Introduction
The European Union’s Artificial Intelligence Act (EU AI Act) is a groundbreaking regulation that aims to promote the development and deployment of trustworthy AI systems. As businesses increasingly rely on AI technologies, including Speech AI and Large Language Models (LLMs), compliance with the EU AI Act becomes crucial. This blog post explores the key challenges posed by the regulation and how Shaip can help you overcome them.
Understanding the EU AI Act
The European Union’s Artificial Intelligence Act (EU AI Act) introduces a risk-based approach to regulating AI systems, categorizing them based on their potential impacts on individuals and society. As businesses develop and deploy AI technologies, understanding the risk levels associated with different data categories is crucial for compliance with the EU AI Act. The EU AI Act classifies AI systems into four risk categories: minimal, limited, high, and unacceptable risk.
Based on the proposal for the Artificial Intelligence Act (2021/0106(COD)), here are the risk categories and the corresponding data types and industries in table format:
Unacceptable Risk AI Systems:
| Data Types | Industries |
| Subliminal techniques to distort behavior | All |
| Exploitation of vulnerabilities of specific groups | All |
| Social scoring by public authorities | Government |
| Real-time’ remote biometric identification in publicly accessible spaces for law enforcement (with exceptions) | Law enforcement |
High-Risk AI Systems:
| Data Types | Industries |
| Biometric identification and categorization of natural persons | Law enforcement, border control, judiciary, critical infrastructure |
| Management and operation of critical infrastructure | Utilities, transportation |
| Educational and vocational training | Education |
| Employment, worker management, access to self-employment | HR |
| Access to and enjoyment of essential private and public services | Government services, finance, health |
| Law enforcement | Law enforcement, criminal justice |
| Migration, asylum, and border control management | Border control |
| Administration of justice and democratic processes | Judiciary, elections |
| Safety components of machinery, vehicles, and other products | Manufacturing, automotive, aerospace, medical devices |
Limited Risk AI Systems:
| Data Types | Industries |
| Emotion recognition or biometric categorization | Al |
| Systems that generate or manipulate content (‘deep fakes’) | Media, entertainment |
| AI systems intended to interact with natural persons | Customer service, sales, entertainment |
Minimal Risk AI Systems:
| Data Types | Industries |
| AI-enabled video games | Entertainment |
| AI for spam filtering | All |
| AI in industrial applications with no impact on fundamental rights or safety | Manufacturing, logistics |
The above tables provide a high-level summary of how different data types and industries map to the AI risk categories defined in the proposed regulation. The actual text provides more detailed criteria and scope definitions. In general, AI systems that pose unacceptable risks to safety and fundamental rights are prohibited, while those posing high risks are subject to strict requirements and conformity assessments. Limited risk systems have mainly transparency obligations, while minimal risk AI has no additional requirements beyond existing legislation.
Key requirements for high-risk AI systems under the EU AI Act.
The EU AI Act stipulates that providers of high-risk AI systems must comply with specific obligations to mitigate potential risks and ensure the trustworthiness and transparency of their AI systems. The listed requirements are as follows:
- Implement a risk management system to identify and mitigate risks throughout the AI system’s life cycle.
- Use high-quality, relevant, and unbiased training data that is representative, and free from errors and biases.
- Maintain detailed documentation of the AI system’s purpose, design, and development.
- Ensure transparency and provide clear information to users about the AI system’s capabilities, limitations, and potential risks.
- Implement human oversight measures to ensure high-risk AI systems are subject to human control and can be overridden or deactivated if necessary.
- Ensure robustness, accuracy, and cybersecurity protection against unauthorized access, attacks, or manipulations.
Challenges for Speech AI and LLMs
Speech AI and LLMs often fall under the high-risk category due to their potential impact on fundamental rights and societal risks. Some of the challenges businesses face when developing and deploying these technologies include:
- Collecting and processing high-quality, unbiased training data
- Mitigating potential biases in the AI models
- Ensuring transparency and explainability of the AI systems
- Implementing effective human oversight and control mechanisms
How Shaip Helps You Navigate Risk Categories
Shaip’s AI data solutions and model evaluation services are tailored to help you navigate the complexities of the EU AI Act’s risk categories:
Minimal and Limited Risk
For AI systems with minimal or limited risk, Shaip can help you ensure compliance with transparency obligations by providing clear documentation of our data collection and annotation processes.
High Risk
For high-risk Speech AI and LLM systems, Shaip offers comprehensive solutions to help you meet the stringent requirements:
- Detailed documentation of data collection and annotation processes to ensure transparency
- Ethical AI Data for Speech AI: Our data collection processes prioritize user consent, data privacy (minimizing PII), and removing biases based on demographics, socio-economic factors, or cultural contexts. This ensures your Speech AI models comply with the EU AI Act and avoid discriminatory outputs.
- Mitigating Bias in Speech Data: We understand the nuances of spoken language and potential biases that can creep into data. Our team meticulously analyzes data to identify and eliminate potential biases, ensuring fairer and more reliable Speech AI systems.
- Model Evaluation with EU AI Act Compliance in Mind: Shaip’s Model Evaluation & Benchmarking solutions can assess your Speech AI models for factors like relevance, safety, and potential biases. This helps ensure your models meet the EU AI Act’s requirements for transparency and fairness.
Unacceptable Risk
Shaip's commitment to ethical AI practices ensures that our data solutions and services do not contribute to the development of AI systems with unacceptable risk, helping you avoid prohibited practices under the EU AI Act.
How Shaip Can Help
By partnering with Shaip, businesses can confidently navigate the complexities of the EU AI Act while developing cutting-edge Speech AI and LLM technologies.
Navigating the EU AI Act’s risk categories can be challenging, but you don’t have to do it alone. Partner with Shaip today to access expert guidance, high-quality training data, and comprehensive model evaluation services. Together, we can ensure your Speech AI and LLM projects comply with the EU AI Act while driving innovation forward.
