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IB DP Psychology — Technology | SL & HL | Paper 1
🎯 Learning Intentions By the end of this note, you will be able to:
- Define human development models, artificial intelligence, and machine learning using IB-aligned terminology.
- Explain how AI systems are designed to replicate or simulate stages of human cognitive and emotional development.
- Describe the role of developmental psychology models (such as Piaget's stages and Vygotsky's sociocultural theory) in informing AI design.
- Evaluate research evidence examining the relationship between AI behaviour and human developmental trajectories using supporting and opposing studies in ACAS format.
- Apply concepts of AI and human development to a real-world case study from cognitive and sociocultural perspectives.
- Discuss the extent to which AI systems genuinely replicate human developmental processes or merely simulate surface-level behaviours.
- Analyse the topic using relevant concept areas: Bias, Causality, Perspective, and Responsibility.
Introduction & Context
Imagine watching a toddler learn to recognise a dog. At first, they might call every four-legged animal a "dog" — a cat, a horse, even a toy bear. Over time, through repeated exposure and correction, they refine their understanding. Now consider a modern AI image classifier: it is trained on thousands of labelled photographs, gradually adjusting its internal parameters until it too can reliably distinguish a dog from a cat. The parallel is striking. Both the child and the AI system appear to be "learning" — but are they doing the same thing?
This question sits at the heart of one of the most fascinating intersections in contemporary psychology: the relationship between artificial intelligence and models of human development. Developmental psychologists have long sought to map the stages through which humans acquire knowledge, language, social understanding, and moral reasoning. Now, AI researchers are drawing on these very same models — not just as inspiration, but as blueprints. Understanding how and why this happens, and what it reveals about both human minds and machine systems, is the focus of this topic.
🔍 Analogy — Scaffolding a Building Think of human development as the construction of a building. The scaffolding that supports each new floor represents the social and environmental support a child receives — what Vygotsky called the Zone of Proximal Development. When engineers design AI learning systems, they often build in a similar kind of scaffolding: the system cannot jump straight to complex tasks, so it is guided through progressively harder challenges with feedback at each stage. Just as a building cannot skip floors, neither the child nor the AI can skip developmental steps without the foundations collapsing.
Core Concepts
Before we can evaluate whether AI genuinely mirrors human development, we need to understand what psychologists mean when they talk about "human development models." These are theoretical frameworks that describe the sequence, mechanisms, and conditions under which human cognitive, social, and emotional capacities emerge from infancy through adulthood. The most influential of these models were not designed with AI in mind — yet they have become central reference points for AI researchers attempting to build systems that learn, adapt, and reason.
📖 Key Definition — Human Development Models Human development models are theoretical frameworks in psychology that describe the systematic, sequential changes in cognitive, emotional, social, and moral capacities across the lifespan. Key models include Piaget's stage theory of cognitive development,