NAM Leadership Consortium AICC Commentary Paper: Public Comment

AI Code of Conduct Commentary Paper: Public Comment

The draft AI Code of Conduct framework is comprised of a set of principles (the Code Principles) grounded in related antecedent work, along with a set of application commitments (Code Commitments) for broad adoption by the key stakeholders of the AI life cycle: developers, researchers, health systems, payers, patients, and federal agencies. The Code Principles provide touchstones around which health AI governance—facilitative and precautionary—can be shaped, tested, validated, and continually improved as technology, governance capability, and insights advance. The Code Commitments are intended to direct the application of these Principles in practice and are oriented to decisions and actions.

The public comment period will be open until May 3, 2024.

2. For the table below, please indicate how well the Code Principle descriptions match the desired attribute (e.g., clear, concise, etc.).
*This question is required.

Space Cell	Clear	Relevant	Complete	Concise	Robust	Adaptable
Engaged: Understanding, expressing, and prioritizing the needs, preferences, goals of people, and the related implications throughout the AI life cycle	Engaged: Understanding, expressing, and prioritizing the needs, preferences, goals of people, and the related implications throughout the AI life cycle: Clear	Engaged: Understanding, expressing, and prioritizing the needs, preferences, goals of people, and the related implications throughout the AI life cycle: Relevant	Engaged: Understanding, expressing, and prioritizing the needs, preferences, goals of people, and the related implications throughout the AI life cycle: Complete	Engaged: Understanding, expressing, and prioritizing the needs, preferences, goals of people, and the related implications throughout the AI life cycle: Concise	Engaged: Understanding, expressing, and prioritizing the needs, preferences, goals of people, and the related implications throughout the AI life cycle: Robust	Engaged: Understanding, expressing, and prioritizing the needs, preferences, goals of people, and the related implications throughout the AI life cycle: Adaptable
Safe: Attendance to and continuous vigilance for potentially harmful consequences from the application of AI in health and medicine for individuals and population groups	Safe: Attendance to and continuous vigilance for potentially harmful consequences from the application of AI in health and medicine for individuals and population groups: Clear	Safe: Attendance to and continuous vigilance for potentially harmful consequences from the application of AI in health and medicine for individuals and population groups: Relevant	Safe: Attendance to and continuous vigilance for potentially harmful consequences from the application of AI in health and medicine for individuals and population groups: Complete	Safe: Attendance to and continuous vigilance for potentially harmful consequences from the application of AI in health and medicine for individuals and population groups: Concise	Safe: Attendance to and continuous vigilance for potentially harmful consequences from the application of AI in health and medicine for individuals and population groups: Robust	Safe: Attendance to and continuous vigilance for potentially harmful consequences from the application of AI in health and medicine for individuals and population groups: Adaptable
Effective: Application proven to achieve the intended improvement in personal health and the human condition, in the context of established ethical principles	Effective: Application proven to achieve the intended improvement in personal health and the human condition, in the context of established ethical principles: Clear	Effective: Application proven to achieve the intended improvement in personal health and the human condition, in the context of established ethical principles: Relevant	Effective: Application proven to achieve the intended improvement in personal health and the human condition, in the context of established ethical principles: Complete	Effective: Application proven to achieve the intended improvement in personal health and the human condition, in the context of established ethical principles: Concise	Effective: Application proven to achieve the intended improvement in personal health and the human condition, in the context of established ethical principles: Robust	Effective: Application proven to achieve the intended improvement in personal health and the human condition, in the context of established ethical principles: Adaptable
Equitable: Application accompanied by proof of appropriate steps to ensure fair and unbiased development and access to AI-associated benefits and risk mitigation measures	Equitable: Application accompanied by proof of appropriate steps to ensure fair and unbiased development and access to AI-associated benefits and risk mitigation measures: Clear	Equitable: Application accompanied by proof of appropriate steps to ensure fair and unbiased development and access to AI-associated benefits and risk mitigation measures: Relevant	Equitable: Application accompanied by proof of appropriate steps to ensure fair and unbiased development and access to AI-associated benefits and risk mitigation measures: Complete	Equitable: Application accompanied by proof of appropriate steps to ensure fair and unbiased development and access to AI-associated benefits and risk mitigation measures: Concise	Equitable: Application accompanied by proof of appropriate steps to ensure fair and unbiased development and access to AI-associated benefits and risk mitigation measures: Robust	Equitable: Application accompanied by proof of appropriate steps to ensure fair and unbiased development and access to AI-associated benefits and risk mitigation measures: Adaptable
Efficient: Development and use of AI associated with reduced costs for health gained, in addition to a reduction, or at least neutral state, of adverse impacts on the natural environment.	Efficient: Development and use of AI associated with reduced costs for health gained, in addition to a reduction, or at least neutral state, of adverse impacts on the natural environment.: Clear	Efficient: Development and use of AI associated with reduced costs for health gained, in addition to a reduction, or at least neutral state, of adverse impacts on the natural environment.: Relevant	Efficient: Development and use of AI associated with reduced costs for health gained, in addition to a reduction, or at least neutral state, of adverse impacts on the natural environment.: Complete	Efficient: Development and use of AI associated with reduced costs for health gained, in addition to a reduction, or at least neutral state, of adverse impacts on the natural environment.: Concise	Efficient: Development and use of AI associated with reduced costs for health gained, in addition to a reduction, or at least neutral state, of adverse impacts on the natural environment.: Robust	Efficient: Development and use of AI associated with reduced costs for health gained, in addition to a reduction, or at least neutral state, of adverse impacts on the natural environment.: Adaptable
