· Responsibility and accountability

42. AI actors and Member States should respect, protect and promote human rights and fundamental freedoms, and should also promote the protection of the environment and ecosystems, assuming their respective ethical and legal responsibility, in accordance with national and international law, in particular Member States’ human rights obligations, and ethical guidance throughout the life cycle of AI systems, including with respect to AI actors within their effective territory and control. The ethical responsibility and liability for the decisions and actions based in any way on an AI system should always ultimately be attributable to AI actors corresponding to their role in the life cycle of the AI system. 43. Appropriate oversight, impact assessment, audit and due diligence mechanisms, including whistle blowers’ protection, should be developed to ensure accountability for AI systems and their impact throughout their life cycle. Both technical and institutional designs should ensure auditability and traceability of (the working of) AI systems in particular to address any conflicts with human rights norms and standards and threats to environmental and ecosystem well being.
Principle: The Recommendation on the Ethics of Artificial Intelligence, Nov 24, 2021

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO)

Related Principles

I. Human agency and oversight

AI systems should support individuals in making better, more informed choices in accordance with their goals. They should act as enablers to a flourishing and equitable society by supporting human agency and fundamental rights, and not decrease, limit or misguide human autonomy. The overall wellbeing of the user should be central to the system's functionality. Human oversight helps ensuring that an AI system does not undermine human autonomy or causes other adverse effects. Depending on the specific AI based system and its application area, the appropriate degrees of control measures, including the adaptability, accuracy and explainability of AI based systems, should be ensured. Oversight may be achieved through governance mechanisms such as ensuring a human in the loop, human on the loop, or human in command approach. It must be ensured that public authorities have the ability to exercise their oversight powers in line with their mandates. All other things being equal, the less oversight a human can exercise over an AI system, the more extensive testing and stricter governance is required.

Published by European Commission in Key requirements for trustworthy AI, Apr 8, 2019

(f) Rule of law and accountability

Rule of law, access to justice and the right to redress and a fair trial provide the necessary framework for ensuring the observance of human rights standards and potential AI specific regulations. This includes protections against risks stemming from ‘autonomous’ systems that could infringe human rights, such as safety and privacy. The whole range of legal challenges arising in the field should be addressed with timely investment in the development of robust solutions that provide a fair and clear allocation of responsibilities and efficient mechanisms of binding law. In this regard, governments and international organisations ought to increase their efforts in clarifying with whom liabilities lie for damages caused by undesired behaviour of ‘autonomous’ systems. Moreover, effective harm mitigation systems should be in place.

Published by European Group on Ethics in Science and New Technologies, European Commission in Ethical principles and democratic prerequisites, Mar 9, 2018

Chapter 1. General Principles

  1. This set of norms aims to integrate ethics into the entire life cycle of AI, to promote fairness, justice, harmony, safety and security, and to avoid issues such as prejudice, discrimination, privacy and information leakage.   2. This set of norms applies to natural persons, legal persons, and other related organizations engaged in related activities such as management, research and development, supply, and use of AI. (1) The management activities mainly refer to strategic planning, formulation and implementation of policies, laws, regulations, and technical standards, resource allocation, supervision and inspection, etc. (2) The research and development activities mainly refer to scientific research, technology development, product development, etc. related to AI. (3) The supply activities mainly refer to the production, operation, and sales of AI products and services. (4) The use activities mainly refer to the procurement, consumption, and manipulation of AI products and services.   3. Various activities of AI shall abide by the following fundamental ethical norms. (1) Enhancing the well being of humankind. Adhere to the people oriented vision, abide by the common values of humankind, respect human rights and the fundamental interests of humankind, and abide by national and regional ethical norms. Adhere to the priority of public interests, promote human machine harmony, improve people’s livelihood, enhance the sense of happiness, promote the sustainable development of economy, society and ecology, and jointly build a human community with a shared future. (2) Promoting fairness and justice. Adhere to shared benefits and inclusivity, effectively protect the legitimate rights and interests of all relevant stakeholders, promote fair sharing of the benefits of AI in the whole society, and promote social fairness and justice, and equal opportunities. When providing AI products and services, we should fully respect and help vulnerable groups and underrepresented groups, and provide corresponding alternatives as needed. (3) Protecting privacy and security. Fully respect the rights of personal information, to know, and to consent, etc., handle personal information, protect personal privacy and data security in accordance with the principles of lawfulness, justifiability, necessity, and integrity, do no harm to the legitimate rights of personal data, must not illegally collect and use personal information by stealing, tampering, or leaking, etc., and must not infringe on the rights of personal privacy. (4) Ensuring controllability and trustworthiness. Ensure that humans have the full power for decision making, the rights to choose whether to accept the services provided by AI, the rights to withdraw from the interaction with AI at any time, and the rights to suspend the operation of AI systems at any time, and ensure that AI is always under meaningful human control. (5) Strengthening accountability. Adhere that human beings are the ultimate liable subjects. Clarify the responsibilities of all relevant stakeholders, comprehensively enhance the awareness of responsibility, introspect and self discipline in the entire life cycle of AI. Establish an accountability mechanism in AI related activities, and do not evade liability reviews and do not escape from responsibilities. (6) Improving ethical literacy. Actively learn and popularize knowledge related to AI ethics, objectively understand ethical issues, and do not underestimate or exaggerate ethical risks. Actively carry out or participate in the discussions on the ethical issues of AI, deeply promote the practice of AI ethics and governance, and improve the ability to respond to related issues.   4. The ethical norms that should be followed in specific activities related to AI include the norms of management, the norms of research and development, the norms of supply, and the norms of use.

