A short note on estimating intelligence from user profiles in the context of universal psychometrics: prospects and caveats

TL;DR

This paper explores the potential to estimate human and machine intelligence from user profiles in social networks and games, discussing prospects, challenges, and the broader implications within universal psychometrics.

Contribution

It introduces a broad inquiry into measuring intelligence from user profiles across humans, machines, and hybrids, highlighting the novelty of profile-based intelligence estimation without interactive testing.

Findings

Analyzes the feasibility of profile-based intelligence measurement.

Discusses challenges and limitations of current methods.

Proposes a framework for future research in universal psychometrics.

Abstract

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?