Unwilling or unable? Using three-dimensional tracking to evaluate dogs' reactions to differing human intentions

Area of Science:

• Canine cognition
• Animal behavior
• Human-animal interaction

Background:

• Understanding nonhuman animal cognition is crucial for human-animal interaction.
• The unwilling-unable paradigm assesses sensitivity to intentions behind actions.
• Previous studies suggest some animals differentiate intentions, but evidence in dogs is debated.

Purpose of the Study:

• To investigate if dogs (Canis familiaris) can differentiate between human unwillingness and inability to provide a reward.
• To apply machine learning-driven 3D tracking for detailed behavioral analysis in dogs.

Main Methods:

• Utilized the unwilling-unable paradigm with 96 pet dogs across two experiments.
• Employed machine-learning driven three-dimensional tracking for precise behavioral analysis.
• Recorded dog reactions to experimenters demonstrating unwillingness versus inability to transfer food.

Main Results:

• Dogs showed significantly more impatient behavior towards experimenters signaling unwillingness compared to inability.
• These findings were consistent across two independent dog samples.
• Machine-learning tracking data corroborated the behavioral observations.

Conclusions:

• Dogs can reliably distinguish between actions based on the experimenter's intention (unwillingness vs. inability).
• The results provide robust evidence for sophisticated intention-reading abilities in dogs.
• Despite differentiating intentions, dogs did not exhibit a subsequent preference between experimenters.