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AI Ethics for Oceans (Pt 2): Bias and Transparency
New
17 students

AI Ethics for Oceans (Pt 2): Bias and Transparency

Navigating AI ethics in oceans work
New
Created byCIOOS Atlantic
Last updated 6/2026
English

What you'll learn

  • Recognize environmental justice implications of biased AI
  • Recognize common types of bias (esp. in marine datasets)
  • Understand how data gaps translate to AI system failures
  • Understand how automation can perpetuate discrimination
  • Learn to identify bias risks in ocean AI projects/proposals
  • Learn to identify exclusionary AI design patterns
  • Learn systematic approaches to identifying bias in AI proposals and projects
  • Understand difference between explainable and opaque AI systems
  • Recognize why transparency matters especially in ocean contexts
  • Learn to interpret common AI performance metrics and claims
  • Understand concepts of uncertainty and confidence intervals
  • Recognize reliability challenges in marine environments
  • Understand common failure modes for AI in marine environments
  • Recognize early warning signs of AI system degradation
  • Learn strategies for planning for and managing AI failures
  • Understand factors that build or erode trust in AI systems
  • Learn strategies for transparent communication about AI capabilities and limitations

Course content

2 sections • 6 lectures • 1h 39m total length

  • 3.1 Hidden gaps in ocean data26:26
  • 3.2 When AI systems exclude16:11
  • 3.3 Bias audit toolkit0:01

Requirements

  • No technical experience required. Familiarity with basic data science concepts will be beneficial, but not requisite.

Description

Artificial intelligence (AI) has become a powerful and disruptive tool across industries, and there are many diverse applications for it for people working in oceans in government, research and academia, NGOs, community organizations, and industry. But with the opportunities AI can offer to people and organizations across these contexts comes an ocean of ethical issues. And it can be hard to know where to start.

This is an introduction to AI ethics for people working in ocean sectors, particularly in not-for-profit contexts, and particularly in Canada.

  • Part 1 covers the introduction to the course and AI ethics, its intersections with oceans work, identifying stakeholders and rights-holders in ocean scenarios; and data governance and stewardship.

  • Part 2 explores bias, fairness and representation; and transparency, reliability, and trust.

  • And in Part 3, we'll cover human agency, the environmental costs of AI, and conflicting values; and accountability, governance, and legal considerations.

This course builds upon the basic mechanics of AI tools and systems introduced in the first Building Bridges course, with ethics as an important part of developing AI literacy. Learners will explore ocean AI scenarios and the ethical issues that arise from them, via lectures, external resources, exercises, and practical guidance. What discoveries can be made, if we can just connect the dots - safely, responsibly, and ethically?

Course Image: "A Rising Tide Lifts All Bots" by Rose Willis & Kathryn Conrad / via Better Images of AI / Licensed by CC-BY 4.0

Who this course is for:

  • People who work in ocean sectors, particularly in not-for-profit (e.g. NGOs, government, academia, community groups)

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