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Responsible Use of AI

Responsible Use of AI in Multimodal Context

Attribution

Original work: "Educators' guide to multimodal learning and Generative AI" — Tünde Varga-Atkins, Samuel Saunders, et al. (2024/25) — CC BY-NC 4.0
Adapted for UK Nursing Education by: Lincoln Gombedza, RN (LD)
Last Updated: December 2025

Despite the way GenAI is often marketed as efficient, trustworthy, innovative and invaluable to boosting users' productivity, integrating GenAI into multimodal learning brings substantial pedagogical, social and ethical challenges.

The Reality Check​

The responsible use of multimodal GenAI in nursing education requires a careful balance of:

  • Ethical considerations
  • Pedagogical effectiveness
  • Legal compliance
  • Practical sustainability

Key Concerns:​

  1. Accuracy — AI's outputs can contain errors or hallucinations
  2. Bias — Reflects entrenched social biases in training data
  3. Over-reliance — May weaken student voice or critical thinking
  4. Uncertainty — Educators and students feel unsure about effective, ethical use
  5. Policy ambiguity — Institutional policies may be vague or unclear
For Nursing Education

These concerns are amplified in nursing where accuracy and patient safety are paramount. A hallucinated medication dose or incorrect clinical procedure could have serious consequences if students don't verify information against authoritative sources.

NMC Regulatory Updates​

December 2025 Update

The Nursing and Midwifery Council (NMC) is actively reviewing its Code and revalidation guidance to include clearer standards on the safe and appropriate use of AI in nursing practice.

Timeline:

  • 2025-2026: Corporate plan development and stakeholder consultation
  • Q3-Q4 2026: Public consultation on proposed AI standards
  • October 2027: Publication of modernised Code with AI guidance

Current Status: Digital and technological literacy is already a foundational requirement in NMC's Standards for pre-registration nursing programmes. Students must demonstrate these capabilities to meet programme outcomes.

What This Means: While formal AI-specific standards are forthcoming, nursing educators should continue developing students' critical AI literacy now. This toolkit aligns with the NMC's emphasis on safe, effective, and ethical practice.

Four Key Cost Areas​

Beckingham and Hartley (2025a) suggest four areas to consider when looking at the cost of using GenAI:

1. Cost to the Individual​

  • Accountability: Students must take responsibility for AI-generated work. Academic integrity and professional honesty are paramount.
  • Privacy: Sharing patient or personal data with AI models poses significant risks. Identifying details must never be uploaded.
  • Cognitive Load: Over-reliance can lead to "skill atrophy" where critical thinking and basic competencies weaken over time.
  • Emotional Impact: Anxiety about "keeping up" and imposter syndrome ("did I write this or did the AI?") are growing concerns.

Read more about individual costs →

2. Cost to the Environment​

  • Energy Consumption: Generative AI models consume vast amounts of electricity for both training and daily queries (far more than standard web searches).
  • Carbon Footprint: Data centers contribute significantly to global emissions. Nursing's commitment to public health includes environmental stewardship.
  • E-Waste: The demand for powerful hardware accelerates device obsolescence, adding to the toxic e-waste stream.

Read more about environmental costs →

3. Cost to Knowledge​

  • The "Google Effect": We tend to remember where to find information rather than the information itself. In clinical practice, immediate internal knowledge is often required.
  • Learning Paradox: Efficiency isn't always effective. The "struggle" of learning builds neural pathways; AI shortcuts can bypass this essential cognitive effort.
  • Epistemic Trust: A shift from trusting peer-reviewed research to trusting opaque algorithmic outputs can erode evidence-based practice.

Read more about knowledge costs →

4. Cost to Future Jobs​

  • Displacement vs. Transformation: While nursing involves irreplaceable human connection, administrative and diagnostic tasks will shift.
  • New Competencies: "AI Literacy" is becoming a core skill alongside clinical competence.
  • Human Premium: Skills that AI cannot replicate—empathy, complex ethical judgment, and physical care—will become even more valuable.

Read more about future employment implications →

Beckingham and Hartley (2025a) Four Key Cost Areas

Let's explore each in depth:

Next Steps​

To understand these costs and how to mitigate them, read the following pages:

Then explore: