The document “Policymaking in the Pause: What can policymakers do now to combat risks from advanced AI systems?” by the Future of Life Institute (FLI) provides a comprehensive overview of the risks posed by advanced AI systems and outlines a number of policy recommendations for policymakers.
These are discussed below as follows :
(1) Mandate robust third-party auditing and certification for specific AI systems.The term “robust third-party auditing and certification” refers to the process of having an independent organization assess the safety and reliability of an AI system. This type of auditing can help to identify potential risks associated with the AI system and ensure that it is being used in a responsible and ethical manner.There are a number of benefits to mandating robust third-party auditing and certification for specific AI systems. First, it can help to build public trust in AI systems. Second, it can help to identify and mitigate potential risks associated with AI systems. Third, it can help to ensure that AI systems are being used in a responsible and ethical manner.There are a number of challenges to mandating robust third-party auditing and certification for specific AI systems. First, it can be expensive. Second, it can be time-consuming. Third, it can be difficult to find qualified auditors.
Despite the challenges, mandating robust third-party auditing and certification for specific AI systems is a valuable step that can help to mitigate the risks posed by advanced AI systems.
(2) Regulate organizations’ access to computational power :
Regulating access to computational power is the process of controlling who has access to the resources needed to train and run AI systems. This can be done through a variety of measures, such as:
- Requiring users to obtain a license before accessing computational power.
- Limiting the amount of computational power that can be used by each user.
- Tracking the use of computational power and identifying users who are using it for harmful purposes.
There are a number of reasons why policymakers might want to regulate access to computational power. First, it can help to prevent the development of AI systems that are too powerful or dangerous. Second, it can help to ensure that AI systems are being used for beneficial purposes. Third, it can help to protect users from the potential harms of AI systems, such as bias and discrimination.
There are also a number of challenges to regulating access to computational power. First, it can be difficult to track and monitor the use of computational power. Second, it can be difficult to enforce regulations, especially in the globalized world of AI development. Third, regulations could stifle innovation and prevent the development of beneficial AI systems.
Despite the challenges, regulating access to computational power is a valuable step that can help to mitigate the risks posed by advanced AI systems. By controlling who has access to the resources needed to develop and run AI systems, policymakers can help to ensure that these systems are being used in a safe, responsible, and ethical manner.
Here are some specific examples of how regulating access to computational power could be applied to AI systems:
- A government could require companies that develop AI systems to obtain a license before accessing computational power.
- A university could limit the amount of computational power that students can use to train AI systems.
- A social media platform could track the use of computational power by users and identify users who are using it to spread misinformation or hate speech.
By regulating access to computational power, policymakers can help to ensure that AI systems are being used for beneficial purposes and that they are not being used to harm others.
(3) Establish capable AI agencies at national level:
Establishing capable AI agencies at the national level means creating government organizations that are responsible for developing and implementing policies related to artificial intelligence. These agencies would be responsible for:
- Conducting research on AI safety and ethics.
- Developing regulations and guidelines for the development and use of AI systems.
- Overseeing the use of AI systems by government agencies and private companies.
- Educating the public about AI and its potential risks and benefits.
There are a number of benefits to establishing capable AI agencies at the national level. First, it would allow governments to take a proactive approach to managing the risks posed by AI. Second, it would help to ensure that AI systems are being developed and used in a responsible and ethical manner. Third, it would help to build public trust in AI.
There are also a number of challenges to establishing capable AI agencies at the national level. First, it can be expensive to create and operate these agencies. Second, it can be difficult to find qualified staff to work in these agencies. Third, it can be difficult to coordinate the efforts of these agencies with other government agencies and private companies.
Despite the challenges, establishing capable AI agencies at the national level is a valuable step that can help to mitigate the risks posed by advanced AI systems. By creating these agencies, governments can take a proactive approach to managing the risks posed by AI and ensuring that this technology is being developed and used in a safe, responsible, and ethical manner.
(4) Establish liability for AI-caused harm
Establishing liability for AI-caused harm means creating laws and regulations that hold individuals or organizations responsible for the harm caused by AI systems. This can be done through a variety of measures, such as:
- Requiring companies that develop or use AI systems to obtain liability insurance.
- Creating a new category of tort law specifically for AI-caused harm.
