Innovation arcade: Exploration lab 
Purpose: To educate students and teachers on the responsible and equitable use of AI technologies in education.
Objectives:
Identify and mitigate bias and discrimination in classroom AI
Bridge the digital divide and ensure equitable access to AI
Examine the long-term risks of synthetic media for students of color
Apply critical theory and principles to create empowering and equitable educational AI
Advocate for the responsible and ethical use of AI in schools
The following is the 7 part outline of this session is based on upcoming podcast series and published book by the same title. Participants will engage in a series of activities to experience, deconstruct, and reconstruct better experiences based on the following activities:
1. Introduction
- Overview of critical theory - how bias and power shape technology
- AI concepts and trends relevant to K-12 education
2. Risks and Biases in Educational AI
- How bias manifests in school data and AI systems
- Case studies of unfair bias and discrimination from classroom AI
- Technical and design strategies to mitigate unfair bias
3. The Digital Divide and AI
- Links between marginalization, digital access, and use of AI
- Uneven access to AI for creativity and learning
- Steps for equitable AI access and literacy
4. AI, Power, and High-Stakes Decisions
- Use of AI in high-stakes areas like admissions, grading, tracking
- Dangers of automating and perpetuating discrimination
- Governance for transparency, accountability and oversight
5. AI-Generated Synthetic Media in Schools
- Capabilities and risks of AI-generated fake audio, images and video
- Harms of deepfakes, especially for students of color
- Developing skills and safeguards against fake classroom media
6. Student Empowerment in an AI-Driven World
- Schools collect student data to train AI systems
- Protecting student privacy and preventing data harms
- Student data rights and responsibilities with educational AI
7. Towards More Equitable Classroom AI
- Applying critical theory to address AI harms
- Principles and practices for empowering and equitable educational AI
- Role of activism and advocacy in shaping AI's future in schools
- Algorithms of Oppression, Noble 2018
- Conflict Theory: Social Theory and the Real World, Coser 2022
- Pedagogy of the Oppressed, Freire 1968.
- Unmasking AI: A Critique of the Justifications for Bias in AI Systems, Buolamwini 2022.
- Abolitionist Tools for the New Jim Code, Benjamin 2019
- Demarginalizing Design, Lanier 2022.
- The New Jim Crow, Alexander 2020.
| Related exhibitors: | Samsung Electronics |
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