Beyond Fear and Feelings Toward Technological Singularity: Understanding Psychological Factors Shaping Attitudes Toward AI

Abstract Artificial Intelligence (AI) has advanced rapidly in recent years and is now embedded in everyday life. However, its novelty and widespread impact make it crucial to explore the psychological factors underlying its acceptance and integration. In the present research ( N = 159), we aim how fear and feelings toward technological singularity – the point at which AI surpasses human intelligence and becomes self-improving – are related to the perceived consequences of technological singularity. As expected, people with more positive attitudes towards AI also perceived technological singularity as more positive and showed lower fear toward it. Next, we tested the proposed model with fear and feelings as predictors, perceived consequences as mediators, and attitudes toward AI as the outcome. We also included the use of AI as an additional predictor of attitudes. The model showed good fit (e.g., CFI and TLI = .99); most predictions were supported. By providing a more in-depth understanding of key factors rooted in the idea of technological singularity and how they influence our attitudes toward AI, our findings can help develop targeted education and awareness campaigns to address concerns and misconceptions about AI.

Authors

Institutions

Publication Details

Journal
Trends in Psychology
Published
2025-07-16
DOI
https://doi.org/10.1007/s43076-025-00473-9
Primary Topic
Death Anxiety and Social Exclusion
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Beyond Fear and Feelings Toward Technological Singularity: Understanding Psychological Factors Shaping Attitudes Toward AI

Renan Pereira Monteiro, Paul H. P. Hanel, Gabriel Lins de Holanda Coelho, Roosevelt Vilar et al.
Trends in Psychology
Death Anxiety and Social Exclusion
article

Beyond Fear and Feelings Toward Technological Singularity: Understanding Psychological Factors Shaping Attitudes Toward AI

Renan Pereira Monteiro, Paul H. P. Hanel, Gabriel Lins de Holanda Coelho, Roosevelt Vilar, Vitor M. Paiva de S. Baptista
article en

Abstract

Abstract Artificial Intelligence (AI) has advanced rapidly in recent years and is now embedded in everyday life. However, its novelty and widespread impact make it crucial to explore the psychological factors underlying its acceptance and integration. In the present research ( N = 159), we aim how fear and feelings toward technological singularity – the point at which AI surpasses human intelligence and becomes self-improving – are related to the perceived consequences of technological singularity. As expected, people with more positive attitudes towards AI also perceived technological singularity as more positive and showed lower fear toward it. Next, we tested the proposed model with fear and feelings as predictors, perceived consequences as mediators, and attitudes toward AI as the outcome. We also included the use of AI as an additional predictor of attitudes. The model showed good fit (e.g., CFI and TLI = .99); most predictions were supported. By providing a more in-depth understanding of key factors rooted in the idea of technological singularity and how they influence our attitudes toward AI, our findings can help develop targeted education and awareness campaigns to address concerns and misconceptions about AI.

Trends in Psychology
University of Essex (GB), Universidade Federal da Paraíba (BR), Faculdade de Ciências Médicas da Santa Casa de São Paulo (BR)
Openalex Percentile: Top 80%
Death Anxiety and Social Exclusion
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.