Accessible: Ensuring that seamless stakeholder access and engagement is a core feature of each phase of the AI life cycle and governance	Accessible: Ensuring that seamless stakeholder access and engagement is a core feature of each phase of the AI life cycle and governance: Clear	Accessible: Ensuring that seamless stakeholder access and engagement is a core feature of each phase of the AI life cycle and governance: Relevant	Accessible: Ensuring that seamless stakeholder access and engagement is a core feature of each phase of the AI life cycle and governance: Complete	Accessible: Ensuring that seamless stakeholder access and engagement is a core feature of each phase of the AI life cycle and governance: Concise	Accessible: Ensuring that seamless stakeholder access and engagement is a core feature of each phase of the AI life cycle and governance: Robust	Accessible: Ensuring that seamless stakeholder access and engagement is a core feature of each phase of the AI life cycle and governance: Adaptable
Transparent: Provision of open, accessible, and understandable information on component AI elements, performance, and their associated outcomes	Transparent: Provision of open, accessible, and understandable information on component AI elements, performance, and their associated outcomes: Clear	Transparent: Provision of open, accessible, and understandable information on component AI elements, performance, and their associated outcomes: Relevant	Transparent: Provision of open, accessible, and understandable information on component AI elements, performance, and their associated outcomes: Complete	Transparent: Provision of open, accessible, and understandable information on component AI elements, performance, and their associated outcomes: Concise	Transparent: Provision of open, accessible, and understandable information on component AI elements, performance, and their associated outcomes: Robust	Transparent: Provision of open, accessible, and understandable information on component AI elements, performance, and their associated outcomes: Adaptable
Accountable: Identifiable and measurable actions taken in the development and use of AI, with clear documentation of benefits and clear accountability for potentially adverse consequences	Accountable: Identifiable and measurable actions taken in the development and use of AI, with clear documentation of benefits and clear accountability for potentially adverse consequences: Clear	Accountable: Identifiable and measurable actions taken in the development and use of AI, with clear documentation of benefits and clear accountability for potentially adverse consequences: Relevant	Accountable: Identifiable and measurable actions taken in the development and use of AI, with clear documentation of benefits and clear accountability for potentially adverse consequences: Complete	Accountable: Identifiable and measurable actions taken in the development and use of AI, with clear documentation of benefits and clear accountability for potentially adverse consequences: Concise	Accountable: Identifiable and measurable actions taken in the development and use of AI, with clear documentation of benefits and clear accountability for potentially adverse consequences: Robust	Accountable: Identifiable and measurable actions taken in the development and use of AI, with clear documentation of benefits and clear accountability for potentially adverse consequences: Adaptable
Secure: Validated procedures to ensure privacy and security, as health data sources are better positioned as a fully protected core utility for the common good, including use of AI for continuous learning and improvement	Secure: Validated procedures to ensure privacy and security, as health data sources are better positioned as a fully protected core utility for the common good, including use of AI for continuous learning and improvement: Clear	Secure: Validated procedures to ensure privacy and security, as health data sources are better positioned as a fully protected core utility for the common good, including use of AI for continuous learning and improvement: Relevant	Secure: Validated procedures to ensure privacy and security, as health data sources are better positioned as a fully protected core utility for the common good, including use of AI for continuous learning and improvement: Complete	Secure: Validated procedures to ensure privacy and security, as health data sources are better positioned as a fully protected core utility for the common good, including use of AI for continuous learning and improvement: Concise	Secure: Validated procedures to ensure privacy and security, as health data sources are better positioned as a fully protected core utility for the common good, including use of AI for continuous learning and improvement: Robust	Secure: Validated procedures to ensure privacy and security, as health data sources are better positioned as a fully protected core utility for the common good, including use of AI for continuous learning and improvement: Adaptable
Adaptive: Assurance that the accountability framework will deliver ongoing information on the results of AI application, for use as required for continuous learning and improvement in health, health care, biomedical science, and, ultimately, the human condition	Adaptive: Assurance that the accountability framework will deliver ongoing information on the results of AI application, for use as required for continuous learning and improvement in health, health care, biomedical science, and, ultimately, the human condition: Clear	Adaptive: Assurance that the accountability framework will deliver ongoing information on the results of AI application, for use as required for continuous learning and improvement in health, health care, biomedical science, and, ultimately, the human condition: Relevant	Adaptive: Assurance that the accountability framework will deliver ongoing information on the results of AI application, for use as required for continuous learning and improvement in health, health care, biomedical science, and, ultimately, the human condition: Complete	Adaptive: Assurance that the accountability framework will deliver ongoing information on the results of AI application, for use as required for continuous learning and improvement in health, health care, biomedical science, and, ultimately, the human condition: Concise	Adaptive: Assurance that the accountability framework will deliver ongoing information on the results of AI application, for use as required for continuous learning and improvement in health, health care, biomedical science, and, ultimately, the human condition: Robust	Adaptive: Assurance that the accountability framework will deliver ongoing information on the results of AI application, for use as required for continuous learning and improvement in health, health care, biomedical science, and, ultimately, the human condition: Adaptable

3. Is this set of Code Principles, and the attendant descriptors, sufficient to focus attention and action on the issues that must be anticipated to ensure that the use of AI in health and health care optimally advances the human condition?
*This question is required.

