Emotional Hermeneutics. Exploring the Limits of Artificial Intelligence from a Diltheyan Perspective
This paper explores the intersection of emotional hermeneutics and artificial intelligence (AI), examining the challenges and potential of integrating deep emotional understanding into AI systems. Drawing on Wilhelm Dilthey's distinction between "explanation" and "understanding", the study highlights the current limitations of AI, particularly large language models, in achieving a genuine interpretative understanding of human emotions. We argue that while AI excels at data-driven explanations, it lacks the capacity for true emotional comprehension due to its inability to have personal experiences and self-awareness. The paper proposes incorporating humanities and social sciences insights to enhance AI's ability to contextualize and interpret emotions. However, it acknowledges that replicating human emotional intelligence in AI may be fundamentally limited by the nature of artificial systems. The study concludes by calling for interdisciplinary collaboration to advance emotional AI research while recognizing the ongoing philosophical questions about the nature of intelligence, and emotional understanding.
doi
10.1145/3648188.3680255
isbn
979-8-4007-0595-3
name
Emotional Hermeneutics. Exploring the Limits of Artificial Intelligence from a Diltheyan Perspective
source
publisher_html_pdf
acm_url
https://dl.acm.org/doi/10.1145/3648188.3680255
authors
Davide Picca
doi_url
https://doi.org/10.1145/3648188.3680255
license
CC BY 4.0
summary
This paper explores the intersection of emotional hermeneutics and artificial intelligence (AI), examining the challenges and potential of integrating deep emotional understanding into AI systems. Drawing on Wilhelm Dilthey's distinction between "explanation" and "understanding", the study highlights the current limitations of AI, particularly large language models, in achieving a genuine interpretative understanding of human emotions. We argue that while AI excels at data-driven explanations, it lacks the capacity for true emotional comprehension due to its inability to have personal experiences and self-awareness. The paper proposes incorporating humanities and social sciences insights to enhance AI's ability to contextualize and interpret emotions. However, it acknowledges that replicating human emotional intelligence in AI may be fundamentally limited by the nature of artificial systems. The study concludes by calling for interdisciplinary collaboration to advance emotional AI research while recognizing the ongoing philosophical questions about the nature of intelligence, and emotional understanding.
published
2024-09-10
conference
HT '24: 35th ACM Conference on Hypertext and Social Media, Poznan, Poland, September 10-13, 2024
open_access
true
acm_html_url
https://dl.acm.org/doi/full/10.1145/3648188.3680255
displayAuthor
Davide Picca (University of Lausanne, Switzerland)
displayPublishTime
2024-09-10