Regulation Of Artificial Intelligence

Regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating artificial intelligence (AI). It is part of the broader regulation of algorithms. The regulatory and policy landscape for AI is an emerging issue in jurisdictions worldwide, including for international organizations without direct enforcement power like the IEEE or the OECD.

Since 2016, numerous AI ethics guidelines have been published in order to maintain social control over the technology. Regulation is deemed necessary to both foster AI innovation and manage associated risks.

Furthermore, organizations deploying AI have a central role to play in creating and implementing trustworthy AI, adhering to established principles, and taking accountability for mitigating risks.

Regulating AI through mechanisms such as review boards can also be seen as social means to approach the AI control problem.

Background

According to Stanford University's 2025 AI Index, legislative mentions of AI rose 21.3% across 75 countries since 2023, marking a ninefold increase since 2016. The U.S. federal agencies introduced 59 AI-related regulations in 2024—more than double the number in 2023.

There is currently no broad consensus on the degree or mechanics of AI regulation. Several prominent figures in the field, including Elon Musk, Sam Altman, Dario Amodei, and Demis Hassabis have publicly called for immediate regulation of AI. In 2023, following ChatGPT-4's creation, Elon Musk and others signed an open letter urging a moratorium on the training of more powerful AI systems. Others, such as Mark Zuckerberg and Marc Andreessen, have warned about the risk of preemptive regulation stifling innovation.

In a 2022 Ipsos survey, attitudes towards AI varied greatly by country; 78% of Chinese citizens, but only 35% of Americans,In 2023, following ChatGPT-4's creation, Elon Musk and others signed an open letter urging a moratorium on the training of more powerful AI systems. agreed that "products and services using AI have more benefits than drawbacks". A 2023 Reuters/Ipsos poll found that 61% of Americans agree, and 22% disagree, that AI poses risks to humanity. In a 2023 Fox News poll, 35% of Americans thought it "very important", and an additional 41% thought it "somewhat important", for the federal government to regulate AI, versus 13% responding "not very important" and 8% responding "not at all important".

Perspectives

The regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating AI. Regulation is now generally considered necessary to both encourage AI and manage associated risks. Public administration and policy considerations generally focus on the technical and economic implications and on trustworthy and human-centered AI systems, regulation of artificial superintelligence, the risks and biases of machine-learning algorithms, the explainability of model outputs, and the tension between open source AI and unchecked AI use.

There have been both hard law and soft law proposals to regulate AI. Some legal scholars have noted that hard law approaches to AI regulation have substantial challenges. Among the challenges, AI technology is rapidly evolving leading to a "pacing problem" where traditional laws and regulations often cannot keep up with emerging applications and their associated risks and benefits. Similarly, the diversity of AI applications challenges existing regulatory agencies, which often have limited jurisdictional scope. As an alternative, some legal scholars argue that soft law approaches to AI regulation are promising because soft laws can be adapted more flexibly to meet the needs of emerging and evolving AI technology and nascent applications. However, soft law approaches often lack substantial enforcement potential.

Cason Schmit, Megan Doerr, and Jennifer Wagner proposed the creation of a quasi-governmental regulator by leveraging intellectual property rights (i.e., copyleft licensing) in certain AI objects (i.e., AI models and training datasets) and delegating enforcement rights to a designated enforcement entity. They argue that AI can be licensed under terms that require adherence to specified ethical practices and codes of conduct. (e.g., soft law principles).

Prominent youth organizations focused on AI, namely Encode Justice, have also issued comprehensive agendas calling for more stringent AI regulations and public-private partnerships.

