Artificial Intelligence (AI) is a field that utilizes computing and often, data and statistics, intensively together to solve problems or make predictions. AI has been evolving with literally unbelievable speed over the past few years, and this has led to an increase in social, cultural, industrial, scientific, and governmental concerns about the ethical development and use of AI systems worldwide. The ASA has issued a statement on ethical statistical practice and AI (ASA, 2024), which echoes similar statements from other groups. Here we discuss the support for ethical statistical practice and ethical AI that has been established in long-standing human rights law and ethical practice standards for computing and statistics. There are multiple sources of support for ethical statistical practice and ethical AI deriving from these source documents, which are critical for strengthening the operationalization of the "Statement on Ethical AI for Statistics Practitioners". These resources are explicated for interested readers to utilize to guide their development and use of AI in, and through, their statistical practice.

Artificial intelligence (AI) are systems designed and programmed to work or act like humans. The process includes AI solving complex problems, learning, and improving themselves over time. At the rate the technology is developing, experts believe that AI will eventually mimic and perform tasks like a human. The positive applications for AI in every significant aspect of human life is beyond measure. The technology is already being deployed in medicine and used extensively in consumer electronics.

This blogpost is an updated round up of the various sets of ethical principles of robotics and AI that have been proposed to date, ordered by date of first publication. I previously listed principles published before December 2017 here; this blogpost appends those principles drafted since January 2018 (plus one in October 2017 I had missed). The principles are listed here (in full or abridged) with links, notes and references but without critique. If there any (prominent) ones I've missed please let me know. I have included these to explicitly acknowledge, firstly, that Asimov undoubtedly established the principle that robots (and by extension AIs) should be governed by principles, and secondly that many subsequent principles have been drafted as a direct response.

In May 2018, Amnesty International, Access Now, and a handful of partner organizations launched the Toronto Declaration on protecting the right to equality and non-discrimination in machine learning systems. The Declaration is a landmark document that seeks to apply existing international human rights standards to the development and use of machine learning systems (or "artificial intelligence"). Machine learning (ML) is a subset of artificial intelligence. It can be defined as " provid[ing] systems the ability to automatically learn and improve from experience without being explicitly programmed." One of the most significant risks with machine learning is the danger of amplifying existing bias and discrimination against certain groups who already struggle to be treated with dignity and respect.

In May 2018, Amnesty International, Access Now, and a handful of partner organizations launched the Toronto Declaration on protecting the right to equality and non-discrimination in machine learning systems. The Declaration is a landmark document that seeks to apply existing international human rights standards to the development and use of machine learning systems (or "artificial intelligence"). Machine learning (ML) is a subset of artificial intelligence. It can be defined as " provid[ing] systems the ability to automatically learn and improve from experience without being explicitly programmed." How is this technology relevant to human rights?

When it comes to developing artificial intelligence, President Trump may want a free-market approach. But a number of experts disagree -- we need guidelines to protect people from discriminatory algorithms. Today, a group of humans rights organizations such as Human Rights Watch, Amnesty International, The Wikimedia Foundation, Access Now, and others called on governments and technology companies to adopt guiding principles to protect human rights. As part of today's RightsCon Toronto symposium, the organizations joined to pen the Toronto Declaration on Machine Learning, which can be found in full on Access Now's website. The declaration calls for engineers to develop and revisit algorithms with the explicit goal of promoting transparency and equality while working to end algorithm-propagated racism and discrimination.

When it comes to developing artificial intelligence, President Trump may want a free-market approach. But a number of experts disagree -- we need guidelines to protect people from discriminatory algorithms. Today, a group of humans rights organizations such as Human Rights Watch, Amnesty International, The Wikimedia Foundation, Access Now, and others called on governments and technology companies to adopt guiding principles to protect human rights. As part of today's RightsCon Toronto symposium, the organizations joined to pen the Toronto Declaration on Machine Learning, which can be found in full on Access Now's website. The declaration calls for engineers to develop and revisit algorithms with the explicit goal of promoting transparency and equality while working to end algorithm-propagated racism and discrimination.