This week, in a neatly self-referential story, an algorithm has been developed to help workers ascertain if their jobs are at risk of automation by… an algorithm. Researchers compared robotic and human abilities to identify the most at-risk jobs (meat packers and slaughterers are high risk; astronomers and neurologists are low risk) and also used the comparison to work out which lower-risk jobs people could safely and easily jump to. Thankfully for the researchers, ‘education, training and library’ ranks low on the robot-revolution risk register…
In other AI-defying news, people are using ‘algospeak’ – language that will not be picked up by AI content moderation systems – to ensure their (sometimes dubious, sometimes legit) content remains live and uncensored. Examples include using ‘unalive’ instead of ‘dead’ and the corn emoji instead of ‘porn’. As well as screening out properly dodgy content, moderation algorithms have been found to censor already marginalised groups, demonetising and down-ranking posts that include words such as ‘gay’, and ‘racist’. To sidestep the filters, people use the palm of a hand to signify white people; sex workers refer to themselves as accountants; and women’s health sites resort to using ‘nip nops’ instead of nipples, and spelling vagina using symbols within captions.
Sticking with the theme of skirting around the rules, documents reported in The Guardian show that the US Immigration and Customs Enforcement (ICE) has worked with private data brokers to find loopholes around sanctuary policies (designed to protect immigrants regardless of their status) to access data aiding the search for immigrants marked for deportation.
In news from ODI Towers, we’ve published our report mapping the UK government’s activity on data literacy. Our findings include that there is a lack of clarity in definition; a risk of duplicated effort; and that more support is required for data literacy both within and outside of the UK government.