Development and validation of the AI attitude scale (AIAS-4): a brief measure of general attitude toward artificial intelligence

Grassini, Simone

doi:10.3389/fpsyg.2023.1191628

Cited by 15 publications

(11 citation statements)

References 87 publications

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“…Another reason to use a structured questionnaire is that it can get detailed information about the AI technologies used, how well they work at finding and responding to threats, and the problems that come with integrating AI [30]. This methodological approach is pivotal for generating actionable insights that can guide the development of more effective AI-powered cybersecurity solutions.…”

Section: Methodsmentioning

confidence: 99%

The Role of AI In Enhancing Threat Detection and Response in Cybersecurity Infrastructures

Onih,

Sevidzem,

Adeniji

2024

IJSMR

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Introduction: Considering growing cyber risks, this study aims to investigate how artificial intelligence (AI) can enhance threat detection and response rates, thereby enhancing cybersecurity systems. It specifically focuses on addressing the urgent requirement for enhanced defence strategies. Methodology: The research utilised a quantitative approach to analyse data gathered from cybersecurity professionals. Surveys are carried out to assess how well AI technologies work in ensuring safety, the challenges faced, and their practical use in various industries. Discussion: The findings show that artificial intelligence, specifically utilizing machine learning and deep learning, significantly improves the capability to detect and mitigate potential risks. Despite this, there are major challenges including high implementation costs, lack of skilled employees, and concerns about data security that act as significant barriers. The study also highlights the broad consensus on the transformative power of AI in revolutionizing cybersecurity, despite the existence of these challenges. Conclusion: It has become obvious that AI technologies have the capability to improve cybersecurity practices through improved identification and response to cyberattacks. However, to make this work, allocating strategic resources for AI infrastructure development, providing extensive training for professionals, and thoroughly assessing ethical implications are crucial.

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Section: Methodsmentioning

confidence: 99%

The Role of AI In Enhancing Threat Detection and Response in Cybersecurity Infrastructures

Onih,

Sevidzem,

Adeniji

2024

IJSMR

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“…General Attitude toward Artificial Intelligence. The Attitude toward Artificial Intelligence Scale (AIAS) assesses public attitudes toward artificial intelligence (AI) [ 49 ]. This scale, validated in the UK and USA, consists of four items that capture individual beliefs about the influence of AI on their lives, careers, and humanity in general [ 49 ].…”

Section: Methodsmentioning

confidence: 99%

“…The Attitude toward Artificial Intelligence Scale (AIAS) assesses public attitudes toward artificial intelligence (AI) [ 49 ]. This scale, validated in the UK and USA, consists of four items that capture individual beliefs about the influence of AI on their lives, careers, and humanity in general [ 49 ]. The AIAS is structured around a single dimension, reflecting a composite attitude toward AI, including perceived utility and potential impact on society.…”

Section: Methodsmentioning

confidence: 99%

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Adaptation and Psychometric Properties of an Attitude toward Artificial Intelligence Scale (AIAS-4) among Peruvian Nurses

Morales-García,

Sairitupa-Sanchez,

Morales-García

et al. 2024

Behavioral Sciences

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Background: The integration of Artificial Intelligence (AI) into various aspects of daily life has sparked growing interest in understanding public attitudes toward this technology. Despite advancements in tools to assess these perceptions, there remains a need for culturally adapted instruments, particularly in specific contexts like that of Peruvian nurses. Objective: To evaluate the psychometric properties of the AIAS-4 in a sample of Peruvian nurses. Methods: An instrumental design was employed, recruiting 200 Peruvian nurses. The Attitude toward Artificial Intelligence in Spanish (AIAS-S), a cultural and linguistic adaptation of the AIAS-4, involved data analysis using descriptive statistics, confirmatory factor analysis (CFA), and invariance tests. Results: The Confirmatory Factor Analysis (CFA) confirmed a unidimensional factor structure with an excellent model fit (χ2 = 0.410, df = 1, p = 0.522, CFI = 1.00, TLI = 1.00, RMSEA = 0.00, SRMR = 0.00). The scale demonstrated high internal consistency (α = 0.94, ω = 0.91). Tests of invariance from configural to strict confirmed that the scale is stable across different demographic subgroups. Conclusions: The AIAS-S proved to be a psychometrically solid tool for assessing attitudes toward AI in the context of Peruvian nurses, providing evidence of validity, reliability, and gender invariance. This study highlights the importance of having culturally adapted instruments to explore attitudes toward emerging technologies in specific groups.

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“…The AI Attitude scale (AIAS-4) developed by Grassini (2023) was utilized for data extraction. The scale consists of 04 items.…”

Section: Tools Usedmentioning

confidence: 99%

Unveiling the Attitudes of University Students Toward Artificial Intelligence

Hajam,

Gahir

2024

Journal of Educational Technology Systems

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The research seeks to delve into and comprehend the attitudes of university students regarding artificial intelligence (AI) and to identify potential factors influencing these attitudes. The research employs a descriptive research design with a quantitative approach. A sample of 240 university students, including both males and females, was selected using simple random sampling. The AI Attitude scale (AIAS-4) developed by Grassini in 2023 was used to collect the data. Statistical techniques, such as “descriptive analysis,” “indeoendent sample t-test,” “one-way ANOVA,” and “post hoc” test were used to analyze the data. The findings indicate that there was no statistically significant difference in attitudes toward AI between male and female university students. Furthermore, our research has substantiated a significant difference in attitudes toward AI among university students specializing in the fields of arts, science, and commerce. The findings of this study suggest that science students displayed a significantly more positive attitude toward AI when compared to their counterparts in the Arts and Commerce streams. Moreover, we examined the impact of educational level on AI attitudes and found no significant difference in attitudes across different educational levels among university students.

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Development and validation of the AI attitude scale (AIAS-4): a brief measure of general attitude toward artificial intelligence

Cited by 15 publications

References 87 publications

The Role of AI In Enhancing Threat Detection and Response in Cybersecurity Infrastructures

The Role of AI In Enhancing Threat Detection and Response in Cybersecurity Infrastructures

Adaptation and Psychometric Properties of an Attitude toward Artificial Intelligence Scale (AIAS-4) among Peruvian Nurses

Unveiling the Attitudes of University Students Toward Artificial Intelligence

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