The latest class session was a fascinating exploration of how digital technology is reshaping our relationship with media, culture, and each other. We dove into a mix of historical context and modern challenges, from the enduring power of print to the ethical questions raised by AI.
The Digital Landscape: A Remix, Not a Replacement
One of the most powerful ideas was that new media doesn't kill old media; it simply changes the landscape. This is known as Remediation Theory. For example, while digital books are everywhere, print isn't going away. Instead, we're seeing a rise in print-on-demand and a renewed appreciation for the physical book. This concept also applies to music, where the shift to solitary digital streaming is met with a nostalgic resurgence of vinyl records and the communal ritual of playing them.
This evolution is even changing how we consume visual media. The rise of social media has pushed a shift toward vertical video to capture attention on our phone screens, a stark contrast to the horizontal format of traditional cinema.
The Ever-Changing Human-Computer Interface
We took a trip back in time to understand how we interact with technology. The command-line interface (CLI), inspired by old teletype machines, was the original way to "talk" to a computer. Interestingly, AI chatbots like ChatGPT represent a return to this conversational, dialogue-based model.
The real revolution came with the Graphical User Interface (GUI), pioneered by Xerox PARC and popularized by Apple's Macintosh. The GUI introduced direct manipulation—the ability to drag and drop files and click on icons. Today, we're so used to this that we often take it for granted. However, the rise of cloud storage has created a form of "skill regression," where we rely on search functions instead of developing organized file systems.
The Complexity of Text Encoding
The class also introduced the Text Encoding Initiative (TEI), a set of detailed guidelines for encoding texts digitally. While it might sound complicated, the real challenge isn't the technical part; it's the intellectual discipline of interpreting a document and deciding how to represent it in a digital format. This act of encoding is, in itself, a form of interpretation, as every choice we make about what to tag or highlight adds meaning to the digital file. This complexity also provides a clear path to professionalization for those who master these skills, particularly in Europe, where the historical and cultural heritage is so vast.
The Ethical Questions of Our Digital Age
Perhaps the most thought-provoking part of the discussion was on the ethical implications of our work. We debated whether AI could ever achieve genuine agency, and if we should welcome it as an "alien agent" or fear it as a "Skynet." This ties into a bigger issue of data and inclusivity. Can we truly respect and archive every global perspective, or will we always have to make difficult choices about what data to keep?
We also discussed the concept of decolonizing data, highlighting the need to recognize marginalized communities as the rightful producers of knowledge, not subjects of extraction. This led to a discussion of OCAP principles (Ownership, Control, Access, and Possession) for Indigenous data.
Finally, we explored a "productivity paradox" related to AI coding tools. While developers feel more productive using them, studies show that they can actually slow people down, in part because we're not contributing new data to the human-created resources that these AIs mine, which raises a long-term sustainability concern for these tools.
Readings for next week:
- Renear. If interested you can look also at, DeRose et al.
- Erin Canning, Susan Brown, Sarah Roger and Kimberley Martin.
- Pierazzo. Textual Scholarship and Text Encoding