Benn, great post. My degree at UCLA was in economics and, as a tech CTO, I've used my skills in logic, reasoning and writing infinitely more than math. I have 2 sons pursuing a career in computer science and I take issue with their math-heavy curriculum. Our industry's over-rotation on math discourages a whole population from considering a career in CS and under prepares those who do for life in the real world.

Benn, excellent article; one which describes how I arrived in math from a desire to be a history professor. My parents were convinced that I would starve in my desired profession, and they had the means to enforce their beliefs. By my SAT and National Merit scores (there used to be separate tests), I was equally competent, and proved to be so. They were, sadly, correct! Far better to explain the outcomes of relatively simple math to those who were afraid of symbols, than to change an engineer's mind, even (maybe especially) when they were wrong. I can now enjoy my retirement in the knowledge that I can figure out a plausible answer to current problems/questions across a broad spectrum, and have the ability to see the flaws in the arguments of the many poltroons and idealogical statisticians among us. And I am still prepared to learn from real experts. Including about fishing and cooking.

I'm a mathematician (MS in applied math) turned data scientist. The biggest benefit to me of going further in math wasn't learning the "advanced methods." It was everything else: how to structure an argument; the humbling experience of often being wrong; the importance of definitions and clear terminology; and, yes, written and verbal communication, because I had to teach a course, write papers, and give presentations.

I hope I'm not guilty of the gatekeeping you warn about here, because I know the other person has expertise that I don't. There isn't one discipline to rule them all. Everyone has something to bring to the table.

Although, if you try to abuse math words to sound smart or win an argument...I will catch you lol

“The predominance of measurable exploitability marks the current reign of technology that Heidegger abhorred. The German philosopher holds that we have become unable to appreciate beauty and wonder in the world. Everything, including us, is perceived as potential input to industrial production.”

Excellent post. It reminds me of a perceptive article by Paul Romer a few years ago of the perils of "mathiness" in economics (https://paulromer.net/mathiness/).

deeper topic hides here. What cultures is math useful for? If you're an Egyptian Pharaoh, your math skills (or even the math skills of your commanders) mean less than the sheer strength and numbers of your army. On the other hand, if you're in a former Soviet Union and you're building a train system that needs to support a hundred million people, math becomes very important.

What I think you're hinted at is not a world wide phenomenon, but a one centric to the United States tech. And maybe not the type of tech that gave us TCP/IP, Wi-FI, and Routers, but the kind of tech that gave us Facebook, Twitter, and (maybe even) Amazon. And here, if I can jump to some conclusions, finding a way to convince everyone that you're a modern version of Egyptian Pharaoh maybe played a bigger role than being good at Math. So, basically, high EQ coupled with engineering? But not Math.

But, again, this is a very US-centric argument. And as a counter argument, I can reference my own upbringing - a highly math-centric culture, in which businesses die or grow based on how well the math works out on the backend - and much less dependent on one's charisma, emotional EQ, etc.

Then there is a question of time. Math was much more important in the US 60-70 years ago, when there were massive country-wide construction projects going on (including Nuclear). Each mistake is catastrophic. Fast forward to today, and the math problems are about optimizing a Taxi's drive path. A complex problem, but one that, even if it fails, can be fixed with a refund, a customer support ticket, or a simple rebooking/retry.

The real question then is not whether Math is important universally. But is Math going to be important in the future, in the United States?

Benn, I think the argument is flawed, as you noted upfront - it was a tough one to defend. Math is hard, and it continues to be exponentially hard when you think about probabilities, equations which deal with sequences, waves and patterns. I was never great at Math, but always above average. From personal experience I can tell you that without math the introduction to Data structures would've been tough, quant would've been tough and physics would've been tough too - particularly mechanics and thermodynamics.

