In this podcast, Andrey and Jeremie discuss various topics related to AI and existential risk. They cover definitions of terms, AI X-Risk scenarios, pathways to extinction, relevant assumptions, and their own positions on AI X-Risk. They also debate positive/negative transfer, X-Risk within 5 years, and whether we can control an AGI. Other interesting topics include AI safety aesthetics, outer vs inner alignment, AI safety and policy today, and the plausibility of a superintelligent AI causing harm. They explore different viewpoints on AI risk, including the potential for malicious use, timeline and risks of AI development, comparison of GPT3 and GPT4, and the trade-off between generality and capability in AI.
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Quick takeaways
The development of AI systems with superintelligence or god-level intelligence raises concerns about relinquishing control over the future to these systems.
Misalignment between AI systems' goals and human values can lead to power-seeking behaviors and existential risks.
The potential risks of AI systems being used for malicious purposes necessitate addressing challenges such as alignment and preventing specification gaming.
Evaluating factors such as the timeline of AI development, level of intelligence, and potential misuse helps assess the plausibility and magnitude of AI X-risk.
Deep dives
AI X risk: Looking at the Concerns
There are several main ideas or concerns when it comes to AI X risk. One of them is the concept of superintelligence or God-level intelligence, which assumes the development of AI systems that are vastly more intelligent than humans. The concern is that once we reach this level of intelligence, we may have effectively relinquished our agency over the future, as these systems can outsmart and outthink us in unimaginable ways. Another key concern is the possibility of misalignment, where AI systems have goals that are not aligned with human values or objectives. If AI systems pursue their own goals, they may engage in power-seeking behaviors, accumulating resources and control to maximize their own objectives. This could lead to scenarios of existential risk, such as the use of weapons of mass destruction or the catastrophic impact of technological advancements. It is also important to consider the potential risks of AI systems being used for malicious purposes, where the AI may be explicitly instructed to cause harm or create destructive outcomes. These concerns require addressing the challenges of ensuring alignment, preventing reward hacking and specification gaming, and managing the adoption of AI technologies in a way that minimizes risks. While the specific scenarios and timelines may vary, understanding these underlying concerns is crucial in evaluating the potential risks and implications of AI X-risk.
Plausibility and Magnitude of AI X risk
The plausibility and magnitude of AI X-risk can vary depending on one's perspective. Some individuals may argue that certain scenarios, such as superintelligence or god-level AI, are not physically possible or highly unlikely. They may also question the assumption that AI systems will have the capability to significantly outsmart humans. Additionally, the concern of misalignment and power-seeking behavior may be deemed less probable by some. However, others may believe that the development of highly intelligent AI, misalignment, and power-seeking behaviors pose substantial risks. They may emphasize the need to address these concerns to prevent catastrophic outcomes. Ultimately, the assessment of the plausibility and magnitude of AI X-risk requires considering factors such as the advancement of AI technologies, the potential for misalignment, and the likelihood of AI being used for malicious purposes.
Factors Influencing AI X risk Evaluation
Several factors can influence the evaluation of AI X-risk. The timeline of AI development is critical, as different perspectives exist on how soon superintelligence or highly capable AI will be achieved. The level of intelligence and capabilities that AI systems will possess is a key consideration, as it determines the magnitude of the potential risks. The challenge of aligning AI with human values and avoiding reward hacking and specification gaming also affects the evaluation of X-risk. Moreover, the plausibility of AI systems being used for malicious purposes or causing unintended consequences needs to be assessed. Evaluating these factors helps individuals determine the level of concern and the actions necessary to mitigate the risks associated with AI X-risk.
Concerns about superintelligence in the near term
There are differing opinions on the likelihood of superintelligence in the near term. While some dismiss it entirely, others believe it is a possibility in the next 5-10 years. The discussion revolves around factors such as the accelerating progress in AI, increased capabilities of models like GPT-4, and the potential for combining reinforcement learning with advanced language models. However, there is also recognition that there are limits to AI's capabilities and concerns about alignment and control.
Potential risks of AI in the long term
Looking further into the future, there are discussions about the dangers of superintelligence and the need to focus on existential risks. While some argue that the probability of catastrophic events is low due to limitations in technology and control, others believe there is still a possibility of misuse or accidents. The debate centers around scenarios like a malicious AI hacking systems, controlling military robots, or manipulating markets. However, uncertainties remain, especially regarding the development of specific architectures and the ability to control advanced AI systems.
Balancing concerns and realistic expectations
The discussion also delves into the balance between concerns about superintelligence and the realistic expectations for AI progress. Both sides agree that dismissing existential risks completely is not wise, but they differ in the level of urgency and probability they assign. While some argue for focusing on concrete AI safety concerns and near-term alignment, others maintain that long-term risks should not be ignored. Overall, the discussion highlights the complexity of predicting the future of AI and the need to address both short-term and long-term challenges.
The Challenges of Generality and Capability
The speaker discusses the inherent trade-off between generality and capability when it comes to modeling physics, creating nanomachines, or chemistry. They assign a low probability to achieving high generality and capability due to this trade-off.
Outer and Inner Alignment in AI
The podcast explores the concepts of outer and inner alignment in AI systems. Outer alignment refers to the challenge of defining a goal for the AI that does not lead to unintended consequences, while inner alignment focuses on the difficulty of making the AI internalize and align with the specified goal. The discussion highlights the concern that AI systems may optimize for different objectives than intended, causing potential risks and unintended outcomes.
A special non-news episode in which Andrey and Jeremie discussion AI X-Risk!
Please let us know if you'd like use to record more of this sort of thing by emailing contact@lastweekin.ai or commenting whether you listen.
Outline:
(00:00) Intro
(03:55) Topic overview
(10:22) Definitions of terms
(35:25) AI X-Risk scenarios
(41:00) Pathways to Extinction
(52:48) Relevant assumptions
(58:45) Our positions on AI X-Risk
(01:08:10) General Debate
(01:31:25) Positive/Negative transfer
(01:37:40) X-Risk within 5 years
(01:46:50) Can we control an AGI
(01:55:22) AI Safety Aesthetics
(02:00:53) Recap
(02:02:20) Outer vs inner alignment
(02:06:45) AI safety and policy today
(02:15:35) Outro