• Skip to primary navigation
  • Skip to main content
52 Aces

52 Aces

Learning, competition and capitalism

  • Start Here
  • Books
  • Courses
  • Newsletter
  • Writing
  • Reading List
  • About
  • Contact

Competition

How to Talk About Algorithms

Ace Eddleman

This is part of The Algorithmic Society, an ongoing series about how algorithms and algorithmic thinking have taken over the world. Want to know when new content shows up? Sign up for my newsletter here.

This invasion of one’s mind by ready-made phrases can only be prevented if one is constantly on guard against them, and every such phrase anaesthetizes a portion of one’s brain. 

-George Orwell, Politics and the English Language

The term “algorithm” has become the latest linguistic tool for sounding sophisticated when talking about technology, a sort of TED Talk-esque shortcut to identifying with the Silicon Valley set. There’s something about the word itself that mystifies the average mind and imbues the user with an air of sophistication.

When someone at a cocktail party starts using the world “algorithm,” it becomes evident that this person is well-read and keeping up with the times. In other words, it’s become another way to signal status by leveraging (the appearance) of technical knowledge.

The word itself has become a stand-in for the god-like power that the largest internet platforms hold over our daily lives, a device for describing the black boxes behind behemoths like Google and Facebook. How we use the term “algorithm” hints at a sort of cowed awe at the sheer magnitude of their impact on the modern world.

We don’t know how they operate or who really pulls the levers (I imagine someone thinking are there levers on algorithms? as they read this) behind the curtain. Owners of algorithms are fine with this, because it makes their lives easier — they get to keep trade secrets to themselves, and they’re given a veneer of respectability in the process.

Ian Bogost described this dynamic best:

The next time you hear someone talking about algorithms, replace the term with ‘God’ and ask yourself if the meaning changes.

-Ian Bogost

Part of this has to do with the connection between algorithms and the gargantuan, public fortunes they’ve created in the era of high technology. There’s a new sort of American dream associated with algorithms, most famously captured in the movie The Social Network.

There’s a scene in that film where Eduardo Saverin and Mark Zuckerberg (played by Andrew Garfield and Jesse Eisenberg, respectively) are working on an algorithm by writing on a window.

Eduardo Saverin (Andrew Garfield) works on an algorithm with Mark Zuckerberg (Jesse Eisenberg)
Eduardo Saverin (Andrew Garfield) works on an algorithm with Mark Zuckerberg (Jesse Eisenberg)

While the algorithm in this scene is for a hacked-together pet project, the implication of the context is clear: algorithms with humble beginnings can conquer the world. Multiple billion-dollar fortunes were spawned by this primordial bit of mathematics that got translated into code.

Now algorithms are all over our cultural landscape, which is itself dominated by business narratives and the investors who drive them.

For example, it is now unimaginable to create a startup that didn’t offer some kind of algorithm that’s at least a minor improvement over another, existing algorithm. Not only is it not cool, but venture capitalists tend to shy away from such businesses because they lack scale. 

In short, algorithms are ever-present in our social media, on our phones, and in every domain imaginable that involves what could be considered “technology.” Algorithms are everywhere, algorithms are in everything, algorithms are everything.

Marc Andreesen famously said “software is eating the world,” but I would argue that the more correct phrasing is “algorithms have already eaten the world.”

Defining Algorithms

An algorithm in action
Image source

There’s an odd contradiction at the heart of our views on algorithms. On the one hand, we all seem to understand (to varying degrees) that algorithms play an outsized role in our lives. On the other, nobody seems to know what the word “algorithm” means.

What’s even weirder about this is that this definitional problem isn’t confined to the tech-illiterate: even computer scientists don’t have a generally-accepted definition of what an algorithm is.

It’s a long-standing debate, and some even say it’s not possible to sort algorithms from non-algorithms because of a computer science concept known as the halting problem.

