Compliance & Responsible AI Fall 2024
45 Questions
0 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to Lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

Who negotiates the Codes that are approved by the European AI Bureau?

  • Independent experts
  • National authorities
  • The public
  • Stakeholders (correct)

    • What is the purpose of the CE marking for high-risk systems?

  • To indicate compliance with GDPR
  • To ensure it is visible, legible, and indelible (correct)
  • To provide a certificate of registration
  • To show general validity within the EU

    • How long must automatically generated logs be retained when possible?

  • 1 year
  • 6 months (correct)
  • 5 years
  • 10 years

    • What is one of the immediate corrective actions required for high-risk systems?

    <p>The withdrawal or deactivation of the system (D)</p> Signup and view all the answers

    What is the maximum penalty for non-compliance according to the outlined obligations?

    <p>€15M or 3% of total turnover (D)</p> Signup and view all the answers

    What is a requirement under GDPR for processing biometric data?

    <p>Obtain user consent before processing (A)</p> Signup and view all the answers

    In the context of generative AI, which statement is true regarding the manipulation of content?

    <p>Disclosure must occur unless there is human review or editorial control (C)</p> Signup and view all the answers

    What obligation does generative AI have when creating content that resembles real people or events?

    <p>Inform the public about the artificial generation of content (D)</p> Signup and view all the answers

    What is a crucial measure to address identified risks in high-risk AI systems?

    <p>Appropriate and targeted risk management measures (B)</p> Signup and view all the answers

    Which of the following is NOT a condition for processing biometric data under GDPR?

    <p>Adhering to requested privacy settings (B)</p> Signup and view all the answers

    What is essential for ensuring the quality of training data in AI systems?

    <p>Best practices and relevant unbiased datasets (D)</p> Signup and view all the answers

    What must be true for generated content not to require a disclosure statement?

    <p>The content underwent human review or editorial control (C)</p> Signup and view all the answers

    What aspect of AI systems requires human supervision to minimize risks?

    <p>Integrated human-machine interfaces (B)</p> Signup and view all the answers

    How can AI systems demonstrate compliance with obligations until harmonized standards are established?

    <p>By relying on codes of good practice (B)</p> Signup and view all the answers

    Which of the following AI systems is still classified as high risk, regardless of compliance exceptions?

    <p>AI systems carrying out profiling (D)</p> Signup and view all the answers

    Which element is NOT included in the quality management system for high-risk AI systems?

    <p>Marketing strategies (D)</p> Signup and view all the answers

    What must stakeholders expect from the Commission regarding compliance guidelines?

    <p>Guidelines and concrete examples within 18 months of entry into force (D)</p> Signup and view all the answers

    What is necessary for maintaining accuracy, robustness, and security in AI systems?

    <p>Constant cybersecurity measures (C)</p> Signup and view all the answers

    What types of technical means are necessary for the integration of general-purpose AI models into AI systems?

    <p>Operating instructions and evaluation strategies (D)</p> Signup and view all the answers

    Which of the following is included in the design specifications and training process of AI models?

    <p>Key design choices and rationale (D)</p> Signup and view all the answers

    What aspect of model training is relevant to understanding its efficiency?

    <p>Estimated energy consumption and training time (C)</p> Signup and view all the answers

    What is a critical component of evaluation strategies for AI models?

    <p>Publicly available evaluation protocols (A)</p> Signup and view all the answers

    What type of testing might be included for internal and external evaluations of AI models?

    <p>Adversarial testing, such as red teaming (A)</p> Signup and view all the answers

    What responsibility does the AI Office have regarding the transparency of AI systems with limited risk?

    <p>Developing codes of good practice (A)</p> Signup and view all the answers

    What should be measured as part of evaluating AI model limitations?

    <p>Evaluation criteria and measures (B)</p> Signup and view all the answers

    Which method is NOT associated with the training and evaluation of AI models?

