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Third Assembly Meeting

Avatar: Official meeting Official meeting
07/09/2020 16:53   comment-square 0 comments
02 October 2020
12:00 - 13:30
Reference: IN-MEET-2020-09-37
Version number 2 (of 2) see other versions

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During this meeting we will be hearing a talk from Ivan Caballero, the founder and CEO of Citibeats

Talk: Collective intelligence on social needs during COVID 19

Citibeats is a fast and easy social data intelligence platform using NLP & machine-learning to turn speech into insights. In 2019, Citibeats was recognized by the World Summit Awards as the best project in the world for governance and civic engagement by the World Economic Forum as ‘the first AI for measuring the SDGs’. bySAP as a universal tool to foster civic responsiveness, and by Twitter as a lead case study of using open data for civic good.

In the days following the outbreak of COVID 19 in Europe, Citibeats has begun launching collective intelligence ‘observatories’ in more than 12 countries, to bring real-time views on social needs to governments, companies and people. By analyzing millions of opinions every week, it is possible to use ‘citizens as a sensor’ for where there are unmet, rising, or outlier social needs that should be a priority to respond to.

meetings
Online
Barcelona
OpenStreetMap - Barcelona

Third Assembly Meeting Hypothesis

Welcome  [ 12:00 - 12:10]

Welcome back after summer break!

Talk with Ivan Caballero, the founder and CEO of Citibeats  [ 12:10 - 12:30]

Playing with Miro  [ 12:30 - 12:35]

Getting to know the Miro board

Prioritising Features  [ 12:35 - 12:50]

Use dotmocracy we're going to prioritise features for the dashboard

Creating 'What if' Scenarios  [ 12:50 - 13:00]

Using the features selected we're going to create scenarios where we think they might be used and envision the kind of professionals that will use them

Next Steps  [ 13:00 - 13:10]

We're going to come full circle and show you how we aim to improve on our user stories that we started with in Rome!

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870792.
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