Elon Musk is an exceptionally gifted engineer and entrepreneur. Nevertheless, that doesn’t guarantee that his visions, when put into practice, will benefit all humanity. One example is Starlink and related ideas, such as building data centres in outer space. These technological assemblages may indeed vastly enhance humanity’s capacity to process information and communicate, while resolving energy bottlenecks on Earth. Still, there are also numerous negative sides, such as the rapid growth of space debris, with associated risks of collisions jeopardising the functions of the entire system of satellite observation of planetary processes, the light noise even disturbing the sights of stars and Earth-bound space observation, or the concentration of economic power in the hands of one individual. How can we find a proper balance between the positive and the negative sides of such technological progress and prowess?
The key factor in enabling the explosive growth of certain technologies is always finance. Financial investors value growth and profit and are therefore willing to put their money into projects. The credit-driven dynamics of capitalism have often been identified as one of its most problematic and often even destructive forces, since it powers cycles of booms and busts. However, a specific technological trajectory often remains, launched during the boom (such as railroads in the 19th century). At the same time, alternatives may have been starved, as with electric cars at the beginning of the 20th century.
Hence, the question is whether finance can become a governance mechanism that considers humanity’s wider interests and the common good. The idea of controlling finance to overcome the ills of capitalism is an old idea among socialist thinkers. Let me mention a lesser-known Chinese economist (to Western readers only, of course), Sun Yefang. China’s most prestigious economics prize is named after him. In the 1950s, he developed a theory in which the government would plan social net investment, mainly through financial channels, while the market would reign in most other sectors. These ideas were revived in the early 1980s when he was rehabilitated after the Cultural Revolution. Clearly, today the Chinese government pursues a similar strategy through its huge state-owned banks and other forms of financialised economic planning, such as special financial vehicles to fund specific industries and technologies.
Liberal economists mostly think that the government cannot know better than the market in selecting and nurturing new technologies. That may be true, but I surmise that in the coming age of AI, this verdict may deserve a second thought. These economists often treat the market as a giant distributed computer that is more powerful than humans at processing information. In this sense, the market looks like a human-technology hybrid that works like a distributed network akin to AI. This raises the possibility that socialist planning might adopt an AI-based approach.
In the 1950s and 1960s. many economists in the East and West thought that, in principle, mathematical models of the economy could apply to both planning and markets. These ideas were refuted in the famous “socialist calculation debate”. Now, the Soviets and other planners, for example, in India, imagined giant models of the economy hosted on supercomputers. What if we imagine a government platform that hosts AI agents that continuously screen markets and technological progress, produce forecasts, and identify investment recommendations? In China today, such a platform may guide the state-controlled financial sector’s credit allocation decisions. The AI differs from old socialist planning and is, in fact, analogous to the market as a distributed computer: the AI is itself an evolutionary process of discovery. The difference from the market is that a socialist planner can prompt the AI with certain preferences. For example, in the case of Musk’s space ambitions, the AI, different from Musk and the funding investors, may give stronger weight to externalities such as space debris.
China could be the place where this socialist economic planning by AI emerges soon. The planner would no longer set financial and economic decisions directly. Still, the AI would follow markets in real time while intervening through a state-owned financial sector powerful enough to shape market trajectories down to the grassroots level, such as selecting and funding start-ups. At the same time, the government does not claim superior knowledge of markets and technologies, only that it has an idea of what is in the public interest. China has many advantages that make such a system work, such as access to huge data pools on the mega-platforms of Chinese tech companies. Socialist economic planning 2.0 would work without a human planner and operate like an artificial market, doubling the real market.
The result would be a technosphere that governs itself. Personally, I would see this as a dystopian future. I wouldn’t recommend adopting this path; instead, I’d heal the flaws of the capitalist system by reintroducing full personal responsibility for economic decisions and turning away from the institutional legacies of the 19th century: limited liability and the corporation as a legal person. But this is a different story, and perhaps less probable than the trajectory we already see emerging in China.
Maybe the economy is too complex for even the best AI to know and hence control using anything approaching model/prediction-based regimes?
Have you written about “full personal responsibility”?
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