Ethical Considerations in AI and Art - Karolina Skorek
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19 Mar Ethical Considerations in AI and Art

Posted at 17:10h in AI, Art 724, Research by
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Artificial Intelligence is revolutionising the way we create and experience art.
However, as with any technology, the adoption of AI in the art world raises important ethical considerations.
In this context, I created a mind map outlining the key ethical issues involved in AI and art that could be a crucial part of my collaboration with Dr. Mobayode Akinsolu. From intellectual property and cultural sensitivity to data security, transparency, and fairness, this mind map provides a structured overview of the ethical landscape of AI-generated art.

Ethical Considerations in AI and Art

  • Intellectual Property
    • Attribution and authorship
      • Determining appropriate credit
      • Balancing rights of creators and AI
    • Copyright and licensing
      • Establishing ownership
      • Licensing for AI tools and datasets
    • Plagiarism and originality
      • Avoiding unintentional copying
      • Ensuring novel and unique elements
  • Cultural Sensitivity
    • Representation and diversity
      • Inclusive datasets for AI models
      • Avoiding cultural appropriation
    • Respect for traditions and heritage
      • Importance of cultural context
      • Avoiding misuse of cultural symbols
  • Data Security and Privacy
    • Protecting personal information
      • Secure storage and processing
      • Compliance with data protection regulations
    • Confidentiality in collaboration
      • Respecting privacy of collaborators
      • Clear agreements on data sharing
  • Transparency and Explainability
    • Openness in AI systems
      • Information about AI tools and techniques
      • Clear labeling of AI-generated art
    • AI model interpretability
      • Understanding AI decision-making
      • Communicating artistic choices
  • Fairness and Bias
    • Reducing bias in AI-generated art
      • Addressing biases in data and algorithms
      • Avoiding perpetuation of stereotypes
    • Promoting fairness in collaboration
      • Equal opportunities for participants
      • Diverse perspectives in AI-driven art
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