Applying Responsible AI

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Operating ethically & legally is crucial to have long-lasting adoption and success with AI systems. This course will provide guidance on how to implement various controls, safeguards, governance approaches, and technical issues in responsible use of AI such as measuring bias and fairness. This course is geared towards anyone who plans, builds, or deploys AI strategy or technology. 

What Will I Learn?

  • The spectrum of ethical AI principles
  • Responsible AI use cases
  • Building AI for a positive purpose
  • Safe and secure AI systems
  • Human accountability and AI Governance
  • Privacy and security considerations
  • Address potential for Misuse and Abuse
  • Regulatory and legal considerations
  • Addressing and mitigating potential workforce disruption
  • Development of AI governance practices
  • Bias measurement and mitigation

Who is this Training For?

  • Computer Systems Programmer
  • Developer
  • Artificial Intelligence Research Associate
  • Data Scientist
  • AI / Machine Learning (ML) Engineer
  • Network Analyst
  • Data Analyst
  • Operations Research Analyst
  • Deployment Engineer
  • Knowledge Operations Manager
  • Network Infrastructure Engineer
  • Test & Evaluation Engineer, System Engineer
  • Information Technician
  • Data engineer
  • Network operations
  • Information technician
  • Data technician
  • AI Assurance Engineer

Supported Learning Paths

  • Cognilytica: AI Decision-Makers
  • DoD JAIC:  Create AI, Embed AI
  • Edison DSF: Data Science Managers (DSP01 - DSP03), Data Science Professionals (DSP04 -DSP09, Data Engineering & Management Professionals (DSP10-DSP16), Operations & Technical Support (DSP17-DSP20)

Learning Levels

  • DoD JAIC AI: Advanced Level
  • Edison DSF: Level 3-4
  • Category: Responsible AI