[Paper Review] Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust

Teresa Scantamburlo, Àtia Cortés+5 more|arXiv (Cornell University)|Aug 19, 2023

Ethics and Social Impacts of AISocial Sciences3 citations

TL;DR

This study investigates European citizens' awareness, attitudes, and trust in artificial intelligence (AI) through a validated survey instrument (PAICE) administered to 4,006 respondents across eight countries. Despite low self-assessed AI knowledge, over half express very positive attitudes toward AI, though trust is undermined by perceived lack of transparency and regulation, highlighting the need for ethical governance, public education, and inclusive policy communication to build a trustworthy AI ecosystem.

ABSTRACT

This paper presents the results of an extensive study investigating the opinions on Artificial Intelligence (AI) of a sample of 4,006 European citizens from eight distinct countries (France, Germany, Italy, Netherlands, Poland, Romania, Spain, and Sweden). The aim of the study is to gain a better understanding of people's views and perceptions within the European context, which is already marked by important policy actions and regulatory processes. To survey the perceptions of the citizens of Europe we design and validate a new questionnaire (PAICE) structured around three dimensions: people's awareness, attitude, and trust. We observe that while awareness is characterized by a low level of self-assessed competency, the attitude toward AI is very positive for more than half of the population. Reflecting upon the collected results, we highlight implicit contradictions and identify trends that may interfere with the creation of an ecosystem of trust and the development of inclusive AI policies. The introduction of rules that ensure legal and ethical standards, along with the activity of high-level educational entities, and the promotion of AI literacy are identified as key factors in supporting a trustworthy AI ecosystem. We make some recommendations for AI governance focused on the European context and conclude with suggestions for future work.

Motivation & Objective

• To assess public awareness, attitudes, and trust in AI among European citizens across diverse national contexts.
• To identify gaps between public perception and actual understanding of AI technologies and regulations.
• To examine how social trends—such as technological optimism without knowledge, policy disconnect, and low engagement in AI education—affect the development of trustworthy AI.
• To validate a new survey instrument (PAICE) for measuring public perceptions of AI across three dimensions: awareness, attitude, and trust.
• To inform AI governance by identifying policy, educational, and communication strategies that can enhance public trust and inclusivity.

Proposed method

• A computer-assisted web interview (CAWI) methodology was used to collect data from a stratified sample of 4,006 European citizens across eight countries.
• A new questionnaire, PAICE (Perceptions on AI by the Citizens of Europe), was designed and validated with three core dimensions: awareness, attitude, and trust.
• Statistical validation included exploratory factor analysis using polychoric correlation matrices and principal axis factoring with oblique rotation to assess internal structure and reliability.
• Descriptive and inferential statistics were used to analyze responses by country, age, and gender, with p-values reported for group comparisons.
• The questionnaire included Likert-scale, dichotomous, and multi-response items to capture nuanced perceptions of AI in various domains (e.g., healthcare, HR, surveillance).
• Supplementary data, including full questionnaire text, response tables, and demographic breakdowns, were made publicly available for reproducibility and reuse.

Figure 1: Responses to Likert scale items associated with awareness. Low-scale values (1 and 2) are represented by red-like colors, while high-scale values (4 and 5) are represented by blue-like colors. Item Q7 is split into sub-items regarding the perceived presence of AI in ten different sectors.

Experimental results

Research questions

• RQ1 What is the level of self-assessed awareness of AI among European citizens across different countries?
• RQ2 How do attitudes toward AI vary across different application domains, such as healthcare, human resources, and surveillance?
• RQ3 What factors most significantly influence public trust in AI systems, and which institutions are perceived as most trustworthy?
• RQ4 To what extent do social trends—such as optimism toward AI despite low knowledge, disconnection from policy efforts, and low engagement in education—create barriers to trustworthy AI?
• RQ5 How reliable and valid is the PAICE questionnaire in measuring public perceptions of AI across diverse European populations?

Key findings

• Over 62% of respondents reported that AI has an impact on their daily lives, a 10-percentage-point increase from previous surveys, indicating growing perceived relevance.
• Despite low self-assessed knowledge, 52.3% of respondents expressed a very positive attitude toward AI, with approval dropping significantly in sensitive domains like human resources management.
• Universities and research centers were ranked as the most trusted entities for ensuring responsible AI use, surpassing national governments and tech companies.
• The PAICE questionnaire demonstrated good internal consistency and adequate validity, supporting its use in measuring public perceptions of AI across awareness, attitude, and trust dimensions.
• A significant disconnect was observed between public perception and EU policy efforts, with many citizens unaware of existing regulatory frameworks and ethical guidelines.
• The study identified three key social trends: uninformed optimism toward AI, disengagement from public AI policy, and low participation in AI education—each posing risks to the development of a trustworthy and inclusive AI ecosystem.

Figure 2: Responses to Likert scale items associated with attitude. Low-scale values (1 and 2) are represented by red colors, while high-scale values (4 and 5) are represented by blue colors. Item Q8 is split in sub-items regarding the attitude towards AI in ten different sectors.