Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube Article Swipe
Kausik Lakkaraju
,
Vedant Khandelwal
,
Biplav Srivastava
,
Forest Agostinelli
,
Hengtao Tang
,
Prathamjeet Singh
,
Dezhi Wu
,
Matt Irvin
,
Ashish Kundu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2402.01760
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2402.01760
Artificial intelligence (AI) has the potential to transform education with its power of uncovering insights from massive data about student learning patterns. However, ethical and trustworthy concerns of AI have been raised but are unsolved. Prominent ethical issues in high school AI education include data privacy, information leakage, abusive language, and fairness. This paper describes technological components that were built to address ethical and trustworthy concerns in a multi-modal collaborative platform (called ALLURE chatbot) for high school students to collaborate with AI to solve the Rubik's cube. In data privacy, we want to ensure that the informed consent of children, parents, and teachers, is at the center of any data that is managed. Since children are involved, language, whether textual, audio, or visual, is acceptable both from users and AI and the system can steer interaction away from dangerous situations. In information management, we also want to ensure that the system, while learning to improve over time, does not leak information about users from one group to another.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2402.01760
- https://arxiv.org/pdf/2402.01760
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391591666
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4391591666Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2402.01760Digital Object Identifier
- Title
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Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's CubeWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-30Full publication date if available
- Authors
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Kausik Lakkaraju, Vedant Khandelwal, Biplav Srivastava, Forest Agostinelli, Hengtao Tang, Prathamjeet Singh, Dezhi Wu, Matt Irvin, Ashish KunduList of authors in order
- Landing page
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https://arxiv.org/abs/2402.01760Publisher landing page
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https://arxiv.org/pdf/2402.01760Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2402.01760Direct OA link when available
- Concepts
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Chatbot, Cube (algebra), Modal, Computer science, Human–computer interaction, Knowledge management, Psychology, Chemistry, Artificial intelligence, Mathematics, Polymer chemistry, CombinatoricsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.components | 56 |
| abstract_inverted_index.uncovering | 13 |
| abstract_inverted_index.collaborate | 79 |
| abstract_inverted_index.information | 46, 141, 160 |
| abstract_inverted_index.interaction | 135 |
| abstract_inverted_index.management, | 142 |
| abstract_inverted_index.multi-modal | 68 |
| abstract_inverted_index.situations. | 139 |
| abstract_inverted_index.trustworthy | 25, 64 |
| abstract_inverted_index.intelligence | 1 |
| abstract_inverted_index.collaborative | 69 |
| abstract_inverted_index.technological | 55 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile |