Ethical AI & AI Quality by Design
summary
Volunteering research persuades standards bodies and British Computer Society to start an AI quality standard and publishes principles and an assessment framework on publicintelligence.org. Work combines software engineering methods, business process modelling and a service bus reference architecture to capture nonfunctional requirements like fairness, explainability and sustainability. Prototypes include a requirements-level simulator for conversational apps that models resources and latency — e.g. 100 concurrent chatbot users: 17s response time — and an online data ethics questionnaire for student projects.
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chapters (25)
- 0:00Introduction
- 0:46Ethical AI
- 5:01Challenges
- 9:04Requirements
- 11:16DevOps Principles
- 12:46Building Blocks of AI
- 14:26Machine Learning Methodology
- 16:11Ethical Principles
- 17:28AI Ethics
- 22:13Responsible AI
- 26:04Ethical AI Challenges
- 27:06Ethical AI Standards
- 27:38Public Intelligence
- 28:07Principles
- 29:31Ethics Quality
- 29:41Quality Metrics
- 30:16Conceptual Soundness
- 31:03Traditional Software System Metrics
- 31:37Software Engineering
- 33:00Software Development Methodology
- 33:27Requirements Engineering
- 36:19Nonfunctional Requirements
- 36:46Project Management
- 38:46Business Process Modeling
- 39:32Question Time
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