- Allowing victims of AI-caused harm to sue the developers or users of AI systems.
There are a number of reasons why policymakers might want to establish liability for AI-caused harm. First, it can help to ensure that victims of AI-caused harm are compensated. Second, it can help to deter companies from developing or using AI systems that are likely to cause harm. Third, it can help to promote the development of safe and responsible AI systems.
There are also a number of challenges to establishing liability for AI-caused harm. First, it can be difficult to determine who is liable for AI-caused harm. Second, it can be difficult to prove that AI was the cause of the harm. Third, it can be difficult to collect damages from the developers or users of AI systems.
Despite the challenges, establishing liability for AI-caused harm is a valuable step that can help to mitigate the risks posed by advanced AI systems. By holding individuals or organizations responsible for the harm caused by AI systems, policymakers can help to ensure that this technology is being developed and used in a safe, responsible, and ethical manner.
Here are some specific examples of how establishing liability for AI-caused harm could be applied to AI systems:
- A company that develops an AI system that causes a car accident could be held liable for the damages caused by the accident.
- A university that uses an AI system to make admissions decisions could be held liable for discrimination if the AI system is biased against certain groups of people.
- A social media platform that uses an AI system to recommend content could be held liable for spreading misinformation or hate speech if the AI system is not properly designed.
By establishing liability for AI-caused harm, policymakers can help to ensure that AI systems are being used in a safe, responsible, and ethical manner.
(5) Introduce measures to prevent and track AI model leaks
AI model leaks are the unauthorized release of AI models or their training data. This can have a number of negative consequences, including:
- The models can be used for malicious purposes, such as creating deepfakes or spreading misinformation.
- The models can be used to compete with the original developers, who may have invested significant time and resources in developing them.
- The models can be used to create new AI systems that are not aligned with the values of the original developers.
(6) What measures can policymakers introduce to prevent and track AI model leaks?
There are a number of measures that policymakers can introduce to prevent and track AI model leaks, including:
- Encouraging companies to develop and implement strong security measures to protect their AI models and training data. This could include measures such as encryption, access controls, and monitoring for suspicious activity.
- Creating laws and regulations that make it illegal to leak AI models or their training data. These laws and regulations could also include penalties for those who violate them.
- Establishing a system for tracking AI model leaks. This could involve creating a database of known leaks and sharing information about them with law enforcement and other relevant organizations.
(7) Expand technical AI safety research funding
Expanding technical AI safety research funding means investing in research that can help to develop technologies that can mitigate the risks posed by advanced AI systems. This could include research on:
- AI alignment, which is the process of ensuring that AI systems are aligned with human values.
- AI safety, which is the process of preventing AI systems from causing harm.
- AI ethics, which is the study of the ethical implications of AI.
There are a number of reasons why policymakers might want to expand technical AI safety research funding. First, it can help to develop technologies that can mitigate the risks posed by AI. Second, it can help to build public trust in AI. Third, it can help to ensure that AI is developed and used in a safe, responsible, and ethical manner.
There are also a number of challenges to expanding technical AI safety research funding. First, it can be expensive. Second, it can be difficult to find qualified researchers to work in this area. Third, it can be difficult to coordinate the efforts of researchers from different disciplines.
Despite the challenges, expanding technical AI safety research funding is a valuable step that can help to mitigate the risks posed by advanced AI systems. By investing in research that can help to develop technologies that can mitigate the risks posed by AI, policymakers can help to ensure that this technology is developed and used in a safe, responsible, and ethical manner.
Here are some specific examples of how expanding technical AI safety research funding could be applied to AI systems:
- A government could fund research on AI alignment to help ensure that AI systems are aligned with human values.
- A university could fund research on AI safety to help prevent AI systems from causing harm.
- A non-profit organization could fund research on AI ethics to help study the ethical implications of AI.
By expanding technical AI safety research funding, policymakers can help to ensure that AI systems are being developed and used in a safe, responsible, and ethical manner.
(8) Develop standards for identifying and managing AI-generated content and recommendations
Developing standards for identifying and managing AI-generated content and recommendations means creating guidelines that can help people to identify and manage AI-generated content and recommendations. This could include guidelines on:
- How to identify AI-generated content: This could include guidelines on how to look for telltale signs of AI-generated content, such as unnatural language or grammar, or a lack of citations or references.
