when the asian is good at math

The numbers are in, and they add up - I'm good at math. I'm also Asian, which might create a problem for you readers out there who've done your homework regarding stereotypes, and the ever-revising standards of political correctness - isn't it problematic to praise me for my math skills? The thinking is that even a positive stereotype reinforces the notion about categorizations being tied to certain abilities. There is a temptation to skirt around the edges of such matters, with perhaps the bravest among us dipping a toe into the water and reporting back to the rest - it's complicated (1). Let me try to simplify the equation. The thing you need to know about me is that I am good at math because I grew up doing a lot of math. I'm not sure if my work rate placed me in the 90th or 95th or 99th percentile in global terms, but as it relates to anyone I met before college I was one of the top two or three hardest workers. I didn't do this alone - there was a lot of support from my parents and a few committed teachers, but the net effect of this support was mostly to get me to do more work, including over the summer and as a part of my hobbies. If you understand this story, you are now free to tell me how good I am at math.

So, I've made this a simple situation - if you know why I am good at math, you can tell me I'm good at math. When I generalize the conclusion, it suggests that if you know why someone is good at something, you can tell them they are good at it even if it reinforces an underlying stereotype. The catch is that this requires effort - just as I had to work on my math skills, you have to work to understand the roots of someone's ability. When I got to college, I met another Asian, and he was far better at math than me. He was also more Asian, to the extent that he grew up in Asia, so I must have wondered. But if there ever was a mystery regarding his superiority in math, I must have solved it from working together on a problem set, or from a late-night observation walking past his table at the library, or perhaps I got the clues from his roommate - he was better at math than me because he worked harder on math than me. Life, like math, can be simple, but you have to work on it until you can work it out.

The problem with the "positive stereotype" - like the Asian who is good at math - seems on the surface a little different from the problem of the more sinister variant - like the Asian is the coronavirus. Frankly, the positive version doesn't seem like a problem to some people, just as it once didn't seem like much of a problem to me. But I came around to the realization that a stereotype is a stereotype, whether it reinforces a positive quality or otherwise, because at the core of any stereotype is a refusal to learn about someone else. A positive stereotype is like winning your bet at the roulette table - the reward obscures the fact that if you keep doing the same thing, you are going to lose. If you think Asians are good at math, then each Asian you meet who happens to be good at math is going to make you feel a bit more confident about beating the house. I can't use this fact to predict exactly what you'll think about the next Asian person you meet, but my bet is that you'll repeat your process, the low-effort approach of associations and assumptions, which means your next thought won't have much to do with this person at all, though of course it will be projected onto him or her. It's only a matter of time before you get it wrong, and though we can hope that no one else is harmed by your slothful thinking, my experience suggests otherwise.

When people have made mistakes about me, it seems that they assumed I would speak, behave, or respond in some way consistent with the stereotypes ascribed to a broader descriptor - male, athlete, Asian, cyclist, bachelor, millennial, reader, Bostonian, it goes on; the perplexing thing is how often this happens with people who already know me beyond these categories. I think the reason has something to do with how much effort it takes to replace an initial impression with a personalized explanation, an effort that seems increasingly unreasonable each time our gut instinct proves its prescience. It's a desire for efficiency, and as a math guy I can speak to the value of efficiency, but when it comes to relating to other people I don't consider efficiency a very important factor. Do you think back fondly on your favorite people and say - you know, those people were great, they were so efficient with me? The argument for efficiency is that it saves time and effort, but those happen to be key ingredients for building strong relationships, and absolutely essential for their maintenance and reinforcement. The positive stereotype trades these commodities for efficiency, which is like refusing to throw the ball during a game of catch so that everyone can save their energy. Why make the effort to start if you can't make the effort to keep going? Maybe it's easier this way, to live out our assigned roles rather than risk discovering what we never knew about each other, but I don't think it adds up.

