Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI

by   Avijit Ghosh, et al.

Generative Artificial Intelligence (AI) has seen mainstream adoption lately, especially in the form of consumer-facing, open-ended, text and image generating models. However, the use of such systems raises significant ethical and safety concerns, including privacy violations, misinformation and intellectual property theft. The potential for generative AI to displace human creativity and livelihoods has also been under intense scrutiny. To mitigate these risks, there is an urgent need of policies and regulations responsible and ethical development in the field of generative AI. Existing and proposed centralized regulations by governments to rein in AI face criticisms such as not having sufficient clarity or uniformity, lack of interoperability across lines of jurisdictions, restricting innovation, and hindering free market competition. Decentralized protections via crowdsourced safety tools and mechanisms are a potential alternative. However, they have clear deficiencies in terms of lack of adequacy of oversight and difficulty of enforcement of ethical and safety standards, and are thus not enough by themselves as a regulation mechanism. We propose a marriage of these two strategies via a framework we call Dual Governance. This framework proposes a cooperative synergy between centralized government regulations in a U.S. specific context and safety mechanisms developed by the community to protect stakeholders from the harms of generative AI. By implementing the Dual Governance framework, we posit that innovation and creativity can be promoted while ensuring safe and ethical deployment of generative AI.


The Chai Platform's AI Safety Framework

Chai empowers users to create and interact with customized chatbots, off...

Hard Choices in Artificial Intelligence

As AI systems are integrated into high stakes social domains, researcher...

Responsible Design Patterns for Machine Learning Pipelines

Integrating ethical practices into the AI development process for artifi...

Acceleration AI Ethics, the Debate between Innovation and Safety, and Stability AI's Diffusion versus OpenAI's Dall-E

One objection to conventional AI ethics is that it slows innovation. Thi...

Understanding artificial intelligence ethics and safety

A remarkable time of human promise has been ushered in by the convergenc...

P4AI: Approaching AI Ethics through Principlism

The field of computer vision is rapidly evolving, particularly in the co...

Modelling the Safety and Surveillance of the AI Race

Innovation, creativity, and competition are some of the fundamental unde...

Please sign up or login with your details

Forgot password? Click here to reset