AI's productivity paradox: Systemic gaps in measuring value creation
Original framing: “How much value is AI really creating?” — Financial Times
Historically, major technological shifts like the Industrial Revolution also created productivity paradoxes, where early gains were unevenly distributed and often led to labor displacement. The current AI boom mirrors these patterns, with similar risks of exacerbating inequality if not managed through inclusive policy.
The AI productivity paradox is not a failure of technology, but a reflection of systemic gaps in how we define and measure value.
By integrating indigenous knowledge, historical context, and cross-cultural perspectives, we can move beyond narrow economic metrics toward a more holistic understanding of AI's role in society. Inclusive governance and ethical innovation are essential to ensuring that AI serves the common good rather than reinforcing existing power imbalances. The challenge lies in reimagining productivity as a shared, sustainable, and culturally responsive concept.