Footnotes

1) It's so complicated that I actually found something helpful on NPR. I think it's a good overview of all the factors in the situation as perceived from various perspectives, but I would offer one revision for the flimsy final sentence - instead of turning the conclusion outward, point it at the readers and remind them that the people who use stereotypes are the ones who are failing. 

the business bro's math of innovation is fifteen percent correct

It's bizarre the way busy business bros make time to talk about innovation - how much they like it, that they believe in it, that they consider themselves innovators, and possibly even inventors, though of course their only recent invention is this fresh charade of self-delusion; busy people don't have time for innovation. It sounds like one of those ancient riddles - if your entire day is allocated to predetermined tasks, how much time is left for new pursuits? I suspect this logic was at the foundation of 3M starting "15 percent time", a program which encourages employees to "set aside a portion of their work time to proactively cultivate and pursue innovative ideas that excite them." If there isn't time for innovation, then the only solution - or at least the initial step - is to make time for innovation. This style of programmatic thinking is not limited solely to 3M, and there are many more successes from this approach than just the famous example of the Post-It note - loyal TOA subscribers reading this on Gmail should pause for a moment in acknowledgement of the email service having been developed during Google's variant of the concept (cleverly renamed "20 percent time" by the tech giant, perhaps to disguise its roots). But the existence of these programs is the exception rather than the rule in most organizations.

The situation concerns me because my experience suggests that innovation is beyond the reach of most organizations, whose leaders seem to think innovation is the result of little more than sporadic votes of confidence. One reality shared across the different roles I've held in three organizations has been the proliferation of busy business bros who allocate every hour of staff time to an existing concern, the frenzy of short-term directives occasionally being interrupted long enough for them to insist - yes yes, we're open to change, invention, and progress. The actions always spoke louder than the words, or at least it was in my case, as I've found over the years that my various attempts at innovation would generally be met with a range of reactions ranging from indifference to open hostility, but rarely support. It reminds me of something Michael Lombardi said on an episode of The GM Shuffle podcast - if you think someone is smart, you should be able to list off two or three specific things about this person that support your position. When I think back to leaders I've worked with who spoke in grand terms about their commitment to innovation, it strikes me that not a single one of them said - here are two or three specific things I've done that demonstrate my commitment. Instead, they always spoke of their intangible qualities, like dedication to the cause; sometimes they wrote checks for future creativity that would have bounced at the patent office.

The temptation is to conclude that organizational behaviors reflect the natural human tendency to crave the familiar and the routine over the unknown. I remain open to the possibility that the business bros of my past feared change at a visceral level and tailored their managerial philosophies such that the status quo could reliably protect them from the horror of tomorrow, this terror being their only certainty regarding the otherwise unknowable future. However, the issue with this conclusion is that there were always certain instances where the gatekeepers would relent in the face of new evidence. In my first managerial role, I could never implement an official work from home program for my team, but working from home was otherwise permitted for a wide range of exceptions including my six weeks on crutches, anyone who moved out of state, or a violent case of the common cold; I was almost fired from another job for trying to automate a certain process using SQL, but a few months later a similar project was assigned to me as a top priority. I am sure millions of workers have asked at some point during the past year - why did it require a worldwide pandemic for our organization to embrace virtual collaboration?

I am intrigued by the possibility that failures to lead innovation are less about business bros being afraid of the unknown and more about them ignoring the underlying math, which in my mind always demonstrates the return on innovation. The example of the COVID-19 pandemic is especially intriguing to this point as almost all employers with the capability shifted to remote work, seemingly overnight, in a mass admission of the new cost-benefit equation. I suspect prior to this moment many organizations existed much like my own, where there was a clear divide between junior and senior management in terms of each group's belief regarding the benefit of widespread remote working arrangements. In fact, my current organization - which years ago grudgingly permitted senior staff to work from home for one day a week, assuming of course that the staff member in question met a long list of additional criteria, a checklist that covered at least one printed page and included critical reminders such as "staff may be asked to attend key meetings in person on their work from home day", this document a testament to the tireless work that addressed every risk associated with one butt being out of one seat for one day a week - this organization of mine suddenly found its entire roster logging into Zoom meetings from home, a transition period that lasted all of three days; there is no official verdict at the time of writing, but all signs point to this being a permanent arrangement, due mostly to the success of the past year. The mentality change, it should go without saying, was due to the sudden mortal risk of riding the Green Line to the office, which convinced everyone that 2019's reservations over working from home suddenly represented trivial concerns in the larger context of the advantages of remote working considerations.

