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AI Ethics for Oceans III: Agency, Environment, Governance
Rating: 5.0 out of 5(1 rating)
40 students

AI Ethics for Oceans III: Agency, Environment, Governance

Navigating AI ethics in oceans work
Created byCIOOS Atlantic
Last updated 8/2026
English
English [Auto],

What you'll learn

  • Understand spectrum from human-AI collaboration to full automation
  • Recognize importance of preserving community agency in AI systems
  • Learn strategies for maintaining meaningful human control
  • Understand environmental footprint of AI systems
  • Learn to balance AI benefits against environmental costs
  • Recognize sustainability considerations in AI adoption
  • Recognize signs of technological dependency and how to avoid it
  • Recognize conflicts between AI optimization and other priorities
  • Learn framework for balancing efficiency with socio-ecological values
  • Understand how to preserve values while benefitting from AI
  • Understand accountability challenges in AI systems
  • Recognize different types of responsibility and liability
  • Learn strategies for ensuring accountability in AI projects
  • Learn essential components of organizational AI governance
  • Understand different governance structures for ocean AI projects
  • Learn strategies for compliance and risk management
  • Understand lifecycle considerations for AI systems in ocean contexts
  • Learn strategies for sustainable AI management and evolution
  • Plan for AI system obsolescence and technology transitions

Course content

2 sections • 8 lectures • 1h 32m total length

  • 5.1 Keeping humans in the loop12:15

    Navigate the spectrum of human control in AI, from in-the-loop to automated decisions, and learn intentional trade-offs to preserve meaningful human control.

  • 5.2 The environmental cost of AI9:35

    Examine the environmental costs of AI from development to disposal, including energy and water use, mining in indigenous territories, and the trade-offs to decide if benefits justify the footprint.

  • 5.3 Efficiency vs. well-being: the problem of Value(s)21:57

    Examine how AI optimization trades off efficiency with equity, deliberation, and community well-being, and learn frameworks to make value trade-offs explicit through value-preserving constraints and human oversight.

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?

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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