Social media originally promised the democratization of media. In today's polarized world of disinformation we know it did not work out. The main reason for that is the business model of advertisement. In this model, our attention and behaviour are modifiable commodities, sold to the highest bidders.
As we have seen, today's centralized platforms and their ad-based model are misused heavily to damage democracy, incite hate and fuel conflict. We are being driven into polarization, losing our common ground. So, it is past time we end this race to the bottom before it is too late.
The existing alternatives -e.g. paywalls- don't work. Primarily, because they contradict the open knowledge model of the Internet, they fragment the web, are non-inclusive and intransparent. We need to think outside the box by fundamentally rearranging the incentive model and building an open, free and democratic alternative. That is what we are working on.
We are building a media-crowdfiltering-system with different stages. People can access all the content for free at the earlier stages. As a small service in return, they filter the noise for the later stages by curating the content. The people at the later stages pay a small amount for the priviledge of seeing only the highest-quality content and not having to go through all the noise themselves.
There is one big catch: The people at the later stages don't pay the small amount to the platform but in fact to the individual pieces of content that changed their life. Their money goes to the creator of this piece of content and everyone who signalled it for them at the earlier stages. At the same time it acts as a vote, further filtering out less good content.
This reward concept makes it a self-sustaining system with no need for outside investment. And at the same time leads to crowdfiltering towards truly life-changing content. The incentives are changed so that everyone involved has the quality of content in mind, and not the click rate.
This is only a very brief description. The talk will explain our approach in more detail.