obviously there has been a lot of coordination with her pr firm and working with her pr firm on, you know, can we get that document, or her firm arranged a series of briefings with her. so it has been really notably sprawling and quite well manicured effort to, you know, undertake this pretty huge project. so that s the consortium and how it worked. and as you said there s a pr firm behind it. but madu, what were the big headlines that came out this week? because we did learn some new stuff, didn t we? oh, yeah. i think we tried to look at it as bands or areas of things| that came out of one of the big things is, i what a major language problem facebook has globally, - and this is an interest- of ours, again, as a global news organisation. languages spoken by huge swathes of the world - arabic, hindi, urdu, . pashto in afghanistan, these are huge numbers - of facebook users and theyjust don t have enough in countryl language support moderators. so much, much of the - misinformation,
these are huge numbers - of facebook users who don t have enough in country- language support moderators. so much of the misinformation, hate speech and, you know, - other types of harmfulj content are just falling through the cracks. in most of the world outside of the us, and in fact - there was a number of one of the documents that said the company allocated 87%| of its budget for developing its misinformation detection i algorithms to the us in 2020. versus 13% to the entire rest of the world. - so i think for me, that was kind of one of the big takeaways, and the fact that they don t really i understand how their own algorithms work. there were documents in there that showed that women were shown less politicali content compared to men but they didn t . really know why. they also said that there - was certainly major systemic biases based on the race. of different users and that people who share frequently - are shown more in the news feed rankings and that tends to correlate
arabic, hindi, urdu, these are huge numbers of facebook users who don t have enough - in country language | support moderators. so much of the misinformation, hate speech and, you know, - other types of harmful content - are just falling through the cracks. in most of the world outside of the us, and in fact - there was a number of one of the documents that said the company allocated 87%| of its budget for developing its misinformation detection i algorithms to the us in 2020. 13% to the entire rest of the world. for me, that was kind of one of the big takeaways, - and the fact that they don t really understand how their own algorithms work. there were documents in there that showed that women were shown - less political content compared to men but they did not really know why. also they said that there was certainly a major - systemic biases based
was what are major like rich - problems that facebook has globally and this is an interest of ours| is a global news organisation. languages spoken by huge swathes of the world, - arabic, hindi, urdu, - pastjune in afghanistan, these are huge numbers of facebook users they don t have enough - in country languagel support moderators. so much of the misinformation, hate speech and, you know, - other types of harmful content - are just falling through the cracks. in most of the world outside of the us, and in fact - there was a number of one of the documents that said the company allocated 87%| of its budget for developing its misinformation detection i algorithms to the us in 2020. 13% to the entire rest of the world. for me that was kind of one of the big takeaways, - and the fact that i don t really understand how their-
pretty huge project. so to you know undertake this pretty huge project. pretty huge pro ect. so that s the consortium] pretty huge project. so that s the consortium and pretty huge project. so that s the consortium and how- pretty huge project. so that s the consortium and how it. the consortium and how it worked. as you said there s a pr firm behind it. but what were the big headlines that came out this week? we did learn some new stuff, didn t we? , , ~ learn some new stuff, didn t we? , , . learn some new stuff, didn t we? , , ~ ., learn some new stuff, didn t we? , , . ., we? oh yes. we look to as areas of thins we? oh yes. we look to as areas of things that we? oh yes. we look to as areas of things that came we? oh yes. we look to as areas of things that came out - we? oh yes. we look to as areas of things that came out of- we? oh yes. we look to as areas of things that came out of one i of things that came out of one of the of things that came out of one of the big of