How much effort do you put in to keeping up with changes in the digital landscape?
There is increased pressure for breakthroughs to happen more quickly, and for the next big thing to appear.
Against this backdrop, the tech hype-cycle is spinning ever-faster, and the big ideas offered by the tech industry have ever-shorter lives as a result.
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In the absence of the kind of broad and deep governmental support that led to many of the breakthroughs of the 20th century, science and tech are reliant on the moonshot ambitions of billionaires and charitable foundations, and this is leading to a narrower view of where progress is most important.
A steady-state model of innovation based on continuous, long-term investment would alter the dynamics of the hype-cycle considerably. Research and development teams would be less reliant on gaining the interest of venture-capital funds and more reliant on demonstrating widely-applicable, socially useful research over a longer time period.
This more considered cycle of innovation would create useful friction, allowing time to evaluate the ethical implications of a technology or product in more detail, including its environmental and social impact. Too often, this work has to be done in the aftermath of innovation – as is now happening with generative AI – as ethics-focused researchers work to catch up to implementation. It would also open up time for the design of products and services to move beyond minimum viable product, to become higher-quality experiences that meet the needs of more diverse groups of people.
These are excerpts from a piece by Sarah Housley in Dezeen. I think it’s on the money.
We’re going to be less able to keep up with the hype-cycle and should focus instead on creating meaningful experiences rather than announceables. That’s at the heart of boring magic. This is going to be harder for managers to communicate upwards to leaders and executives though. The necessary slowing.
I wonder whether the deceleration will be based on the distance between hyped technologies, the workforce in an organisation, and their deep understanding (or not) of those technologies.
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