If you strip away the buzzwords that litter certain TED Talks about innovation, I suspect you'll find that the truth underpinning programs like "15 percent time" is the same as for any other successful business practice - the balance of costs and benefits associated with the approach is beneficial to the company. This is crucial because the business bros who hide their fear of change by keeping everyone busy may find a cost-benefit approach more convincing, as many did when COVID-19 simplified the calculus of working from home - after all, the only consistent truth about business bros is that, given two numbers, they will cleverly steer their organizations toward the more beneficial of the figures. I suppose the logical conclusion, then, is to explain the math of innovation in the simplistic terms necessary for allowing a busy business bro to see the benefit. I usually refer to this as "managerial math" and the concept is simple - you have to figure out if the innovation has a profit, just as you would do in building the case for any other business plan.

I'll use the example of innovation through coaching to highlight this idea. The math involves accounting for the following - on the cost side, I consider the time I spend coaching, the time a colleague spends learning, the opportunity cost to both coach and colleague, and the possibility of allocating resources in the future to repair errors associated with misusing the new technique; on the benefits side, I tally the time saved from reapplying the new skill across future iterations, the direct cost savings or revenue gains of a new approach, and the possibility of inspiring colleagues to pursue additional training. I'm comfortable estimating these aspects of the equation but those concerned of painting with broad brushstrokes are advised to incorporate a comfortable margin that protects against this risk - for example, only proceed if benefits exceed cost by over 10%.

Below is one calculation using a situation from a few years ago - I was considering an email to a large group which would explain a trick I thought they could use in Excel files. I came up with the following estimates:

Costs (known)

• Time to draft email: one hour
• Cost - one hour of my salary
• Time to read email: one hour (sixty colleagues, half will delete or ignore, two minutes each for the thirty who read the email)
• Cost - one hour of aggregate salary among sixty total (thirty responsive) colleagues

Costs (unknown)

• Fixing future errors
• Opportunity cost of writing/reading email

Benefits (known)

• One percent annual efficiency for three colleagues
• Response rate to email: three colleagues (assuming ten percent read and respond)
• Time saved in Excel: three hours (one hour per colleague based on one hundred total Excel hours in a year)

Benefits (unknown)

• Colleagues develop curiosity and proactively pursue additional skills

In other words, by writing out the email, I figured it would cost us two hours with certainty in terms of my time plus the time thirty colleagues spent reading the email. In addition, there was an unknown risk associated with someone screwing up the concept and making a mess of an existing file or process. I expected a one percent efficiency increase for the three colleagues that ultimately read and applied the email, with each of those three saving one hour per year based on an estimate that they spent one hundred hours each year using Excel. As it was on the cost side, I also noted the possible gain of these three colleagues choosing to pursue additional skill development opportunities based on this exposure to a new technique. The stated numbers give a clear verdict - three hours of gain for two hours of cost, so writing the email was a great use of my time - a 50% return on the overall investment.

If I think back to the various supervisors and managers from my three different career stops, I would estimate 100% of them would pursue any opportunity with a 50% return, with that morning's original priorities relegated to secondary status with immediate effect. However, there is a catch - I'm fairly certain not a single one of them would agree that my spending an hour on an instructional email demonstrated a good use of my time, even if I used my above calculation to demonstrate the error in the rebuttal. It could be due to any number of factors, with the most likely being a dispute over my assumptions, but the key is that the specific nature of the dispute doesn't matter because each moment spent in additional discussion adds to the cost side of the above calculation. If the process of making my case takes up a half-hour of work for two people, then the stated benefit in the math is wiped away - it's now three hours of cost for three hours of benefit; effectively, any business bro who filibusters through a presentation of managerial math is strengthening the objection through the cost associated with the act of objecting.

