The Scary Black Box: AI Driven Recommender Algorithms as The Most Powerful Social Force

Résumé 0

Recommender algorithms shape societies by individually exposing online users to everything they see, hear and feel online in real time. We examine development of recommender algorithms from the Page Rank and advertising platforms to Social Media Trending tools to draw conclusions about their social effects. Decisions on how to simplify the complex world around us into dozens of possibilities immensely affect societies and individuals. Similar to our perceptive apparatus, algorithms are eyes and ears in the online world, as they focus our attention towards what they "think" should be important, which is similar to news priming. That's why recommender algorithms are compared to mass media given their similar roles to sell products and prolong content exposure of online users. This inquiry concludes that AI driven recommender algorithms represent the most powerful social force at present. This indicates that recommender algorithms should be transparent to everyone and controlled by society as a public good. As recommender algorithms are usually based on artificial intelligence, human beings cannot see what's inside the black box, but should be able to set them for the benefit of individual and social well being. The fact that algorithms can be customized empowers societies to tackle the issues such as fake news, social polarization, echo chambers and spread of negative emotions, which ultimately affect individual well being and democratic capacity. Limitation of this inquiry is lack of quantitative analyisis. The main recommendations for further research is experiment on how much algorithms can predict our needs and wants.