EDUCATION & LEARNING · HIGHER EDUCATION · COURSE

Foundations of AI Ethics

A philosophy-grounded pathway for analyzing consequential AI decisions through competing ethical frameworks, justice and power, epistemic responsibility, human agency, objections, and revision.

02Evidence

Reason
Evidence
Reflect

Higher Education collection Responsible AI & Academic Integrity

Status: Reviewed faculty pathway

Version: 1.0.0

Estimated time: 165 minutes

Completion record: Created only after independent review approval.

Credential pathway: A reviewed completion may be separately authorized for a Logos Professional reviewed-completion credential. Enrollment or course completion alone does not guarantee issuance.

EVIDENCE MODEL

How the pathway turns learning into reviewable evidence

01Learn

02Apply

03Demonstrate

04Review

05Verify

Learning objectives

Distinguish ethical analysis from technical performance, legal compliance, and principle checklists.
Analyze an AI decision through consequentialist, duty- and rights-based, justice, virtue, care, and epistemic perspectives.
Identify how power, uncertainty, human agency, and responsibility shape the ethics of AI deployment.
Defend and revise a context-sensitive ethical judgment in response to a serious objection or affected-party perspective.

Learning sequence

Diagnostic reflection
Six philosophy-grounded lessons
Structured ethical analysis
AI ethical decision brief
Implementation reflection
Deterministic rubric suggestion
Independent human review

Required evidence

AI decision and affected stakeholders
Initial ethical judgment
Competing values, rights, duties, and interests
Multi-framework ethical analysis
Strongest objection or marginalized perspective
Revised ethical judgment
Human authority and accountability plan
Justice, accessibility, care, and power considerations
Evidence and conditions for reassessment

Certificate requirements

Acknowledge the course disclosure and complete the formative diagnostic.
Complete every reviewed lesson check in this published course version.
Submit the structured reasoning exercise, applied professional artifact, and implementation reflection.
Receive independent human review approval against the published rubric.
Receive separate administrator issuance of a Logos Professional Certificate of Completion.

The certificate verifies Logos Professional's reviewed-completion record only. It is not automatic institutional PD, CE, CEU, academic credit, licensure credit, or employer recognition.

What this certificate demonstrates

A named learner completed this published pathway, submitted authentic evidence, and received the required independent human review under the stated version and rubric.

Evidence base

Recommendation on the Ethics of Artificial Intelligence

UNESCO · UNESCO · 2021

Provides a global human-rights and human-dignity framework for AI ethics, including fairness, transparency, human oversight, privacy, sustainability, and accountability.

REVIEWED

Artificial Intelligence Risk Management Framework (AI RMF 1.0)

National Institute of Standards and Technology · NIST AI 100-1 · 1.0 (2023)

Connects trustworthy-AI characteristics to governance, risk identification, measurement, and management while preserving contextual human judgment.

REVIEWED

The Belmont Report

National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research · U.S. Department of Health and Human Services · 1979

Offers a durable applied-ethics model for respect for persons, beneficence, and justice that helps learners distinguish principles from their context-sensitive application.

REVIEWED