Safe and Ethical AI (SEA) Platform Network · Linking Artificial Intelligence Principles (LAIP)

(b) Autonomy

The principle of autonomy implies the freedom of the human being. This translates into human responsibility and thus control over and knowledge about ‘autonomous’ systems as they must not impair freedom of human beings to set their own standards and norms and be able to live according to them. All ‘autonomous’ technologies must, hence, honour the human ability to choose whether, when and how to delegate decisions and actions to them. This also involves the transparency and predictability of ‘autonomous’ systems, without which users would not be able to intervene or terminate them if they would consider this morally required.

Principle: Ethical principles and democratic prerequisites, Mar 9, 2018

Published by European Group on Ethics in Science and New Technologies, European Commission

Related Principles

Proportionality and harmlessness.

It should be recognised that AI technologies do not necessarily, in and of themselves, guarantee the prosperity of humans or the environment and ecosystems. In the event that any harm to humans may occur, risk assessment procedures should be applied and measures taken to prevent such harm from occurring. In other words, for a human person to be legally responsible for the decisions he or she makes to carry out one or more actions, there must be discernment (full human mental faculties), intention (human drive or desire) and freedom (to act in a calculated and premeditated manner). Therefore, to avoid falling into anthropomorphisms that could hinder eventual regulations and or wrong attributions, it is important to establish the conception of artificial intelligences as artifices, that is, as technology, a thing, an artificial means to achieve human objectives but which should not be confused with a human person. That is, the algorithm can execute, but the decision must necessarily fall on the person and therefore, so must the responsibility. Consequently, it emerges that an algorithm does not possess self determination and or agency to make decisions freely (although many times in colloquial language the concept of "decision" is used to describe a classification executed by an algorithm after training), and therefore it cannot be held responsible for the actions that are executed through said algorithm in question.

Published by OFFICE OF THE CHIEF OF MINISTERS UNDERSECRETARY OF INFORMATION TECHNOLOGIES in Recommendations for reliable artificial intelligence, Jnue 2, 2023

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

(a) Human dignity

The principle of human dignity, understood as the recognition of the inherent human state of being worthy of respect, must not be violated by ‘autonomous’ technologies. This means, for instance, that there are limits to determinations and classifications concerning persons, made on the basis of algorithms and ‘autonomous’ systems, especially when those affected by them are not informed about them. It also implies that there have to be (legal) limits to the ways in which people can be led to believe that they are dealing with human beings while in fact they are dealing with algorithms and smart machines. A relational conception of human dignity which is characterised by our social relations, requires that we are aware of whether and when we are interacting with a machine or another human being, and that we reserve the right to vest certain tasks to the human or the machine.

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

2. Autonomy

[QUESTIONS] How can AI contribute to greater autonomy for human beings? Must we fight against the phenomenon of attention seeking which has accompanied advances in AI? Should we be worried that humans prefer the company of AI to that of other humans or animals? Can someone give informed consent when faced with increasingly complex autonomous technologies? Must we limit the autonomy of intelligent computer systems? Should a human always make the final decision? [PRINCIPLES] The development of AI should promote the autonomy of all human beings and control, in a responsible way, the autonomy of computer systems.

Published by University of Montreal, Forum on the Socially Responsible Development of AI in The Montreal Declaration for a Responsible Development of Artificial Intelligence, Nov 3, 2017

1 Protect autonomy

Adoption of AI can lead to situations in which decision making could be or is in fact transferred to machines. The principle of autonomy requires that any extension of machine autonomy not undermine human autonomy. In the context of health care, this means that humans should remain in full control of health care systems and medical decisions. AI systems should be designed demonstrably and systematically to conform to the principles and human rights with which they cohere; more specifically, they should be designed to assist humans, whether they be medical providers or patients, in making informed decisions. Human oversight may depend on the risks associated with an AI system but should always be meaningful and should thus include effective, transparent monitoring of human values and moral considerations. In practice, this could include deciding whether to use an AI system for a particular health care decision, to vary the level of human discretion and decision making and to develop AI technologies that can rank decisions when appropriate (as opposed to a single decision). These practicescan ensure a clinician can override decisions made by AI systems and that machine autonomy can be restricted and made “intrinsically reversible”. Respect for autonomy also entails the related duties to protect privacy and confidentiality and to ensure informed, valid consent by adopting appropriate legal frameworks for data protection. These should be fully supported and enforced by governments and respected by companies and their system designers, programmers, database creators and others. AI technologies should not be used for experimentation or manipulation of humans in a health care system without valid informed consent. The use of machine learning algorithms in diagnosis, prognosis and treatment plans should be incorporated into the process for informed and valid consent. Essential services should not be circumscribed or denied if an individual withholds consent and that additional incentives or inducements should not be offered by either a government or private parties to individuals who do provide consent. Data protection laws are one means of safeguarding individual rights and place obligations on data controllers and data processors. Such laws are necessary to protect privacy and the confidentiality of patient data and to establish patients’ control over their data. Construed broadly, data protection laws should also make it easy for people to access their own health data and to move or share those data as they like. Because machine learning requires large amounts of data – big data – these laws are increasingly important.

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