# Spanish Adaptation and Validation of the General Attitudes Towards Artificial Intelligence Scale (GAAIS)

## TL;DR

This study adapts and validates a scale to measure attitudes toward artificial intelligence in Spanish, showing it is reliable and useful for understanding public perceptions.

## Contribution

The study provides a validated Spanish version of the General Attitudes towards Artificial Intelligence Scale (GAAIS) with confirmed reliability and validity.

## Key findings

- The Spanish adaptation of GAAIS confirmed a two-factor structure (Positive and Negative GAAIS) with good fit indices.
- The scale demonstrated adequate internal consistency and validity, including convergent and discriminant validity.
- The model's invariance was confirmed, supporting its use in assessing ambivalent attitudes toward AI.

## Abstract

Artificial intelligence (AI) is generating a profound and quick transformation in several areas of knowledge, as well as in industry and society on a global scale, and is considered one of the most significant technological advances of the present era. Understanding citizens’ attitudes toward AI is essential forguiding its development and implementation. To achieve this, valid and reliable instruments are needed to assess attitudesin different sociocultural contexts. With this objective, the General Attitudes towards Artificial Intelligence Scale (GAAIS) was adapted to Spanish. The sample comprised 644 participants: 327 men and 316 women, aged between 18 and 78 years (M = 33.06, SD = 14.91). The original two-factor structure (Positive GAAIS and Negative GAAIS) was validated using Confirmatory Factor Analysis (CFA). Both the fit indices and the internal consistency of the scale were adequate. Furthermore, the validity of the measure (i.e., convergent and discriminant) and the invariance of the model were confirmed. The analyses performed support the adequacy of the model and, therefore, the usefulness of the instrument, considering the ambivalence that people often experience regarding AI. The limitations of the study and the implications for the design of public policies and intervention strategies that promote the ethical, equitable, and socially responsible use of AI are discussed in this study.