AI regulation could derive from basic principles. A 2020 Berkman Klein Center for Internet & Society meta-review of existing sets of principles, such as the Asilomar Principles and the Beijing Principles, identified eight such basic principles: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and respect for human values. AI law and regulations have been divided into three main topics, namely governance of autonomous intelligence systems, responsibility and accountability for the systems, and privacy and safety issues. A public administration approach sees a relationship between AI law and regulation, the ethics of AI, and 'AI society', defined as workforce substitution and transformation, social acceptance and trust in AI, and the transformation of human to machine interaction. The development of public sector strategies for management and regulation of AI is deemed necessary at the local, national, and international levels and in a variety of fields, from public service management and accountability to law enforcement, healthcare (especially the concept of a Human Guarantee), the financial sector, robotics, autonomous vehicles, the military and national security, and international law.

Henry Kissinger, Eric Schmidt, and Daniel Huttenlocher published a joint statement in November 2021 entitled "Being Human in an Age of AI", calling for a government commission to regulate AI.

As a response to the AI control problem

Regulation of AI can be seen as positive social means to manage the AI control problem (the need to ensure long-term beneficial AI), with other social responses such as doing nothing or banning being seen as impractical, and approaches such as enhancing human capabilities through transhumanism techniques like brain-computer interfaces being seen as potentially complementary. Regulation of research into artificial general intelligence (AGI) focuses on the role of review boards, from university or corporation to international levels, and on encouraging research into AI safety, together with the possibility of differential intellectual progress (prioritizing protective strategies over risky strategies in AI development) or conducting international mass surveillance to perform AGI arms control. For instance, the 'AGI Nanny' is a proposed strategy, potentially under the control of humanity, for preventing the creation of a dangerous superintelligence as well as for addressing other major threats to human well-being, such as subversion of the global financial system, until a true superintelligence can be safely created. It entails the creation of a smarter-than-human, but not superintelligent, AGI system connected to a large surveillance network, with the goal of monitoring humanity and protecting it from danger. Regulation of conscious, ethically aware AGIs focuses on how to integrate them with existing human society and can be divided into considerations of their legal standing and of their moral rights. Regulation of AI has been seen as restrictive, with a risk of preventing the development of AGI.

Global guidance

The development of a global governance board to regulate AI development was suggested at least as early as 2017. In December 2018, Canada and France announced plans for a G7-backed International Panel on Artificial Intelligence, modeled on the International Panel on Climate Change, to study the global effects of AI on people and economies and to steer AI development. In 2019, the Panel was renamed the Global Partnership on AI.

The Global Partnership on Artificial Intelligence (GPAI) was launched in June 2020, stating a need for AI to be developed in accordance with human rights and democratic values, to ensure public confidence and trust in the technology, as outlined in the OECD ''Principles on Artificial Intelligence'' (2019). The 15 founding members of the Global Partnership on Artificial Intelligence are Australia, Canada, the European Union, France, Germany, India, Italy, Japan, the Republic of Korea, Mexico, New Zealand, Singapore, Slovenia, the United States and the UK. In 2023, the GPAI has 29 members. The GPAI Secretariat is hosted by the OECD in Paris, France. GPAI's mandate covers four themes, two of which are supported by the International Centre of Expertise in Montréal for the Advancement of Artificial Intelligence, namely, responsible AI and data governance. A corresponding centre of excellence in Paris will support the other two themes on the future of work, and on innovation and commercialization. GPAI also investigated how AI can be leveraged to respond to the COVID-19 pandemic.

The OECD AI Principles were adopted in May 2019, and the G20 AI Principles in June 2019. In September 2019 the World Economic Forum issued ten 'AI Government Procurement Guidelines'. In February 2020, the European Union published its draft strategy paper for promoting and regulating AI.

