Social media, search engines, and recommendation systems provide a constant stream of data that shapes our knowledge, beliefs and decisions. We are constantly presented with content from a variety of sources, often without context. This content gets amalgamated into new constellations in the feeds, lists and streams we encounter (and sometime curate) on our devices. With the rise of consumer-facing, generative AI tools, the line between synthetic and other media becomes increasingly blurred. All of this has far-reaching implications for how individual people and society as a whole engage with information and knowledge. But here’s the thing: Not only is it becoming increasingly difficult to distinguish fact from opinion, but also to understand why certain content ends up in our feeds, recommendations or search results in the first place. Yet it’s more important than ever to understand it. This is where infrastructural meaning-making comes into play, and it’s something that the datafied society needs to understand.
- infrastructural meaning-making
- source criticism