4. If not, what changes are necessary to either the Code Principles or the attendant descriptors?

4. For the table below, please indicate how well the Code Commitments match the desired attribute (e.g., clear, concise, etc.).

*This question is required.

Space Cell	Clear	Relevant	Complete	Concise	Robust	Adaptable
Focus: Protect and advance human health and human connection as the primary aims	Focus: Protect and advance human health and human connection as the primary aims: Clear	Focus: Protect and advance human health and human connection as the primary aims: Relevant	Focus: Protect and advance human health and human connection as the primary aims: Complete	Focus: Protect and advance human health and human connection as the primary aims: Concise	Focus: Protect and advance human health and human connection as the primary aims: Robust	Focus: Protect and advance human health and human connection as the primary aims: Adaptable
Benefits: Ensure equitable distribution of benefit and risk for all	Benefits: Ensure equitable distribution of benefit and risk for all: Clear	Benefits: Ensure equitable distribution of benefit and risk for all: Relevant	Benefits: Ensure equitable distribution of benefit and risk for all: Complete	Benefits: Ensure equitable distribution of benefit and risk for all: Concise	Benefits: Ensure equitable distribution of benefit and risk for all: Robust	Benefits: Ensure equitable distribution of benefit and risk for all: Adaptable
Involvement: Engage people as partners with agency in every stage of the lifecycle	Involvement: Engage people as partners with agency in every stage of the lifecycle: Clear	Involvement: Engage people as partners with agency in every stage of the lifecycle: Relevant	Involvement: Engage people as partners with agency in every stage of the lifecycle: Complete	Involvement: Engage people as partners with agency in every stage of the lifecycle: Concise	Involvement: Engage people as partners with agency in every stage of the lifecycle: Robust	Involvement: Engage people as partners with agency in every stage of the lifecycle: Adaptable
Workforce well-being: Renew the moral well-being and sense of shared purpose to the health care workforce	Workforce well-being: Renew the moral well-being and sense of shared purpose to the health care workforce: Clear	Workforce well-being: Renew the moral well-being and sense of shared purpose to the health care workforce: Relevant	Workforce well-being: Renew the moral well-being and sense of shared purpose to the health care workforce: Complete	Workforce well-being: Renew the moral well-being and sense of shared purpose to the health care workforce: Concise	Workforce well-being: Renew the moral well-being and sense of shared purpose to the health care workforce: Robust	Workforce well-being: Renew the moral well-being and sense of shared purpose to the health care workforce: Adaptable
Monitoring: Monitor and openly and comprehensibly share methods and evidence of AI’s performance and impact on health and safety	Monitoring: Monitor and openly and comprehensibly share methods and evidence of AI’s performance and impact on health and safety: Clear	Monitoring: Monitor and openly and comprehensibly share methods and evidence of AI’s performance and impact on health and safety: Relevant	Monitoring: Monitor and openly and comprehensibly share methods and evidence of AI’s performance and impact on health and safety: Complete	Monitoring: Monitor and openly and comprehensibly share methods and evidence of AI’s performance and impact on health and safety: Concise	Monitoring: Monitor and openly and comprehensibly share methods and evidence of AI’s performance and impact on health and safety: Robust	Monitoring: Monitor and openly and comprehensibly share methods and evidence of AI’s performance and impact on health and safety: Adaptable
Innovation: Innovate, adopt, collaboratively learn, continuously improve, and advance the standard of clinical practice	Innovation: Innovate, adopt, collaboratively learn, continuously improve, and advance the standard of clinical practice: Clear	Innovation: Innovate, adopt, collaboratively learn, continuously improve, and advance the standard of clinical practice: Relevant	Innovation: Innovate, adopt, collaboratively learn, continuously improve, and advance the standard of clinical practice: Complete	Innovation: Innovate, adopt, collaboratively learn, continuously improve, and advance the standard of clinical practice: Concise	Innovation: Innovate, adopt, collaboratively learn, continuously improve, and advance the standard of clinical practice: Robust	Innovation: Innovate, adopt, collaboratively learn, continuously improve, and advance the standard of clinical practice: Adaptable

5. Is this set of Code Commitments sufficient to capture the actions needed to ensure application of the Code Principles in practice? *This question is required.

6. If not, what changes are necessary to the Code Commitments?

6. Please provide any additional insight, feedback or suggestions here: