9. Ban the Attribution of Responsibility to Robots

Robots should be designed and operated as far as is practicable to comply with existing laws, fundamental rights and freedoms, including privacy. This is linked to the question of legal responsibility. In line with Bryson et al 2011, UNI Global Union asserts that legal responsibility for a robot should be attributed to a person. Robots are not responsible parties under the law.
Principle: Top 10 Principles For Ethical Artificial Intelligence, Dec 11, 2017

Published by UNI Global Union

Related Principles

(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

(h) Data protection and privacy

In an age of ubiquitous and massive collection of data through digital communication technologies, the right to protection of personal information and the right to respect for privacy are crucially challenged. Both physical AI robots as part of the Internet of Things, as well as AI softbots that operate via the World Wide Web must comply with data protection regulations and not collect and spread data or be run on sets of data for whose use and dissemination no informed consent has been given. ‘Autonomous’ systems must not interfere with the right to private life which comprises the right to be free from technologies that influence personal development and opinions, the right to establish and develop relationships with other human beings, and the right to be free from surveillance. Also in this regard, exact criteria should be defined and mechanisms established that ensure ethical development and ethically correct application of ‘autonomous’ systems. In light of concerns with regard to the implications of ‘autonomous’ systems on private life and privacy, consideration may be given to the ongoing debate about the introduction of two new rights: the right to meaningful human contact and the right to not be profiled, measured, analysed, coached or nudged.

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

1. Principle 1 — Human Rights

Issue: How can we ensure that A IS do not infringe upon human rights? [Candidate Recommendations] To best honor human rights, society must assure the safety and security of A IS so that they are designed and operated in a way that benefits humans: 1. Governance frameworks, including standards and regulatory bodies, should be established to oversee processes assuring that the use of A IS does not infringe upon human rights, freedoms, dignity, and privacy, and of traceability to contribute to the building of public trust in A IS. 2. A way to translate existing and forthcoming legal obligations into informed policy and technical considerations is needed. Such a method should allow for differing cultural norms as well as legal and regulatory frameworks. 3. For the foreseeable future, A IS should not be granted rights and privileges equal to human rights: A IS should always be subordinate to human judgment and control.

Published by The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems in Ethically Aligned Design (v2): General Principles, (v1) Dec 13, 2016. (v2) Dec 12, 2017

4. Adopt a Human In Command Approach

An absolute precondition is that the development of AI must be responsible, safe and useful, where machines maintain the legal status of tools, and legal persons retain control over, and responsibility for, these machines at all times. This entails that AI systems should be designed and operated to comply with existing law, including privacy. Workers should have the right to access, manage and control the data AI systems generate, given said systems’ power to analyse and utilize that data (See principle 1 in “Top 10 principles for workers’ data privacy and protection”). Workers must also have the ‘right of explanation’ when AI systems are used in human resource procedures, such as recruitment, promotion or dismissal.

Published by UNI Global Union in Top 10 Principles For Ethical Artificial Intelligence, Dec 11, 2017

4 Foster responsibility and accountability

Humans require clear, transparent specification of the tasks that systems can perform and the conditions under which they can achieve the desired level of performance; this helps to ensure that health care providers can use an AI technology responsibly. Although AI technologies perform specific tasks, it is the responsibility of human stakeholders to ensure that they can perform those tasks and that they are used under appropriate conditions. Responsibility can be assured by application of “human warranty”, which implies evaluation by patients and clinicians in the development and deployment of AI technologies. In human warranty, regulatory principles are applied upstream and downstream of the algorithm by establishing points of human supervision. The critical points of supervision are identified by discussions among professionals, patients and designers. The goal is to ensure that the algorithm remains on a machine learning development path that is medically effective, can be interrogated and is ethically responsible; it involves active partnership with patients and the public, such as meaningful public consultation and debate (101). Ultimately, such work should be validated by regulatory agencies or other supervisory authorities. When something does go wrong in application of an AI technology, there should be accountability. Appropriate mechanisms should be adopted to ensure questioning by and redress for individuals and groups adversely affected by algorithmically informed decisions. This should include access to prompt, effective remedies and redress from governments and companies that deploy AI technologies for health care. Redress should include compensation, rehabilitation, restitution, sanctions where necessary and a guarantee of non repetition. The use of AI technologies in medicine requires attribution of responsibility within complex systems in which responsibility is distributed among numerous agents. When medical decisions by AI technologies harm individuals, responsibility and accountability processes should clearly identify the relative roles of manufacturers and clinical users in the harm. This is an evolving challenge and remains unsettled in the laws of most countries. Institutions have not only legal liability but also a duty to assume responsibility for decisions made by the algorithms they use, even if it is not feasible to explain in detail how the algorithms produce their results. To avoid diffusion of responsibility, in which “everybody’s problem becomes nobody’s responsibility”, a faultless responsibility model (“collective responsibility”), in which all the agents involved in the development and deployment of an AI technology are held responsible, can encourage all actors to act with integrity and minimize harm. In such a model, the actual intentions of each agent (or actor) or their ability to control an outcome are not considered.

Published by World Health Organization (WHO) in Key ethical principles for use of artificial intelligence for health, Jun 28, 2021