Data Literacy Education in the Era of AI

Use of data for business in many industries, including but not limited to education, research, health and finance, faces new opportunities and challenges in the era of Artificial Intelligence (AI). AI literacy demands data literacy. This elicits the essential questions of: what does data literacy look like in the AI era? How should I become fluent with data as a researcher, educator, healthcare provider, government employee, citizen, etc. to navigate this new data and information environment?

This panel will explore the facets of AI opportunities, challenges and ethical considerations in developing data literacy in the AI age. Our panelists will share insights from their work across academia, industry, and healthcare to address topics such as: understanding AI training data and its implications, detecting potential biases in datasets, and evaluating AI system outputs. We will discuss practical strategies for building data literacy skills at both individual and institutional levels. The session will conclude with an opportunity for audience members to ask questions about data literacy capabilities in an AI-driven world.

Questions:

1. Opening Thoughts 1). What data literacy efforts exist in your organization? What is your role? 2). What are the AI products / services in your organization, and how are they used?

2. Ethical Considerations for data and AI 1). What keeps you up at night? 2). What are not enough professionals aware of in terms of ethics, data, and AI?

3. Opportunities for data literacy 1). How to engage with data quality when approaching data literacy education? 2). What are the most exciting opportunities for cultivating data literacy in this AI age?

4. Practical challenges and considerations 1).How to optimize the use of organizational AI resources to develop learning materials or perform administrative tasks? 2). How to benchmark or assess the efficacy of AI models interacting with data?