Back to the Future: What can we learn from past predictions for 2020?
Tuesday 26th November 2019
London EC1A 2FD
It’s November 2019. Our cities are under threat from climate emergency and pollution. We make phone calls using video and there are virtual assistants in our homes, helping to make our lives slightly easier. People travel by flying car and there are a number of biological robots wreaking havoc on the city of Los Angeles in an attempt to extend their 4-year lifespans.
It’s fortuitous that this month’s breakfast exploring the nature of past predictions, and what we can learn about forecasts for the future, happens to take place in the month in which Ridley Scott’s 1982 film Blade Runner was set. The opening paragraph describes the film’s context and in it we can see the fickle nature of the future. Sometimes you can be very right – as with the issues of pollution, video-calling and virtual assistants – and sometimes you can be very wrong – our cars remain grounded and they will for some time, and our most advanced forms of artificial intelligence are algorithms that perform forms of data analysis by trial and error.
Blade Runner is science fiction but predicting the future – to varying degrees of certainty and success – is something that we all do, every day, from estimating how long it’s going to take to get from A to B, to predicting how much we’ll need in our pension pot in order to retire comfortably.
For businesses, getting predictions right can be crucial in growing market share, and gaining a strategic advantage; getting them wrong can lead to missed opportunity and in some cases, massive disruption of the status quo. Just ask Steve Ballmer, who, while CEO of Microsoft in 2007 said that there was “no chance the iPhone is going to get any significant market share. No Chance”.
At Trajectory, we strive for a world in which the future is better understood, better planned and less feared and an understanding of the nature prediction – and its limitations – is crucial to this aim. By looking back at historical predictions for our present and our immediate future, we believe that much can be learned about how to look forward.
Join us for breakfast on Tuesday 26th November as we explore the nature of predictions for 2020, what we can learn from them, and what they might mean for the way we understand predictions for the future.
Please email Ruairi (email@example.com) to reserve your complimentary place and join us for breakfast.
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