At its core, Generative AI refers to artificial intelligence systems that can produce new content—like text, images, code, or even music—in response to a prompt or input. Think of it as a very sophisticated creative assistant. These tools learn from vast amounts of existing data and then generate novel outputs that often mimic human-created content.
Popular examples you might have heard of include:
Large Language Models (LLMs): Tools like ChatGPT, Claude, and Gemini that generate human-like text, answer questions, summarize information, and much more.
Image Generators: AI like DALL-E 3, Midjourney, and Stable Diffusion that create images from text descriptions.
Code Generators: AI that can write or debug programming code.
Image created by Trina Adams
CC BY-NC-SA 4.0
The ability of generative AI to produce sophisticated content raises important questions, especially in an academic environment. Here's why ethical considerations are so crucial:
Academic Integrity: Universities and instructors value original thought and honest representation of your work. Submitting AI-generated content as your own without proper acknowledgment can be considered plagiarism.
Learning Process: The purpose of assignments is for you to learn, think critically, and develop skills. Over-reliance on AI can bypass this crucial learning process.
Accuracy and Bias: AI models learn from existing data, which can sometimes contain inaccuracies, biases, or outdated information. Blindly trusting AI-generated content can lead to misinformation in your work.
Fairness and Equity: Not all students have equal access to or proficiency with advanced AI tools, which can create an uneven playing field if their use isn't guided by clear policies.
Transparency: It's important to be transparent with your instructors about how you've used AI, just as you would cite any other source.
Understanding these ethical dimensions is the first step toward using generative AI responsibly and effectively as a student.