Artificial Intelligence (AI) Library Guide

As generative AI tools become increasingly prevalent in academic settings, it's essential to understand how they intersect with the principles of academic integrity. While these tools can support learning and research by assisting with writing, brainstorming, and summarizing, they also present new challenges.

Issues such as misinformation, bias, false or fabricated citations, and plagiarism can arise when AI is used without critical evaluation or proper citation. This section guides recognizing these risks and using AI tools responsibly, ensuring that your academic work remains ethical, accurate, and trustworthy

Generative AI tools can be helpful for tasks like brainstorming ideas, organizing information, summarizing sources, or exploring different perspectives on a topic. However, it's important to be aware of their limitations. These tools don't always rely on verified facts or follow scholarly research practices. In many cases, they produce what are called “hallucinations”—false or misleading information that sounds convincing but may be partially or entirely made up. This can include fake citations, incorrect data, or distorted explanations.

Some AI tools can also be used to create deepfakes—realistic-looking but entirely fake images, videos, or audio recordings. These are often designed to spread misinformation and can be especially harmful in political or social contexts.

Another important limitation is that generative AI systems often don't have access to the most recent information. Since many are trained on older datasets, they may provide outdated or incomplete perspectives on current events or recent research.

When using AI tools for research or learning, always double-check information against reliable sources—and don't hesitate to ask a librarian for help!

Another important limitation of generative AI is the bias that can be built into the responses it creates. These tools are trained on massive amounts of online content, which means they often reflect the same biases—social, political, cultural, or otherwise—that exist in that content. Because AI systems work by predicting the most likely words or phrases based on patterns in their training data, they can unintentionally reinforce stereotypes or misinformation.

Some AI tools also use a method called reinforcement learning with human feedback (RLHF) to improve their responses. However, the humans involved in this process may carry their own biases, which can influence how the AI learns and responds.

As a result, AI tools have been found at times to generate responses that are socially or politically biased, and in some cases, even include sexist, racist, or offensive content. It's always a good idea to critically evaluate AI-generated information and consult trusted sources when conducting research or working on assignments.

Generative AI tools have introduced new challenges when it comes to academic integrity, especially around plagiarism.

Plagiarism is usually defined as presenting someone else's ideas or work as your own. Even though generative AI tools aren’t people, using text from them without proper citation is still considered plagiarism. According to the Cyprus University of Technology Rules, because the words weren’t written by you, using them without acknowledgment violates academic honesty policies.

Keep in mind that different courses and instructors may have their own rules about whether and how AI tools can be used. Always check your syllabus and, when in doubt, ask your professor for clarification or your subject librarian.

About AI Detection Tools

There are several tools designed to detect AI-generated content, but they’re still in development and not always reliable. These tools can sometimes produce false positives (incorrectly flagging original work as AI-generated), and they often struggle to detect AI-generated writing accurately because it doesn’t directly copy existing sources.

At this time, Cyprus University of Technology uses Turnitin’s AI detection feature in its plagiarism screening tool!

Another academic integrity concern with generative AI tools is the risk of false or inaccurate citations.

According to the Cyprus University of Technology, including false citations in your work—whether it’s intentional or accidental—is a violation of academic integrity standards. Generative AI tools have been known to create fake citations that look real but refer to non-existent sources. Even when a citation points to an actual article or book, the summary or quotation provided by the AI may be inaccurate or misleading.

If you choose to use generative AI tools in your research, it’s essential to double-check every citation for accuracy and reliability. Never assume that references generated by AI are correct—always verify them using library databases or other trusted academic sources.