EU legislators negotiate on Artificial Intelligence. European Companies Unite to Criticize EU’s Regulation.
In June 2023, the European Parliament (EP) drafted its position on A.I. european law, adding more restrictions to the rules of the Commission’s draft Regulation. On 27 June, EP and Council started negotiations and a second round will be held in July 2023. In the meantime, some of the largest companies in Europe have taken collective actions to criticize the proposal for the european A.I. Regulations, arguing that the Artificial Intelligence Act is ineffective and could have a negative impact on competition. In an open letter sent to the European Parliament, the Commission, and the member states last Friday, over 150 executives from companies such as Renault, Heineken, Airbus, and Siemens have criticized the AI Act for its potential to “jeopardize Europe’s competitiveness and technological sovereignty”.
(original: EN – Other languages: automatic translation)
Brussels, 4 July 2023
End of June, Council of the EU and European Parliament held first round of negotiations on the draft EU Regulations that will govern the use of A.I.
Both legislative institutions start with their own proposals:
The EU aims to finalize the AI Act by the end of the year.
Tech giants and European companies worried about restrictive bias
The economic impact of A.I.
AI will acquire a decisive weight in many fields of the economy, from transport, to retail, to marketing, to healthcare, etc.
If the scientific and industrial world is in fibrillation for the actions taken by different continents, it must be remembered that the entire world economy will be affected by artificial intelligence.
The AI value chain refers to the various stages and components involved in the development, deployment, and utilization of artificial intelligence technologies. It encompasses a range of activities, from data collection and preprocessing to algorithm development, model training, deployment, and ongoing maintenance.
The AI value chain typically includes the following components:
1. Data Acquisition: The process of gathering relevant and diverse data from various sources, which serves as the foundation for AI algorithms and models.
2. Data Preprocessing: Data cleaning, filtering, and transformation to ensure its quality, consistency, and suitability for AI applications.
3. Algorithm Development: Designing and developing algorithms that can process and analyze the collected data to extract meaningful insights or perform specific tasks.
4. Model Training: Using the prepared data to train AI models, which involves feeding the data into algorithms to optimize their performance and enable them to make accurate predictions or classifications.
5. Model Deployment: Integrating trained models into production systems or applications, making them available for real-time or batch processing.
6. Model Evaluation and Monitoring: Continuously assessing the performance and effectiveness of deployed models, monitoring their outputs, and making necessary adjustments or improvements.
7. Integration and Application: Incorporating AI capabilities into specific applications, products, or services to enhance functionality, efficiency, or user experience.
8. Ethical Considerations: Ensuring that AI technologies adhere to ethical standards, privacy regulations, and legal frameworks to protect individuals’ rights and mitigate potential biases or risks.
9. Maintenance and Updates: Ongoing support, maintenance, and updates to keep AI systems performing optimally, address issues, and incorporate advancements or changes in technology.
10. Business Impact: Leveraging AI capabilities to drive business value, improve decision-making processes, automate tasks, enhance productivity, and unlock new opportunities for innovation and growth.
The AI value chain involves collaboration among various stakeholders, including researchers, data scientists, engineers, domain experts, policymakers, and business leaders, each contributing to different stages of the process. By understanding and optimizing each step in the value chain, organizations can harness the full potential of AI technologies to achieve their goals and gain a competitive edge in the digital age.
EU accelerates and chooses a risk-based approach
EU is adopting a risk-based approach, imposing restrictions based on the perceived level of risk associated with specific AI applications. It bans certain AI tools considered “unacceptable,” such as analytics systems used by law enforcement to predict criminal behavior. Additionally, it introduces limits on “high-risk” technologies, including recommendation algorithms and tools that can influence elections. The legislation also focuses on generative AI, imposing obligations on companies to label AI-generated content and disclose the use of copyrighted data in training AI models.EU says that its approach to AI is proactive and aims to solidify its position as a global leader in tech regulation. It adds to the suite of existing regulatory tools aimed at Silicon Valley companies and sets standards that could influence policymakers worldwide. The alignment between European and U.S. regulators has grown stronger in recent years, as both sides recognize the need to address the power of tech giants. European officials have engaged in discussions with U.S. lawmakers on AI, sensing a greater urgency in Congress to regulate AI technologies.
The United States is just getting started and wants to avoid losing leadership
However, U.S. lawmakers are actively discussing AI policy and legislation, building on smaller policy actions that have been taken recently. These actions include bills to exclude generative AI from Section 230 liability protection and proposals for a National AI Commission and a federal office to encourage competition with China. US agencies like the FTC, Department of Commerce, and US Copyright Office have also issued statements and guidelines regarding AI, particularly generative AI.
Three key themes have emerged in these discussions:
- protecting innovation is a priority, as the US is home to major AI companies
- aligning technology, especially AI, with democratic values is emphasized, differentiating US AI companies from Chinese counterparts
- the future of Section 230, which shields tech companies from content liability, remains a significant question for AI regulation
While discussions will continue, Congress plans to form invite-only groups to delve into specific aspects of AI starting in the fall. There may be discussions on banning specific AI applications and potential revival of comprehensive tech legislation proposals. The focus is on achieving comprehensive and rapid AI regulation, drawing significant attention.
A.I. in the world is growing fast
While the United States and Europe have traditionally been at the forefront of AI research and development, other countries, including China, have made significant strides in recent years.
China has emerged as a major player in the AI landscape, with a strong focus on AI technology, research, and applications. The Chinese government has recognized the strategic importance of AI and has made substantial investments to foster its growth. Chinese companies, such as Baidu, Alibaba, and Tencent, have actively pursued AI advancements and have become global leaders in certain AI domains.
It’s worth noting that different countries have varying approaches and priorities when it comes to AI. The United States and Europe have emphasized ethical considerations, privacy protection, and regulation as AI technology continues to evolve. In contrast, China has prioritized rapid technological development and AI deployment in various sectors, including surveillance, healthcare, and transportation.
International collaboration and knowledge-sharing in AI are crucial for driving advancements and addressing global challenges. Many AI researchers and organizations across different countries actively collaborate and contribute to the global AI community. Cooperation, exchange of ideas, and sharing best practices can lead to breakthroughs that benefit humanity as a whole.
Ultimately, AI development and its impact are not limited to specific countries or regions. It is a global endeavor with the potential to revolutionize various industries, improve daily lives, and shape the future of society worldwide.
Source: © European Union, 1995-2023