Lachlan Phillips, a prominent voice within the "ex-accelerationist" (exo/acc) movement, has articulated a vision for a post-capitalist economic model he terms "collaborativism." Phillips posits that transcending the limitations of capitalism does not necessitate collectivism, but rather a system built on collective benefits achieved through largely collaborative engagement. This concept, outlined in a recent social media post, points to open source development and neural networks as prime examples of this new paradigm.
"I think the transcending the shortcomings of capitalism doesn't mean collectivism. It means collaborativism," Phillips stated in his tweet. He elaborated, "Collective benefits through largely collaborative engagement. Open source is an example of this. As are neural networks. Individual pursuits within massively collaborative pools."
This perspective resonates with the growing discourse around decentralized AI and collaborative economy models, which aim to distribute power and value more equitably. Projects like Sahara AI and Aevir are actively building platforms where AI development, ownership, and benefits are shared among participants, moving away from centralized control. These initiatives often leverage blockchain technology to ensure fair compensation and transparent attribution for contributors, addressing concerns about data ownership and the concentration of power.
Phillips further suggested that neural networks, at a philosophical level, represent a system where individuals collaborate within a shared pool, allowing for diverse contributions without "forking the underlying codebase." In such a system, he argues, traditional competition becomes largely irrelevant as individual contributions can be made and remunerated seamlessly. This echoes the sentiment in decentralized AI platforms that incentivize contributions of data, compute power, and expertise through tokenized rewards.
The exo/acc thinker envisions an economic environment where "rapid consensus through mutual dependency" replaces central command, fostering "ecological conditions for market economies to reach homeostasis without predatory capitalism and without central control." This aligns with the goals of decentralized AI, which seeks to mitigate risks associated with centralized AI, such as limited data access, inflexible models, and a lack of transparency and accountability. The movement aims to create a more resilient and open digital future where innovation is driven by a global community rather than a few tech monopolies.