talk that Sarah Mae gave at a conference many years ago. Right after that talk, my partner and I went to Spain and took a self-guided bike tour. It turned out that the directions were really bad.

00:02:57.600 Every day, at the end of the day, we would have ridden 60 or 80 kilometers, and it would be getting dark and raining. We would be looking for our hotel, and we would just look at each other and say, 'Well, at least we're improving our luck.' It made the whole trip better; it was amazing how just that slight change in perspective changed how much we enjoyed the trip and how lucky we felt.

00:03:35.800 So, if we take these four components together, they suggest that you can make your own luck. Wiseman, after identifying these four things, took the unlucky people and taught them these concepts. They reported being luckier later.

00:03:46.690 Now, maybe you're already making your own luck. Certainly, it's true that you’re lucky to be here today. Think about that—how did you get to be in this room? Someone paid for you, or you got time off work, maybe your boss paid for it, or you paid for yourself. You got a hotel, and you’re eating, I'm assuming.

00:04:07.329 As a group, we programmers are incredibly lucky. I have some data from 2017, which I apologize for because it's mostly right, and it’s hard to get precise data about the things I’m about to talk about. I went into a dataset from 2017 and arbitrarily selected some categories of programming jobs that totaled 2.3 million people. The dataset showed that the median income in 2017 across all these jobs was $85,000.

00:04:39.789 Now, I think this is an underreporting. If you look at more recent data, you'll see numbers suggesting that programmers make, on average, around $100,000, and if you're a system developer, maybe $110,000. So, I'm going to take some liberties with this number and estimate it to be around $93,000 as a median.

00:05:05.560 Now, does anybody know the median income of the average worker in the United States? You’re probably making, or you will make, on average, three times the median salary of the average worker in the US. I picked this 2017 dataset because they broke it out by gender. So just to set the scene, with that 2.3 million, there were about 1.7 million men and around 600,000 women.

00:05:40.870 Now, it's reported this way because at the Bureau of Labor and Statistics, there are only two radio buttons. If we can believe that 390 out of every 100,000 humans are non-binary, this number probably in real life looks different. Now, I realize that 9,022 is a small number that you can barely see on that chart, but 9,000 people is a significant number and they deserve their own representation.

00:06:07.420 If we turn this into a percentage, and I made up some numbers for this conference based on data I gathered right before it sold out, I noticed something interesting: despite their enormous efforts and the great improvements women have made over the years, the number of women in tech seems to be going down. However, the number of people identifying as non-binary has increased.

00:06:45.450 So, sorry for the data that could be all wrong; a lot of people didn't answer that question, and I distributed those non-answers in proportion to male and female responses. I also assumed everyone who identified as non-binary was included in that category, so just consider that!

00:07:11.110 Now, let's look at ethnicity. This is 2019 data. Overall, it seems to indicate more diversity than is genuinely present. The bigger companies—Google, Microsoft, Facebook, Twitter—are more like 56% white and 37% Asian. So, some of those influential companies are less diverse than the overall group we have here.

00:07:43.930 So, I have income data. The median income for men was around $87,000, while for women it was about $79,000. For women in programming, that translates roughly to 90% of the median income achieved by men, which is significantly better than the general average across all jobs, where women earn about 80 cents on the dollar for men. So, we are seeing improvements, but the downside is that, in the normal world across all jobs, women hold about half of the positions but only 25% of programming jobs.

00:08:19.690 So, while we’re making more money, the ratio of women is still a problem. But there’s hope! Since I had all that data, of course, I thought about putting it into a Google spreadsheet and visualizing who got what piece of the pie.

00:08:48.510 If you break down the numbers by gender, you’ll see that men represent about 75% of the total workforce, yet they take home a disproportionate amount of the income. It turns out that white people generally get about 50% of all programmer salaries, and when you add Asians into the mix, those two categories account for about 80% of the total income.

00:09:30.440 Then the rest of the minor categories are so small that they didn’t even get room on the pie chart! So now, with all this data in mind, you have to ask yourself: who are the winners and losers here? But here's a question I often consider: if you were an outsider and you moved to the U.S. for a programming job, what demographic category would you choose?

00:10:06.160 You’d essentially choose to be a white male. From Wiseman's research, we know you can improve your luck, but you're pretty much stuck with your demographic. If you happen to be born into a higher-paying demographic, lucky you! But speaking of luck, let’s talk about the neighborhoods we’re born into.

00:10:25.930 It turns out your neighborhood matters a lot. Raj Chetty is a micro economist at Harvard who studies social mobility, which is how likely it is for someone to move up in income compared to their parents. He founded a center at Harvard called Opportunity Insights and developed a remarkable mapping tool.

00:10:46.490 They took anonymized data for twenty million people, gathering income tax returns and census data and created this comprehensive mapping tool. What it does is map data back to the census tract where people were born, with many options to dive deep into various factors and analyze how socioeconomic conditions influence outcomes.

00:11:33.180 They found that the performance outcomes for children born in neighborhoods that seem demographically similar can vary significantly. For example, places that are seemingly alike can have drastically different outcomes for the children raised there. This visualization shows that some areas have poor outcomes for children born there in the late 70s or early 80s.

