A short note on estimating intelligence from user profiles in the context of universal psychometrics: prospects and caveats
There has been an increasing interest in inferring some personality traits from users and players in social networks and games, respectively. This goes beyond classical sentiment analysis, and also much further than customer profiling. The purpose here is to have a characterisation of users in terms of personality traits, such as openness, conscientiousness, extraversion, agreeableness, and neuroticism. While this is an incipient area of research, we ask the question of whether cognitive abilities, and intelligence in particular, are also measurable from user profiles. However, we pose the question as broadly as possible in terms of subjects, in the context of universal psychometrics, including humans, machines and hybrids. Namely, in this paper we analyse the following question: is it possible to measure the intelligence of humans and (non-human) bots in a social network or a game just from their user profiles, i.e., by observation, without the use of interactive tests, such as IQ tests, the Turing test or other more principled machine intelligence tests?
Code (0)
등록된 구현이 없습니다.
Tasks
Sentiment AnalysisSimilar Papers 제목 키워드 기반
Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning
The rapid growth of generative artificial intelligence (AI) has introduced unprecedented computational demands, driving significant increases in the energy footprint of data centers. However, existing power consumption d…
The Personalization Trap: How User Memory Alters Emotional Reasoning in LLMs
When an AI assistant remembers that Sarah is a single mother working two jobs, does it interpret her stress differently than if she were a wealthy executive? As personalized AI systems increasingly incorporate long-term …
Emotional IntelligenceEnd-to-end Training for Recommendation with Language-based User Profiles
Many online platforms maintain user profiles for personalization. Unfortunately, these profiles are typically not interpretable or easily modifiable by the user. To remedy this shortcoming, we explore natural language-ba…
Recommendation SystemsReinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective
In this paper, we study the problem of mobile user profiling, which is a critical component for quantifying users' characteristics in the human mobility modeling pipeline. Human mobility is a sequential decision-making p…
Decision MakingGraph Representation LearningRepresentation LearningSequential Decision MakingDiffusionGS: Generative Search with Query Conditioned Diffusion in Kuaishou
Personalized search ranking systems are critical for driving engagement and revenue in modern e-commerce and short-video platforms. While existing methods excel at estimating users' broad interests based on the filtered …