AI Risk Database: The Essential Reference for Using AI in Education
콘
콘텐주
1
Outline
The AI Risk Database is an essential reference for the safe and effective use of AI in education. This database systematically categorizes and analyzes over 700 AI-related risks, making it an important tool for teachers and students to understand and prepare for potential risks of AI technology. Given the rapidly developing impact of AI technology on education, the importance of this comprehensive risk analysis data is growing.
Key Components
1.
AI Risk Database :
Over 700 risk insights extracted from 43 existing frameworks
Includes detailed descriptions, sources, and relevant examples for each risk.
2.
Causal Taxonomy :
Entity: Human vs AI system
Intent: Intentional vs. Unintentional
Timing: Pre-distribution vs. post-distribution
3.
Domain Taxonomy :
AI risk classification into 7 major areas and 23 sub-areas
Provides educational implications for each area
Utilization in the education field
Utilization for teachers
1.
Development of AI Ethics Education Curriculum :
Designing practical and specific AI ethics lessons using a variety of risk cases from the database
Provide students with opportunities to think critically about the potential risks and implications of AI.
Example: When designing a lesson on the topic of “AI bias,” use the database’s discrimination-related cases to select topics for discussion.
2.
Choosing and Evaluating AI Tools :
Identifying potential risks in advance when introducing AI tools for education
Evaluating AI tools across a range of dimensions, including student data protection, fairness, and transparency
Example: When introducing an automatic scoring system, establish evaluation criteria by referring to the “AI System Safety, Failures, and Limitations” area of the database.
3.
Communication with parents and administrators :
Clearly explain the potential risks and countermeasures associated with the introduction of AI technology.
Supporting the establishment of AI-related policies and guidelines by utilizing systematic classification of databases
Example: Using a database in a presentation on the introduction of an AI tutoring system at a parent information session
4.
Teacher Professional Development :
Empowering educators in the digital age by understanding AI risks
Self-directed learning using databases and study group operation with fellow teachers
Utilization for students
1.
Improving AI Literacy :
Develop the ability to understand the different types of risks in AI and recognize them in real life
Develop the ability to understand and critically evaluate the pros and cons of AI technology in a balanced manner
Example: Deepfake detection practice using the “false information” area of the database
2.
Project-based learning :
Project to establish AI risk analysis and response measures using databases
Seeking solutions to AI ethical dilemmas based on real-world cases
Example: Group project on the topic of “AI and Privacy”, analysis of relevant cases in database
3.
Career Exploration and Preparation :
Explore a variety of career opportunities in AI ethics and safety
Promoting understanding of the ethical and social aspects that should be considered in the development and use of AI
Example: Exploring the job of “AI Ethics Consultant” based on various risk areas in the database.
4.
Fostering digital citizenship :
Understand the impact of AI technology on society and grow into a responsible digital citizen
Discussion and essay writing using the socio-economic risk areas of the database
Key Risk Areas and Educational Implications
1.
Discrimination and Harmful Content
Educational Implications: Recognizing Data Bias, Emphasizing the Importance of Inclusive AI Design
Use Case: Analysis of Bias in AI-Based Admissions Systems
2.
Privacy and Security
Educational Implications: Recognize the importance of digital citizenship education and student data protection
Use Case: Establishing Privacy Guidelines When Using Learning Analytics Tools
3.
False information
Educational implications: Media literacy education, improving critical thinking skills
Use Case: Practical Guide to Authenticity Verification of AI-Generated News Articles
4.
Malicious actors and abuse
Educational Implications: Raising AI Security Awareness, Ethical Hacking Education
Use Case: Online Safety Education Through AI Chatbot Abuse Cases
5.
Human-Computer Interaction
Educational Implications: Building Healthy Relationships with AI, Digital Wellbeing Education
Use Case: Analyzing the Pros and Cons of Interactions Between AI Tutors and Students
6.
Socio-economic and environmental risks
Educational Implications: Understanding the Social Impact of AI and Finding Sustainable Ways to Use AI
Use Case: Discussing the Impact of AI Automation on the Job Market
7.
AI System Safety, Failures, and Limitations
Educational Implications: Recognize AI’s Limitations, Emphasize Human Roles and Responsibilities
Usage example: Analysis of error cases in AI decision-making system and establishment of response measures
Advantages of using databases
1.
Systematic risk analysis : Understand AI risks from various perspectives through classification by cause and area.
2.
Real-World Case-Based Learning : Over 700 specific risk cases provide hands-on learning.
3.
Stay informed : Stay informed of the latest AI risk trends with our continuously updated database.
4.
Versatile applications : Can be used for a variety of purposes, including teaching materials, policy making, and research.
Precautions when using a database
1.
Consider context : The context of each risk case must be fully understood and applied to the educational environment.
2.
A balanced approach : We need to address the benefits and possibilities of AI as well as its risks.
3.
Age Appropriateness : Content should be selected and presented appropriately for the students' age and level of understanding.
4.
Continuous Updates : The database should be checked periodically for the latest information and reflected in the training content.
Future prospects and development direction
1.
Expanding Education-Specific Data : We will continue to add risk data related to AI use cases in education.
2.
Building a community of teachers : We plan to develop a platform where they can share and discuss teaching cases utilizing the database.
3.
Developing a student interface : We plan to build a database interface that students can easily understand and utilize.
4.
AI Risk Simulation Tool : We plan to develop an educational AI risk simulation tool based on a database.
Conclusion
The AI Risk Database is a valuable resource for the safe and effective use of AI in education. It allows teachers and students to systematically understand the potential risks of AI and explore countermeasures. It can also be used as a practical tool for AI ethics education and AI literacy improvement.
In a rapidly changing digital age, it is critical for educators and learners alike to understand and prepare for the impact of AI technology. The AI Risk Database is a key resource to support these efforts, enabling a balanced approach to maximizing the benefits and minimizing the risks of AI in education.
This database will continue to be updated and improved in the future. It will develop into a more useful and practical resource through active participation and feedback from the education community. At this important time when AI is shaping the future of education, we hope that the AI Risk Database can contribute to creating a safe and innovative educational environment.
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