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The Toronto Declaration: Protecting the Rights to Equality and Non-Discrimination in Machine Learning Systems is a declaration that advocates responsible practices for
machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
practitioners and governing bodies. It is a joint statement issued by groups including
Amnesty International Amnesty International (also referred to as Amnesty or AI) is an international non-governmental organization focused on human rights, with its headquarters in the United Kingdom. The organization says it has more than ten million members and sup ...
and
Access Now Access Now is a non-profit organization founded in 2009 with a mission to defend and extend the digital civil rights of people around the world. Access Now supports programs including an annual conference on Human Rights (RightsCon), an index ...
, with other notable signatories including
Human Rights Watch Human Rights Watch (HRW) is an international non-governmental organization, headquartered in New York City, that conducts research and advocacy on human rights. The group pressures governments, policy makers, companies, and individual human r ...
and The Wikimedia Foundation. It was published at
RightsCon Access Now is a non-profit organization founded in 2009 with a mission to defend and extend the digital civil rights of people around the world. Access Now supports programs including an annual conference on Human Rights (RightsCon), an index ...
on May 16, 2018. The Declaration focuses on concerns of algorithmic bias and the potential for
discrimination Discrimination is the act of making unjustified distinctions between people based on the groups, classes, or other categories to which they belong or are perceived to belong. People may be discriminated on the basis of race, gender, age, relig ...
that arises from the use of machine learning and
artificial intelligence Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech re ...
in applications that may affect people's lives, "from policing, to welfare systems, to healthcare provision, to platforms for online discourse." A secondary concern of the document is the potential for violations of information privacy. The goal of the Declaration is to outline "tangible and actionable standards for states and the private sector." The Declaration calls for tangible solutions, such as reparations for the victims of algorithmic discrimination.


Contents

The Toronto Declaration consists of 59 articles, broken into six sections, concerning
international human rights law International human rights law (IHRL) is the body of international law designed to promote human rights on social, regional, and domestic levels. As a form of international law, international human rights law are primarily made up of treaties, ag ...
, duties of states, responsibilities of
private sector The private sector is the part of the economy, sometimes referred to as the citizen sector, which is owned by private groups, usually as a means of establishment for profit or non profit, rather than being owned by the government. Employment The ...
actors, and the
right to an effective remedy The Right to an effective remedy is the right of a person whose human rights have been violated to legal remedy. Such a remedy must be accessible, binding, capable of bringing perpetrators to justice, provide appropriate reparations, and prevent fur ...
.


Preamble

The document begins by asking the question, "In a world of machine learning systems, who will bear accountability for harming
human rights Human rights are Morality, moral principles or Social norm, normsJames Nickel, with assistance from Thomas Pogge, M.B.E. Smith, and Leif Wenar, 13 December 2013, Stanford Encyclopedia of PhilosophyHuman Rights Retrieved 14 August 2014 for ce ...
?" It argues that all practitioners, whether in the public or private sector, should be aware of the risks to human rights and approach their work with human rights in mind – conscious of the existing international laws, standards, and principles. The document defines human rights to include "the right to privacy and data protection, the right to freedom of expression and association, to participation in cultural life, equality before the law, and access to effective remedy"; but it states that the Declaration is most concerned with equality and non-discrimination.


Using the framework of international human rights law

The framework of international human rights law enumerates various rights, provides mechanisms to hold violators to account, and ensures remedy for the violated. The document cites the
United Nations Human Rights Committee The United Nations Human Rights Committee is a treaty body composed of 18 experts, established by a 1966 human rights treaty, the International Covenant on Civil and Political Rights (ICCPR). The Committee meets for three four-week sessions per y ...
's definition of discrimination as "any distinction, exclusion, restriction or preference which is based on any ground ncluding but not limited torace, colour, sex, language, religion, political or other opinion, national or social origin, property, birth or other status, and which has the purpose or effect of nullifying or impairing the recognition, enjoyment or exercise by all persons, on an equal footing, of all rights and freedoms." Governments should proactively create binding measures, and private entities should create internal policies, to protect against discrimination. Measures may include protections for sensitive data, especially for vulnerable populations. Systems should be designed in collaboration with a diverse community in order to prevent discrimination in design.


Duties of states: human rights obligations

Governments today are deploying machine learning systems, often in collaboration with private entities. Even when development is contracted to such third parties, governments retain their obligation to protect human rights. Before implementation, and on an ongoing basis thereafter, they should identify risks and conduct regular audits, then take all necessary measures to mitigate these risks. They should be transparent about how machine learning is implemented and used, avoiding black box systems whose logic cannot be easily explained. Systems should be subject to strict oversight from diverse internal committees and independent judicial authorities. Governments must also protect citizens from discrimination by private entities. In addition to oversight, they should pass binding laws against discrimination, as well as for data protection and privacy, and they should provide effective means to remedy for affected individuals. It is important for national and regional governments to expand on and contextualize international law.


Responsibilities of private sector actors: human rights due diligence

Private entities are responsible for conducting "human rights due diligence." Just like governments, private entities should identify risks before development by considering common risks and consulting stakeholders, "including affected groups, organizations that work on human rights, equality and discrimination, as well as independent human rights and machine learning experts." They should design systems that mitigate risks, subject systems to regular audits, and forego projects that carry too high of risks. They should be transparent about assumed risks, including details of the technical implementation where necessary, and should provide a mechanism for affected individuals to dispute any decisions that affect them.


The right to an effective remedy

"The right to justice is a vital element of international human rights law." Private entities should create processes for affected individuals to seek remedy, and they should designate roles for who will oversee these processes. Governments must be especially cautious when deploying machine learning systems in the justice sector. Transparency, accountability, and remedy can help.


References

{{reflist Machine learning Information ethics 2018 documents Computing and society Manifestos