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Hardwiring Ethics: How Human-Centered Approaches Can Bring Back Justice in AI

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Grand Hyatt - Texas Ballroom B

Innovator Talk
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Session description

This innovator talk guides educators to integrate ethical practice in their use of AI through UNESCO’s human-centered mindset and justice-oriented competencies. Participants will try strategies for embedding ethics micro-lessons that ensure students hardwire the constructs of ethics whenever AI is used for learning.

Outline

1. Introduction (10 minutes)

A. Overview of AI Ethics and Literacy:
Introduce the session by explaining the importance of integrating AI ethics into classroom teaching. Highlight how the increasing presence of AI in education requires a thoughtful, structured approach to ensure students engage with AI responsibly and ethically.

B. Session Objectives and Why they Matter
Participants will be introduced to the session objectives, which include the following with a brief discussion of some of the potential pitfalls they may address in the use of AI. Some guiding questions will include:

- How can frameworks on ethics be useful to creating a curriculum that uses AI?
- How could the development of Human-Centered Critical Thinking in Students strengthen the learning of ethical concepts?
- To what extent do issues of justice lead to better digital citizens?

2. Main Content (30 minutes)

A. Hardwiring Ethics through a Foundation of Core Values (10 minutes)
- Mini-lecture: Describe 4 core values from the UNESCO competencies and the Digital Promise AI framework and discuss overlaps and challenges

B. Developing Human Centered Critical Thinking in Students (10 minutes) (what can a human do that AI can’t?)

- Mini-lecture: Explain how students can develop agency and human-centered thinking; including understanding the limitations of AI that only humans possess and human determination
- Activity: Micro-lesson on Human Centeredness: Participants analyze AI outputs, using the following micro-lesson steps:

 1. Be self aware and Define your Role
 2. prioritize human well-being and describe how empathy guides this
 3. Exercise Decision making independent of the AI (autonomy and choice)
 4. Reflect on your autonomy and agency

C. Building Practical Justice and Ethics for AI Use (10 minutes)
- Mini-lecture: Highlight key concepts on justice-oriented thinking, and outlining how bias, prejudice, privacy, and proportionality, can align to digital citizenship
- Activity: Micro-Lesson on Justice-oriented Evaluation Participants evaluate AI outputs, using the following micro-lesson steps:

 1. Identify what the core values of respect and fairness mean to you
 2. Employ “do no harm” thinking
 3. Describe your personal responsibility in ensuring your safety and privacy
4. Reflect on how to evaluate proportionality as a key component of justice

3. Conclusion (10 minutes):

A. The Intersection of Human-Centered Actions and Justice-Oriented Thinking: Participants will diagram the connections across these themes by discussing the overlaps that create ethical conduct when using AI, which then promote digital citizenship.
Participants discuss the challenges and opportunities of using this micro-lesson approach, and how teacher leaders may model and advocate for these opportunities with colleagues.

B. Call to Action: Encourage participants to take these micro-lessons back to their schools and start incorporating human-centered, justice-oriented ethics when students use AI. Participants are encouraged to model these behaviors in their own use of AI for teaching.

C. Reference: Where to get more information for UNESCO and Digital Promise

4. Q&A (10 minutes): Open the floor for any remaining questions or thoughts.

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Supporting research

1. Adams, C., Pente, P. Lemermeyer, G., and Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligence, 4 (100131), 1-10.

2. Yang, S.J.H., Ogata, H. Matsui, T., and Chen, Nian-Shing. (2021). Human-centered artificial intelligence in education: Seeing the invisible through the visible. Computers and Education: Artificial Intelligence, 2(100008), 1-5.

3. Miao, F., & Shiohira, K. (2024). AI competency framework for students. The United Nations Educational, Scientific, and Cultural Organization. Paris, France. https://unesdoc.unesco.org/ark:/48223/pf0000391105

4. Mills, K., Ruiz, P., Lee, K., Coenraad, M., Fusco, J., Roschelle, J., & Weisgrau, J. (2024). AI literacy: A framework to understand, evaluate, and use emerging technology. Digital Promise. Retrieved from https://digitalpromise.org/

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Presenters

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Professor Department of Teaching & Learning
University of Texas Rio Grande Valley
ISTE Certified Educator
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President
Rockcliffe University Consortium

Session specifications

Topic:

Artificial Intelligence

Grade level:

PK-12

Audience:

Teacher Development, Teacher

Attendee devices:

Devices useful

Attendee device specification:

Smartphone: Android, iOS, Windows
Laptop: Chromebook, Mac, PC
Tablet: Android, iOS, Windows

Participant accounts, software and other materials:

Access to any generative AI tool is optional.

Subject area:

Teacher Education, Other: Please specify

ISTE Standards:

For Educators:
Leader
  • Advocate for equitable access to technology, high-quality digital content, and learning opportunities to meet the diverse needs of all students.
Citizen
  • Foster digital literacy by encouraging curiosity, reflection, and the critical evaluation of digital resources.
  • Mentor students in safe, legal, and ethical practices with digital tools and content.

TLPs:

Develop Expertise, Ignite Agency