There could also be an outright refusal to consider the managerial math, which is a problem in its own way, but I think the underlying objection in such a case follows a track that I'm quite familiar with from experience - they would point out that my hour writing the email meant an hour lost for a different priority. It would likely be implied at this point that seeing as how the superior set the priorities to begin with, the eventual conclusion of any discussion was destined to affirm the superior's original set of objectives; the battle ahead of me to change existing priorities promised to be bloody, and forever uphill, with pyrrhic victory representing the closest thing to a positive outcome. This is the worst form of objection to innovation in my mind because most mediocre managers actually think they are asking a smart question - if you do this, what do you have to stop doing? It never occurs to them that questions like this often hold back innovation.

I actually encountered an endorsement of this question recently in a mediocre management book, which should have been named Good But Not Great Questions for Good But Not Great Managers. It sounds good, this question - if you do this, what do you have to stop doing? - but it imposes an unnecessary scarcity consideration onto the topic of innovation, which is inappropriate given that new thinking lives on the infinite side of known boundaries. If I think about how to ask this question without shoehorning the scarcity mentality, I end up with a superior question - why aren't we already doing this? I suppose an alternate formation offers a similar upside - when else can we do this? The power of a program like "15 percent time" is obvious when considering these reframed versions of the merely good question - if you do this, what do you have to stop doing? The answer lies in the inverse - if we don't do this, then we don't innovate. As noted above, it's also often the case that small innovations lose their marginal return in the course of prolonged discussion, debate, or justification. The unspoken value of a program like "15 percent time" is that it should eliminate the need for these questions - there is no discussion required when the employee is encouraged to direct time toward projects that have the faintest hint of innovation. In the context of the coaching example from above, it's also worth noting that the response rate to such an email might improve if those colleagues felt like working on the skill was an acceptable use of their "15 percent time", which is yet another possible benefit to such a program - it creates time to pursue meaningful learning opportunities.

This leads me to my overall point, which is that the biggest barrier for innovation in most cases is talking about it - by definition, innovation is about discovery within the unknown, and I don't consider the unknown among those topics which invite intelligent discourse. Even the managerial math that I outlined above, compelling though it may be in certain cases, seems like it does more harm than good in the way it suggests the possibility of a knowing conversation about an unknowable subject. The only way an organization can demonstrate a commitment to innovation is to set as many of its people as possible to the task, which of course means all of them, and to set them to the task in a way that eliminates any and all known barriers to innovation. I believe a program like "15 percent time" helps move an organization closer to innovation, but in some ways I find the broad definition from 3M ("pursue innovative ideas") too narrow for my tastes. I recommend a variant of this program that encourages employees to use time in a self-directed manner, even if it's as little as 5 or 10 percent, with the only requirement being the self-belief that the activity will someday help the organization. I would clarify that this includes personal and professional development projects, and for organizations that do not allow for remote work I would even recommend allowing "offsite" time to count within the parameters of this program; I would allow anything that did not attract the notice of the local police. I suggest such extremes because ultimately innovation comes down to one necessary ingredient, time, which means a policy whose administrative requirements take time away from itself is self-defeating -  the moment people busy themselves with justifications, the program itself has become the obstacle; busy people don't have time for innovation.

proper corona admin, vol 87 - college logic

I remember being surprised when I found out I could take logic as a college course. Logic was pretty simple as far as I was concerned. What next, a major in common sense? I could see where logic might be useful, like the way memorizing the periodic table could help in chemistry, but no one ever explained to me why it might fit a liberal arts curriculum.