At the United Nations (UN), several entities have begun to promote and discuss aspects of AI regulation and policy, including the UNICRI Centre for AI and Robotics. In partnership with INTERPOL, UNICRI's Centre issued the report ''AI and Robotics for Law Enforcement'' in April 2019 and the follow-up report ''Towards Responsible AI Innovation'' in May 2020. At UNESCO's Scientific 40th session in November 2019, the organization commenced a two-year process to achieve a "global standard-setting instrument on ethics of artificial intelligence". In pursuit of this goal, UNESCO forums and conferences on AI were held to gather stakeholder views. A draft text of a ''Recommendation on the Ethics of AI'' of the UNESCO Ad Hoc Expert Group was issued in September 2020 and included a call for legislative gaps to be filled. (The CC BY 4.0 licence means that everyone have the right to reuse the text that is quoted here, or other parts of the original article itself, if they credit the authors. More info: Creative Commons license) Changes were made as follows: citations removed and minor grammatical amendments. UNESCO tabled the international instrument on the ethics of AI for adoption at its General Conference in November 2021; this was subsequently adopted. While the UN is making progress with the global management of AI, its institutional and legal capability to manage the AGI existential risk is more limited.

An initiative of International Telecommunication Union (ITU) in partnership with 40 UN sister agencies, AI for Good is a global platform which aims to identify practical applications of AI to advance the United Nations Sustainable Development Goals and scale those solutions for global impact. It is an action-oriented, global & inclusive United Nations platform fostering development of AI to positively impact health, climate, gender, inclusive prosperity, sustainable infrastructure, and other global development priorities.

Recent research has indicated that countries will also begin to use artificial intelligence as a tool for national cyberdefense. AI is a new factor in the cyber arms industry, as it can be used for defense purposes. Therefore, academics urge that nations should establish regulations for the use of AI, similar to how there are regulations for other military industries.

In recent years, academic researchers have made more efforts to promote multilateral dialogue and policy development, advocating for the adoption of international frameworks that govern the deployment of AI in military and cybersecurity contexts, with a strong emphasis on human rights and international humanitarian law. Initiatives such as the Munich Convention process, which brought together scholars from institutions including the Technical University of Munich, Rutgers University, Stellenbosch University, Ulster University, and University of Edinburgh, have called for a binding international agreement to protect human rights in the age of AI.

Regional and national regulation

The regulatory and policy landscape for AI is an emerging issue in regional and national jurisdictions globally, for example in the European Union and Russia. Since early 2016, many national, regional and international authorities have begun adopting strategies, actions plans and policy papers on AI. These documents cover a wide range of topics such as regulation and governance, as well as industrial strategy, research, talent and infrastructure.

Different countries have approached the problem in different ways. Regarding the three largest economies, it has been said that "the United States is following a market-driven approach, China is advancing a state-driven approach, and the EU is pursuing a rights-driven approach."

Australia

In October 2023, the Australian Computer Society, Business Council of Australia, Australian Chamber of Commerce and Industry, Ai Group (aka Australian Industry Group), Council of Small Business Organisations Australia, and Tech Council of Australia jointly published an open letter calling for a national approach to AI strategy. The letter backs the federal government establishing a whole-of-government AI taskforce.

Additionally, in August of 2024, the Australian government set a Voluntary AI Safety Standard, which was followed by a Proposals Paper later in September of that year, outlining potential guardrails for high-risk AI that could become mandatory. These guardrails include areas such as model testing, transparency, human oversight, and record-keeping, all of which may be enforced through new legislation. As noted, however, Australia has not yet passed AI-specific laws, but existing statutes such as the Privacy Act 1988, Corporations Act 2001, and Online Safety Act 2021 all have applications which apply to AI use.

In September 2024, a bill also was introduced which granted the Australian Communications and Media Authority powers to regulate AI-generated misinformation. Several agencies, including the ACMA, ACCC, and Office of the Australian Information Commissioner, are all expected to play roles in future AI regulation.

Brazil

On September 30, 2021, the Brazilian Chamber of Deputies (Câmara dos Deputados) approved the Brazilian Legal Framework for Artificial Intelligence (Marco Legal da Inteligência Artificial). This legislation aimed to regulate AI development and usage while promoting research and innovation in ethical AI solutions that prioritize culture, justice, fairness, and accountability. The 10-article bill established several key objectives: developing ethical principles for AI, promoting sustained research investment, and removing barriers to innovation. Article 4 specifically emphasized preventing discriminatory AI solutions, ensuring plurality, and protecting human rights.

