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How to Speak Machine
Computational Thinking for the Rest of Us
How to Speak Machine (2019) prepares us for a future where computers will play an increasingly dominant role in business, politics, and our personal lives. It helps us understand the inner workings of the machines we use every day and how their programming can perpetuate social issues or be used to exploit our personal data. By learning how to speak machine, we can arm ourselves with the knowledge we need to ensure that the future is inclusive and safe for everyone.
- Entrepreneurs interested in forming a tech start-up
- Policymakers who need to keep regulations up to date with technological advancements
- Anyone who wants to understand the basics behind how computers “think”
John Maeda is a designer, computer scientist, author, and former president of the Rhode Island School of Design. He is an executive at Automattic, a web developer, where he aims to increase diversity and inclusion in the tech world. He has written interdisciplinary books on design and technology, such as The Laws of Simplicity and Design by Numbers.
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How to Speak Machine
Computational Thinking for the Rest of Us
- Read in 13 minutes
- Audio & text available
- Contains 8 key ideas
Synopsis
How to Speak Machine (2019) prepares us for a future where computers will play an increasingly dominant role in business, politics, and our personal lives. It helps us understand the inner workings of the machines we use every day and how their programming can perpetuate social issues or be used to exploit our personal data. By learning how to speak machine, we can arm ourselves with the knowledge we need to ensure that the future is inclusive and safe for everyone.
Key idea 1 of 8
Machines are good at repeating tasks endlessly.
Think back to the last time you ran laps around a track or sprinted on a treadmill. By the end, your heart was probably racing, and you were out of breath. Whether you were the fittest person in the gym or not, you would have eventually gotten tired. A computer, on the other hand, can run figurative laps around a track forever without taking a break.
The “track” a computer program runs on consists of lines of code written by a human programmer. Code is based on if-then logic, where if one condition is met, another action follows.
To illustrate this, take the first simple computer program the author encountered when he was in seventh grade. A friend showed him how he could get the computer to type out his name, Colin, over and over again to infinity with just two lines of code:
10 PRINT “COLIN”
20 GOTO 10
Colin’s program is an example of a simple loop, which functions like a conveyor belt on an assembly line. Each task is performed in sequence until, eventually, you reach an endpoint and start again. However, there’s an even more elegant way in which computers work in loops. This is called recursion.
If loops are like assembly lines, recursion is more like a Russian matryoshka nesting doll that contains progressively smaller copies of the original, outermost doll. However, because they’re made of physical material, you’ll eventually have made the smallest doll possible. Computers, though, can contain infinitely small or infinitely large copies of the same code.
To visualize this infinite recursion, take a look at the name of an operating system created in the 1980s by MIT’s Richard Stallman. The system was created to compete with Unix, a different operating system, so it was appropriately named the GNU Project, or GNU’s Not Unix. Notice how this name contains recursion. The “G” itself stands for “GNU.” Yes, another acronym. So you can see where this is going. If you continue to expand the acronym every time, you’ll just wind up with more of the same one. Expand “GNU,” and you get GNUNU. Do it again, and you’re left with GNUNUNU, and so on forever.
These loops and recursions can only be stopped with a command or by an error getting in the way. So you can just imagine the power of a machine that never tires while doing exactly what you tell it to do.
Key ideas in this title
- Machines are good at repeating tasks endlessly.
- Computers think exponentially.
- Machines are quickly growing more and more lifelike.
- Machines have changed the way businesses manufacture and sell products.
- Digital consumption allows companies to get up-close-and-personal with your data – for better or for worse.
- There’s a diversity problem in the tech world, and machines can perpetuate it.
- Machines process data, and data alone can’t always paint a complete picture.
- Final summary
