🧪 This platform is in early beta. Features may change and you might encounter bugs. We appreciate your patience!
distinction_bias_enhanced
The tendency to view two options as more different when evaluating them simultaneously than when evaluating them separately. Joint evaluation amplifies small differences that would be imperceptible or irrelevant in actual experience.
When comparing two TVs side by side in a store, a small resolution difference seems crucial. At home with only one TV, the difference would be unnoticeable.
When choosing between two job offers side by side, a candidate fixates on a $2,000 salary difference that, evaluated separately, they would have considered trivial relative to the overall compensation.
A shopper comparing two nearly identical laptops in a store agonizes over a minor weight difference of 200 grams — a distinction they would never notice in daily use if they had only ever owned one of the two models.
Binary (yes/no) questions an LLM must answer to identify this aspect:
Are two or more options being evaluated simultaneously (joint evaluation)?
Type: binaryDo differences between options appear larger in joint evaluation than they would in separate evaluation?
Type: binaryWould the person's preference change if they could only see one option at a time?
Type: binaryThe tendency to view two options as more different when evaluating them simultaneously than when evaluating them separately. Joint evaluation amplifies small differences that would be imperceptible or irrelevant in actual experience.
Side-by-side comparison activates contrast detection, making even trivial differences salient. In actual use, these differences vanish because there is no reference point.
Evaluate options in the context of actual use, not in artificial comparison settings. Ask: will this difference matter in my daily experience?
Consumer purchasing decisions, job candidate selection, real estate comparisons, and performance evaluations.
Use these tools to detect, analyze, or train this aspect.