crowdsourcing, data science & machine learning to measure violence & abuse against women on twitter

Amnesty International just released on December 18 a study on abuse and harassment on twitter account of female politicians and journalists in the US and the UK. Realised through the collaboration of thousands of crowdsourced volunteers labeling  tweets from the database and the machine-learning expertise of the London branch of ElementAI, branch driven by my friend Julien Cornebise with the main purpose of producing AI for good (as he explained at the recent Bayes for good workshop). Including the development of an ML tool to detect abusive tweets, called Troll Patrol [which pun side is clear in French!]. The amount of abuse exposed by this study and the possibility to train AIs to spot [some of the] abuse on line are both arguments that support Amnesty International call for the accountability of social media companies like twitter on abuse and violence propagated through their platform. (Methodology is also made available there.)

Bayes for good

A very special weekend workshop on Bayesian techniques used for social good in many different sense (and talks) that we organised with Kerrie Mengersen and Pierre Pudlo at CiRM, Luminy, Marseilles. It started with Rebecca (Beka) Steorts (Duke) explaining [by video from Duke] how the Syrian war deaths were processed to eliminate duplicates, to be continued on Monday at the “Big” conference, Alex Volfonsky (Duke) on a Twitter experiment on the impact of being exposed to adverse opinions as depolarising (not!) or further polarising (yes), turning into network causal analysis. And then Kerrie Mengersen (QUT) on the use of Bayesian networks in ecology, through observational studies she conducted. And the role of neutral statisticians in case of adversarial experts!

Next day, the first talk of David Corlis (Peace-Work), who writes the Stats for Good column in CHANCE and here gave a recruiting spiel for volunteering in good initiatives. Quoting Florence Nightingale as the “first” volunteer. And presenting a broad collection of projects as supports to his recommendations for “doing good”. We then heard [by video] Julien Cornebise from Element AI in London telling of his move out of DeepMind towards investing in social impacting projects through this new startup. Including working with Amnesty International on Darfour village destructions, building evidence from satellite imaging. And crowdsourcing. With an incoming report on the year activities (still under embargo). A most exciting and enthusiastic talk!