    <p>Identifying user needs and preferences (D)</p> Signup and view all the answers

    What is the amount of penalty for prohibited practices?

    <p>€35M (B)</p> Signup and view all the answers

    Which of the following factors influences the penalties imposed?

    <p>Nature and severity of the violation (A)</p> Signup and view all the answers

    What is the penalty for inaccurate, incomplete, or misleading information?

    <p>€7.5M (A)</p> Signup and view all the answers

    What is emphasized as critical in the relationship between AI vendors and regulators?

    <p>Collaboration for compliance and responsible innovation (A)</p> Signup and view all the answers

    How does the level of risk relate to obligations and penalties?

    <p>Higher risk leads to greater obligations and heavier penalties (D)</p> Signup and view all the answers

    What is the main purpose of general-purpose AI models?

    <p>To exhibit significant generality across various tasks (D)</p> Signup and view all the answers

    What does the risk-based approach to AI systems involve?

    <p>Classifying AI systems into levels based on potential harm (D)</p> Signup and view all the answers

    What is NOT included in the definition of an AI system?

    <p>Generating outputs that do not influence environments (D)</p> Signup and view all the answers

    Which authority is NOT mentioned as part of the framework for AI regulation?

    <p>National Security Agency (C)</p> Signup and view all the answers

    What is a primary function of the EU's AI Office?

    <p>To assess methodologies and monitor AI regulations (B)</p> Signup and view all the answers

    What distinguishes high-risk AI systems?

    <p>They are subject to more stringent compliance obligations. (A)</p> Signup and view all the answers

    When is the entry into force date of the AI Regulation?

    <p>August 1, 2024 (B)</p> Signup and view all the answers

    What is excluded from the category of general-purpose AI models?

    <p>Models used for research and development before commercialization (D)</p> Signup and view all the answers

    What is a significant concern that the European Union aims to address with its AI legislation?

    <p>Safety and liability implications of AI (D)</p> Signup and view all the answers

    How many months after the entry into force does the general-purpose AI obligation take effect?

    <p>12 months (D)</p> Signup and view all the answers

    What is the aim of the European Regulation on AI?

    <p>To enhance trust and excellence in AI technologies (D)</p> Signup and view all the answers

    Who oversees the national regulatory sandbox according to the framework?

    <p>National supervisory authorities (C)</p> Signup and view all the answers

    What is meant by 'prohibited practices' in relation to AI systems?

    <p>Certain AI applications deemed too risky (D)</p> Signup and view all the answers

    What does the term 'supervisory authorities' refer to in the context of AI regulation?

    <p>Government entities responsible for compliance and monitoring (D)</p> Signup and view all the answers

    Flashcards

    High-Risk AI Systems

    AI systems that could pose significant risks to health, safety, or fundamental rights of individuals.

    Risk Management System

    A system for identifying, assessing, and mitigating risks related to high-risk AI systems.

    Data and Data Governance

    Ensuring the quality, bias-free nature, and appropriateness of data used to train high-risk AI systems.

    Technical Documentation

    Detailed documentation of AI systems, as required by the AI Regulation.

    Signup and view all the flashcards

    Traceability

    The ability to track the history and lifecycle of a high-risk AI system.

    Signup and view all the flashcards

    Human Supervision

    Requirements for integrated human oversight in high-risk AI systems.

    Signup and view all the flashcards

    Compliance Exceptions

    Certain high-risk AI systems may be exempt if they do not pose a significant risk and follow narrow procedural tasks or improve previous human activities.

    Signup and view all the flashcards

    Presumption of Conformity

    Using harmonized European standards or codes of practice to demonstrate compliance, until specific standards are developed.

    Signup and view all the flashcards

    AI Regulation Timeline

    The European AI Regulation's stages of implementation: prohibited practices first (6 months from 08/01/2024), then general-purpose AI models (12-months), high-risk systems (24 months), and finally all obligations (36 months).

    Signup and view all the flashcards

    High-Risk AI Systems

    AI systems with potential significant harm if malfunctioning, mis-used, or wrongly implemented.

