How do we make sense of changing human social norms? Ask a bot,

People love new technology. Last week, half the internet was experimenting with ChatGPT, a new artificial intelligence chatbot that can write text on almost any subject under the sun with only the most basic of instructions. You should have a go. Reactions so far focus on predicting the end of education (it can churn out an essay in seconds) or arguing that it’s fun but irrelevant to human progress.

Sceptics should note that machine learning and big data analysis is supporting social science progress. Take the debate about cultural norms, where some emphasise the persistence of views passed between generations, while others argue ideas converge between places over time. We struggle to know which view is accurate (surveys of public attitudes are relatively recent or only national).

But fear not. Recent research used machine learning to examine 193m pages of local US newspapers from the past 160 years to measure attitudes towards women and how they vary across the US. For example, it measured whether the language in those pages associates men with careers and women with caring, or whether feminism is seen as dangerous extremism or desirable equality campaigning in different places.

The conclusion is clear: gender norms have converged hugely in the US with the variation in attitudes between places falling by around 70%. It’s not a totally smooth ride – the 1970s saw divergence in attitudes towards feminism as that generation’s culture war heated up. But people becoming more similar is the real story despite what today’s culture warriors might hope. The researchers put this down to lower costs of travelling or communicating over time.

And it’s not just that attitudes have converged, they’ve done so in the right direction as gender norms across the US have headed towards the “not Neanderthal”. It’s not just technology making progress.

Torsten Bell is chief executive of the Resolution Foundation. Read more at

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