Published by National Governance Committee for the New Generation Artificial Intelligence, China in Ethical Norms for the New Generation Artificial Intelligence, Sep 25, 2021

· Right to Privacy, and Data Protection

32. Privacy, a right essential to the protection of human dignity, human autonomy and human agency, must be respected, protected and promoted throughout the life cycle of AI systems. It is important that data for AI systems be collected, used, shared, archived and deleted in ways that are consistent with international law and in line with the values and principles set forth in this Recommendation, while respecting relevant national, regional and international legal frameworks. 33. Adequate data protection frameworks and governance mechanisms should be established in a multi stakeholder approach at the national or international level, protected by judicial systems, and ensured throughout the life cycle of AI systems. Data protection frameworks and any related mechanisms should take reference from international data protection principles and standards concerning the collection, use and disclosure of personal data and exercise of their rights by data subjects while ensuring a legitimate aim and a valid legal basis for the processing of personal data, including informed consent. 34. Algorithmic systems require adequate privacy impact assessments, which also include societal and ethical considerations of their use and an innovative use of the privacy by design approach. AI actors need to ensure that they are accountable for the design and implementation of AI systems in such a way as to ensure that personal information is protected throughout the life cycle of the AI system.

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO) in The Recommendation on the Ethics of Artificial Intelligence, Nov 24, 2021

· Transparency and explainability

37. The transparency and explainability of AI systems are often essential preconditions to ensure the respect, protection and promotion of human rights, fundamental freedoms and ethical principles. Transparency is necessary for relevant national and international liability regimes to work effectively. A lack of transparency could also undermine the possibility of effectively challenging decisions based on outcomes produced by AI systems and may thereby infringe the right to a fair trial and effective remedy, and limits the areas in which these systems can be legally used. 38. While efforts need to be made to increase transparency and explainability of AI systems, including those with extra territorial impact, throughout their life cycle to support democratic governance, the level of transparency and explainability should always be appropriate to the context and impact, as there may be a need to balance between transparency and explainability and other principles such as privacy, safety and security. People should be fully informed when a decision is informed by or is made on the basis of AI algorithms, including when it affects their safety or human rights, and in those circumstances should have the opportunity to request explanatory information from the relevant AI actor or public sector institutions. In addition, individuals should be able to access the reasons for a decision affecting their rights and freedoms, and have the option of making submissions to a designated staff member of the private sector company or public sector institution able to review and correct the decision. AI actors should inform users when a product or service is provided directly or with the assistance of AI systems in a proper and timely manner. 39. From a socio technical lens, greater transparency contributes to more peaceful, just, democratic and inclusive societies. It allows for public scrutiny that can decrease corruption and discrimination, and can also help detect and prevent negative impacts on human rights. Transparency aims at providing appropriate information to the respective addressees to enable their understanding and foster trust. Specific to the AI system, transparency can enable people to understand how each stage of an AI system is put in place, appropriate to the context and sensitivity of the AI system. It may also include insight into factors that affect a specific prediction or decision, and whether or not appropriate assurances (such as safety or fairness measures) are in place. In cases of serious threats of adverse human rights impacts, transparency may also require the sharing of code or datasets. 40. Explainability refers to making intelligible and providing insight into the outcome of AI systems. The explainability of AI systems also refers to the understandability of the input, output and the functioning of each algorithmic building block and how it contributes to the outcome of the systems. Thus, explainability is closely related to transparency, as outcomes and ub processes leading to outcomes should aim to be understandable and traceable, appropriate to the context. AI actors should commit to ensuring that the algorithms developed are explainable. In the case of AI applications that impact the end user in a way that is not temporary, easily reversible or otherwise low risk, it should be ensured that the meaningful explanation is provided with any decision that resulted in the action taken in order for the outcome to be considered transparent. 41. Transparency and explainability relate closely to adequate responsibility and accountability measures, as well as to the trustworthiness of AI systems.

Published by The United Nations Educational, Scientific and Cultural Organization (UNESCO) in The Recommendation on the Ethics of Artificial Intelligence, Nov 24, 2021