Edward Quince's Wisdom Bites: AI, Productivity, and the Redefinition of Human Value

As artificial intelligence rockets to the forefront of economic discourse, it compels us to re-examine fundamental questions about productivity, the nature of work, and the very essence of human value.

The sources highlight that real economic growth "can come from only two sources - more worker hours and greater efficiency in output per hour". AI is positioned as a primary driver of this efficiency, with significant capital expenditure occurring in the field, promising increases in "productive processes". However, this transformative power also brings profound questions. As Christine Lagarde noted, AI, alongside remote work and green energy, represents "fundamental changes in economic relationships" that can lead to "supply side disruptions" and "relative price changes amongst sectors".

A critical concern is the impact of readily available AI on human cognition and the value of knowledge. Simon Winchester warns of "Digital Amnesia," where "today's all-too readily available stockpile of information will lead to a lowered need for the retention of knowledge, a lessening of thoughtfulness, and a consequent reduction in the appearance of wisdom in society". If "with all the new AI technology and GPT's will we ever need to retain any information?", then what becomes the purpose of traditional learning? Some even suggest that "in the AGI era, the only defensible reason for universities to remain in operation is to offer students an opportunity to learn from faculty whose expertise surpasses current AI".

For individuals, the message is clear: "If you do average work for average pay, AI is going to be able to do it cheaper than you," as Seth Godin observes. This "double disruption" from AI and institutional instability raises worries about the very existence of "careers as we know them in 5 years". Our blog highlights the paradox of AI in finance, potentially "making junior bankers’ lives easier in the short term, but undermining their development in the long term" by automating core learning tasks.

The financial implications are also being scrutinized. While AI promises efficiency, the "cost of serving LLM-generated answers" is "a LOT more" than traditional search, casting doubt on the sustainability of existing "search cash cow" models. As AI reshapes markets and industries, the wise approach involves focusing on "ambition," understanding "customer problems deeply," and leveraging what AI can do. It necessitates continuous adaptation, discerning genuine productivity from "hype," and investing in skills that transcend mere information retention.