Can AI see emotions evoked from photographs?

A study based on Russel’s circumplex model of affect using the latest LLM AI models (Google’s Gemini, Claude AI, and Meta’s Llama 4) and the OASIS dataset as baseline. Part of the Emotional Geographies project.

TL;DR: Yes! They can.

And the best observed models are Google’s Gemini.

A generalized bias across all models was to consider photos evoking a higher arousal than human evaluators. Most models also considered valence slightly more negative than the study showed, but that is in a considerably lower magnitude than arousal bias.

How well each model did with the OASIS Dataset

Here we can explore individual examples of how each model interpreted each photograph (and explanations).

Stop! ✋

No unauthorized personnel beyond this point… Dangerous code ahead

Data

Data used in this study is proceed locally, being made available within a duckdb local instance.

Model performance

Overall performance measured for each model

Model outputs

What each model outputted for each photo.

Oasis dataset

Original dataset used as baseline.

Model parameters

Graph base

Aux code to help plotting

Emotions circle

    SELECT
      -- img.photo_id
      -- , img.resolution
      -- , img.file_path as local_path
      -- , CONCAT('https://emotional-geographies-s3-bucket.s3.us-east-1.amazonaws.com/oasis_dataset/',img.file_name) as url
      count(*)
      from
      imagefile img
      left join model_output mo on
         (img.photo_id = mo.photo_id and mo.model='gemini-2.5-flash')
      where
         true
         and left(img.photo_id,5) = 'oasis'
         and mo.photo_id is null
-- limit 3