The video, What are Large Language Models, uses words like understand and conversation when referring to what LLMs can do. To be clear, while LLMs use sophisticated algorithms to decode language, they are incapable of human understanding and conversation. As in the example of Generative Adversarial Networks (GANs), they learn in a trial-and-error fashion until they can generate outputs that replicate or mimic true meaning. But the outputs may not be true or accurate. LLMs are, therefore, prone to "hallucinations", meaning they will always generate a confident or authoritative response, even if it is inaccurate. This is because LLMs are incapable of understanding truth or the meaning of words; they can only generate responses based on learned patterns.
If Large Language Models are prone to "hallucinations", what does this mean for you, the end user?
How might the use of generative AI in academic writing impact the integrity of your work?
What biases might be embedded in generative AI outputs that could affect your decision-making?
What role does critical thinking play in your ethical and responsible use of generative AI?
Identify Ethical Dilemmas
The use of generative AI in university raises significant ethical dilemmas. A few major concerns are
Plagiarism - Since AI-generated content resembles human writing so closely, it may be difficult to resist using it in your academic writing without permission or proper attribution.
Bias - The content generated by generative AI can perpetuate biases from its training data, posing challenges to diversity and inclusion.
Intellectual Property - The use of AI-generated content can lead to copyright infringement if used without proper attribution or without verifying the source of the original content.
Privacy - Students might inadvertently share personal, confidential or sensitive information, unaware of the extent to which the information is used, shared or stored by the AI.
While these are significant challenges, with proper oversight, GenAI can be used in an ethical and responsible way. Complete the activities below to test your understanding of (i) the ethical dilemmas GenAI poses for learning in university and (ii) some of the strategies you can adopt to use it ethically and responsibly.
Ethical Dilemmas GenAI Poses for Learning in University
Activity 1 - Drag and Drop
Strategies You Can Adopt
Students can adopt several strategies to address the ethical dilemmas that arise from using GenAI in a university setting. Being well-informed, understanding limitations, seeking guidance from professors and instructors, and engaging in open discussions are just a few. In this activity, select at least three strategies that best address the ethical dilemmas associated with the use of generative AI to complete your coursework.