When it comes to ‘intelligence’, AI is still drinking piss and eating glue

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If the postwar computer scientists who conceived of AI had chosen a different name such as ‘applied statistics’, we would be spared a lot of confusion

Network room at a Google data centre: Social media has been flooded with screenshots of Overview’s unhinged responses to innocuous search terms. Photograph: Google

But then I started using an app that employed machine learning to convert recorded speech into text. The thing was surprisingly accurate and efficient, and I was impressed by its ability to automate a process I found incredibly dull and time-consuming. It wasn’t perfect; it struggled with strong accents, and muffled words, and it often made completely stupid errors for no obvious reason – but then, so did I, and it took me a lot longer to make them.

Requiem for a middleweight: the life and death of Darren SutherlandI have long been highly sceptical of many of the claims made for machine learning, and the things it might be capable of. But this most recent leap in transcription software seemed to me to present a strong case for the technology’s potential. As a tool, a device for minimising labour and freeing up time for the more creative aspects of my work, it was undoubtedly powerful.

It was the sort of thing I might expect if I had employed a very efficient person to do all the annoying but necessary drudgery that my work involves

 

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