00:12:04.500 Nashville, like the south in general, tends to have sadder outcomes. That said, if you look closely, the results aren’t random. In this map, we can see that the census tracts struggle significantly based on their socioeconomic conditions. It’s worth noting that places like South Dakota have comparable outcomes for their kids.

00:12:36.660 If you look at the areas where kids born in the late 70s and early 80s have faced adversity, they are often tied to the neighborhoods they grew up in. For example, I can zoom in on Los Angeles where significant differences arise. Here, you’ll see the current household income relative to low-income parents and the incarceration rates of black male children born to the lowest income parents.

00:13:12.000 Looking at the Watts neighborhood shows an astonishing difference in incarceration rates, contrasting just a couple of miles away. The district does have similar demographics, yet the difference in outcomes appears to be connected to features specific to the neighborhoods rather than the qualities of the people living there.

00:13:54.500 The American dream suggests that with enough hard work, success is possible irrespective of your beginnings. How often do you think this dream is realized? Chetty analyzed the data and determined that the chance of rising from the bottom of the income distribution in the US to the top is around 7.5%.

00:14:13.500 If you're born in the upper Midwest, it’s more like 14 or 15%. However, if you're born in the south, that's reduced to about 4 or 5%. There are places in the southeast, like Atlanta and Charlotte, that have experienced significant economic growth over the past two decades, yet the outcomes for children born to low-income parents there remain abysmal.

00:14:50.750 So, what really influences the outcomes for children? It turns out that neighborhoods where residents are segregated by income and race consistently lead to worse outcomes. The more segregated the neighborhoods, the less favorable the outcomes for the children, who will eventually pay taxes to finance things like Social Security.

00:15:16.600 It also appears that neighborhoods where family structures are intact perform better. To clarify, having two parents is not required for good outcomes; it’s more about the distribution of family types within the neighborhood.

00:15:31.340 Communities with higher social capital—where people know each other and are willing to help one another—achieve better results. Chetty estimated that if a low-income family could move from a low-upward mobility neighborhood to one with higher mobility, their child's lifetime earnings could increase by $260,000.

00:16:24.800 Some cities, like Detroit and Seattle, are currently conducting experiments where they assist low-income individuals with moving to higher-opportunity neighborhoods by offering Section 8 vouchers to overcome the barriers preventing that movement. If you’re considering relocating, you should definitely check out the Chetty map to find the neighborhoods best suited for children.

00:16:52.639 But it’s essential to acknowledge that neighborhoods don’t affect everyone equally. Chetty’s research indicates that black boys and white boys growing up in similar neighborhoods with families earning similar incomes have different experiences—with black boys having significantly less upward mobility.

00:17:24.860 Also, affluent black families face a higher risk of downward mobility. Chetty describes a disparity, indicating that white families are on a ladder of prosperity while black families are on a treadmill, where it's easy to fall off.

00:18:03.000 The neighborhood you’re born into has a lot to do with your outcomes. It may influence success even more than your parents do. However, gender and race still pose significant barriers.

00:18:34.020 I grew up in Randolph, West Virginia. My father, who was dyslexic, had a tough time in school. Frustrated, he left school and joined the Army. After boot camp, he met my mother, and they eventually married. They lived humbly, transitioning from struggling to thriving through a combination of hard work and opportunities that arose.

00:19:27.520 Over the years, my father decided to find better-paying work, in the process gaining skills that would allow him to support our family well. They moved into a neighborhood with affordable housing, where the mortgage rate was comparatively low and facilitated by programs aimed at helping working families.

00:20:10.890 I grew up witnessing the struggles of family life and following their journey up the socioeconomic ladder. So, the Chetty map of Parkersburg, where I lived, shows that the current median household income for female children who grew up there is around $40,000 per year.

00:21:10.730 This means my success is significant relative to the other women who lived in that area. My parents were genuinely successful compared to their parents, and their gradual ascent within the income distribution started with home ownership.

00:21:59.540 Home ownership plays a vital role in wealth accumulation and its effects are felt for generations. However, there’s still a substantial gap in home ownership by race—rooted in historical injustices.

00:22:45.580 In 1865, President Lincoln set aside land for former slaves, and in a twist, a year later, President Johnson reversed it. Following that, systematic barriers blocked many blacks from accumulating property. The result was that on the eve of the Great Depression, most blacks, having only recently emerged from generations of servitude, still did not own property.

00:23:32.480 After the Great Depression, as the U.S. government sought to help stimulate housing, new policies encouraged home ownership, but they maintained discriminatory practices favoring white communities. Redlining developed, whereby neighborhoods with black residents were marked as risky.

00:24:28.460 When they mapped these neighborhoods, those graded like D—whether economically sound or not—could not receive loans. It essentially forced black families into renting while whites were pushed along the highway of prosperity via home ownership.

00:25:26.150 The redlining practice had profound effects, and it escalated after the Great Depression. Eventually, the social and economic ramifications have reached into the present, with those neighborhoods’ historical designs still shaping our social fabric.

