Ethical Considerations is one of the five components of AI literacy in the ALiF Standard. Every conforming implementation addresses all five, with emphasis that varies by professional role.
Key elements
- Ethical principles and frameworks
- Policy awareness and compliance
- Risk management
- Governance approaches
Example competencies
- Understands and applies ethical guidelines in AI use
- Adheres to institutional policies on AI
- Identifies and mitigates potential risks
- Contributes to ethical AI governance
How it relates to the other components
Ethical Considerations (ETH) as cross-cutting. Ethical reasoning is not confined to the ETH component. Every component has ethical dimensions: how data is collected (DAT), how tools are used (TEC), how outputs are assessed (EVA), and how implementations are designed (PRA). The dedicated ETH component provides the explicit frameworks and governance structures, but ethical awareness permeates the entire framework.
Sub-competencies (3)
ETH.1 Responsibility
The ability to use AI in ways that are transparent, accountable, and consistent with professional and ethical standards. This sub-competency encompasses understanding the ethical principles governing AI use, properly attributing AI contributions to work products, communicating openly about AI use to colleagues and stakeholders, and making ethical judgments about when and how to deploy AI tools.
Proposed in ALiF 2.0: Adds disclosing AI-generated or AI-altered media in professional communication, so that others can tell synthetic content from records of real events.
| Foundation (L1) | Intermediate (L2) | Advanced (L3) |
|---|---|---|
| Understands core ethical principles for AI use. Attributes AI contributions accurately. Adheres to basic guidelines for responsible AI use. Identifies straightforward ethical concerns. | Applies ethical frameworks to complex situations. Creates transparent documentation of AI use. Guides peers on responsible AI practices. Navigates ethical tensions when guidelines conflict. | Develops ethical guidance and policy for teams or organizations. Shapes institutional culture around responsible AI use. Creates decision frameworks that others use for ethical reasoning in novel situations. |
ETH.2 Compliance
The ability to operate within the institutional policies, regulatory frameworks, and professional guidelines that govern AI use. This sub-competency encompasses knowledge of relevant policies at organizational, professional, and governmental levels; the capacity to document AI use in ways that satisfy compliance requirements; and the ability to help establish or improve governance structures where they are lacking.
| Foundation (L1) | Intermediate (L2) | Advanced (L3) |
|---|---|---|
| Knows relevant institutional policies on AI use. Follows established documentation requirements. Adheres to professional guidelines. Identifies when policy guidance is unclear or missing. | Implements compliance procedures for AI use in team settings. Creates documentation systems satisfying governance requirements. Assists in developing or refining AI policies. Monitors compliance across defined workflows. | Develops compliance frameworks for organizations that balance accountability with innovation. Leads policy development initiatives that incorporate stakeholder input. Designs sustainable governance systems that adapt to evolving regulatory landscapes. |
ETH.3 Risk Management
The ability to identify, assess, and mitigate risks associated with AI use in professional contexts. This sub-competency encompasses recognizing potential harms (privacy violations, bias amplification, misinformation, dependency risks), evaluating the likelihood and severity of identified risks, and implementing safeguards and mitigation strategies.
Proposed in ALiF 2.0: Adds synthetic media and AI-mediated influence, and dependency risks to expertise: skills that erode, fail to develop or develop incorrectly through reliance on AI, and lost practice opportunities for others.
| Foundation (L1) | Intermediate (L2) | Advanced (L3) |
|---|---|---|
| Identifies basic risks associated with AI use (privacy, accuracy, dependency). Recognizes when AI use may cause harm. Follows established safeguards. Reports risk concerns appropriately. | Conducts structured risk assessments for AI implementations. Develops mitigation strategies for identified risks. Creates risk monitoring procedures. Assists in developing organizational risk management approaches. | Designs proactive risk identification systems that anticipate emerging threats. Leads organizational risk strategy for AI that integrates with broader institutional risk governance. Develops safeguards that evolve with changing AI capabilities. |
Definitions and level descriptors are quoted from ALiF Standard v1.0r1. The level descriptors are informative; role-specific descriptors are in the Competency Framework.