AI & collective memory

Area of Science:

• Digital Humanities
• Artificial Intelligence Studies
• Sociology of Memory

Background:

• Collective memory traditionally relies on shared experiences within a generation or group.
• The concept of collective memory has evolved, often mythologized with technological advancements.
• Previous technologies were assumed to unify memory, but Generative AI presents a different challenge.

Purpose of the Study:

• To analyze the impact of Generative AI (GAI) on the concept and formation of collective memory.
• To investigate how GAI reconfigures the representation, access, and use of the past.
• To argue that GAI undermines traditional notions of collective memory.

Main Methods:

• Literature review and conceptual analysis of Generative AI and collective memory theories.
• Examination of GAI's mechanisms: extracting, remixing, and replaying interactions.
• Analysis of the implications for individual identity and societal memory formation.

Main Results:

• GAI fundamentally alters how the past is represented, accessed, and communicated.
• GAI fragments individual identities and experiences, making group cohesion difficult.
• The technology creates a 'black box' memory, obscuring human agency in shaping the past.

Conclusions:

• Generative AI, unlike previous technologies, offers no prospect for unifying collective memory.
• The agentic nature of AI challenges the coherence of shared experiences and group identity.
• Societies face a future of fragmented memory with diminished human control over historical narratives.