This ambiguity can be viewed as a positive or a negative, depending on the algorithm and how you relate to it. But that’s all part of a larger exploration that I’ll get into later. For now, we need to come up with some kind of starting point for discussing algorithms that makes sense.

Since there isn’t a single, unified definition of an algorithm, we’ll have to use a simplified (and therefore flawed) one for now:

A set of well-defined steps for solving a specific class of problems.

What’s nice about this definition is that it gives us the ability to generalize the idea of an algorithm beyond its mathematical and computational origins. We can use it to describe any process that’s designed to operate in a repeatable, predictable manner.

We could say, for example, that low-tech activities like cooking involve the use of algorithms. After all, a recipe is a set of unambiguous steps (add ½ cup sugar, bake for 25 minutes, etc.) for “solving” specific food-related problems (how to convert ingredients into food, which in turn solves the problem of being hungry, etc.).

Bureaucratic procedures at a large company or government organization are also algorithmic if we run with this definition.

An employee can also be seen as a sort of algorithm as well — their whole job is to perform a specific set of tasks in order to accomplish goals for the organization. They do this by performing algorithms for each problem they’re presented with.

A Transformative Force

It’s also worth adding another dimension to this definition:

Algorithms transform some set of input values into a desired output or set of outputs.

This is key to understanding all thing algorithmic. Algorithms transform what they take in and generate something novel in the process.

In some sense, this is the most important way to look at algorithms. It makes you realize that there’s some objective involved, that what the algorithms are creating isn’t just math — they’re machines of creation.

Algorithms aren’t just transforming inputs from computer systems, either. As they integrate more and more with physical objects (including people), they are using the real world itself as a set of inputs and creating new landscapes in their wake.

Now we can start to unravel the linguistic consequences of using the word “algorithm” the way we do. By talking about algorithms as our digital overlords — never to be questioned or examined in a meaningful way — we hand them power they don’t deserve.

Even though they’re designed by high-caliber computer scientists, these algorithms are still designed and operated by humans. This means they’re flawed in countless ways, and even our most powerful computers can’t rid themselves of their designer’s human errors.

When you embrace that fact, it becomes clear that talking about algorithms with a glint of admiration in our eyes is often a mistake. While some are worthy of praise, quite a few are far more fragile, inaccurate and exploitable than their owners would like you to know.

More than anything, we need to get rid of this idea that algorithms are simply hand-waving mechanisms for explaining new technology. Algorithms are real, they serve specific purposes and it’s possible to at least begin to understand how they operate if you equip yourself to probe them.

Their impact, despite their flawed nature, is large. We’ve built, and continue to build, an algorithmic society, and it’s simply irresponsible to treat algorithms in such a haphazard way. It is the duty of every intelligent, capable adult in this new world to get a handle on what algorithms are and how they are shaping our world.

And this starts by learning to talk about algorithms not as magical code-driven dragons. It starts by seeing how they’re infiltrating not just our computers, but our very identities, our everyday existence.

They are fractal, spinning themselves through increasing levels of abstraction as they generate billions of dollars and shift our personal lives in ways that even their creators often don’t understand.

Algorithms are, in short, the most important topic of the modern era. It is my goal with this series to give you a glimpse into just how large of an impact they’re having, and then provide you with the tools you need to navigate this world more intelligently.

There will be more to learn, but consider this the starting point.

Losing Games

Ace Eddleman

This is part of my 5 Minute Concepts series, which is designed to help you understand fundamental concepts about subjects like learning, memory and competition in the shortest time possible. Each episode is available in video format on my YouTube channel and audio via my podcast. If you prefer to read, the transcript is below.

Want to know when new content shows up? Sign up for my newsletter here.

Much of what I create revolves around the idea of competing intelligently. My overall hypothesis about competition is that most people do it haphazardly, and expect their own intuitions — mixed with a recognition of incentives — to carry them to victory.

Thinking this way is a serious error. It leads to making the same mistakes over and over again, and creates situations where meaningful learning takes much longer than it should.

