Citation: Alan Liu, “Messages and Values ??in the Age of Machine Learning: From Postcards to Social Media,” Prace Kulturoznawcze 26, no. 4 (2023): 125–29, https://doi.org/10.19195/0860-6668.26.4.8.
- Excerpt (first paragraphs):
If Stanislaw Pietraszko were to update his essay “Messages and Values” today, would he write about social media instead of postcards?Superficially, the analogy between postcards and social media seems unavoidable. After all, Facebook, Twitter, Instagram, TikTok, and other social media transmit short messages of text, images, and/or videos characterized by the same feature that Pietraszko noticed distinguishes postcards from letters: “the public availability of the verbal text” (and other content). One can assume, then, that Pietraszko and other scholars of the “axiosemiotics” of the postcard such as Zdzislaw W?sik would today also wish to discuss social media forms whose “excessive” and “redundant” performativity (to use Pietraszko’s terms) make them objects not just of information but also, and often primarily, of culture. After all, the visual “filters” that users frequently apply to their Instagram or TikTok posts are perfect examples of such excess or redundancy. There is almost no informational and only cultural value, for instance, in making oneself look like a cat.Yet one doubts that Pietraszko would have been content with just a superficial comparison of postcards to social media. His theoretical analysis was systemic in its aims, focusing on postcards to formulate a general relation between “messages and values” based on the difference between the semiotic function of information and the axiological values of culture. One surmises that today Pietraszko would want to pursue the same kind of systemic analysis by looking deeper into the systems of information and culture behind social media—a level of analysis, however, that poses challenges to his axiosemiotic approach.
- Excerpt (last paragraph):
“Culture … is neither communication nor information,” Pietraszko wished to believe. But for those working in data science now, the challenge is that communication and information are saturated by cultural values that cannot be partitioned off. Reciprocally, for those working in cultural studies, the challenge is that cultural values increasingly are fused to the instrumental functions of communication and information (as when a “like” in social media is exploited by the system to promote an advertisement). Instrumental functions cannot be compartmentalized from values because in the final analysis the very concept of instrumentality or functionality (and its underlying logics of cause and effect) are changing. Functionalism now incorporates probabilistic operations of predictive modeling that—as technology companies like to say—“just work,” but work in semiotically non-understandable ways that perhaps most resemble how culture works.