    Signup and view all the flashcards

    General-purpose AI Models

    AI models capable of diverse tasks, often trained with massive datasets.

    Signup and view all the flashcards

    Prohibited Practices

    Specific AI practices deemed unacceptable under the AI Act.

    Signup and view all the flashcards

    AI Systems Definition

    Automated systems exhibiting adaptability and influencing physical/virtual environments; inferring and operating independently to produce outputs.

    Signup and view all the flashcards

    AI Legislation Around the World

    Regulations concerning Artificial Intelligence across countries; comparison of approaches, timelines and legislation.

    Signup and view all the flashcards

    European Union's Lawfare Strategy

    EU's approach to regulation and enforcement concerning AI and related technologies.

    Signup and view all the flashcards

    Supervisory Authorities

    Groups overseeing the AI regulation and compliance. Including national and EU authorities.

    Signup and view all the flashcards

    Application Timeline

    The schedule for implementation of the AI regulations in different phases.

    Signup and view all the flashcards

    EU AI Regulation

    EU legislation for governing and regulating artificial intelligence.

    Signup and view all the flashcards

    AI System Categories

    Classifications of AI systems based on their potential risk from low to high.

    Signup and view all the flashcards

    Risk-Based Approach

    AI compliance and assessment based on the estimated risk.

    Signup and view all the flashcards

    EU AI Committee

    Organization that oversees and coordinates AI related initiatives in the EU.

    Signup and view all the flashcards

    Definitions of AI Systems and Models

    Specific parameters used in categorizing AI systems and their components.

    Signup and view all the flashcards

    Artificial Intelligence: (EU) approach

    EU's strategy to ensure that AI is developed and used responsibly and with trust.

    Signup and view all the flashcards

    AI Office

    The EU body responsible for assessing and monitoring AI.

    Signup and view all the flashcards

    Supplier Obligations

    Responsibilities of AI system suppliers regarding conformity, marking, and corrective actions in the EU.

    Signup and view all the flashcards

    CE Marking

    A visible, legible, and indelible mark signifying EU conformity for high-risk AI systems.

    Signup and view all the flashcards

    Automatically Generated Logs

    Records of activities from high-risk AI systems, kept for at least 6 months, potentially required by GDPR.

    Signup and view all the flashcards

    Immediate Corrective Actions

    Actions taken by AI system suppliers to address risks, including withdrawal or deactivation.

    Signup and view all the flashcards

    Model and Open Source Compliance

    Requirements for AI models and open source components concerning compliance. Copyright directive and technical documentation.

    Signup and view all the flashcards

    Technical Documentation (AI)

    Detailed description of an AI model, including training process, data, resources, and energy consumption.

    Signup and view all the flashcards

    Evaluation Strategies

    Methods for assessing AI model performance, including criteria, measures, and limitations.

    Signup and view all the flashcards

    Adversarial Testing

    Testing AI models to see if they can be tricked or manipulated.

    Signup and view all the flashcards

    System Architecture

    How software components in an AI system interact and work together.

    Signup and view all the flashcards

    Artificially Generated Content

    Content created by AI, often indistinguishable from human-created content.

    Signup and view all the flashcards

    Codes of Good Practice (AI)

    Guidelines for developing and using AI systems ethically and responsibly, especially for content detection.

    Signup and view all the flashcards

    Publicly Available Evaluation Protocols

    Standardized methods for testing and evaluating AI performance, widely accessible.

    Signup and view all the flashcards

    AI Model Training Data

    Data used to teach an AI model how to perform a task, includes for training, validation, andtesting

    Signup and view all the flashcards

    AI Sanctions

    Financial penalties for AI system failures or violations of the AI Act (EU).

    Signup and view all the flashcards

    AI Collaboration

    Cooperation between AI developers and regulators for responsible AI development.

    Signup and view all the flashcards

    AI Transparency (Obligations)

    Requirement for AI developers to disclose information about their models.

