The goal of this project is to find evidence of a universal mind and discover if key human cognitive biases are adaptive. We aim to do this by comparing the core features and biases of qualitative probabilistic inferences across humans, kea, and rats.
To achieve this, my objectives are to test if these three species show similar information processing patterns when solving innovative, non-verbal, probabilistic inference tasks. These tasks will explore four core aspects of probabilistic inference:
• Making statistical inferences from populations to samples: We will investigate how each species draws conclusions about individual instances based on broader statistical information.
• Updating and combining probabilistic information: We will examine their ability to adjust beliefs and integrate new data when faced with changing probabilities.
• Integrating different knowledge types to make domain-general statistical inferences: This involves assessing their capacity to combine various forms of knowledge to make broad statistical judgments.
• Using perceptions of randomness to make probabilistic predictions: We will study how they utilize their understanding of randomness to anticipate future probabilistic events.
To achieve this, I am leading an interdisciplinary team, comprising of myself as the Principal Investigator (PI), two post-doctoral researchers, three PhD students and a technician.