AI Toolkit: Libraries and Essays for Exploring the Technology and Ethics Behind AI

Source publication / research team or educational organization described in paper

Not specified in extracted text

Researchers, educators, instructors, or facilitators as described in the source publication

• Research / curriculum design context

Course implementation or course design

Not specified in extracted text

Not specified in extracted text

Ethics / responsible AI

• The paper provides limited implementation detail in the extracted abstract; additional manual review may be needed for local replication.

Unspecified / broad education

Mixed or not explicitly specified; infer from target learner group and intervention design.

Varies by intervention; not specified unless the paper explicitly describes prerequisites.

• Document the AI education intervention, course, tool, or resource described in the source publication.
• Extract the learner context, AI role, pedagogy, outcomes, and constraints for AAB registry comparison.
• In this paper we describe the development and evaluation of AITK, the Artificial Intelligence Toolkit.

• Support AAB comparison across AI literacy, AI education, teacher training, higher education, and workforce contexts.
• Capture evidence maturity, transferability, and limitations rather than treating the publication as product endorsement.

• Not an AAB endorsement of the tool, curriculum, provider, or result.
• Not a direct replication record unless the source paper reports implementation details sufficient for replication.

Ethics / responsible AI

Not specified in extracted text

• Evaluator

• Primary interaction pattern inferred from publication: Curriculum / course design, Learning tool / resource design, Ethics / responsible AI education.
• AI capability focus: Ethics / responsible AI.

• Include bias, fairness, transparency, and social impact discussion as part of the learning design.

• Review the publication’s reported context, learner group, AI tool or curriculum, implementation process, and outcome evidence.
• Map the case to AAB registry fields for comparison across educational levels and AI capability types.
• Use the source publication and PDF for any manual verification before public registry release.

• Human educators/researchers remain responsible for instructional design, supervision, interpretation, and ethical safeguards.
• AI systems or AI concepts provide the learning object, support tool, evaluator, simulator, or automation context depending on the paper.

• Instructional / curriculum-based learning
• Registry extraction emphasizes explicit learning goals, observed outcomes, constraints, and safety limitations.

• The paper provides limited implementation detail in the extracted abstract; additional manual review may be needed for local replication.

• Case classified under: Published empirical study.
• Pedagogical pattern: Instructional / curriculum-based learning.
• Any additional adaptations should be verified against the full paper before public-facing publication.

• Engagement evidence should be interpreted according to the source paper’s reported method and sample.
• Our pilot studies and usability testing results indicate that AITK is easy to navigate and effective at helping users gain a better under- standing of AI.

• Our pilot studies and usability testing results indicate that AITK is easy to navigate and effective at helping users gain a better under- standing of AI.

In this paper we describe the development and evaluation of AITK, the Artificial Intelligence Toolkit. This open-source project contains both Python libraries and computational es- says (Jupyter notebooks) that together are designed to allow a diverse audience with little or no background in AI to in- teract with a variety of AI tools, exploring in more depth how they function, visualizing their outcomes, and gaining a better understanding of their ethical implications.

• Include bias, fairness, transparency, and social impact discussion as part of the learning design.

• Activity documentation

• Can be used as an AAB evidence record for cross-case comparison, standards drafting, and evidence-maturity mapping.
• Supports identification of recurring patterns in AI literacy, AI education implementation, teacher preparation, assessment, and responsible AI learning.

• AI literacy
• Conceptual understanding
• Ethics and responsible use
• Curriculum / course design
• Learning tool / resource design
• Ethics / responsible AI education
• Ethics / responsible AI

• Completed

Unspecified / broad education

Research / curriculum design context

Ethics / responsible AI

Instructional / curriculum-based learning

Medium

Low to Medium

AI Toolkit: Libraries and Essays for Exploring the Technology and Ethics Behind AI

• Levin Ho
• Morgan McErlean
• Zehua You
• Douglas Blank
• Lisa Meeden

Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 39 No. 28, EAAI-25

2025

10.1609/aaai.v39i28.35171

https://ojs.aaai.org/index.php/AAAI/article/view/35171

https://ojs.aaai.org/index.php/AAAI/article/view/35171/37326

008_AI Toolkit_ Libraries and Essays for Exploring the Technology and Ethics Behind AI.pdf

6

In this paper we describe the development and evaluation of AITK, the Artificial Intelligence Toolkit. This open-source project contains both Python libraries and computational es- says (Jupyter notebooks) that together are designed to allow a diverse audience with little or no background in AI to in- teract with a variety of AI tools, exploring in more depth how they function, visualizing their outcomes, and gaining a better understanding of their ethical implications. These notebooks have been piloted at multiple institutions in a variety of hu- manities courses centered on the theme of responsible AI. In addition, we conducted usability testing of AITK. Our pilot studies and usability testing results indicate that AITK is easy to navigate and effective at helping users gain a better under- standing of AI. Our goal, in this time of rapid innovations in AI, is for AITK to provide an accessible resource for faculty from any discipline looking to incorporate AI topics into their courses and for anyone eager to learn more about AI on their own.

• Research / curriculum design context

• The paper provides limited implementation detail in the extracted abstract; additional manual review may be needed for local replication.

Not specified in extracted text unless noted in duration field.

Requires educators/researchers/facilitators with sufficient AI literacy and pedagogy knowledge for the target learners.

Infrastructure depends on AI tool type, learner devices, data access, and institutional policy context.

High

• group_size
• duration

This entry was automatically extracted from the PDF text and manifest metadata. Fields should be manually verified before public registry publication, especially group size, location, duration, and outcome claims.