Group 1 - The core viewpoint of the article emphasizes that the value of cognitive labor has shifted significantly in the AI era, where traditional metrics of effort and knowledge are no longer sufficient for success [2][3][5] - The new formula for effective decision-making in a complex environment is now based on cognitive structure, judgment ability, and responsibility, rather than merely completing tasks [6][22] - Low cognitive labor is characterized by three structural deficiencies: lack of structural understanding, lack of judgment ability, and inability to take cognitive responsibility [8][9][10] Group 2 - AI is not merely replacing jobs but is consuming low cognitive areas, excelling in tasks such as information organization and template-based analysis [14][15][16] - In complex systems, low cognitive labor can even create negative value, leading to structural inefficiencies and misinterpretations of uncertainty [17][18][20] - Individuals who retain irreplaceable value in the AI era possess a complete feedback loop: positioning, judgment, accountability, and model updating, which AI cannot replicate [21][22][24] Group 3 - The valuation of cognitive labor is transitioning from a headcount model to a focus on cognitive nodes, indicating that a single clear cognitive node can outperform a low cognitive density team [23][24] - The article argues that this shift is not a reflection of coldness but rather a structural reality where value judgments are increasingly based on cognitive capability rather than effort or tenure [25][26][28]