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AI Ethics for Oceans (Pt 1): Intro + Data Management
Rating: 5.0 out of 5(1 rating)
60 students

AI Ethics for Oceans (Pt 1): Intro + Data Management

Navigating AI ethics in oceans work
Created byCIOOS Atlantic
Last updated 6/2026
English
English [Auto],

What you'll learn

  • Understand the importance of ethical AI
  • Identify patterns of AI failure that learners should watch for
  • Recognize power imbalances in ocean AI development
  • Recognize real-world consequences of unethical AI in marine contexts
  • Understand why ocean environments present unique ethical challenges
  • Understand unique vulnerabilities of ocean-dependent communities
  • Appreciate why standard AI ethics frameworks may be insufficient for marine contexts
  • Learn a systematic approach to identifying all affected parties in ocean AI projects
  • Understand different types of stakes and impacts
  • Practice using stakeholder mapping frameworks
  • Understand competing models of data ownership in marine contexts
  • Appreciate complexity of data ownership in international waters
  • Recognize practical implications of data stewardship for ocean AI projects
  • Recognize how traditional Western research approaches may conflict with community values
  • Understand/learn FAIR, OCAP, and CARE principles, their application to marine data, and how they complement or are in conflict with each other
  • Recognize types of sensitive data in marine contexts
  • Understand privacy and security challenges unique to ocean environments
  • Learn strategies for protecting sensitive information while enabling research

Course content

2 sections • 6 lectures • 57m total length

  • 1.1 Introduction4:49

    Explore why ethics matter in Ocean AI. Examine how ethical issues arise and affect people and systems, and how data, bias, transparency, and governance shape responsible AI use.

  • 1.2 Why ocean AI ethics is complex19:46
  • 1.3 Stakeholder Mapping Exercise1:22

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: "Distorted Fish School" by Lone Thomasky & Bits&Bäume / 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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