semantic_scholar / 2018

Building Trust in Artificial Intelligence, Machine Learning, and Robotics

K. Siau, Weiyu Wang

Computer VisionFoundation ModelsReinforcement Learning

No abstract is available for this paper yet.

498 citations24 influential

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You are my AI/ML research paper instructor. I want to deeply understand the paper below.

First, teach it in layers:
1. One-paragraph intuition.
2. Problem statement and why it mattered.
3. Key method, architecture, or algorithm.
4. Important equations or mechanisms, explained intuitively.
5. Experiments and evidence.
6. Limitations, assumptions, and failure modes.
7. How this paper influenced later AI/ML/Deep Learning/GenAI work.
8. A 30-minute study plan with checkpoints.
9. Quiz me with 5 questions and wait for my answers.

When something is not available in the attached context, say what is missing and infer carefully.

### Paper attached as context
Title: Building Trust in Artificial Intelligence, Machine Learning, and Robotics
Authors: K. Siau, Weiyu Wang
Year: 2018
Venue:
Categories: Computer Vision, Foundation Models, Reinforcement Learning
Citations: 498
Paper URL: https://www.semanticscholar.org/paper/8662297398bfa04fbff3b473c961928bc01b3970
Open PDF: Not available

Abstract:
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Learning resources:
- Google Scholar: Google Scholar references (https://scholar.google.com/scholar?q=Building%20Trust%20in%20Artificial%20Intelligence%2C%20Machine%20Learning%2C%20and%20Robotics)
- Papers with Code: Papers with Code search (https://paperswithcode.com/search?q=Building%20Trust%20in%20Artificial%20Intelligence%2C%20Machine%20Learning%2C%20and%20Robotics)
- Semantic Scholar: Semantic Scholar paper page (https://www.semanticscholar.org/paper/8662297398bfa04fbff3b473c961928bc01b3970)
- YouTube: YouTube explanations (https://www.youtube.com/results?search_query=Building%20Trust%20in%20Artificial%20Intelligence%2C%20Machine%20Learning%2C%20and%20Robotics+paper+explained)