Ajeya Cotra, Senior Program Officer at Open Philanthropy, and Helen Toner, Director of Strategy at Georgetown University’s Center for Security and Emerging Technology, discuss the risks and rewards of AI technology, including its use in law enforcement and potential harms. They also explore responsible scaling policies, the frustration of limited access to scientific research, and the significance of AI systems having engaging personalities.
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Quick takeaways
Unintended consequences and drawbacks of AI technologies must be considered to avoid harm to individuals, as seen in cases of false arrests caused by facial recognition systems that disproportionately affect minority groups.
The complexity and unpredictability of advanced AI systems highlight the need for cautious development and testing, especially in determining their real-world capabilities, to mitigate potential risks and ensure safety.
Deep dives
Unintended Harms of AI
AI is already being used in ways that pose risks and harms to individuals. For example, facial recognition systems used by police have resulted in false arrests, disproportionately affecting minority groups. This highlights the importance of considering the unintended consequences and drawbacks of AI technologies.
Challenges of Predicting AI Safety
One of the challenges in ensuring AI safety is the inability to predict the capabilities and behavior of advanced AI systems in advance. The current models, especially large language models, lack systematic ways to determine their real-world capabilities. The complexity and unpredictability of AI systems raise concerns about potential risks and the need for cautious development and testing.
Responsible Scaling Policies for AI
There is a growing concept of responsible scaling policies that aim to bridge the gap between fully open-sourcing AI models and completely withholding their capabilities. These policies involve clear guidelines on the capabilities of AI systems and the necessary protections to ensure their safe deployment. The goal is to find a balance between openness and caution to prevent potential misuse or unintended consequences.
Considering Public Opinion and Data Privacy in AI
AI developers should take public opinion into account and be mindful of privacy concerns when developing AI technologies. While data privacy is crucial, there are techniques such as federated learning and differential privacy that can help protect sensitive information. Balancing user engagement, privacy, and responsible use of AI is a challenge that developers should address.
Platformer's Casey Newton moderates a conversation at Code 2023 on ethics in artificial intelligence, with Ajeya Cotra, Senior Program Officer at Open Philanthropy, and Helen Toner, Director of Strategy at Georgetown University’s Center for Security and Emerging Technology. The panel discusses the risks and rewards of the technology, as well as best practices and safety measures.