    Signup and view all the flashcards

    AI Risk & Penalties

    Higher-risk AI systems have more stringent obligations and larger penalties.

    Signup and view all the flashcards

    AI Codes of Practice

    Rules and guidelines for ethical and safe use of AI.

    Signup and view all the flashcards

    Biometric Data Consent

    Obtaining permission before processing biometric and other personal data, as required by GDPR.

    Signup and view all the flashcards

    Deepfake Disclosure

    Telling people content is artificially created or manipulated (images, audio, video, text).

    Signup and view all the flashcards

    Emotion Recognition Obligations

    Inform users of emotion recognition/biometric use and obtain their consent, by GDPR.

    Signup and view all the flashcards

    Generative AI Disclosure

    Must disclose that text or other generated content is artificial.

    Signup and view all the flashcards

    Generated Content Review

    Requires human review/editorial oversight before publishing generative content unless an exception applies.

    Signup and view all the flashcards

    Study Notes

    Compliance & Responsible AI

    • Presented by Dr. Nathalie Devillier
    • Fall 2024 session
    • Focuses on the compliance of AI systems

    Course Presentation

    • Covers context and benchmarks
    • Explores risk-based approach and prohibited systems
    • Outlines compliance obligations for high-risk systems
    • Discusses transparency of AI systems with limited risk

    Context and Benchmarks

    • Examines AI legislation globally
    • Presents the European Union's Lawfare Strategy
    • Details the European Regulation on AI, including its timeline
    • Discusses supervisory authorities and definitions of AI systems and models

    AI Legislation Around the World

    • Presents a global tracker map
    • Illustrates jurisdictions in focus (e.g., Australia, Brazil, Canada)

    European Union's Lawfare Strategy

    • Provides a timeline, including key dates for statements on AI and robotics; digital services regulation; digital markets regulation; regulation on digital resilience (end of trialogue); artificial intelligence; and others

    Application Timeline

    • Shows phased implementation for AI regulation
    • Introduces various deadlines concerning prohibited practices and all obligations

    Supervisory Authorities

    • Highlights the role of member states (France is not yet designated) in applying AI regulation
    • Outlines oversight of national regulatory sandboxes
    • Mentions controls and sanctions
    • Describes the EU perspective on the Al Office, methodologies for assessment and monitoring, national authorities' role, and the development of the Al Committee

    Definitions and Categories

    • Details general purpose AI model (Art. 3(63)) and AI system (Art. 3(1)) definitions
    • Explains systemic risk model (Art. 2(65)) 
    • Explains risk-based approach in 4 levels

    AI Systems

    • Defines AI systems as automated systems designed for varying autonomy levels
    • Explicit or implicit inputs determine outputs like predictions, content, recommendations, or decisions influencing physical or virtual environments

    General Purpose AI Models

    • Defines general purpose AI models trained with large datasets, using large-scale self-supervision and exhibiting wide task generality
    • Excludes systems used for research, development, or prototyping before commercial launch

    Systemic Risk

    • Defines systemic risk as high-impact capabilities of general-purpose AI models, significantly impacting the Union market due to their scale or potential for foreseeable negative consequences in public health, safety, public security, fundamental rights or society

    The Risk Approach

    • Links risk levels to practical applications & legal obligations
    • Categorizes risk levels from unacceptable (forbidden actions) to minimal (no or almost no obligations)

    Risk-based Approach: AI Systems - EU Artificial Intelligence Act

    • Classifies risk levels with examples: unacceptable (social scoring, manipulation), high risk, limited risk, minimal risk
    • Relates risks to prohibited, conformity assessment, transparency obligations, and no obligation categories

    Prohibited AI Practices

    • Outlines practices prohibited in AI systems (e.g., subliminal techniques, exploitation of vulnerabilities, risk assessments for predicting offenses, real-time biometric identification in public places, database expansion via non-targeted harvesting of data)
    • Includes limitations for workplace or educational settings (except for safety/medical reasons)

