About this webinar
The upcoming e-learning session is a repeat webinar of the Hash Sharing session we gave on 7 June 2019. The reason for repeating this webinar is two-fold. First, it is a crucial topic and secondly, we want to maximise participation from the Asia Pacific region.
In this repeat webinar, we will look at the benefits and challenges with image, video, and audio hashing in detecting, classifying and moderating terrorist content online. If you are a tech company or a tech professional interested in learning more about how your organisation can use hashing effectively, this will be a great opportunity for you to hear from some of the leading engineers in the field.
About our webinar series
Tech Against Terrorism and the Global Internet Forum to Counter Terrorism (GIFCT) are pleased to present our series of free e-learning webinars on tackling terrorist use of the internet whilst respecting human rights.
These free webinar sessions are particularly suited for tech professionals, content moderators and others interested in learning more about terrorist use of technology and the internet more widely, and aims to help them protect their platforms and services from terrorist exploitation.
Over the course of the upcoming webinars, GIFCT and Tech Against Terrorism will convene some of the industry's leading policy researchers and engineers to explore practical ways to support support smaller tech companies in tackling the terrorist use of the internet whilst respecting human rights.
As a participant, you will have the opportunity to engage directly with policy makers and engineers from Facebook, Google, Twitter and Microsoft as well as wide range of academics and industry experts. Forthcoming webinars over the next 6 months will cover the following topics (dates TBD):
Supporting the global tech industry in tackling the terrorist use of the internet whilst respecting human rights.
Supporting the global tech industry in tackling the terrorist use of the internet whilst respecting human rights | Implemented by @quant_spark
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