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Artificial Intelligence (AI) Library Guide

Data Security and Privacy in AI

As generative AI tools become more widely used in academic and everyday settings, it's important to understand the privacy and data security risks associated with these technologies.

Many AI tools—especially those available online—collect and store user input. This means that anything you type into an AI system could potentially be saved, reviewed, or used to further train the tool. Sensitive information, such as personal data, research findings, or proprietary content, should not be entered into generative AI platforms unless you are certain of the tool’s privacy practices.

Some key considerations:

  • Not all AI tools are private. Public versions of tools do not guarantee confidentiality. Even anonymized data can sometimes be used to improve the model.
  • Uploaded files and content may be stored. When using AI features that analyze PDFs, datasets, or documents, check whether the tool retains or shares those files.
  • Institutional policies may apply. Cyprus University of Technology has guidelines on the appropriate and ethical use of AI tools, particularly in handling student or research data.

For these reasons, it’s important to:

  • Read the privacy policy and terms of use of any AI tool before using it.
  • Avoid sharing confidential, sensitive, or personally identifiable information in prompts.
  • Reach out to the Library or IT department with questions about secure and appropriate AI use.

Legal and Ethical Frameworks for AI

As AI technology becomes more embedded in education, research, and everyday life, governments and institutions are developing legal frameworks to guide its responsible use. Below are some of the major regulatory efforts and ethical guidelines shaping how AI is governed.

European Union: AI Act (2024)

  • The EU AI Act is the world’s first comprehensive legal framework for AI.
  • It categorizes AI systems by risk levels (unacceptable, high, limited, and minimal) and regulates them accordingly.
  • Key features include:
    • Bans on AI systems that pose unacceptable risks (e.g., social scoring).
    • Strict requirements for high-risk systems, including transparency, human oversight, and accountability.
    • Obligations for developers to assess and mitigate bias and discrimination.

United States: Emerging Policies

The U.S. does not yet have a comprehensive national AI law but has several guiding policies:

  • The Blueprint for an AI Bill of Rights (2022), developed by the White House Office of Science and Technology Policy, outlines principles such as data privacy, algorithmic fairness, and human oversight.
  • The Executive Order on Safe, Secure, and Trustworthy AI (2023) directs federal agencies to establish standards for responsible AI development.
  • Sector-specific regulations (e.g., in healthcare, education, and finance) are evolving to include AI-specific guidelines.

UNESCO: Recommendation on the Ethics of Artificial Intelligence (2021)

  • Adopted by 193 countries, this global framework emphasizes human rights, fairness, accountability, and environmental sustainability in AI development and use.
  • Promotes ethical impact assessments and data governance best practices.

Canada: Directive on Automated Decision-Making

  • Applies to federal institutions using AI in decision-making.
  • Requires algorithmic impact assessments to ensure transparency, fairness, and public trust.

Institutional and Research Guidelines

Many universities and research organizations are adopting internal AI usage policies, including:

  • Guidelines for academic integrity and AI use in coursework.
  • Data privacy rules when using AI in research involving human subjects.
  • Policies on responsible citation and disclosure when AI tools are used in scholarly work.

Why This Matters for Students and Researchers

Understanding AI legal frameworks helps you:

  • Use AI tools ethically and legally in academic work.
  • Recognize your rights and responsibilities when sharing data with AI systems.
  • Prepare for future roles in fields where AI regulation compliance is essential.

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