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.
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.”
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.
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