Eye Tracking and Altruism

Are traditional psychological tests giving us an overly generous view of human nature? When people make financial decisions that benefit others, do they do so out of pure altruism, or are they simply trying to keep things fair?

In a 2025 study published in Frontiers in Psychology, Qian-Hui Wang and colleagues addressed these questions by exploring how option inequality distorts measurements of Social Value Orientation (SVO)—the framework psychologists use to quantify prosocial tendencies.

Altruism Versus Fairness

In behavioral economics, prosocial choices can be shaped by two distinct motivations:

• Altruism: A participant’s willingness to give up their own money specifically to increase another person’s payout, regardless of the final income gap.
• Fairness (Inequality Aversion): A participant’s desire to minimize the income gap (the absolute payout difference |Self – Other|) between themselves and another person.

In traditional SVO measures, in which participants choose between two payout allocation pairs, these two factors are confounded. For example, if a participant chooses Option A ($98 for self / $63 for other) over Option B ($100 for self / $50 for other), standard tests classify the choice as “altruistic” because the participant sacrificed $2 of their own money. However, Option A also shrinks the inequality gap from $50 (|100 – 50|) down to $35 (|98 – 63|). Standard SVO tests cannot determine if the choice was driven by true generosity or a simple dislike for inequality, leading to potentially inflated altruism scores.

The Eye Tracking Task

To separate these motivations, researchers conducted a within-subjects experiment with 65 university students using two distinct conditions:

1. Standard SVO (Uncontrolled Inequality): Participants completed 24 standard allocation pairs where option inequality naturally varied.
2. Inequality-Controlled (IC) Condition: Researchers engineered 64 custom allocation pairs where the income gap (|Self – Other|) was kept strictly constant across both options in a trial. For instance, choosing between Option A ($71 self / $41 other) versus Option B ($53 self / $83 other). Because both options carry an identical $30 inequality gap, inequality aversion is neutralized. Choosing Option B means sacrificing $18 of your own money, so the other person gets $42 more—isolating pure altruism as the deciding factor.

High-Precision Eye Tracking: Participants completed 88 trials while an EyeLink 1000 Plus eye tracker monitored eye movements at 1,000 Hz. The researchers created Interest Areas (IAs) – one for each of the values in the two pairs, and measured total fixation count, search depth, and gaze transitions between the IAs.

Inequality Distorts Altruism Scores

When fairness was controlled, participants’ calculated altruism scores dropped significantly. This confirms that conventional SVO tests systematically overestimate generosity by confusing it with a preference for equal outcomes.

Importantly, the EyeLink eye-tracking data provided insights into the underlying cognitive process:

• Higher Cognitive Complexity: The Inequality-Controlled task induced significantly higher total fixation counts.
• Deeper Search & Option Comparisons: Participants searched more overall information and exhibited more option-wise transitions in the IC condition.

Deprived of the “fairness shortcut,” participants had to invest greater cognitive effort and engage in deeper, bottom-up information processing to trade off personal gain against the other person’s payout.

Standard psychological measures frequently mistake a preference for equal outcomes for genuine generosity. By combining inequality-controlled tasks with high-precision eye tracking, researchers proved that controlling for fairness reveals true altruistic tendencies and the deeper cognitive effort required to make prosocial choices.

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