    Subliminal or Intentionally Deceptive Techniques

    • Describes the meaning of subliminal and intentional deceptive techniques
    • Explains the objective effect (material alteration of behavior) and result (decision-making impairment), with potential harm to individuals

    Exploitation of Vulnerabilities

    • Explains how AI systems exploit vulnerabilities due to age, health, or economic standing
    • Focuses on activities aiming to alter target behavior or causing significant harm

    Rating People Based on Social Behavior

    • Explains how systems evaluate or classify individuals based on characteristics using a social score
    • Highlights potential for less favorable or unfavorable treatment which might be unjustified or disproportionate for the original data

    Compliance Obligations: High-Risk AI Systems

    • Lists management systems for high-risk AI, including data and data governance, technical documentation, traceability, human oversight, accuracy & robustness, and security plus quality management
    • Explains that appropriate and targeted measures need to address the identified risks

    Exceptions

    • Identifies situations where AI systems, such as those with specific tasks, may not pose significant risk of harm to individual safety.
    • States that Annex III systems performing profiling still fall within the high-risk category.

    Presumption of Conformity

    • Describes the possibility of harmonized EU standards to demonstrate compliance
    • Highlights the use of codes of good practice

    Supplier Obligations

    • Enlists requirements for suppliers of high-risk AI systems, including declaration of conformity, CE marking, registration, logs, corrective actions, cooperation with authorities, information provision, and potential penalties

    Models and Open Source

    • Explains differences between basic and systemic risk models, particularly documentation requirements: copyright and training datasets for open-source; technical documentation for others

    Obligation: Technical Documentation

    • Emphasizes the need to provide clear documentation concerning models (training, testing, evaluation results)
    • Explains obligations of Al providers integrating models, intellectual property policy, and summary of training content
    • Outlines cooperation with the Commission, European AI Office, and national authorities for compliance

    Technical Documentation: General Description

    • Covers essential elements like tasks, acceptable use policies, release dates, architecture, modality, and model licenses

    Technical Documentation: Detailed Description

    • Outlines detailed technical requirements based on means, design specifications, training process, and information concerning data usage, resources, training times, operations, and estimations of energy consumption and other relevant details

    Additional Information

    • Outlines evaluations and adversarial testing processes
    • Explains system architecture and how components interact.

    Transparency of AI Systems with Limited Risk

    • Describes the Al Office's focus on developing codes of good practice for transparency
    • Presents examples of case studies (emotion recognition/biometric categorization and generative AI) as specific issues needing attention

    Case 1: Emotion Recognition or Biometric Categorization

    • Discusses obligations arising from the GDPR for transparency regarding emotion recognition and biometric data processing, such as user consent and data processing conditions.

    Case 2: Generative AI

    • Highlights obligations pertaining to the disclosure of artificially generated or manipulated content
    • Includes measures for transparency, human review, or legal person control

    Sanctions

    • Lists financial penalties for various violations related to prohibited practices, shortcomings in information accuracy, and moderation practices for SMEs

    Conclusion - Key Takeaways

    • Underscores collaboration between AI vendors and regulators for responsible AI practices
    • Emphasizes the obligation of transparency between designers and suppliers
    • Highlights that AI obligations are dynamic and harmonization, especially in codes of practice, is important.
    • Links penalties to the level of risk in AI systems

    Studying That Suits You

    Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

    Quiz Team

    Related Documents

    Compliance & Responsible AI Fall 2024 PDF

    Description

    Explore the critical aspects of compliance in AI systems with Dr. Nathalie Devillier. This course covers global AI legislation, risk-based approaches, and the European Union's Lawfare Strategy, focusing on compliance obligations for high-risk AI systems. Understand transparency requirements and benchmarks in the evolving landscape of AI regulations.

    More Like This

    Use Quizgecko on...
    Browser
    Open
    Browser
    Browser