Artificial Intelligence Resources
The videos below cover the AI topics "Introduction to AI," "Responsible AI," "AI and the Workforce," and "AI Engineering."
Introduction to AI
AI for Everyone
AI for Everyone is a free course created by Andrew Ng introducing concepts of AI for non-engineers. "AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone-- especially your non-technical colleagues--to take."
Time required: 12 hours
Responsible AI
Responsible AI Guidelines: Operationalizing DoD’s Ethical Principles for AI
Defense Innovation Unit's RAI Guidelines aim to provide a clear, efficient process of inquiry for personnel involved in AI system development to achieve the following goals:
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ensure that the DoD's Ethical Principles for AI are integrated into the planning, development, and deployment phases of the technical lifecycle
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effectively examine, test, and validate that all programs and prototypes align with DoD's Ethical Principles for AI
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leverage a process that is reliable, replicable, and scalable across a variety of programs
Time required: varies
Artificial Intelligence Ethics Framework for the Intelligence Community
This is an ethics guide for United States Intelligence Community personnel on how to procure, design, build, use, protect, consume, and manage AI and related data. Answering these questions, in conjunction with your agency-specific procedures and practices, promotes ethical design of AI consistent with the Principles of AI Ethics for the Intelligence Community.
Time required: 15 minutes
Download the Artificial Intelligence Ethics Framework for the Intelligence Community
Deloitte’s Trustworthy AI Framework: Bridging the Ethics Gap Surrounding AI
This framework introduces six dimensions for organizations to consider when designing, developing, deploying and operating AI systems. The framework helps manage common risks and challenges related to AI ethics and governance.
Time required: varies
Designing Ethical AI Experiences: Checklist and Agreement
This document can be used to guide the development of accountable, de-risked, respectful, secure, honest, and usable artificial intelligence (AI) systems with a diverse team aligned on shared ethics.
Time required: varies
AI and the Workforce
5 Ways to Start Growing an AI Engineering Workforce
This blog post discusses growth in the field of artificial intelligence (AI) and how organizations can hire and train staff to take advantage of the opportunities afforded by AI and machine learning—and the critical need for an AI engineering discipline to grow the AI workforce.
Time required: 10 minutes
AI Engineering
Human-Centered AI
This white paper discusses Human-Centered AI: systems that are designed to work with, and for, people. As the desire to use AI systems grows, human-centered engineering principles are critical to guide system development toward effective implementation and minimize unintended consequences.
Time required: 15 minutes
Robust & Secure AI
This white paper discusses Robust and Secure AI systems: AI systems that reliably operate at expected levels of performance, even when faced with uncertainty and in the presence of danger or threat. These systems have built-in structures, mechanisms, or mitigations to prevent, avoid, or provide resilience to dangers from a particular threat model.
Time required: 15 minutes
Scalable AI
This white paper discusses Scalable AI: the ability of AI algorithms, data, models, and infrastructure to operate at the size, speed, and complexity required for the mission. Scalability is a critical concept in many engineering disciplines and is crucial to realizing operational AI capabilities.