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Assessment · Attitude and trust surveys

General Attitudes towards Artificial Intelligence Scale (GAAIS)

What positive and negative views of AI do staff hold?

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Who answers Staff, each about their own views
How long 20 questions, or 10 in the short form
Can you use it? Free to use, ask before changing
Testing Strong

Tested in several studies, including by teams other than its authors or in other languages, and the results held up.

In short

A 20-question survey, with a 10-question short form, that scores positive and negative views of AI separately. It is the best-tested attitude scale here, but translating it needs the authors’ consent.

For whoever runs the assessment: an HR or operations lead, an internal project team, or an outside consultant.

What it measures

Two things, scored separately:

  • Positive views: AI as useful, 12 questions.
  • Negative views: concerns about AI, 8 questions.

The short form keeps the two scores in 10 questions.

How to use it

  1. If your staff work in English, Spanish or Turkish, use the published version unchanged.
  2. Report the positive and negative scores side by side, by team.
  3. For any other language, write to the authors first. If consent is slow or refused, use an openly licensed scale.

What it does not measure

  • AI at work. The questions are about AI in general.
  • Trust in a particular system.

How it was tested

  • The first study built the scale and showed that the questions split into the two parts.
  • A second study by the same authors confirmed that structure on new data.
  • The short form was tested in 2026, including on 500 people chosen to mirror the UK population.
  • A Spanish version was tested on 644 people. The two-part structure held, and the questions worked the same way across groups.
  • A Turkish version has also been published.

That is more testing, by more teams, than any other attitude scale in this section.

Licence and access

The full scale is in the appendix of the 2020 article. The licence, CC BY-NC-ND 4.0, lets you share the work unchanged for non-commercial purposes. It does not let you publish changed versions, and a translation is a changed version. A consultancy that sells assessments would also need consent for commercial use.

Alternatives

Other assessments with a similar job, and when to prefer each.

Practices that use it

The details

Testing
Strong Tested in several studies by its authors, including a sample built to mirror the UK population. Separate teams tested Spanish and Turkish versions. The Spanish study confirmed the same two-part structure.
Looks at
Person
How the answers are collected
A survey answered by each person about their own views.
Length
20 questions; short form 10 questions
Cost
Free for non-commercial use
Licence
CC BY-NC-ND 4.0You may use the published version unchanged for non-commercial purposes, with credit. Publishing a translation or a changed version needs the authors’ consent.
Languages
English, Spanish, Turkish
By
Schepman and Rodway, 2020

Sources

  1. Schepman and Rodway (2020). Initial validation of the general attitudes towards Artificial Intelligence Scale. Computers in Human Behavior Reports. doi:10.1016/j.chbr.2020.100014
  2. Schepman and Rodway (2022). The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust. International Journal of Human–Computer Interaction. doi:10.1080/10447318.2022.2085400
  3. Schepman and Rodway (2026). Validation of the Short General Attitudes Towards Artificial Intelligence Scale: The Short GAAIS-10. International Journal of Human–Computer Interaction. doi:10.1080/10447318.2025.2610446
  4. Asef Arees, Guntín, Fariña Rivera and Novo Pérez (2025). Spanish Adaptation and Validation of the General Attitudes Towards Artificial Intelligence Scale (GAAIS). European Journal of Investigation in Health, Psychology and Education. doi:10.3390/ejihpe15110230

Related studies on this site

  • The same AI pressure can raise or lower willingness to use AI Chang, Zhang, Cai and Guo (2024). Does AI-Driven Technostress Promote or Hinder Employees’ Artificial Intelligence Adoption Intention? A Moderated Mediation Model of Affective Reactions and Technical Self-Efficacy. Psychology Research and Behavior Management, 17, 413–427.
  • Ready for change, resistant, or both? Repovš, Drnovšek and Kaše (2019). Change Ready, Resistant, or Both? Exploring the Concepts of Individual Change Readiness and Resistance to Organizational Change. Economic and Business Review, 21(2).