Meursault as a Data Point
This research addresses ethical dilemmas in data-driven societies by critiquing the reliance on data-driven narratives and advocating for humanistic values in AI, though it is incremental in applying existing NLP methods to a literary case study.
This paper tackles the problem of reducing human experiences to quantifiable metrics by analyzing Meursault from Camus' The Stranger using NLP techniques like BERT and VADER, revealing limitations in applying algorithmic models to complex human experiences such as existential alienation and moral ambiguity.
In an era dominated by datafication, the reduction of human experiences to quantifiable metrics raises profound philosophical and ethical questions. This paper explores these issues through the lens of Meursault, the protagonist of Albert Camus' The Stranger, whose emotionally detached existence epitomizes the existential concept of absurdity. Using natural language processing (NLP) techniques including emotion detection (BERT), sentiment analysis (VADER), and named entity recognition (spaCy)-this study quantifies key events and behaviors in Meursault's life. Our analysis reveals the inherent limitations of applying algorithmic models to complex human experiences, particularly those rooted in existential alienation and moral ambiguity. By examining how modern AI tools misinterpret Meursault's actions and emotions, this research underscores the broader ethical dilemmas of reducing nuanced human narratives to data points, challenging the foundational assumptions of our data-driven society. The findings presented in this paper serve as a critique of the increasing reliance on data-driven narratives and advocate for incorporating humanistic values in artificial intelligence.