More than that, I think the purpose of a field of study cannot be reduced to the flavor of the decade from an employment perspective and its utility in our jobs alone. As hard math is, its harder to find enough people who will be long term interested in pursuing the field further. It's a sampling problem, if you show the subject to 1MM maybe 10 will be keen to further the field. Without the focus that Math receives, it will be dead under the weight of $'s that young people make solving simple linear algebra through python functions (not easy I admit).

And for the pure progress of the field, let's keep solving.

Love this post Benn! Like Dave I have a son in college - he loves sports statistics, showing his analysis in Tableau, and is learning R. But he has HATED the fact that the stats curriculum is so math-heavy - he would rather learn data-science tasks like data cleansing, statistical summaries, and how to communicate his analysis to others.

Being highly numerate doesn't serve that much daily data practitioners - we all agree. But maths help a lot to comfortably think in guesstimates and understand a problem/solution space.

Imo, that's where maths really shine.

Moreover, there is something full-filling to understand the common underlying concepts between all problems and systems (which maths bring 99% of the time).

I agree that if we did have good data visualisation courses that built skills over a number of years, then those people would likely be well suited for roles as analysts. Maths is a long term learned skill, like music, art, and writing. Most buzzword courses are weeks or months long at most. They are not long term, difficult, or challenging…and I suspect knowledge is not always well retained. I know people who are good musicians who are very capable analysts, but I’ve seen many more fail, for their inability to understand and grow in the field.

I hire people into data roles, from many backgrounds, but I find those with a maths/science/eng background pick things up faster, and grow in the role quicker. Those without are still capable but they find it much more challenging.

Benn, great post. My degree at UCLA was in economics and, as a tech CTO, I've used my skills in logic, reasoning and writing infinitely more than math. I have 2 sons pursuing a career in computer science and I take issue with their math-heavy curriculum. Our industry's over-rotation on math discourages a whole population from considering a career in CS and under prepares those who do for life in the real world.

Benn, excellent article; one which describes how I arrived in math from a desire to be a history professor. My parents were convinced that I would starve in my desired profession, and they had the means to enforce their beliefs. By my SAT and National Merit scores (there used to be separate tests), I was equally competent, and proved to be so. They were, sadly, correct! Far better to explain the outcomes of relatively simple math to those who were afraid of symbols, than to change an engineer's mind, even (maybe especially) when they were wrong. I can now enjoy my retirement in the knowledge that I can figure out a plausible answer to current problems/questions across a broad spectrum, and have the ability to see the flaws in the arguments of the many poltroons and idealogical statisticians among us. And I am still prepared to learn from real experts. Including about fishing and cooking.

Once again, Benn does a fantastic job of roasting himself and barbecuing our sacred cows. Great sequel to last week's post!

edited Jan 12I'm a mathematician (MS in applied math) turned data scientist. The biggest benefit to me of going further in math wasn't learning the "advanced methods." It was everything else: how to structure an argument; the humbling experience of often being wrong; the importance of definitions and clear terminology; and, yes, written and verbal communication, because I had to teach a course, write papers, and give presentations.

I hope I'm not guilty of the gatekeeping you warn about here, because I know the other person has expertise that I don't. There isn't one discipline to rule them all. Everyone has something to bring to the table.

Although, if you try to abuse math words to sound smart or win an argument...I will catch you lol

Wow! That entire section "Shape Rotators sell words"

https://benn.substack.com/i/95079164/shape-rotators-sell-words

That's really awesome and yes, I'm guilty of using math-y jargon as rhetoric thus the vibe to convince people as well.

Only when it's done to me, do I realize something's off.

have you been reading Heidegger, Benn? 👀

https://www.thecollector.com/martin-heidegger-science-cannot-think/

“The predominance of measurable exploitability marks the current reign of technology that Heidegger abhorred. The German philosopher holds that we have become unable to appreciate beauty and wonder in the world. Everything, including us, is perceived as potential input to industrial production.”

Excellent post. It reminds me of a perceptive article by Paul Romer a few years ago of the perils of "mathiness" in economics (https://paulromer.net/mathiness/).

