Systems thinking vs Artificial Intelligence

Systems Thinking vs. Artificial Intelligence (AI)

Feature Systems Thinking Artificial Intelligence
Nature Conceptual, human-centered framework Computational, data-driven algorithms
Purpose Understanding complexity and dynamics Automating or enhancing tasks through pattern recognition
Input Mental models, qualitative and quantitative data Primarily quantitative data
Focus Whole-system behavior, feedback, and structure Prediction, classification, optimization
Adaptability Based on experience, reflection, and interpretation Based on data availability and algorithmic design

They are not mutually exclusive. AI can be enhanced by systems thinking to address biases, account for systemic consequences, and improve ethical governance.