Updated OECD AI Principles to keep up with novel and increased risks from general purpose and generative AI

Jun 12, 2024

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On May 3, 2024, the OECD released updated AI Principles that build upon the 2019 version with some notable differences that respond to risks emerging from latest technological developments such as general purpose and generative AI systems.

This article contains a summary of the changes as well as a line-by-line comparison of the old and new AI Principles.

The most notable changes are:

Principle 1.1 now explicitly calls out environmental sustainability, acknowledging increased concerns around the environmental footprint of large language models over the past years.
Principle 1.2 received a new heading which now includes respect for the rule of law, human rights and democratic values, and privacy, while fairness has been there all along. However, all of these elements were previously included in the Principle itself. The Principle also specifically mentions that mis- and disinformation amplified by AI must be addressed while respecting freedom of expression. Some more details are added around the required safeguards with an emphasis on human agency and oversights as well as risks resulting from misuse.
Principle 1.3 saw only slight changes. One of them is the specification of information requirements enabling an understanding of the AI system, which now explicitly include capabilities and limitations.
Elements of Principle 1.4 have been moved to Principle 1.5 “Accountability” while override, repair, decommission, and information integrity requirements were added.
Principle 1.5 receives a large addition covering ongoing systematic risk management and responsible business conduct, calling out specifically harmful bias, human rights including safety, security, and privacy, as well as labour and intellectual property rights. Net new among those is bias, which did not find any mention in the previous version of the Principles

Summary

New additions to the OECD AI Principles that had not been included previously are environmental sustainability, mis- and disinformation, as well as bias.

Increased emphasis is placed most notably on risk management practices highlighting novel risks and mechanisms to address risks such as override, repair, decommissioning, and cooperation between AI actors. Privacy, too, takes a more prominent position than before with now 3 vs. 1 mention in the Principles.

How Private AI can Facilitate Adherence to Privacy Principle and Bias Mitigation

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Table 1

The table below displays a colour-coded line-by-line comparison of the old and new principles with green indicating new additions, yellow a re-organization, and red deletions.

Old Principles	New Principles
1.1 Inclusive growth, sustainable development, and well-being Stakeholders should proactively engage in responsible stewardship of trustworthy AI in pursuit of beneficial outcomes for people and the planet, such as augmenting human capabilities and enhancing creativity, advancing inclusion of underrepresented populations, reducing economic, social, gender and other inequalities, and protecting natural environments, thus invigorating inclusive growth, sustainable development and well-being.	1.1. Inclusive growth, sustainable development and well-being Stakeholders should proactively engage in responsible stewardship of trustworthy AI in pursuit of beneficial outcomes for people and the planet, such as augmenting human capabilities and enhancing creativity, advancing inclusion of underrepresented populations, reducing economic, social, gender and other inequalities, and protecting natural environments, thus invigorating inclusive growth, well-being, sustainable development and environmental sustainability.
1.2 Human-centred values and fairness AI actors should respect the rule of law, human rights and democratic values, throughout the AI system lifecycle. These include freedom, dignity and autonomy, privacy and data protection, non-discrimination and equality, diversity, fairness, social justice, and internationally recognised labour rights. To this end, AI actors should implement mechanisms and safeguards, such as capacity for human determination, that are appropriate to the context and consistent with the state of art.	1.2. Respect for the rule of law, human rights and democratic values, including fairness and privacy a) AI actors should respect the rule of law, human rights, democratic and human-centred values throughout the AI system lifecycle. These include non-discrimination and equality, freedom, dignity, autonomy of individuals, privacy and data protection, diversity, fairness, social justice, and internationally recognised labour rights. This also includes addressing misinformation and disinformation amplified by AI, while respecting freedom of expression and other rights and freedoms protected by applicable international law. b) To this end, AI actors should implement mechanisms and safeguards, such as capacity for human agency and oversight, including to address risks arising from uses outside of intended purpose, intentional misuse, or unintentional misuse in a manner appropriate to the context and consistent with the state of the art.
1.3 Transparency and explainability AI Actors should commit to transparency and responsible disclosure regarding AI systems. To this end, they should provide meaningful information, appropriate to the context, and consistent with the state of art: to foster a general understanding of AI systems, to make stakeholders aware of their interactions with AI systems, including in the workplace, to enable those affected by an AI system to understand the outcome, and, to enable those adversely affected by an AI system to challenge its outcome based on plain and easy-to-understand information on the factors, and the logic that served as the basis for the prediction, recommendation or decision.	1.3. Transparency and explainability AI Actors should commit to transparency and responsible disclosure regarding AI systems. To this end, they should provide meaningful information, appropriate to the context, and consistent with the state of art: i. to foster a general understanding of AI systems, including their capabilities and limitations, ii. to make stakeholders aware of their interactions with AI systems, including in the workplace, iii. where feasible and useful, to provide plain and easy-to-understand information on the sources of data/input, factors, processes and/or logic that led to the prediction, content, recommendation or decision, to enable those affected by an AI system to understand the output, and, iv. to provide information that enable those adversely affected by an AI system to challenge its output.
1.4 Robustness, security, and safety AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety risk. To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outcomes and responses to inquiry, appropriate to the context and consistent with the state of art.	1.4. Robustness, security and safety a) AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety and/or security risks b) Mechanisms should be in place, as appropriate, to ensure that if AI systems risk causing undue harm or exhibit undesired behaviour, they can be overridden, repaired, and/or decommissioned safely as needed. c) Mechanisms should also, where technically feasible, be in place to bolster information integrity while ensuring respect for freedom of expression.
1.5 Accountability AI actors should be accountable for the proper functioning of AI systems and for the respect of the above principles, based on their roles, the context, and consistent with the state of art.	1.5. Accountability a) AI actors should be accountable for the proper functioning of AI systems and for the respect of the above principles, based on their roles, the context, and consistent with the state of the art. b) To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outputs and responses to inquiry, appropriate to the context and consistent with the state of the art. c) AI actors, should, based on their roles, the context, and their ability to act, apply a systematic risk management approach to each phase of the AI system lifecycle on an ongoing basis and adopt responsible business conduct to address risks related to AI systems, including, as appropriate, via co-operation between different AI actors, suppliers of AI knowledge and AI resources, AI system users, and other stakeholders. Risks include those related to harmful bias, human rights including safety, security, and privacy, as well as labour and intellectual property rights.