I look back and realize my problem - I was just a kid. Or I should say, I wasn't an adult, which meant I had never lived in the real world. My bubble kept me blissfully unaware of the atrophied state of public logic, which lowered the standard for making reasoned arguments. The president himself goes on stage and suggests increased COVID testing leads inevitably to increased COVID prevalence; it passes for logic in this country.

put up the house and bet the odds

It's Friday afternoon, and like many Americans - like many people, probably - I've spent the past few days pulling in election analysis from an eclectic set of sources: network news, the FiveThirtyEight live blog, people calling and texting; each new update had an undeniable effect, though generally very small, on my mood at the time. But if I think about the source that had the strongest influence over me, there's only one possibility - the betting odds, which I tracked across a handful of European markets. It was a bit of a roller coaster - Biden started on Tuesday at around 65%, which doesn't strictly equate to a 65% chance of victory (but thinking of it in those terms is appropriate for the context of this piece). Later that night, Trump jumped up to almost 75% at 10 PM (EST) as Ohio and Florida cleared their throats, then Biden clawed back to almost even by around 1 AM for the lack of other surprises, which is when I finally called it a night. I learned the next morning that Trump had actually surged past 70% again at around 3 AM, but by the time I saw it news from Wisconsin and Michigan had pushed Biden above 70%, saving me the trouble of worrying about Trump's brief rally. As you know, Biden's looked more likely to win with each passing day; he's at 95% at time of writing.

I think my undergraduate background in statistics coupled with my lifetime interest in sports - and perhaps the occasional winner I've cashed at the Keno desk - predispose me toward accepting the betting market as the most reliable source of real-time election analysis. But when I share this preference, I'm often met with confusion - what makes someone putting up the odds or betting the house more reliable than a news network, or a pollster? It's been an interesting experience trying to answer this question, almost like being asked to explain my positions on certain issues, like ending racism; it's hard to explain what we take for granted. My standard responses have included attempts to describe a variety of related factors - the underlying science of probability, the nature of betting markets, or the inability of media coverage to correctly link cause and effect.

I realized last night - while listening to complaints about certain networks calling Arizona too early - that I should have offered a far simpler answer: the betting markets work because there are consequences for being wrong. A person who wagers $100 on an election outcome ends up with one of two results - more than $100, or $0. Which of those outcomes do you think is more likely to result in another bet? The far more straightforward consideration is that casinos go out of business very quickly if the oddsmakers set ill-advised betting lines. On the other hand, if Fox News turns out to be wrong about its early Arizona call, will they be banned from covering the 2024 election?

These considerations alone ensure nothing, but it's suggestive of the type of person who prefers to wager on an outcome rather than speculate endlessly on camera about all remaining possibilities. The confident bettor is also more likely to wager large amounts, and dollar totals are reflected in the odds (with wagers, unlike in an election, the tally is almost always irrelevant). The betting market of my imagination likely has no time for the faces that filled my screens this past week, these pundits who earnestly analyze the results in real-time and weave the newest event into an ever-evolving web of predictions. It didn't take long to realize the same people who were wrong four years ago were back to explain why they were wrong again; you'd be forgiven for thinking the media operated like the Supreme Court, and offered lifetime appointments. 

I don't blame the media for the state of election analysis (I have other media complaints, which I'm saving for later). I certainly don't blame any individual within the media for the state of election analysis, even if some of them - like the pollsters - should probably know better, having been burned once by their pie charts in the sky. I believe the media is doing the best it can as it covers an endlessly complex story, which is essentially a series of fifty counting exercises that is confused by the countless ways each next vote can count, or when, and that's assuming they count at all, and then of course the question of whether we can count on those folks who would rather count ballots than count votes, and then this all leads to a final count being tracked simultaneously to the smaller counts, which is what really counts; I just don't think it's possible to cover this adequately, like a five-foot blanket on a six-foot man. But it's important to me that I understand the system of incentives and consequences that contextualize someone's opinion because I'll know what's at stake; the architect can tell me the bridge is sound, but I'd much rather he cross first.

leftovers - reading review, what if (math at scale)

I noted last week that understanding scale spoke better to math skills than being able to compute sums. In an election year, it's particularly valuable. I heard Biden speaking the other day about "billions and billions of dollars", it sounded quite Trump-like, but if you understand that our country has around 330 million people, you learn to hear that as "hundreds and hundreds of dollars per person" which in the sense of policy doesn't seem like very much.

