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Citations + Plagiarism

Generative AI and Academic Honesty

Artificial Intelligence poses significant challenges and/or concerns to those interested in maintaining and upholding Academic Honesty at Niagara College. Academic Honesty means acting in an honest and trustworthy manner in all aspects of one's academic career, and, more specifically, refraining from engaging in any form of academic dishonesty to obtain any type of academic advantage or credit (Niagara College, 2019). Therefore, the use of a work derived from Artificial Intelligence, without acknowledgement and/or proper citation, could be considered an academically dishonest act at Niagara College. Generative AI such as ChatGPT should only be used when permission has been given by your professor to do so, and you should always cite the portions of your finished product or project that were taken from Artificial Intelligence according to the citation style you have been assigned.

Niagara College Statement on Academic Integrity and Artificial Intelligence.

Generative AI and Information Literacy

Even when using Generative AI, such as ChatGPT, with the permission of your professor, there are ethical questions to consider. Generative AI, while powerful, is not without its drawbacks. Here are some key limitations to consider:

  1. Factual Accuracy: AI models are trained on vast datasets, but they don't inherently fact-check the information they process. As a result, responses may contain inaccuracies or be based on outdated information.
  2. Citation Reliability: Generative AI can often provide incorrect or even fabricated citations, making it challenging to verify the sources of information.
  3. Timeliness: Many AI models have a knowledge cutoff date, meaning they may not have access to the most recent information on current events or trends.
  4. Bias and Discrimination: AI models can reflect the biases present in the data they are trained on. This can lead to discriminatory or harmful outputs, especially if the training data is biased.
  5. Labor Exploitation: The development of some AI models has involved the exploitation of workers, particularly in low-wage countries, who are tasked with training the AI to recognize harmful content.
  6. Privacy Concerns: Generative AI models often collect and process user data, raising concerns about privacy and data security.
  7. Copyright Issues: The use of copyrighted material in AI training and outputs can lead to legal disputes and copyright infringement.

It's essential to be aware of these limitations and use generative AI critically, verifying information from reliable sources and considering the potential biases in the outputs.