Comparing US Algorithmic Accountability Act and EU AI Act: Navigating the Future of AI Governance
As artificial intelligence (AI) continues to permeate various aspects of our lives, the need for effective governance and regulation becomes increasingly crucial. In recent years, both the United States and the European Union have proposed legislative frameworks aimed at addressing the challenges posed by AI technologies. The US Algorithmic Accountability Act (AAA) and the EU AI Act are two key pieces of legislation that seek to establish a regulatory landscape for AI on both sides of the Atlantic.
At the time I write this, none of it has been enacted into law yet. However, it is very possible that the EU AI Act will become effective in 2021, and the US will likely follow suit afterwards.
In this article, we will delve into the similarities and differences between these two proposals, exploring what they can teach us about the future direction of AI regulation. So, let’s dive in and see how these two giants are shaping the world of AI governance.
I. The US Algorithmic Accountability Act
The AAA, introduced in 2022, aims to address the potential risks associated with automated decision systems (ADS) and their impact on individuals and communities. The Act requires companies to conduct impact assessments on their ADS, evaluating the system’s accuracy, fairness, and potential biases. These assessments must be submitted to the Federal Trade Commission (FTC), which is granted broad discretion in determining what constitutes a “critical” system, such as those used in housing or employment decisions.
One notable aspect of the AAA is its focus on ex-ante regulation, meaning that companies must assess and mitigate potential risks before deploying their AI systems. This approach emphasizes the importance of proactive risk management and accountability, rather than relying solely on reactive measures after harm has occurred.
The new law is mainly targeting tech giants, which distinguishes it from the European Union’s proposed Artificial Intelligence Act.
II. The EU AI Act
On the other side of the pond, the EU AI Act takes a more comprehensive approach to AI regulation. The Act covers a wide range of AI applications, from high-risk systems like biometric identification to lower-risk systems like chatbots. It establishes a legal framework for AI governance, including requirements for transparency, accountability, and human oversight.
Unlike the AAA, the EU AI Act places a strong emphasis on ex-post regulation, requiring continuous monitoring of data sets and AI systems once they are on the market. This approach aims to ensure compliance with fundamental rights and includes provisions for effective legal remedies for those affected by AI-related violations.
III. Comparing the Two Approaches
While both the AAA and the EU AI Act share common goals of promoting transparency, accountability, and fairness in AI systems, there are some key differences in their approaches to regulation.
1. Scope: The AAA focuses primarily on “critical” ADS, while the EU AI Act covers a broader range of AI applications. This difference reflects the varying priorities and regulatory philosophies of the two jurisdictions.
2. Ex-ante vs. Ex-post Regulation: The AAA emphasizes proactive risk management through impact assessments, while the EU AI Act places greater emphasis on continuous monitoring and ex-post controls. The EU AIC is not completely devoid of guidelines to ensure pre-emptive control, particularly for Generative and General AI. However, they have especially placed a heavy focus on post-hoc regulation. This distinction highlights the different approaches to balancing innovation and risk mitigation in AI governance.
3. Enforcement: The AAA designates the FTC as the primary enforcer of its provisions, whereas the EU AI Act relies on a more decentralized enforcement structure, involving national authorities and sector-specific regulators. This difference underscores the varying degrees of centralization in the two regulatory frameworks.
IV. Lessons for the Future of AI Governance
As we compare and contrast the US AAA and the EU AI Act, several key insights emerge that can inform the future direction of AI regulation:
- The importance of striking a balance between ex-ante and ex-post regulation, ensuring that AI systems are both proactively designed to minimize risks and continuously monitored for compliance with fundamental rights.
- The need for a flexible and adaptive regulatory framework that can accommodate the rapidly evolving nature of AI technologies and their applications.
- The value of international cooperation and dialogue in shaping AI governance, as evidenced by the ongoing collaboration between the US and EU on AI policy matters.
As AI continues to transform our world, the US Algorithmic Accountability Act and the EU AI Act offer valuable insights into the future of AI governance. By examining the similarities and differences between these two legislative proposals, we can better understand the challenges and opportunities that lie ahead in regulating this powerful technology. Ultimately, the success of AI regulation will depend on our ability to strike the right balance between fostering innovation and protecting the rights and interests of individuals, communities, and society as a whole.
