Algorithmic culture started before the internet

Algorithmic culture is the entanglement of computation with everyday meaning-making, and it did not begin with feeds or recommendation engines. Ted Striphas argues in Algorithmic Culture Before the Internet (Columbia University Press, 2023) that cultures of calculation, sorting, and standardized notation shaped print, markets, and public life long before Silicon Valley. For brand strategists, the point is historical humility: algorithms are not an alien layer on "real" culture. They continue older logics of classification, ranking, and gatekeeping.

What is algorithmic culture?

Striphas treats algorithmic culture as sociological condition where procedural decision-making participates in cultural production and consumption. Recommendation systems are the visible tip. Earlier forms include cataloging, indexing, credit scoring, broadcast scheduling, and editorial formulas that decide what reaches whom.

Our vault synthesis links Striphas to marketing practice: when brands optimize only for platform metrics, they inherit centuries of computational habit without naming the bias.

Why does the pre-internet history matter for brands?

It reframes accountability. If algorithms feel like neutral pipes, teams outsource judgment to vendors. If algorithms are cultural institutions with genealogy, teams must audit what gets ranked, suppressed, and normalized.

Striphas also notes historical cases where mathematical notation adapted to printing technology and legal problems, reminding us that "objective" systems serve prior social orders.

How should studios respond?

Read platform mechanics as editorial choices, not weather. Document voice and entity consistency so answer engines and social feeds do not flatten positioning. Pair quant performance with ethnographic reading of what communities actually do with the content.