Recent years have witnessed a notable shift in public discourse surrounding artificial intelligence (AI) as a solution to the global challenge of aging populations. While earlier online discussions were optimistic about AI's potential, this optimism has seemingly waned. This article explores the reasons behind this shift, focusing on the fundamental difference between human and machine needs and the limitations of AI in addressing complex societal problems like population aging.
The once-promising narrative of AI resolving the challenges of an aging population seems to have faded into obscurity. Online discussions and fervent support for this concept, once prevalent, have seemingly disappeared. The reason for this shift lies in a deeper understanding of the complexities involved, particularly the fundamental differences between human and machine needs.
AI, while capable of automating tasks and enhancing efficiency in various sectors, cannot replicate the cyclical nature of human needs and desires. An AI-powered store, for example, might effectively manage inventory and reduce labor costs. However, it cannot replace the fundamental consumption patterns of humans. An automated vending machine, although eliminating the need for human staff, cannot replicate the continuous cycle of human consumption—from food and water to personal care and entertainment. This is because machines, unlike humans, do not have inherent needs beyond the initial programming.
The core of the problem lies in the insatiable nature of human needs. While AI can address immediate needs and optimize resource allocation, it cannot address the fundamental cyclical nature of human consumption. A person's needs are not one-time purchases. A human, unlike a machine, requires constant sustenance and replenishment, and the satisfaction of those needs is not a one-time transaction. The example of historical figures like Empress Dowager Cixi and Emperor Xuanzong, despite their lavish lifestyles, highlights this crucial point. Their opulent circumstances, while fulfilling immediate needs, did not guarantee long-term survival or the satisfaction of future needs.
The comparison further illustrates the limitations of AI in addressing complex societal problems. AI can optimize and automate, but it cannot anticipate or replicate the intricate interplay of needs and desires that shape human behavior and drive economic cycles. The cyclical nature of human consumption, with its inherent demands for continual replenishment, is a critical factor that AI cannot address.
In conclusion, the decline in the narrative of AI as a solution to population aging reflects a pragmatic understanding of the limitations of technology in addressing complex human needs. While AI can certainly play a role in optimizing various sectors, it cannot substitute for the fundamental biological and social requirements of a growing aging population. A more holistic approach, one that acknowledges the intricate interplay of human needs and technological advancements, is crucial to effectively addressing the challenges of an aging global population.
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