As we enter 2024, the central debate surrounding generative artificial intelligence (AI) revolves around the pace of innovation. The divide between those advocating for effective accelerationism (e/acc) and those supporting deceleration (decels) has become increasingly pronounced. Effective accelerationists believe in pushing technology and innovation as fast as possible, envisioning artificial general intelligence (AGI) that can revolutionize human life positively. Prominent figures like venture capitalist Marc Andreessen and Alphabet and Google alum Guillaume Verdon champion this techno-optimistic perspective.
On the other side, proponents of deceleration, concerned about the unpredictable risks of AI, emphasize the need for caution and slowing down progress. The AI alignment problem is a critical aspect of this debate, addressing the potential scenario where AI becomes so intelligent that humans lose control. Organizations like the Machine Intelligence Research Institute (MIRI) focus on aligning AI systems with human goals to prevent existential risks.
Government officials and policymakers are taking notice of the potential dangers associated with AI. The U.S. and the U.K. have introduced measures to establish standards for AI safety and security. President Biden’s executive order and the creation of the AI Safety Institute in the U.K. reflect growing awareness of the need for responsible AI development. However, skepticism remains about whether these measures go far enough.
The business landscape is also evolving, with responsible AI becoming a business imperative for many organizations. Amazon, for example, has integrated responsible AI safeguards across its organization, recognizing the importance of ethical considerations in AI development. While responsible AI may slow down innovation, it is seen as an essential step toward ensuring the safety, security, and inclusivity of AI systems.
Despite these efforts, some experts, like Malo Bourgon, CEO of MIRI, remain skeptical and predict that AI systems could reach catastrophic levels by 2030. Bourgon suggests that governments may need to be prepared to halt AI systems indefinitely until developers can robustly demonstrate their safety.
As we navigate the future of AI in 2024, finding a balance between innovation and responsible development will be crucial to harnessing the potential benefits of AI while mitigating risks. The debate between accelerationists and decelerationists is likely to shape the trajectory of AI advancements in the coming year.