AI in Education: Prioritize Real-World Impact Over Speculative Futures

Why It Matters

Designers developing AI-driven educational tools should ground their efforts in current capabilities and address immediate user needs and potential harms. This approach ensures that innovations are relevant, ethical, and contribute meaningfully to the learning environment, rather than chasing unproven technological advancements.

Key Finding

The paper argues that discussions about AI in education should focus on current, tangible AI applications and their limitations, rather than future possibilities. It highlights the social and environmental costs, and the subjective nature of AI claims, urging a move away from viewing AI as a neutral tool towards recognizing its political implications.

Key Findings

• The discourse around AI in education often overemphasizes speculative technologies at the expense of 'actually existing' AI.
• AI has significant limitations in modeling complex social contexts and simulating human intelligence, autonomy, and emotions.
• The use of AI in education carries potential social harms that need to be addressed.
• Claims about AI are inherently value-driven and not neutral.
• The environmental and ecological sustainability of AI development and implementation is a critical concern.

Research Evidence

Aim: What are the key areas of contention that require careful consideration when discussing and implementing AI in educational settings?

Method: Literature Review and Critical Analysis

Procedure: The research critically examines current discourse surrounding AI in education, identifying five broad areas of contention: the distinction between actual and speculative AI, the limitations of AI in simulating human cognition and emotion, the potential social harms, the value-laden nature of AI claims, and the environmental impact of AI development.

Context: Educational Technology and Artificial Intelligence

Design Principle

Ground AI innovation in educational design with practical realities, ethical awareness, and a focus on demonstrable user benefit.

How to Apply

Before embarking on a new AI-driven educational design project, conduct a thorough review of existing AI capabilities relevant to the problem, identify potential negative social impacts, and assess the environmental footprint of the proposed solution.

Limitations

The paper's focus is on broad areas of contention, and specific technological limitations or social harms may vary significantly depending on the AI application and educational context.

Student Guide (IB Design Technology)

Simple Explanation: Don't get too caught up in what AI *might* do in the future for education. Focus on what it *can* do now, what its limits are, and if it could cause any problems for students or the planet.

Why This Matters: Understanding the real-world impact and limitations of AI is crucial for designing responsible and effective educational technologies that truly benefit learners.

Critical Thinking: How can designers ensure that the pursuit of AI innovation in education does not exacerbate existing inequalities or create new forms of harm?

IA-Ready Paragraph: The implementation of AI in educational design necessitates a critical approach, moving beyond speculative futures to address 'actually existing' AI. As Selwyn (2022) notes, it is crucial to foreground the limitations of AI in simulating human intelligence and social contexts, acknowledge potential social harms, and consider the value-driven nature of AI claims. Furthermore, the environmental sustainability of AI development must be a key consideration, framing AI in education not as a neutral tool but as a political action with differential impacts.

Project Tips

• When proposing an AI solution for a design project, clearly distinguish between current capabilities and future aspirations.
• Actively research and discuss the potential negative consequences and ethical dilemmas of your AI design.

How to Use in IA

• Reference this research when discussing the ethical considerations, limitations, or the practical application of AI in your design project's evaluation or justification sections.

Examiner Tips

• Ensure your design project critically engages with the limitations and potential negative consequences of the AI technologies you propose or utilize.

Independent Variable: ["Focus on speculative AI technologies","Focus on 'actually existing' AI technologies"]

Dependent Variable: ["Attention to limitations of AI","Attention to social harms of AI","Attention to environmental impact of AI"]

Controlled Variables: ["Discourse around AI in education"]

Strengths

• Provides a critical framework for evaluating AI in education.
• Highlights important, often overlooked, considerations like social harm and environmental impact.

Critical Questions

• What are the ethical responsibilities of designers when developing AI for educational purposes?
• How can we measure and mitigate the social harms associated with AI in learning environments?

Extended Essay Application

• An Extended Essay could explore the ethical frameworks for AI development in education, or conduct a comparative analysis of the social impact of different AI educational tools.

Source

The future of <scp>AI</scp> and education: Some cautionary notes · European Journal of Education · 2022 · 10.1111/ejed.12532