Miles Brundage and Tim Hwang discuss the intersection of AI and cryptocurrency, risks of emerging technologies, contrasting policy approaches, interdisciplinary research at FHI, short-term vs long-term AI concerns, and predictions for superhuman gaming and meta learning.
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Quick takeaways
The potential misuse of AI for malicious purposes, such as generating fake news or carrying out cyber attacks, highlights the need for responsible use and the establishment of norms.
Collaboration among industry, academia, and government is crucial for effective AI policy and governance, as it allows for a better understanding, synthesis of expertise, and sharing of best practices.
To ensure safe and beneficial AI development, proactive measures should be taken to address the long-term impact and risks associated with AI, including considerations of value alignment, sustainability, and potential existential risks.
Deep dives
Concerns about AI in the short term
In the short term, there are several concerns surrounding AI. One of the main issues is the potential misuse of AI for malicious purposes, such as generating fake news or carrying out cyber attacks. This highlights the need to take the dual-use nature of AI seriously and establish norms for responsible use. As AI becomes more accessible, issues related to privacy, robustness, and transparency also arise. The challenge lies in addressing these concerns and ensuring that AI systems are fair, accountable, and transparent.
Importance of Collaboration
Collaboration between different sectors, including industry, academia, and government, is crucial for effective AI policy and governance. While the perspectives and constraints may differ, there is common cause in maximizing the benefits of AI and minimizing risks. Close collaboration can lead to better understanding, synthesis of expertise, and sharing of best practices. Moreover, collaboration between policy experts and technical researchers can help address the societal implications of AI and foster the development of responsible AI systems.
The Need for Long-Term Thinking
In addition to addressing immediate concerns, it is crucial to think about the long-term impact and risks associated with AI. This includes considerations of value alignment, sustainability, and potential existential risks. While the long-term implications may seem far off, proactive measures should be taken to ensure safe and beneficial AI development. Collaboration, research, and the establishment of norms can help address the impact of AI on a global scale.
The Intersection of Short-Term and Long-Term Issues
Many of the concerns and challenges in the short-term and long-term intersect and can benefit from common approaches. For example, issues like fairness, transparency, and accountability are relevant in both timeframes. Norms established in the short-term can set positive precedents and inform the development of AI systems in the long-term. By addressing immediate concerns and engaging in long-term thinking, AI can be harnessed for positive impact while minimizing risks.
Openness and Publishing
The default norm in AI research is currently openness and publishing, which allows for transparency and collective understanding. However, there may be considerations in specific domains where openness needs to be balanced with responsible practices. Norms around openness versus restricted sharing may need to evolve in the future, especially if concerns around security or adverse consequences arise. Balancing the need for knowledge diffusion and responsible dissemination of AI research is crucial for effective governance.
Miles Brundage is an AI Policy Research Fellow with the Strategic AI Research Center at the Future of Humanity Institute. He is also a PhD candidate in Human and Social Dimensions of Science and Technology at Arizona State University.