Predicting the future — A historical overview

(Of failing to see the potential in new technologies)

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Resisting new technologies — the early days

The pattern is simple: first, people don't believe in the impact of these technologies, then after a while, when these technologies prove themselves and become widespread, people can't understand how someone in the past would have ever made such terrible forecasts.

[1800 ]— Steam ships

[1830] —High speed trains

[1876] Telephones

[1878] — Electric street lights

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Demonstration of Yablochkov’s arc lamp on the Avenue de l’Opera in Paris (1878), the first form of electric street lighting

[1883] — X-Rays

[1889] — Alternating current

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Nikola Tesla vs Thomas Edison (AC-DC electricity war)

[1901] — Sub-Marines

[1902] — Cars

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Early predictions were that Henry Ford’s horseless carriage was simply a “fad”

[1905] — Planes

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Da Vinci’s first plane designs

[1913] — Radio

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Telegraph kills live communication (prediction from 1907 — took 100 years to come true)

[1916] — Tanks

[1917] — Cinema

[1926] — Rockets

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The first rocket which could fly high enough to get into space was the V2 missile which was first launched by Germany in 1942

[1932] — Nuclear energy

[1946] — Televisions

[1947] — Calculators

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ENIAC: “Electronic Numerical Integrator and Calculator” (30 tons calculator)

[1959] — Xerox photocopiers

[1977] — Personal computers

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Altair 8800 — First personal computer introduced in January 1975;

[1981] — Storage

[1982] — Cell phones

[1995] — Internet

[2003] — Music streaming

[2007] — Iphones

Ballmer Laughs at iPhone

[2008] — Google and amazon

[2019-…] — What’s next?

The most impressive past success

Arthur Clarke predicting the internet in 1964

Predictions are a risky business. Even more so if they’re about the immediate future. Once shown to be wrong, the words return to their origin like a boomerang, and the quotes go on to forever haunt the speaker (source here)

The next big failures at predicting the future

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A policemen under a traffic light (in 1953). The city of New York was able to reassign all of its 6,000 officers working on the traffic squad after replacing them by automated traffic lights; this saved the city $12,500,000.
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Disruptive technologies —first disbelieve, then hype cycle, then slow adoption, then ubiquitous phase where we ask ourselves: how did we live in a world without this technology before?

Interested in artificial intelligence, machine learning, neural networks, data science, blockchain, technology, astronomy. Co-founder of Datathings, Luxembourg

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