Artificial intelligence (AI) has been a buzzword in education for some time now, with the potential to revolutionize how we teach and learn. One of the most promising areas of AI development is generative AI, which uses machine learning to create new content based on patterns and relationships in existing data. This technology has been used to generate everything from music and art to natural language and code.
In education, generative AI has the potential to create personalized and adaptive learning experiences for students. By analyzing data about a student's interests, learning style, and performance, AI can create content that is tailored to their needs. This could include everything from interactive simulations and virtual environments to assessments that adapt to the student's level of understanding.
However, the use of AI in education also raises ethical concerns, such as issues of academic integrity, fairness, and bias in grading and assessment. If AI is used to grade student work, for example, there is a risk that the system may be biased against certain students or groups based on past data.
To ensure that the use of generative AI in education is ethical and responsible, policies and guidelines need to be developed. These policies should address issues such as understanding student learning and outcomes, data sources, privacy, bias and fairness, and the impact on academic integrity. In this proposal, we explore the potential of generative AI in education, its impact on teaching, and the challenges and ethical concerns associated with its use. Attendees will gain a better understanding of the potential of generative AI in education and how to navigate its ethical and practical considerations.