Don’t replace, augment

When considering what exactly lies ahead when we consider the potential impacts of ever-accelarating advances in Machine Learning and various forms of Artificial Intelligence, my favourite diagram is this one.

I hope that the trend will be more about augmenting human potential, rather than by simply replacing it, so that we can do new things instead of automating the same jobs. Indeed based on past advances in technology the best outcomes come from unlocked innovation.

Most of the hype currently is around the use of LLMs in chat-based interfaces and image generators, and while they can offer impressive abilities to process and outputs, this is just a facile manifestation that hints at the potential of AI. I think that as the hype fades we can appreciate truly ground-breaking advancements that are often happening in the background: in STEM, research, medicine, environmental technologies, and many other sectors where ML and AI are making software incredibly powerful and the UX of using it better and better for humans.

A good outcome would see job creation (fully 60 percent of people are now employed in occupations that did not exist in 1940 1) with the elimination of needlessly mundane tasks that computers can do much better than humans (computers never get tired, they can carry out a task indefinitely and can make sense of vast quantities of data).

This must go hand-in-hand with responsible implementation, governance and societal participation in this new economy.

For more in-depth reading, please read these excellent articles from the Design in Tech 2024 Report.

https://designintech.report/designintechreport-2024.html#/criticallify-urself

  1. David Autor, Anna Salomons, and Bryan Seegmiller, “New Frontiers: The Origins and Content of New Work, 1940–2018,” NBER Preprint, July 26, 2021. ↩︎

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