Beyond the hype: Reframing AI through algorithms and culture

In an era of extended AI hype following the emergence of generative AI, one might almost think of the term “algorithm” as a relic of the past. This is of course an exaggeration, and perhaps strange, coming from a scholar whose career has been built on something called critical algorithm studies. Even if exaggerations are overstatements for effect—not meant to be taken literally—these days, popular and academic discourse seems replete with mentions of “AI,” while “algorithm” has moved somewhat into the background. As the head of a newly funded research hub on reimagining AI, I am frequently invited to speak about AI’s social and cultural impacts, particularly within the Norwegian context where I reside. A common theme across all these discussions is the sense of radical newness and urgency for political and societal interventions. While it is true that generative AI is novel in the sense that tools like ChatGPT and Midjourney have introduced user-friendly interfaces—making AI accessible to ordinary citizens—AI, at its core, is still fundamentally driven by algorithms. When I hear students, journalists, and policymakers alike talk about AI as if the terms algorithms, data, or computation never existed, I am naturally alarmed that we are simply jumping to the next umbrella term and technology hype cycle, disregarding decades of knowledge creation that could help put the current AI craze into much-needed perspective. This essay reviews three of the most recent books on algorithms and culture, each offering valuable insights that can help reintroduce this crucial knowledge into the conversation.