The Ghost in the Machine
AI, Materialism, and the Future of Industry
The technological trajectory of a society is a product of its existing material conditions; the shape of Artificial Intelligence is molded by the inescapable gravity of the material world. To understand the divergent development paths of different civilizations, we must examine their existing material conditions. As Marx reminded us, "It is not the consciousness of men that determines their existence, but their social existence that determines their consciousness."
The integration of any revolutionary technology isn't merely a neutral act of "innovation" dictated by the dreams of engineers, as Silicon Valley would have us believe. It is a dialectical process that's determined by the existing relations of production and the level of development of the productive forces. AI, like any tool, seeks material niches within the prevailing economic structure. Its application is determined by the immediate, concrete needs and constraints of the society that births it. "The hand-mill gives you society with the feudal lord; the steam-mill society with the industrial capitalist," Engels observed. Today, the neural network reveals the contours of the society that wields it.
Decades of deindustrialization and the triumph of finance-led capitalism have left the US productive base profoundly impoverished, with manufacturing's share of GDP and employment being a shadow of its mid-20th century peak. The dominant sectors are finance, services, information, and consumption. As such, the immediate, overwhelming material reality for capital presents a scarcity of large-scale, integrated physical production processes to optimize, coupled with immense pressure to automate high-wage cognitive and service labor and extract new rent from digital platforms.
Faced with a desert of tangible industry, capital necessarily channels AI into the fertile oases that remain, such as the vast, high-value service and information sectors. Generative AI in the form of chatbots, code assistants, and design tools thrives here. These are the abundant niches for automating knowledge work like writing, coding, and design, as well as for personalizing advertising, optimizing financial algorithms, and creating digital content for attention economies. These applications require minimal integration with physical infrastructure, such as factories and assembly lines.
Returns are faster and more visible in software and services with low marginal costs, fitting the short-term profit cycle dominant in US finance capital. Automating a $150k designer is more immediately lucrative in this context than optimizing a factory line that has been largely offshored. The focus on short-term gains reinforces the underlying contradiction found in the detachment of the dominant economic engine from the production of tangible use-values. It creates a society of "digital phantoms," where a virtual economy masks a hollowed-out material base, deepening inequality and social fragmentation.
It’s a stark contrast with a society whose material reality is rooted in industrial production. China, for instance, stands as the world's undisputed manufacturing heartland. Its material reality is defined by a vast, complex, and ever-expanding industrial base with factories, power grids, railways, agricultural systems, and burgeoning advanced R&D. Here, the imperative for "high-quality development" is paramount for the sustained improvement of the standard of living for the working majority.
Within this crucible of industry, AI finds additional, materially necessary niches not present in a financialized economy like the US. Here, AI becomes a tool for survival and advancement within the existing productive structure, a strategy that many Chinese people are optimistic about. As Dr. Wong, the founder of Alibaba Cloud, notes, the Chinese market acts as a crucial "test bed" that allows for "millions of things" to be explored, enabling the rapid testing and refinement of new technologies to make them market-ready. For example, AI is being used to maintain the world's largest high-speed railway system and to manage the country's high-voltage power lines via specialized robotics. In biomanufacturing, an AI-powered system now predicts and controls fermentation processes, promoting efficiency where engineers once had to monitor production lines 24/7. AI also enables precision agriculture, with algorithms helping to sow and cultivate crops to ensure food security. Even in healthcare, AI is being applied to accelerate drug discovery. There is broad application of AI across different sectors, from factory robots to industrial upgrades, demonstrating China's focus on refining and empowering its colossal industrial machinery.
Guided by the maxim, "Seek truth from facts," and the Party's role in directing development, the state actively shapes the material conditions in a way that focuses production on direct use-value. It invests in industrial IoT, 5G infrastructure, and sets strategic priorities (e.g., "Made in China 2025") that create the very niches AI fills. Profit is sought, but within the framework of national industrial development, forging a dialectical unity of state direction and market mechanisms that is at the core of China's path of development. The innovation cycle is a collective effort, as Dr. Wong explains it's "not one single company, but it's an entire ecosystem, an entire country's stubborn mindset to move on." He suggests that this collective effort is what makes the ecosystem healthy and competitive.
The contradiction between the scale and complexity of China's industry and the limits of human management creates a natural niche for tools that can analyze vast amounts of data and see patterns that humans would otherwise miss. This is especially true as the country's massive build-up of wind and solar power continues to break records, leading to a nosedive in power prices for factories. AI becomes a conduit, amplifying human capacity within the physical productive process, aiming for qualitative leaps in productive power. China's approach to AI aligns with Engels' view of technology as the lever for human emancipation through the mastery of nature, and is now a focus of universities as well.
The divergence in the way new technology is developed does not stem from culture, ideology, or even the inherent nature of AI itself. It is the inescapable consequence of the differing structure of the productive forces that form the material bedrock of each society. The US, with its deindustrialized landscape, must seek AI's value in the realm of information and services, as it is the only large-scale terrain left. China, with its colossal, active industrial machinery, deploys AI to refine and empower that machinery because it is the most urgent material need. "The mode of production of material life conditions the general process of social, political and intellectual life," Marx declared. The AI we see is the ghost in the machine of our actual, existing economic structures. Our future is built, first and foremost, on the ground beneath our feet.