Twitter 2.0: The Digital Agora
Instead of fostering escalation of outrage we should overcome confirmation bias by confronting users with alternative perspectives
After 12 years and 47.809 tweets, I left Twitter in August, which had nothing to do with Elon Musk. Quite the contrary, I’m glad someone took the initiative to fix Twitter; although his motives might be questionable, a successful outcome is unlikely. Just as Georg Christoph Lichtenberg (1744–1792) once wrote:
I cannot say whether things will get better if we change; what I can say is they must change if they are to get better.
When I joined Twitter in 2010, it was just a timeline of the people I chose to follow. Any confirmation bias was my fault. Over the years following, Twitter took the path other social media companies already had trodden: By implementing an algorithmically optimized feed (instead of the chronological timeline), Twitter finally became a first-class citizen of the attention economy. It ceased to be a place for discovering and discussing ideas, with its main objective becoming catching and holding our attention (and selling it to advertisers). And the easiest way to catch attention is by systematically amplifying our outrage.
During the corona pandemic, this pattern of outrage escalation didn’t serve us well in finding appropriate solutions to this complex problem. It led to a bitter fight of believers against deniers without any middle ground. It became evident and untenable for me that Twitter was no longer a digital agora but rather the Colosseum.
I do not know Elon Musk, but if I were to give him advice for overhauling Twitter, this would be it. As we now have the technology to identify content that will likely catch the user’s attention, we could likewise use it to find the best antithesis to a given topic. Imagine you read about a recent event that upsets you, and therefore you like a tweet expressing your outrage. The curation algorithm now uses this data to take you down the rabbit hole by showing you more and even more outrageous content along the same lines. However, it seems feasible to find equally popular content on the same topic from a different filter bubble and display it next to the one you liked. The basic idea of this experiment is to counteract the confirmation bias by confronting you with an alternative perspective instead of more of the same.
