AI’s existential risk is a pressing concern that continues to perplex the tech world. While debates about dystopian scenarios persist, there is a more immediate issue at hand: the emergence of semi-autonomous AI agents making independent decisions. These agents, found in trading robots and even language generation models like ChatGPT, are plagued by practical problems such as inaccurate citations, lazy decision-making, and unpredictability. This lack of trust in AI systems and the machine learning algorithms behind them has had serious repercussions, as seen in cases like Minnesota’s lawsuit against UnitedHealth Group and the creditworthiness assessment industry’s blunders.
Recognizing the importance of addressing this trust gap, experts propose the creation of an inference economy as a solution. This innovative concept offers a formal arena for rectifying flawed AI outputs. The inference economy revolves around a marketplace for verifiable machine intelligence, comprising two layers. Firstly, a tournament-style competition allows data scientists and modelers to improve upon existing ML models and earn a share of the generated revenue. Secondly, an open marketplace enables the consumption of verified streams of inferences.
The inference economy brings together various concepts, including Web3 validation staking, streaming payments, and zero-knowledge proofs. By combining these ideas with competitive ML models, the inference economy offers a trustless system where AI agents or developers can select streams of inferences from a diverse range of community-vetted machine learning models. This significantly reduces the risk associated with unreliable data, as bad streams can be replaced with better ones in the marketplace. Consequently, AI agents can operate based on well-screened and trusted streams of inferences.
The significance of the inference economy lies in its ability to address the pivotal issue of AI accountability. Trustless systems demand robust technologies and heightened security measures, making the integration of Web3 design philosophies essential. Grounded in verified machine intelligence and a pool of brilliant minds comprising data scientists and modelers, the inference economy provides a tangible solution to concerns about AI’s potential negative impact.
At its core, the inference economy focuses on creating a marketplace that offers high-performing and verifiable ML models for businesses to deploy. Whether it’s credit scoring, NFT recommendations, crypto price predictions, or sports analysis, organizations can derive immense value from an inference economy that restores trust in machine intelligence.
In conclusion, the inference economy paves the way for a future where AI is held accountable and can be trusted to provide reliable and secure inferences. By commercializing the pursuit of honest and verifiable machine learning production, this innovative approach ensures that organizations can harness the full potential of AI while mitigating the risks associated with its use. With its strong foundation in verified machine intelligence and a community-driven marketplace, the inference economy offers a practical solution to the challenges of AI in today’s evolving technological landscape.
