Compliance in AI: Policies and Best Practices

Discover in this presentation, all AI rules and regulations and what companies should do to stay compliant.

1. Compliance in AI: Policies and Best Practices

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3. General Intro Guest Presentation Current AI laws Q&A Agenda

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8. Importance of Compliance in AI

9. Importance of AI Compliance AI regulation is one topic that unites governments and industries internationally. Standards are being created to ensure responsible AI adoption with a focus on accountability, transparency, and fairness. Key concerns include mitigating bias, privacy violations, and ethical misuse of AI. 39% of U.S businesses are investing in responsible AI practices to meet regulatory requirements (Source: PWC). Source: PWC

10. The AI Laws and Regulations

11. EU AI Act The EU AI Act is the most comprehensive AI regulation, adopted in 2024. It introduces compliance requirements based on the risk AI systems pose to humans and fundamental rights. The Act uses a risk-based approach with 3 levels of risk: minimal, high, and unacceptable. AI systems interacting with users must follow transparency obligations. Full compliance will phase in over 36 months to allow businesses to adapt. Source: CEPS

12. Penalties Under the EU AI Act Severe violations (Prohibited AI systems): Fines up to € 35 million or 7% of worldwide annual turnover, whichever is higher. Lesser violations (misleading or incomplete information): Fines up to € 7.5 million or 1% global annual turnover, whichever is higher. Penalties apply to providers, deployers , distributors, and notified bodies.

13. The White House Blueprint for an AI Bill of Rights It focuses on making sure AI systems are safe and effective. The main purposes are: Preventing algorithmic discrimination. Protecting data privacy. Offering clear notice and explanation. about their use. Providing human alternatives and fallback options. The aim is to uphold civil rights, equal opportunity and democratic values in deploying and using AI technologies. Source: Enterra Solutions

14. Colorado Privacy Act Colorado SB24-205 (Effective 2026): First U.S. law regulating AI systems, focusing on preventing algorithmic discrimination. Developers must assess and mitigate bias, while developers must ensure transparency and accountability. SB21-169 (Insurers and AI): Insurers using AI must prevent unfair discrimination. They must implement governance, conduct testing, and report to the Division of Insurance to protect consumers from discriminatory AI outcomes.

15. AI Video Interview Act – Illinois, USA A state law regulating the use of AI in video interviews for job applicants. Companies using AI in hiring processes must comply with the Illinois AI Video Interview Act. Biometric Information Privacy Act (BIPA), which governs the collection and storage of biometric data, including data used in AI systems.

16. Canada’s AI and Data Act (AIDA) 2024 This act mandates a rigorous assessment and mitigation of risks for high-impact AI systems, ensuring adherence to safety and ethical guidelines. Entities under AIDA are required to conduct risk assessments, establish risk mitigation measures, and ensure continuous monitoring. They should publicly disclose information about the functioning, intended use and risk management of high-impact AI systems. Source: techstrong.ai

17. China’s New Generative AI Measures These measures apply to the use of generative AI that provides services to the “public” within the territories of China. They require service providers to: Protect users’ input information and usage records. Collect and retain personal information in accordance with the principles of minimization and necessity. Establish mechanisms for handling complaints and requests to promptly reply to individuals requests for correcting, deleting, or masking their personal info. Source: CryptoSlate

18. Countries With AI Framework Brazil AI Bill of Rights UK AI Safety Summit Saudi Arabia AI Ethics Principles (SDAIA) Australia AI Ethics Framework South Korea National Strategy for AI Source: techstrong.ai

19. How Does this Affect US!

20. Potential AI Misuse

21. Some AI apps, like FaceApp , use AI to enhance photos but raise concerns about data privacy. There was a controversy over the app’s privacy policy, which claimed debates over data ownership. Questions arose about who controls and owns user data when using AI-based services. AI and Photo Privacy Source: Qualcomm

22. Deepfake technology creates fake videos and poses serious security threats. Experts warn deepfakes could spread false information, undermining public trust. This technology may threaten national security and democracy if misused by bad actors. Deepfakes and Security Threats Source: Adobe

23. Amazon’s AI hiring tool was biased against women because it learned from data reflecting a male-dominated tech industry. The AI system favored male candidates, highlighting how biased data can lead to unfair outcomes. Amazon discontinued the tool, understanding the need to address biases to prevent workplace discrimination. AI Bias in Hiring (Amazon 2018)

24. Implementing Compliance Measures Within AI

25. Evaluate Ethical Impacts and Ensure Transparency Conduct ethical assessments to address potential biases and societal impacts in AI models. Keep detailed records of AI operations for compliance. Clearly inform users when AI makes decisions and how it impacts them. For high-risk AI applications, perform DPIAs to assess how the system could impact user privacy and compliance. This is especially important under GDPR and other global privacy regulations.

26. Apply Data Privacy and Protection Measures Only gather the data necessary for the AI system’s purpose. Manage consent by obtaining and allowing easy withdrawal of user consent. Use anonymization or pseudonymization to protect personal data. Enable data access: Provide users with the ability to access, correct, delete or transfer their data. Source: Twelvesec

27. Train Employees and Ensure Accountability Educate your staff, providing regular training on AI compliance and ethical practices. Define clear roles and responsibilities for individuals monitoring AI system outputs. Develop accountability frameworks that include audit trails, error tracking and bias detection mechanisms.

28. Use Privacy-Enhancing Technologies (PETs) Incorporate differential privacy to ensure that individual data are protected while allowing AI systems to analyze aggregate data for insights. Use federated learning to train AI models on decentralized data sources without needing to move personal data. Ensure all personal data used in AI systems is encrypted both at rest and in transit to protect against unauthorized access. Source: A-Team Insight

29. Continuously Monitor and Improve AI Systems Deploy monitoring tools and techniques such as real-time analytics and performance dashboards to identify and address deviations promptly. Conduct periodic reviews and updates of your AI compliance program to address emerging regulatory changes.

30. Additional Resources and Tools Sample DPIA Template AI Compliance Checklist OneTrust (Data Protection Tool) TrustArc (Data Protection Tool) IBM AI Fairness 360 (Bias Detection Tool) Google’s TensorFlow Privacy (Privacy-Enhancing Tool for Differential Privacy) PySyft (Privacy-Enhancing Tool for Federated Learning) Source: ico.org.uk

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