What’s more important, in my opinion, is that we recognize just how competitive the world is. Competition exists at all levels of life, all the way down to single-celled organisms. Competition is a key component of evolutionary biology, and there isn’t any form of life on earth that can escape this dynamic.

There’s competition for money, competition for status, competition for relationships. There’s competition everywhere.

Life is competition and competition is life.

With all that being said, there’s an idea that’s just as important to keep in mind: sometimes, you’re playing a game you can’t win — no matter how intelligent you are or how hard you work. When you find yourself in this kind of game, what can be called a losing game, you need to exit that game as fast as you can.

Recognizing losing games like this is a skill in and of itself, one that many people find hard to develop. It’s particularly common in American culture, where we’re constantly told that hard work is the answer to all of life’s problems.

An extreme example I like to use is professional basketball. The first requirement for playing basketball at the pro level is to be very tall, which is something you can’t train for. You’re either born with tall genetics or you aren’t.

This can be a hard pill to swallow for people who don’t hit those height requirements but love the game enough to dedicate their lives to it. Someone who is only average height can spend every waking hour refining their game, doing everything they can to get better, and still come up short.

The problem in this situation isn’t that the player isn’t committed or intelligent enough. It’s just not a game they can win — and there’s nothing they can do about that.

Instead, this same player could find another way to be involved with the game. Maybe they could find work as a talent scout, or a commentator, or a sports writer, and still play for fun in recreational leagues.

Maybe they’re an exceptional programmer or mathematician, and that could allow them to build some kind of technological product that is intertwined with basketball.

Those are all winnable games for this fictional person: they offer odds with large payoffs and none of them have requirements that are impossible to train for.

What tends to drive people like this crazy is the search for glory. They want to do what’s most admired in society, like playing a sport professionally.

The irony is that wasting time on paths like this more often than not generates an excessive amount of unnecessary misery. Most people don’t really know what they want, they just think they know, so they waste their time pursuing goals that other people or society set for them.

That same player who wants to be a player more than anything might find more fulfillment in an auxiliary role than they can estimate.

Instead of wasting years pursuing a professional playing career that ends badly, they should find something else that might even end up being more fulfilling (or even lucrative).

Sometimes you can create the game yourself, and sometimes you have to go play someone else’s game. Either way, you should be doing this kind of analysis on a regular basis. Every now and then, stop and ask yourself: Is this a game I can win?

I’ve failed at this more times than I can count, and it’s cost me dearly on a few occasions. Hopefully you can heed my words and not make the same mistakes I have. Don’t play games you can’t win — find a place where you can play with favorable odds, and then throw yourself into that.

A Conversation About Risk

Ace Eddleman

We’re all taking a collective “L” at the moment due to the coronavirus, so I’ve been thinking about what I’d like to accomplish during my time as a quarantine hobbit. What struck me as the most important (and interesting) topic to dive into is risk, specifically how it’s viewed and managed by real people.

[Read more…] about A Conversation About Risk

Managing the Exploration-Exploitation Dilemma

Ace Eddleman

Managing the Exploration-Exploitation Dilemma

At the core of every life is a single, difficult question: should I learn more, or should I make the most of what I already know? This is known as “the exploration-exploitation dilemma” (aka “the exploration-exploitation tradeoff“), and it’s the most important problem you’ll ever face.

[Read more…] about Managing the Exploration-Exploitation Dilemma

How to Win, a New Course

Ace Eddleman

“First live, then philosophize.” -Arthur Schopenhauer

Today I’m releasing a brand new, high-quality video course about how to compete and, more importantly, how to win.

[Read more…] about How to Win, a New Course
  • Go to page 1
  • Go to page 2
  • Go to page 3
  • Go to Next Page »

Copyright 52 Aces & Ace Eddleman © 2021 · Log in

  • Start Here
  • Books
  • Courses
  • Newsletter
  • Writing
  • Reading List
  • About
  • Contact