Modern Assessments of Intelligence Must Be Fair and Equitable

Area of Science:

• Psychology
• Educational Measurement
• Cognitive Science

Background:

• Traditional intelligence assessments have historically perpetuated inequality and injustice.
• There is a critical need to re-evaluate assessment practices for diversity, equity, and inclusion (DEI).

Purpose of the Study:

• To identify DEI concerns in current intelligence assessment practices.
• To propose a modern, non-general intelligence (g) framework for equitable assessments.
• To review empirical evidence supporting non-g models for fairness.

Main Methods:

• Analysis of diversity, equity, and inclusion issues in assessment.
• Definition of a non-g, emergent intelligence view using process overlap theory.
• Review of empirical data, particularly sub-measures of g, to support the proposed model.

Main Results:

• Identified significant DEI challenges in conventional intelligence testing.
• Proposed process overlap theory as a foundation for a non-g emergent intelligence model.
• Empirical evidence suggests non-g models can enhance fairness in intelligence evaluation.

Conclusions:

• Shifting towards non-g, emergent intelligence models is crucial for equitable assessment.
• Researchers and practitioners should adopt strategies that promote fairness and inclusivity.
• The process overlap theory offers a promising avenue for developing more just intelligence measures.