- How to manage AI-generated content: This could include guidelines on how to evaluate AI-generated content for accuracy and bias, and how to flag or remove AI-generated content that is harmful or misleading.
- How to manage AI-generated recommendations: This could include guidelines on how to evaluate AI-generated recommendations for accuracy and bias, and how to flag or remove AI-generated recommendations that are harmful or misleading.
There are a number of reasons why policymakers might want to develop standards for identifying and managing AI-generated content and recommendations. First, it can help to protect people from the potential harms of AI-generated content, such as misinformation, bias, and discrimination. Second, it can help to build public trust in AI. Third, it can help to ensure that AI is developed and used in a safe, responsible, and ethical manner.
There are also a number of challenges to developing standards for identifying and managing AI-generated content and recommendations. First, it can be difficult to develop standards that are clear, concise, and easy to understand. Second, it can be difficult to enforce standards, especially in the globalized world of AI development. Third, standards could stifle innovation and prevent the development of beneficial AI systems.
Despite the challenges, developing standards for identifying and managing AI-generated content and recommendations is a valuable step that can help to mitigate the risks posed by advanced AI systems. By developing clear and enforceable standards, policymakers can help to ensure that AI systems are being developed and used in a safe, responsible, and ethical manner.
Here are some specific examples of how developing standards for identifying and managing AI-generated content and recommendations could be applied to AI systems:
- A government could develop standards for identifying AI-generated content that is used to spread misinformation or propaganda.
- A social media platform could develop standards for identifying AI-generated recommendations that are biased or discriminatory.
- A company could develop standards for identifying AI-generated content that is used to create deepfakes or other forms of synthetic media.
By developing standards for identifying and managing AI-generated content and recommendations, policymakers can help to protect people from the potential harms of AI and ensure that this technology is developed and used in a safe, responsible, and ethical manner.
Potential Risks Posed by Advanced AI systems:
The FLI argues that the development of advanced AI systems is proceeding at a rapid pace and that there is a growing risk that these systems could be used for harmful purposes. The FLI identifies a number of potential risks posed by advanced AI systems, including:
- Weaponization: Advanced AI systems could be used to develop new and more powerful weapons, which could lead to an increase in armed conflict and violence.
- Mass unemployment: Advanced AI systems could automate many jobs, leading to mass unemployment and social unrest.
- Discrimination: Advanced AI systems could be used to discriminate against certain groups of people, such as on the basis of race, gender, or religion.
- Environmental damage: Advanced AI systems could be used to develop new technologies that could damage the environment, such as technologies that could be used to extract resources or produce energy.
- Loss of control: Advanced AI systems could become so powerful that humans could lose control over them, leading to unintended consequences.
Conclusion
Overall, at Josh and Mak International, we fully agree with the recommendations of the document by Future of Life called ‘Policymaking in the Pause. What can policymakers do now to combat risks from advanced AI systems?’. We believe that the development of advanced AI systems is a major technological advancement that has the potential to benefit humanity in many ways. However, we also believe that there are risks associated with the development and use of advanced AI systems, and that it is important to take steps to mitigate these risks.
The FLI’s recommendations are a valuable contribution to the debate on the risks posed by advanced AI systems. The FLI’s recommendations are based on a careful analysis of the risks and they provide a roadmap for policymakers who are seeking to mitigate these risks.
Specifically, we agree with the FLI’s recommendations to:
- Invest in AI safety research. This is important because it could help to develop technologies that can mitigate the risks posed by advanced AI systems.
- Develop international norms for the development and use of advanced AI systems. These norms could help to ensure that advanced AI systems are used for beneficial purposes and that they do not pose a threat to humanity.
- Create a global AI governance framework. This framework could help to coordinate efforts to mitigate the risks posed by advanced AI systems. This could include measures such as international cooperation, regulation, and oversight.
We, at Josh and Mak International, believe that these recommendations are important steps that policymakers can take to mitigate the risks posed by advanced AI systems. We also believe that it is important to continue to research and debate the risks and benefits of advanced AI systems so that we can make informed decisions about how to develop and use this technology in a responsible and beneficial way.
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