HBS to Math: “If I were married to you, I’d put poison in your coffee.”

Math to HBS : “If I were married to you, I’d drink it.”

Great writing Benn!

edited Jan 6deeper topic hides here. What cultures is math useful for? If you're an Egyptian Pharaoh, your math skills (or even the math skills of your commanders) mean less than the sheer strength and numbers of your army. On the other hand, if you're in a former Soviet Union and you're building a train system that needs to support a hundred million people, math becomes very important.

What I think you're hinted at is not a world wide phenomenon, but a one centric to the United States tech. And maybe not the type of tech that gave us TCP/IP, Wi-FI, and Routers, but the kind of tech that gave us Facebook, Twitter, and (maybe even) Amazon. And here, if I can jump to some conclusions, finding a way to convince everyone that you're a modern version of Egyptian Pharaoh maybe played a bigger role than being good at Math. So, basically, high EQ coupled with engineering? But not Math.

But, again, this is a very US-centric argument. And as a counter argument, I can reference my own upbringing - a highly math-centric culture, in which businesses die or grow based on how well the math works out on the backend - and much less dependent on one's charisma, emotional EQ, etc.

Then there is a question of time. Math was much more important in the US 60-70 years ago, when there were massive country-wide construction projects going on (including Nuclear). Each mistake is catastrophic. Fast forward to today, and the math problems are about optimizing a Taxi's drive path. A complex problem, but one that, even if it fails, can be fixed with a refund, a customer support ticket, or a simple rebooking/retry.

The real question then is not whether Math is important universally. But is Math going to be important in the future, in the United States?

Benn, I think the argument is flawed, as you noted upfront - it was a tough one to defend. Math is hard, and it continues to be exponentially hard when you think about probabilities, equations which deal with sequences, waves and patterns. I was never great at Math, but always above average. From personal experience I can tell you that without math the introduction to Data structures would've been tough, quant would've been tough and physics would've been tough too - particularly mechanics and thermodynamics.

More than that, I think the purpose of a field of study cannot be reduced to the flavor of the decade from an employment perspective and its utility in our jobs alone. As hard math is, its harder to find enough people who will be long term interested in pursuing the field further. It's a sampling problem, if you show the subject to 1MM maybe 10 will be keen to further the field. Without the focus that Math receives, it will be dead under the weight of $'s that young people make solving simple linear algebra through python functions (not easy I admit).

And for the pure progress of the field, let's keep solving.

Love this post Benn! Like Dave I have a son in college - he loves sports statistics, showing his analysis in Tableau, and is learning R. But he has HATED the fact that the stats curriculum is so math-heavy - he would rather learn data-science tasks like data cleansing, statistical summaries, and how to communicate his analysis to others.

Great post Benn, thanks !

Funny because I wrote an article recently on why do we study maths (🖇️ https://medium.com/@benoit.pimpaud/why-do-we-study-mathematics-52d75d7fd049).

Being highly numerate doesn't serve that much daily data practitioners - we all agree. But maths help a lot to comfortably think in guesstimates and understand a problem/solution space.

Imo, that's where maths really shine.

Moreover, there is something full-filling to understand the common underlying concepts between all problems and systems (which maths bring 99% of the time).

As usual, Seth Godin says it best:

https://seths.blog/2023/01/build-a-new-one/

"Nothing much changes until someone cares enough to build an alternative."

I agree that if we did have good data visualisation courses that built skills over a number of years, then those people would likely be well suited for roles as analysts. Maths is a long term learned skill, like music, art, and writing. Most buzzword courses are weeks or months long at most. They are not long term, difficult, or challenging…and I suspect knowledge is not always well retained. I know people who are good musicians who are very capable analysts, but I’ve seen many more fail, for their inability to understand and grow in the field.

I hire people into data roles, from many backgrounds, but I find those with a maths/science/eng background pick things up faster, and grow in the role quicker. Those without are still capable but they find it much more challenging.