Patanjali's five kleshas (afflictions) as a framework for identifying and addressing deep structural biases embedded in AI training and knowledge systems.
The kleshas—avidya (ignorance), asmita (ego), raga (attachment), dvesha (aversion), and abhinivesha (fear of change)—represent fundamental patterns that distort perception and knowledge in both minds and systems. Applied to AI, these five afflictions map onto structural biases that persist despite technical efforts to remove them. Avidya manifests as incomplete training data and blind spots in model design. Asmita appears when developers believe their frameworks are neutral when they encode particular worldviews. Raga shows up as attachment to familiar patterns, limiting innovation. Dvesha creates aversion to inconvenient data that challenges comfortable narratives. Abhinivesha appears as resistance to upgrading systems that no longer serve. Recognizing these patterns is essential for building genuinely improved knowledge systems. Rather than treating bias as a technical problem to be solved once, Patanjali suggests understanding it as a recurring human tendency that requires ongoing awareness and discipline. For teams building AI, this framework offers a psychological and philosophical language for addressing why bias persists despite good intentions, pointing toward cultural and structural shifts needed alongside technical improvements.
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