Ten core principles in a human-rights centred approach to the Ethics of AI
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Ten core principles in a human-rights centred approach to the Ethics of AI

UNESCO

1 PROPORTIONALITY AND DO NO HARM

The use of AI systems must not go beyond what is necessary to achieve a legitimate aim. Risk assessment should be used to prevent harms which may result from such uses.

2 SAFETY AND SECURITY

Unwanted harms (safety risks) as well as vulnerabilities to attack (security risks) should be avoided and addressed by AI actors.

3 RIGHT TO PRIVACY AND DATA PROTECTION

Privacy must be protected and promoted throughout the AI lifecycle. Adequate data protection frameworks should also be established.

4 MULTI-STAKEHOLDER AND ADAPTIVE GOVERNANCE & COLLABORATION

International law & national sovereignty must be respected in the use of data. Additionally, participation of diverse stakeholders is necessary for inclusive approaches to AI governance.

5 RESPONSIBILITY AND ACCOUNTABILITY

AI systems should be auditable and traceable. There should be oversight, impact assessment, audit and due diligence mechanisms in place to avoid conflicts with human rights norms and threats to environmental wellbeing.

6 TRANSPARENCY AND EXPLAINABILITY

The ethical deployment of AI systems depends on their transparency and explainability. For example, people should be made aware when a decision is informed by AI. The level of transparency and explainability should be appropriate to the context, as there may be tensions between transparency and explainability and other principles such as privacy, safety and security.

7 HUMAN OVERSIGHT AND DETERMINATION

Member States should ensure that AI systems do not displace ultimate human responsibility and accountability.

8 SUSTAINABILITY

AI technologies should be assessed against their impacts on ‘sustainability’, understood as a set of constantly evolving goals including those set out in the UN’s Sustainable Development Goals.

9 AWARENESS AND LITERACY

Public understanding of AI and data should be promoted through open and accessible education, civic engagement, digital skills and AI ethics training, media and information literacy.

10 FAIRNESS AND NON-DISCRIMINATION

AI actors should promote social justice, fairness, and non-discrimination while taking an inclusive approach to ensure AI’s benefits are accessible to all.

Policy Area 9: Communication and Information

112. Member States should use AI systems to improve access to information and knowledge. This can include support to researchers, academia, journalists, the general public and developers, to enhance freedom of expression, academic and scientific freedoms, access to information, and increased proactive disclosure of official data and information.

113. Member States should ensure that AI actors respect and promote freedom of expression as well as access to information with regard to automated content generation, moderation and curation. Appropriate frameworks, including regulation, should enable transparency of online communication and information operators and ensure users have access to a diversity of viewpoints, as well as processes for prompt notification to the users on the reasons for removal or other treatment of content, and appeal mechanisms that allow users to seek redress.

114. Member States should invest in and promote digital and media and information literacy skills to strengthen critical thinking and competencies needed to understand the use and implication of AI systems, in order to mitigate and counter disinformation, misinformation and hate speech. A better understanding and evaluation of both the positive and potentially harmful effects of recommender systems should be part of those efforts.

115. Member States should create enabling environments for media to have the rights and resources to effectively report on the benefits and harms of AI systems, and also encourage media to make ethical use of AI systems intheir operations.

Excerpted from: UNESCO. Recommendation on the Ethics of Artificial Intelligence. Adopted on 23 November 2021. Published in 2022. Available in Open Access under the Attribution-NonCommercial-ShareAlike 3.0 IGO (CC-BY-NC-SA 3.0 IGO) license.

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