Craig A. Kaplan, an AGI expert and founder of iQ Company, dives deep into the world of Artificial General Intelligence. He discusses how AI can mirror human intelligence through innovative architectures and collective decision-making processes. Kaplan emphasizes the importance of safety and ethical frameworks in developing superintelligent AI. He also shares insights on navigating complex problem spaces and the collaboration between humans and AI. Finally, the morality of AI agents and the risks of misalignment with human values take center stage.
The architecture of collective intelligence promotes a common framework for collaboration between human and AI agents to solve problems effectively.
The podcast underscores the need for layered safety mechanisms to manage the risks associated with increasingly capable AI systems and ensure ethical adherence.
Deep dives
Collective Intelligence Architecture
The architecture of collective intelligence aims to enable collaboration between human and AI agents. This approach emphasizes establishing a common framework for both parties to engage in sequential, logical thought processes. It highlights the necessity of designing a system where humans and AIs can interchangeably solve problems by employing shared methods and representations. The idea is to create a unified theory of problem-solving that can seamlessly integrate and process contributions from both human and AI counterparts, enhancing overall efficiency.
Problem-Solving Models
A notable reference in the discussion is the unified theory of problem-solving proposed by researchers at Carnegie Mellon University. This theory models problem-solving as navigating from an initial state to a goal state using a series of actions or operators. It acknowledges the trial-and-error nature of solving various problems, whether trivial or complex, such as brushing teeth or tackling climate change. Such a model not only assists in problem-solving for AI but also scales well, allowing continuous learning from prior attempts to improve future outcomes.
Safety Mechanisms in AI
The podcast emphasizes the critical importance of safety mechanisms as AI systems evolve in complexity and capability. It suggests implementing layered safety checks that operate in real-time while AI agents generate multiple sub-goals rapidly. Ensuring these checks occur consistently helps mitigate risks and guarantees that AI actions adhere to established ethical standards. The conversation also likens this framework to democratic checks and balances, where diverse AI agents must negotiate value conflicts, thus enhancing system reliability.
Future of AI Development
Looking ahead, significant advancements in AI are expected, particularly in developing agent-based systems that leverage collective intelligence. The transition from large language models to more autonomous AI agents is seen as a natural progression that will lead to enhanced problem-solving capabilities. The speaker predicts a timeline where increased collaboration among agents results in the emergence of artificial general intelligence (AGI) and potentially superintelligence. Alongside this, there will be an ongoing emphasis on aligning these intelligent systems with human values to ensure that ethical considerations remain central to their design and function.
Artificial General Intelligence - AGI - an AI system that’s as intelligent as an average human being in all the ways that human beings are usually intelligent. Helping us understand what it means and how we might get there is Craig A. Kaplan, founder of iQ Company, where he invents advanced intelligence systems.
He also founded and ran PredictWallStreet, a financial services firm whose clients included NASDAQ, TD Ameritrade, Schwab, and other well-known financial institutions. In 2018, PredictWallStreet harnessed the collective intelligence of millions of retail investors to power a top 10 hedge fund performance, and we talk about it in this episode.
Craig is a visiting professor in computer science at the University of California, and earned master’s and doctoral degrees from famed robotics hub Carnegie Mellon University, where he co-authored research with the Nobel-Prize-winning economist and AI pioneer Dr. Herbert A. Simon.
In the conclusion of the interview, we talk about the details of the collective intelligence architecture of agents, why Craig says it’s safe, morality of superintelligence, the risks of bad actors, and leading indicators of AGI.
All this plus our usual look at today's AI headlines.