AI (Artificial Intelligence)
Artificial Intelligence (AI)
To prepare students for the future, MVLA is committed to supporting schools in integrating AI into teaching and learning. We provide educators with the tools and strategies to harness AI, empowering students with the skills to thrive in an AI-driven world.
In today’s rapidly evolving technological landscape, equipping students with AI literacy and the skills for responsible AI use is essential. As AI becomes increasingly integrated into various aspects of life, students need to understand, navigate, and engage with these technologies ethically and effectively to succeed in the future.
Key Terms
Generative AI - An artificial intelligence system that can generate text, images, or other media in response to prompts. These platforms learn from (or "are trained by") the data and algorithms that the programmers use. These then generate outputs that have similar characteristics based on prompts, often very quickly and with no other effort needed beyond a prompt. Popular examples include ChatGPT, Microsoft CoPilot, and Google Gemini.
Prompts - The words, phrases, and directions that you use with a generative AI platform to craft output. The more detail used in a prompt, the better the result.
Bias - An AI platform is only as good as the data that is fed into it, and since humans choose the data that a generative AI uses, their biases can still be present. Biased outputs can discriminate based on race, gender, social class, and other factors.
Algorithm - An algorithm is a set of instructions that is designed to accomplish a task. Often these are designed to focus in on a user's preferences and tendencies.
AI Slop - AI slop is the low-quality, often fake content, such as text, images, or videos, that is generated by AI. It’s currently overwhelming social media and the internet. The concern for education is that AI has improved to the point that it can make it difficult to distinguish reality from this new wave of fictitious or inaccurate AI-generated content
AI Hallucination – confident but false, inaccurate, or nonsensical information generated by artificial intelligence. These outputs appear grammatically correct and realistic, but are fabrications not supported by training data, often caused by inadequate data, overfitting, or flawed logic.
Generative AI Explained in Two Minutes
AI Literacy
What is AI Literacy?
AI literacy involves the ability to understand and interact with AI systems. It includes the skills required to comprehend how AI works, evaluate its impact, and apply AI tools responsibly in various contexts. AI literacy empowers students to become informed users and creators in an AI-driven world.
Key Components of AI Literacy:
- Understanding AI: Grasping how AI systems function and their applications.
- Evaluating Impact: Assessing the implications of AI technologies on society, ethics, and privacy.
- Responsible Use: Applying AI tools in ways that are ethical and beneficial.
- Creating with AI: Developing and using AI tools to solve problems and innovate.
What is Responsible AI Use?
Responsible AI use involves the ethical and thoughtful application of AI technologies. It encompasses the norms of appropriate, safe, and mindful interaction with AI, ensuring its deployment respects privacy, fairness, and societal values.
Key Components of Responsible AI Use:
- Ethical Application: Understanding and practicing ethical AI development and use.
- Privacy and Security: Protecting personal and sensitive data when using AI.
- Transparency: Being aware of how AI systems make decisions and ensuring clear communication about AI’s role.
- Inclusivity: Ensuring AI benefits everyone and reduces biases in its application.