On 14th June, the European Parliament passed the EU Artificial Intelligence Act (AI Act). The law is expected to be legislated in 2024 and will have a significant impact on organizations that develop, deploy, and maintain AI systems.
Machine learning engineers will be responsible for ensuring AI use cases are properly documented, reviewed, and monitored to comply with the AI Act regulations. The act categorizes AI use cases as unacceptable, high risk, medium risk, or low risk, depending on the level of harm to individuals and society. In particular, AI Governance documentation accessibility will need to shift from traditional documentation to a more comprehensive understanding of the technical workÃs limitations within the organization.
Moreover, generative AI liability is another crucial aspect, and organizations need to conduct internal studies to evaluate AI systems. Machine learning engineers do not need to understand the full regulation, as legal or compliance teams are responsible for that.
Testing and human evaluations are significant in ensuring model quality, and organizations should develop comprehensive playbooks outlining different re-evaluation workflows and processes for high-risk AI use cases.
Lastly, AI engineers must embrace responsible AI governance and implement robust conformity assessment processes, such as comprehensive risk management, post-market monitoring, and efficient incident reporting procedures, an essential aspect of ensuring effective compliance with the AI Act and building trust in AI systems.
Frequently Asked Questions (FAQs) Related to the Above News
What is the EU Artificial Intelligence Act?
The EU Artificial Intelligence Act is a new law that was passed by the European Parliament on 14th June 2021. It is expected to be legislated in 2024 and will impact organizations that develop, deploy, and maintain AI systems.
Who is responsible for ensuring compliance with the AI Act regulations?
Machine learning engineers will be responsible for ensuring AI use cases are properly documented, reviewed, and monitored to comply with the AI Act regulations.
How are AI use cases categorized under the AI Act?
AI use cases are categorized as unacceptable, high risk, medium risk, or low risk depending on the level of harm to individuals and society.
Is traditional documentation enough for AI Governance under the AI Act?
No, documentation accessibility needs to shift to a more comprehensive understanding of the technical work's limitations within the organization.
What is generative AI liability?
Generative AI liability is an important aspect that organizations need to evaluate internally to ensure compliance with the AI Act regulations.
Who is responsible for understanding the full regulation under the AI Act?
Legal or compliance teams are responsible for understanding the full regulation under the AI Act.
What is significant in ensuring model quality under the AI Act?
Testing and human evaluations are significant in ensuring model quality under the AI Act.
What should organizations do to ensure compliance for high-risk AI use cases?
Organizations should develop comprehensive playbooks outlining different re-evaluation workflows and processes for high-risk AI use cases.
What is responsible AI governance?
Responsible AI governance is the concept of developing and implementing robust conformity assessment processes, such as risk management, post-market monitoring, and incident reporting procedures, to ensure effective compliance with the AI Act and building trust in AI systems.
What is the timeline for legislation under the AI Act?
The AI Act is expected to be legislated in 2024.
Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.
