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Twenty Years of Personality Computing: Threats, Challenges and Future Directions

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arxiv 2503.02082 v1 pith:5PMZZSIV submitted 2025-03-03 cs.CL

classification cs.CL
keywords personalitycomputingfieldchallengesdirectionsfuturehumanpotential
verification ladder T0 review T1 audit T2 compute T3 formal
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Personality Computing is a field at the intersection of Personality Psychology and Computer Science. Started in 2005, research in the field utilizes computational methods to understand and predict human personality traits. The expansion of the field has been very rapid and, by analyzing digital footprints (text, images, social media, etc.), it helped to develop systems that recognize and even replicate human personality. While offering promising applications in talent recruiting, marketing and healthcare, the ethical implications of Personality Computing are significant. Concerns include data privacy, algorithmic bias, and the potential for manipulation by personality-aware Artificial Intelligence. This paper provides an overview of the field, explores key methodologies, discusses the challenges and threats, and outlines potential future directions for responsible development and deployment of Personality Computing technologies.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. GGBond: Growing Graph-Based AI-Agent Society for Socially-Aware Recommender Simulation

    cs.MA 2025-05 reject novelty 5.0 of 10

    GGBond is an agent-based simulator that couples a five-layer cognitive agent model with a dynamic multilayer social graph to evaluate recommender systems under long-term feedback.

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