6. User Control and Consent • Informed Consent: Ensure users are informed about and consent to how their data is used by AI systems. • User Control: Provide users with control over their data and options to opt-out of certain AI functionalities if desired. 7. Compliance with Regulations • Legal Compliance: Adhere to existing laws and regulations governing AI and data use. Stay informed about evolving legal standards and adapt accordingly. • Ethical Standards: Follow industry-specific ethical standards and guidelines, which may include adherence to professional codes of conduct. • Copyrights: Ensure that
attribution or the necessary rights being obtained. This includes content produced by AI systems, which could unintentionally violate existing copyrights. 8. Continuous Monitoring and Improvement • Ongoing Evaluation: Continuously monitor AI systems for performance, fairness, and potential negative impacts. Update and refine systems based on feedback and new developments. • User Feedback: Incorporate feedback from users and stakeholders to improve AI systems and address any concerns that arise. 9. Collaboration and Engagement • Stakeholder Engagement: Engage with diverse
stakeholders, including ethicists, sociologists, and affected communities, to gather a range of perspectives and insights. • Cross-Disciplinary Collaboration: Foster collaboration between AI developers, domain experts, and policymakers to ensure comprehensive and well- rounded approaches to AI deployment. 10. Environmental Considerations • Energy Efficiency: Strive for energy-efficient AI systems to minimize environmental impact. Consider the carbon footprint of training and deploying AI models. 11. Disclosure and Attribution • Transparent authorship: AI- generated content used in
no copyrighted material is published without proper
38 – Florida Technology Magazine – 2024 Fall Edition
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