Edition 11: My Family's Slave
Also, why you need to spend more money, and why you can't always trust data
Election week is here. Though it’ll take days, if not weeks, for the final result to be announced, nothing less than the survival of the entire American experiment is at stake. If you haven’t voted yet, now is the time to make yourself heard. Then, take some time to unwind - as we round the corner to the final months of an unbelievably exhausting year, our collective mental health is stretched as never before. Since the weather’s been nice lately, I’ve been trying to incorporate a nice long walk into my daily routine to get a bit of peace.
Passing by the Land’s End labyrinth - a maze of rocks set up by local artists.
On to today’s edition:
Also available to read in Chinese
Admitting the truth would have meant exposing us all. We spent our first decade in the country learning the ways of the new land and trying to fit in. Having a slave did not fit. Having a slave gave me grave doubts about what kind of people we were, what kind of place we came from. Whether we deserved to be accepted. I was ashamed of it all, including my complicity. Didn’t I eat the food she cooked, and wear the clothes she washed and ironed and hung in the closet? But losing her would have been devastating.
Let me start by saying: you have to read this story. No quote or summary will do it justice.
Having hired “help” in the family is fairly common among Asian households, particularly in Asia where income inequality is high and labor is particularly cheap. The lives of such laborers are never easy, but it is still an occupation of sorts: a means to get by and send money back to the even more destitute.
Not so for the terribly unfortunate people who are victims of modern day slavery, a rung lower than indentured servitude that persists, perniciously, out of sight in a world where slavery is an evil defeated, where such conditions could no longer exist.
The author tells the story of Lola, his family’s slave, who was given to his mother as a “gift”, becoming an indispensable yet ostracized and hidden member of his family. This incredibly emotional, deeply troubling piece also offers moments of hope, not for Lola’s freedom but for her ability to adapt to the terrible hand she was dealt early in life.
I’m continually blown away by the sheer magnitude of human resilience, of people’s ability to persevere, and even to suffer in silence and live on knowing things may never get better. There is a quiet, tragic dignity in Lola’s existence that is distinctly and beautifully human. This is a deeply personal tale of one family’s dark secret, but the characters and traits feel universal in a way - this is a story of struggling to make ends meet in a foreign world, a struggle for identity and purpose, and a story about loved ones above all.
All this threatens to make Chetty’s work much more difficult. The American dream is dead, as he’d proved with exhaustive government data showing today’s workers can no longer expect to earn more than their parents did. Now those left behind by the economic changes of the past few decades could be robbed of any remaining opportunities to get ahead.
This Bloomberg piece is part bio on Raj Chetty, Harvard economist and data wizard, and part coverage on the dual divergence in earning and spending between the haves and have-nots of America. All data is sourced from https://tracktherecovery.org/, a website wherein Chetty and team are regularly delivering updates on the state of the economic recovery (or lack thereof).
At a glance, as one might expect, things are not great.
As has been widely reported, high wage employment (also benefitting from the opportunity to do remote work) has largely bounced back to pre-pandemic levels. “Essential” low-employment work has a ways to go.
In this chart, the green line represents spending by high earners, and the pink line spending by lower earners. While low income spending has actually returned to pre-pandemic levels, high earners are notably spending less than before. As they withhold discretionary purchasing power, small and local businesses (which often employ blue collar low earners) are disproportionately hurt.
We had a brush with a liquidity crisis back in March, and now a solvency crisis for small businesses is upon is. If spending doesn’t resume to levels that can sustain local economies, a downward spiral triggering small businesses closures and job losses could result in a further economic downturn.
This all points to rougher times ahead, but there’s something we as higher earners can do, which is to inject our own money to the businesses that need it most. Shop small, shop local, and tip for takeout. While the pandemic will continue to affect certain businesses more than others, any amount of spending is better than none.
There is a new form of consumption that has taken over our lives: dashboards, tracking everything from the spread of COVID to election polling projections, from our financial wellness to our fitness.
In this data-driven world, dashboards are the inescapable, ultimate way of ingesting information at a glance. Just as car dashboards quickly tell us what we need to know (how fast you’re going, how much gas you have left), we rely on digital dashboards to make sense of our environment and even ourselves. Is this reliance becoming over-reliance?
This article details a some common fallacies that we run into when we trust what dashboards are telling us at face value. For example:
Garbage in, garbage out. Data is only as trustworthy as its source, and a dashboard with missing or intentionally obscured data will lead to misleading conclusions.
Dashboards privilege certain data types. Dashboards favor quantitative metrics and immediate indicators, meaning the nuance of effects over time, or effects on complicated subjects (like mental health) may be lost.
Dashboards reflect the creator’s intentions. Given purposeful inclusion and presentation of data, a dashboard (or any collection of data) is by definition never unbiased.
Dashboards elide caution. By standardizing the appearance of metrics, dashboards can mistakenly oversimplify or downsize information worthy of special caution.
The illusion of being informed. The average citizen poring over Covid dashboards in March and April had no idea if the visualizations were accurate, current or comparable - and rarely do politicians. And yet, politicians (and others in power) often act on this information as if it were a reliable source by default.
The article contains many more of such examples. That’s not to say that dashboards and data collection are bad - even when imperfect, they are usually a force for good.
Higher transparency and clarity are always beneficial. What’s also beneficial is a healthy dose of caution, even skepticism, especially as we get into these Presidential elections. Check multiple vetted sources and trust your judgment. Just as light bends in water, the truth bends in data.