The emergence of Artificial Intelligence (AI) has changed many industries, leading to debates over the appropriate ways to regulate these quickly developing technologies. In order to handle the complexities and problems provided by AI, the convergence of governance and AI entails not just setting regulatory norms but also developing international collaboration. This chapter examines the state of AI governance today, looking at the frameworks that currently regulate the field, the necessity of international cooperation, and the effects of different methods for regulation.
THE NEED OF AI GOVERNANCE
Artificial Intelligence is becoming more and more integrated into every aspect of our life, from entertainment and transportation to healthcare and banking. As a result of their extensive use, worries concerning privacy, security, prejudice, and responsibility have surfaced. A McKinsey analysis states that 50% of businesses have implemented AI in at least one function, demonstrating the technology's widespread impact across all industries (McKinsey & Company, 2022). Strong governance mechanisms that can guarantee responsible AI development and deployment are therefore desperately needed.
Detrimental outcomes may result from unclear regulatory norms. According to a World Economic Forum research, for example, 75% of people are worried about the ethical ramifications of AI, especially in light of the possibility of abuse, loss of privacy, and job displacement (World Economic Forum, 2021). These worries emphasise how urgent it is to set up governance frameworks that support accountability, equity, and transparency in AI systems.
PRESENT AI REGULATORY STANDARDS
A number of nations and organisations have started working to create AI regulatory guidelines. The important regulatory frameworks and recommendations are covered in the following sections.
European Union (EU) AI Act
With the proposal of the AI Act, which is anticipated to be a historic piece of legislation, the European Union has adopted a proactive approach to AI regulation. AI systems are divided into four risk categories under the AI Act: unacceptable, high, limited, and minimum risk. High-risk systems, including those employed in biometric identification or vital infrastructures, would be subject to stringent regulations, including duties for transparency and compliance assessments (European Commission, 2021).
The European Union seeks to provide a comprehensive regulatory framework that promotes innovation while also safeguarding citizens' rights. The AI Act is expected to provide up to €300 billion in yearly economic growth by 2025, according to the European Commission (European Commission, 2021). This comprehensive legal framework may serve as a model for other areas looking to create their own AI governance laws.
AI Initiatives in the US
The main sources of guidance for AI governance in the US are a mix of industry- specific laws and moral principles. In order to encourage AI research and development while guaranteeing its responsible use, the National AI Initiative Act was signed into law in January 2021 (U.S. Congress, 2021). Furthermore, a number of government organisations are creating best practices and recommendations for AI applications, such as the National Institute of Standards and Technology (NIST) and the government Trade Commission (FTC).
Although the American strategy places a strongly emphasises on creativity and adaptability, questions have been raised over the absence of a unified federal regulatory framework. According to a Brookings Institution analysis, the United States is lagging behind other nations in enacting comprehensive AI legislation, which might reduce its competitiveness internationally (Brookings Institution, 2022).
International Programs and Structures
Global AI governance guidelines are being actively developed by a number of international organisations. AI guidelines created by the Organisation for Economic Co-operation and Development (OECD) encourage responsible management of reliable AI. These guidelines highlight how important it is for AI development to be inclusive, accountable, and transparent (OECD, 2019). In addition, the United Nations Educational, Scientific, and Cultural Organisation (UNESCO) has published guidelines on AI ethics that support safeguarding basic liberties and human rights in AI systems (UNESCO, 2021).
In addition, governments, business, and civil society organisations come together under the 2020 launch of the Global Partnership on AI (GPAI) to promote global collaboration in AI governance. The GPAI is dedicated to advancing ethical AI practices and tackling worldwide AI-related issues, including prejudice and discrimination (GPAI, 2020).
ISSUES WITH AI GOVERNANCE
Even with the advancements in the creation of AI regulations, a number of obstacles still need to be addressed. These difficulties may make good governance more difficult and need global cooperation.
Quick Progress in Technology
Regulatory efforts are frequently outpaced by the rapid advancement of AI, making it challenging for legislators to stay up to date. Rapid technological advancements in fields like artificial intelligence, natural language processing, and autonomous systems are bridging the gap between innovation and regulation. 86% of CEOs, according to a PwC survey, think that regulations are not keeping up with the rate at which AI is being used (PwC, 2021).
The necessity for flexible regulatory frameworks that can keep up with technological improvements is highlighted by this problem. It also highlights how crucial international collaboration is to bringing standards and best practices across national boundaries.
Bias and Ethical Considerations
AI systems have the potential to reproduce biases seen in training data, producing unfair results. According to a research by the AI Now Institute, there are racial and gender biases in face recognition systems; women and persons of colour misidentification rates are notably higher (AI Now Institute, 2018). These moral dilemmas cast doubt on the justice and accountability of AI applications.
Regulatory frameworks that prioritise ethical concerns and provide tools for auditing and monitoring AI systems are necessary to solve these challenges. In order to create standardised methods for bias reduction and to advance fairness in AI technology, international cooperation is also essential.
Security and Privacy of Data
Since AI systems rely so much on data, it is critical to protect data security and privacy. Publicised data breaches have sparked worries about how AI systems can exploit personal data. Although it is a noteworthy attempt to address data privacy problems, the EU's General Data Protection Regulation (GDPR) (Regulation (EU) 2016/679) may not be very successful in the context of AI. In order to create frameworks that safeguard data privacy and facilitate data sharing for AI research and development, international cooperation is crucial. Working together can result in the development of standards and guidelines that support ethical data practices internationally.
INTERNATIONAL COLLABORATION'S SIGNIFICANCE IN AI GOVERNANCE
Establishing efficient governance structures requires international cooperation, given the global character of AI technology. Together, we can tackle common issues and advance ethical AI practices globally.
Exchange of Best Practices
Countries may exchange lessons learnt and best practices in AI governance through international collaboration. Forums like the GPAI give interested parties a place to share information and insights, encouraging a cooperative approach to AI governance. By exchanging experiences, nations may steer clear of common errors and create more functional regulatory systems.
Bringing Standards Together
Harmonising regulatory requirements across national borders can facilitate the development and application of AI technology. Different laws can obstruct commerce and innovation, making it challenging for businesses to do international business. Aligning standards via collaborative activities can foster an environment that is more favourable for the development and application of AI. The AI principles established by the OECD provide a framework for coordinating global standards and offer directives that nations can customise to fit their unique circumstances. Adopting shared principles can help nations develop a more cohesive strategy for AI governance.
Addressing Global Challenges
AI presents distinct worldwide issues, including dangers to public health, climate change, and security. AI may be used in collaborative efforts to successfully solve these problems. AI in climate modelling and prediction, for example, can improve international efforts to tackle climate change. Utilising AI's potential for societal benefit can be facilitated by international cooperation through cooperative research projects and data-sharing agreements. The application of collaborative techniques can enhance the beneficial effects of AI technology while guaranteeing that ethical principles are respected.
Conclusion
Effective governance frameworks are becoming more and more necessary as AI develops. To ensure that AI technologies are developed and used responsibly, international collaboration and the adoption of regulatory norms are essential. Even with ongoing difficulties, teamwork may promote creativity while resolving prejudice, data privacy, and ethical issues.
A multi-stakeholder strategy involving governments, business, academia, and civil society is necessary to go forward. Stakeholders may establish a regulatory environment that supports AI systems' accountability, transparency, and justice by cooperating. In the end, efficient AI governance will make it possible for society to capitalise on AI's advantages while reducing its hazards, opening the door to a day when AI is used for the greater good.