The federal debt is another story, but again one better told with per-capita numbers - we're around $82K each for one year, which is just under the median income. That seems like a better way to think about it than all the other metrics posted by websites like US debt clock, which seem interested only in alarming us under the guise of providing information.

eight grand is thirteen bucks

I saw an interesting story last week - Russell Westbrook, star guard for the Houston Rockets, left an $8K tip for hotel staff as he left the NBA bubble. This was a serious gesture of gratitude and generosity, and before I stick my tongue in cheek I want to point out that eight grand is always eight grand; it changed lives, and those lives were changed by Russell Westbrook.

But we here at TOA, sometimes we can't help ourselves, at least when it comes to the numbers, because some things are better understood in a personalized context. So I had to ask myself, what is an $8K tip for the True On Average Joe?

I started with Westbrook's annual salary - $38.5M for this season. Then, I calculated the proportion of his salary that was represented by his tip - 0.00021%. I came up with the following figures based on a series of True On Average Joe salaries:

• $7,500 annual salary
• You would pay $750 income tax on this amount
• Tip - $1.58 
• $12,760 annual salary
• Federal poverty level
• Tip - $4.20
• $61,937 annual salary
• Median household income in the US
• Tip - $13.01

Thirteen bucks, for the average American! And those figures aren't even adjusted for the bubble lasting months. I'm not here to pat my own ass, but even in 2020 I've left larger tips (in proportion to my salary) - for a one-off concern like takeout.

So what's my point? It's not to suggest anything about Westbrook - he's one of the NBA's great examples of giving back, and the work he's done for his community through his foundation speaks to his immeasurable off-court impact. But maybe it's better to highlight those accomplishments, which would demonstrate a more significant truth to how Westbrook changes lives, rather than settling once again for the distraction of fluttering dollar bills or glittering silver coins; our adulation of money, even in a legitimate sense, only makes it all the easier for frauds and phonies to flash wads of bills as they fake their way into power. Or maybe we should merely be consistent - the next time the president leaves a $3 tip, we should all applaud, and toast the man whose generosity is twice that of certain NBA superstars.

false on average (the running average deficit)

Those who read TOA with one eye on the abacus will have surely noted an odd phenomenon - despite my claim that this blog produces an average of 300 words a day, the true 'on average' (!) number is always going to be higher (1).

Like with any accounting trick, there are a couple of ways to demonstrate the reality. Let's say I post a 900 word essay every three days. One stat is the running average - see below (an asterisk (*) denotes a new post):

*Day 1 - 900 words per day
Day 2 - 450 words per day
Day 3 - 300 words per day
*Day 4 - 450 words per day
Day 5 - 360 words per day
Day 6 - 300 words per day

The budget method looks like this:

*Day 1 - +600 words
Day 2 - +300 words
Day 3 - on budget
*Day 4 - +600 words
Day 5 - +300 budget
Day 6 - on budget

Both methods tell the same story, but which is better? I think it depends on the context. I prefer running averages if I'm using the information as one factor among many in a decision. For example, I use running averages to track my writing time, and I try to prioritize writing if the average falls below my goal of 90 minutes per day. But this is only a guide, it's not like I cancel all my plans so I can write like mad anytime my average drops below the target because decisions about writing include too many other factors. If it's 1AM and I'm tired, I have to go to bed regardless of the suggestions made by my writing metrics.

The budget method is better for the TOA word count because my main concern is tracking reader workload. The budget speaks in the language of accumulated reader fatigue at the start of the next post and the metric helps me understand the appropriate length. I'm currently massively above budget (a shade over 2000 words) so it's probably going to be two posts per week until I'm back under budget.

I don't think most people worry too much about the relative strengths and weaknesses of budgets and running averages, but I highly encourage taking a moment to reflect on the most appropriate method. A budget is ideal if you allow it to dictate quick adjustments to your plan, but if you are going to stick to the course then perhaps a running average paints a better picture.

Footnotes / endnotes

0. TLDR...

Casino gamblers 'budget' by leaving the debit card at home - once the cash is gone, the night is over.

1. This post increased the TOA budget deficit by 125 - we're 2300 words in the red since May 31.

This doesn't even consider my accounting principles, which include 'buy one get one' Sundays and only counting posts if they exceed one hundred and fifty words.