When the bill was first released to the public, it faced substantial criticism, alarming the government for critical provisions. The underlying issue is that this bill failed to thoroughly and carefully address accountability, transparency, and inclusivity principles. Article VI establishes subjective liability, meaning any individual that is damaged by an AI system and is wishing to receive compensation must specify the stakeholder and prove that there was a mistake in the machine's life cycle. Scholars emphasize that it is out of legal order to assign an individual responsible for proving algorithmic errors given the high degree of autonomy, unpredictability, and complexity of AI systems. This also drew attention to the currently occurring issues with face recognition systems in Brazil leading to unjust arrests by the police, which would then imply that when this bill is adopted, individuals would have to prove and justify these machine errors.

The main controversy of this draft bill was directed to three proposed principles. First, the non-discrimination principle, suggests that AI must be developed and used in a way that merely mitigates the possibility of abusive and discriminatory practices. Secondly, the pursuit of neutrality principle lists recommendations for stakeholders to mitigate biases; however, with no obligation to achieve this goal. Lastly, the transparency principle states that a system's transparency is only necessary when there is a high risk of violating fundamental rights. As easily observed, the Brazilian Legal Framework for Artificial Intelligence lacks binding and obligatory clauses and is rather filled with relaxed guidelines. In fact, experts emphasize that this bill may even make accountability for AI discriminatory biases even harder to achieve. Compared to the EU's proposal of extensive risk-based regulations, the Brazilian Bill has 10 articles proposing vague and generic recommendations.

The Brazilian AI Bill lacks the diverse perspectives that characterized earlier Brazilian internet legislation. When Brazil drafted the Marco Civil da Internet (Brazilian Internet Bill of Rights) in the 2000s, it used a multistakeholder approach that brought together various groups—including government, civil society, academia, and industry—to participate in dialogue, decision-making, and implementation. This collaborative process helps capture different viewpoints and trade-offs among stakeholders with varying interests, ultimately improving transparency and effectiveness in AI regulation.

In May 2023, a new bill was passed, superseding the 2021 bill. It calls for risk assessments of AI systems before deployment and distinguishes "high risk" and "excessive risk" systems. The latter are characterized by their potential to expose or exploit vulnerabilities and will be subject to regulation by the Executive Branch.

Canada

The ''Pan-Canadian Artificial Intelligence Strategy'' (2017) is supported by federal funding of Can $125 million with the objectives of increasing the number of outstanding AI researchers and skilled graduates in Canada, establishing nodes of scientific excellence at the three major AI centres, developing 'global thought leadership' on the economic, ethical, policy and legal implications of AI advances and supporting a national research community working on AI. The Canada CIFAR AI Chairs Program is the cornerstone of the strategy. It benefits from funding of Can$86.5 million over five years to attract and retain world-renowned AI researchers. The federal government appointed an Advisory Council on AI in May 2019 with a focus on examining how to build on Canada's strengths to ensure that AI advancements reflect Canadian values, such as human rights, transparency and openness. The Advisory Council on AI has established a working group on extracting commercial value from Canadian-owned AI and data analytics. In 2020, the federal government and Government of Quebec announced the opening of the International Centre of Expertise in Montréal for the Advancement of Artificial Intelligence, which will advance the cause of responsible development of AI. In June 2022, the government of Canada started a second phase of the Pan-Canadian Artificial Intelligence Strategy. In November 2022, Canada has introduced the Digital Charter Implementation Act (Bill C-27), which proposes three acts that have been described as a holistic package of legislation for trust and privacy: the Consumer Privacy Protection Act, the Personal Information and Data Protection Tribunal Act, and the Artificial Intelligence & Data Act (AIDA).

In September of 2023, the Canadian Government introduced a Voluntary Code of Conduct for the Responsible Development and Management of Advanced Generative AI Systems. The code, based initially on public consultations, seeks to provide interim guidance to Canadian companies on responsible AI practices. Ultimately, its intended to serve as a stopgap