00:25:56.490 Now, encountering outdated maps of redlining shows a significant echo today. The maps align with Chetty's current data, demonstrating that past decisions on housing and finance have lasting effects. Further deviations from these maps occur due to systemic changes.

00:26:43.530 In the 60s, urban renewal projects disregarded thriving neighborhoods in favor of transportation routes for urban expansion. The educational system, too, suffered from white flight—white families moved out of the areas where desegregation occurred, leaving the remaining schools without adequate resources.

00:27:28.100 With only minor diversions to the neighborhood maps, the legacies of inequality are evident. Today, 85% of residents in neighborhoods once graded A are enjoying a middle to upper-level income,

00:28:04.690 while those regions that were more heavily redlined are predominantly low-income neighborhoods.

00:28:50.600 This snapshot reflects not only systemic racial issues but also the deeply entrenched matters surrounding education. Schools that are funded through property taxes disadvantage low-income areas due to their inability to accumulate wealth.

00:29:36.460 When districts are segregated, those in cities with high concentrations of poverty disproportionately have access to lower-quality educational resources, while wealthier districts can provide their children with a superior education.

00:30:22.120 As my partner learned while evaluating a school in Louisiana, conditions in many schools are deplorable. Schools with failing roofs and leaking structures reflect distress, hindering any potential for growth in children who learn there.

00:31:10.390 The dismissal of labor unions has also led to a significant reduction in workers’ power to advocate for better wages. This is reflected in the minimum wage, where current projections for living expenses demonstrate that the minimum wage in comparison to the cost of living has not kept up.

00:31:56.750 Healthcare disparities further compound these issues; we spend more on healthcare without providing the same outcomes. The reality is a reality where a household can face bankruptcy due to medical expenses within the same report that states the median income is dropping.

00:32:35.780 The gap regarding educational access ties into a bigger issue; privatization of education creates less opportunity for people to pursue their goals without accumulating debt, transforming their prospects for wealth and stability.

00:33:11.850 Housing, education, and health are interconnected systems that require comprehensive solutions aimed at addressing the underlying issues rather than patching up the outputs. Over the years, these systems have solidified a society split into winners and losers.

00:34:02.180 The alarming concentration of wealth reveals that the upswing favors a particular demographic. It’s no coincidence that wealth has become deeply entrenched within one upper circle while pushing many into poorer conditions.

00:34:33.620 As wealth becomes synonymous with competency and intelligence, it easily leads to the erroneous conclusion that personal efforts alone account for success. Those who are at the top while overlooking the systemic barriers contributing to their achievements will often miss the fundamental aspects of the system.

00:35:03.600 This blind spot often influences their decisions; rather than using their privilege to advocate for systematic changes, they pour money into short-lived charitable initiatives. It's essential to remember that the super-wealthy benefit from systems in place that protect their interests.

00:35:43.110 Policy proposals from the elite often emphasize giving back, but true change requires them to consider how they can alter systems leading to inequality. It's vital to shift towards empowering communities while reallocating power back to those who understand their plight.

00:36:25.750 Now, I can’t help but reflect on my own privilege and prosperity. The marked divergence between my background and many others illustrates how much of this is baked into the structure long before we arrived at our conclusions and choices.

00:37:11.740 I felt fortunate, thinking that my own hard work earned me my position, but research has shown me that much of it also comes down to the systemic issues around us.

00:37:47.200 As I conclude, I want to extend an apology for the world we are leaving behind. It's not your fault, but it's upon you to do something about it. So, what can you do? First, prepare yourself for the uncomfortable truth around complicity. It's a revealing experience.

00:38:35.200 Then give back! If you have the means, amplify your charitable efforts, but recognize that the focus must also shift towards addressing the core issues. Solutions need to be public, democratic, and institutional.

00:39:19.890 You are capable of creating meaningful changes in governance. The government can serve as an instrument of good when it addresses wealth disparity. Passing legislative reforms that strengthen the middle class is also essential, along with housing programs that genuinely aim to address homeowner costs.

00:39:54.250 Confront the history of inequality as a slave nation and consider the implications of reparations. Empower yours and others’ voices to help balance the pervasive inequities rampant within our current form of capitalism.

00:40:40.390 Lastly, we must urgently address climate change. You represent the brightest minds, and it’s imperative that we rally for these systemic changes that serve everyone. We can't simply rely on fate or chance.

00:41:22.490 While I wished to reflect on personal luck and hard work, through this investigation, I could not ignore the underlying issues at play or the biases inherent in systems as they exist.

00:41:53.720 We've arrived at a critical moment where outcomes still skew heavily based on race, class, and historic injustice, but we must advocate for systemic reform in the way we think about opportunity and success.

00:42:26.510 So, there is hope, albeit with hard work ahead. It depends on you to work to build a world that is fair for everyone. Actively engaging in these systemic updates is essential for future generations.

00:43:07.920 Start thinking about what steps you can take to build a more viable future, not just for yourself, but for everyone.

00:43:30.163 Thank you.

See Slides on speakerdeck.com