Old Principles

New Principles

1.1 Inclusive growth, sustainable development, and well-being

Stakeholders should proactively engage in responsible stewardship of trustworthy AI in pursuit of beneficial outcomes for people and the planet, such as augmenting human capabilities and enhancing creativity, advancing inclusion of underrepresented populations, reducing economic, social, gender and other inequalities, and protecting natural environments, thus invigorating inclusive growth, sustainable development and well-being.

1.1. Inclusive growth, sustainable development and well-being

1.2 Human-centred values and fairness

AI actors should respect the rule of law, human rights and democratic values, throughout the AI system lifecycle. These include freedom, dignity and autonomy, privacy and data protection, non-discrimination and equality, diversity, fairness, social justice, and internationally recognised labour rights.

To this end, AI actors should implement mechanisms and safeguards, such as capacity for human determination, that are appropriate to the context and consistent with the state of art.

1.2. Respect for the rule of law, human rights and democratic values, including fairness and privacy

a) AI actors should respect the rule of law, human rights, democratic and human-centred values throughout the AI system lifecycle. These include non-discrimination and equality, freedom, dignity, autonomy of individuals, privacy and data protection, diversity, fairness, social justice, and internationally recognised labour rights. This also includes addressing misinformation and disinformation amplified by AI, while respecting freedom of expression and other rights and freedoms protected by applicable international law.

b) To this end, AI actors should implement mechanisms and safeguards, such as capacity for human agency and oversight, including to address risks arising from uses outside of intended purpose, intentional misuse, or unintentional misuse in a manner appropriate to the context and consistent with the state of the art.

1.3 Transparency and explainability

AI Actors should commit to transparency and responsible disclosure regarding AI systems. To this end, they should provide meaningful information, appropriate to the context, and consistent with the state of art:

to foster a general understanding of AI systems,

to make stakeholders aware of their interactions with AI systems, including in the workplace,

to enable those affected by an AI system to understand the outcome, and,

to enable those adversely affected by an AI system to challenge its outcome based on plain and easy-to-understand information on the factors, and the logic that served as the basis for the prediction, recommendation or decision.

1.3. Transparency and explainability

i. to foster a general understanding of AI systems, including their capabilities and limitations,

ii. to make stakeholders aware of their interactions with AI systems, including in the workplace,

iii. where feasible and useful, to provide plain and easy-to-understand information on the sources of data/input, factors, processes and/or logic that led to the prediction, content, recommendation or decision, to enable those affected by an AI system to understand the output, and,

iv. to provide information that enable those adversely

affected by an AI system to challenge its output.

1.4 Robustness, security, and safety

AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety risk.

To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outcomes and responses to inquiry, appropriate to the context and consistent with the state of art.

1.4. Robustness, security and safety

a) AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety and/or security risks

b) Mechanisms should be in place, as appropriate, to ensure that if AI systems risk causing undue harm or exhibit undesired behaviour, they can be overridden, repaired, and/or decommissioned safely as needed.

c) Mechanisms should also, where technically feasible, be in place to bolster information integrity while ensuring respect for freedom of expression.

1.5 Accountability

AI actors should be accountable for the proper functioning of AI systems and for the respect of the above principles, based on their roles, the context, and consistent with the state of art.

1.5. Accountability

a) AI actors should be accountable for the proper functioning of AI systems and for the respect of the above principles, based on their roles, the context, and consistent with the state of the art.

b) To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outputs and responses to inquiry, appropriate to the context and consistent with the state of the art.

c) AI actors, should, based on their roles, the context, and their ability to act, apply a systematic risk management approach to each phase of the AI system lifecycle on an ongoing basis and adopt responsible business conduct to address risks related to AI systems, including, as appropriate, via co-operation between different AI actors, suppliers of AI knowledge and AI resources, AI system users, and other stakeholders. Risks include those related to harmful bias, human rights including safety, security, and privacy, as well as labour and intellectual property rights.