Please Choose Reprex in The Hague Innovators Award Online Vote
Reprex Wants To Talk To You All
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How to vote?
- Your vote is not final yet, you must click on a confirmation link to prove that it was you who voted. Go to your email. (Your email is only recorded to avoid double voting, they will not add your address to any marketing databases.)
- You receive a text that your code is recorded and you have nothing else to do. (Your address is safe with the municipality of The Hague.)
How to share the word?
- Please share our video message on YouTube among your colleagues and friends.
The message is the message! We are an ethical data and AI company, and one of our topics is detecting if algorithms are biased towards the English language speakers. We want to teach the computer to understand small languages, and of course, everyone, who is under-represented in data: womxn, former colonial nations.
🇳🇱 🇬🇧 🇧🇦 🇨🇿 🇭🇺 🇩🇪 🇱🇹 🇫🇷 🇸🇰 🇪🇸 🇹🇷 + Catalan.
2 Retweet our appeal from one of our observatory Twitter accounts. For music audiences:
💙 We ask you, humbly, to support us with a vote or by sharing our appeal. We're part of the #opensource, #opendata, and #openscience movement that depends on your support to stay online and thriving, but many of our users or simply look the other way🤦🏻♀️ https://t.co/24LoImPf6r— Digital Music Observatory (@DigitalMusicObs) November 1, 2022
Like our LinkedIn page and share our appeal.
Or just send the link to this post from the browser your colleagues and friends.
Why vote for us?
We are finalists in The Hague Innovation Awards with a product offering and a message that big data and AI should work for all: ethnic minorities, small nations, small languages, womxn. We are measuring why certain artists are not getting recommended and paid on global streaming platforms, or why NGOs do not find the right data about fighting greenwashing. We want to help small businesses, civil society organizations, and NGOs who cannot hire a data engineer and a data scientist to fight data monopolies. Who cannot defend themselves from the dark patterns of greedy algorithms?