science

Maes–Garreau law

Maes–Garreau law is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Maes–Garreau law rather than just read about it. In short: The Maes–Garreau law is the statement that "most favorable predictions about future technology will fall within the Maes–Garreau point", defined as "the latest possible date a prediction can come true and still remain in the lifetime of the person making it". Specifically, it relates to predictions of a technological singularity or other radical future technologies.

Key takeaways

Maes–Garreau law belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Maes–Garreau law to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Maes–Garreau law from memory before moving on to harder problems.

Reference excerpt

The Maes–Garreau law is the statement that "most favorable predictions about future technology will fall within the Maes–Garreau point", defined as "the latest possible date a prediction can come true and still remain in the lifetime of the person making it". Specifically, it relates to predictions of a technological singularity or other radical future technologies. It has been referred to as a "law of human nature", although Kelly's evidence is anecdotal.

Origin Kevin Kelly, editor of Wired magazine, created the law in 2007 after being influenced by Pattie Maes at MIT and Joel Garreau (author of Radical Evolution). In 1993, Maes listed a number of her colleagues at MIT that had publicly predicted mind uploading (the replication of a human brain on a computer), and noted that the innovations were generally slated to occur approximately 70 years after the birth of the predictor. As quoted by her colleague Rodney Brooks:

She took as many people as she could find who had publicly predicted downloading of consciousness into silicon, and plotted the dates of their predictions, along with when they themselves would turn seventy years old. Not too surprisingly, the years matched up for each of them. Three score and ten years from their individual births, technology would be ripe for them to download their consciousnesses into a computer. Just in the nick of time! They were each, in their own minds, going to be remarkably lucky, to be in just the right place at the right time.

Failed attempts to verify Maes-Garreau The Machine Intelligence Research Institute released a paper detailing a much larger set of 95 AI predictions extracted from a database of 257 AI predictions, which finds a broad array of estimates significantly before and after a predictor's estimated longevity, thus contradicting the law. MIRI states a stronger rule as being "Maes-Garreau": "the predictor expects AI to be developed at the exact end of their life."

References

Worked examples

Example 1 — a first encounter with Maes–Garreau law

Start with the simplest possible case. Write down what Maes–Garreau law claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Maes–Garreau law before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Maes–Garreau law ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Maes–Garreau law

In research: Maes–Garreau law appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Maes–Garreau law in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Maes–Garreau law is common in secondary-school and first-year university syllabi. It links to neighbouring topics Futures studies, Futures studies stubs, so understanding it makes those chapters shorter.
In everyday life: Look for Maes–Garreau law outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Maes–Garreau law in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Maes–Garreau law means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Maes–Garreau law out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Maes–Garreau law in simple terms?

Why does Maes–Garreau law matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Maes–Garreau law?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Maes–Garreau law.