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Responsible Use

Cost to the Individual

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)

When using GenAI in nursing education, there are significant personal costs and responsibilities that both educators and students must consider.

Personal Accountability​

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For Students

Academic Integrity

  • Using AI in ways your university's assessment policy doesn't allow, or without the acknowledgement it requires, can be academic misconduct. Policies differ, so check the rules for each assessment
  • The NMC Code asks you to "act with honesty and integrity at all times" (standard 20.2), and this extends to academic work
  • Using AI to complete assessments without disclosure undermines professional development

Clinical Competence

  • Over-reliance on AI for clinical reasoning can weaken critical thinking skills
  • Students must develop independent clinical judgment for patient safety
  • AI should supplement, not replace, clinical learning experiences

Professional Identity

  • Nursing requires empathy, compassion, and human connection
  • Excessive AI use may diminish development of these essential qualities
  • Students need authentic experiences to develop professional values
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For Educators

Pedagogical Responsibility

  • Educators must model responsible AI use
  • Clear guidance needed on when and how AI should be used
  • Responsibility to teach AI literacy alongside clinical skills

Assessment Design

  • Need to create AI-resilient assessments that measure authentic competence
  • Responsibility to ensure assessments align with NMC standards
  • Must balance innovation with academic rigor

Privacy and Data Protection​

Patient Confidentiality

Never input patient-identifiable information into AI tools unless your organisation has approved that specific tool for that purpose. For teaching, use fictional or synthetic cases. Removing names and dates usually only pseudonymises information, and pseudonymised data is still personal data under UK GDPR and the Data Protection Act 2018 (ICO anonymisation guidance).

🔒 Personal Information

Be cautious with personal student data. Comply with UK GDPR and your university's data protection policies. Rare conditions, unusual events, places and dates can identify someone even without a name, so build scenarios from scratch rather than editing real ones.

👣 Digital Footprint

On many consumer plans, conversations are stored and may be used to train models unless you change the setting. Work and education accounts (for example Microsoft 365 Copilot with enterprise data protection) generally don't train on your data. Use the tools your organisation has approved, check the privacy settings of anything else, and keep professional standards in every conversation.

Cognitive Costs​

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Critical Thinking

Skill Atrophy

Over-reliance on AI can weaken problem-solving and clinical reasoning. In a survey of 319 knowledge workers, higher confidence in GenAI was linked to less critical thinking (Lee et al., 2025); a study of 666 people found heavier AI use associated with lower critical-thinking scores, mediated by cognitive offloading (Gerlich, 2025). Both are correlational: they show a link, not that AI causes the decline.

Learning Depth

AI-generated summaries may reduce deep engagement, leading to surface-level learning that doesn't support expertise. An MIT study of 54 people writing essays found weaker brain connectivity and poorer recall of their own work among ChatGPT users (Kosmyna et al., 2025); it is a small preprint and its methods have been questioned, so treat it as a warning sign rather than proof.

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Metacognition

Self-Awareness

Students must recognise when they rely too heavily on AI and understand their own learning processes, strengths, and areas for growth.

Time, Effort & Finance​

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The Efficiency Paradox

Short-term vs. Long-term: AI may save time initially but can create dependency. Quick answers don't build lasting knowledge.

Skill Investment: Learning to use AI effectively (prompt engineering) requires significant time and practice.

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Financial Costs

Premium Tools: The most capable models usually need a subscription of roughly £18 to £20 a month, which creates equity issues. Institution-provided tools (such as Microsoft 365 Copilot for NHS staff) and student offers can narrow the gap; see Institutional Considerations.

Hidden Costs: Data usage, potential hardware upgrades, and professional training expenses.

Emotional Considerations​

Addressing Anxiety

Students and educators may face anxiety about AI use, fear of plagiarism accusations, or "imposter syndrome" regarding AI-assisted work. Open dialogue and clear guidelines are key to mitigation.

Mitigation Strategies​

For Students

  1. Set Boundaries: Use AI as a supplement, not a replacement. Maintain regular practice without AI.
  2. Practice Transparency: Always disclose AI use and keep records of your process.
  3. Develop Self-Awareness: Regularly assess your understanding without AI.

For Educators

  1. Provide Clear Guidelines: specific policies on acceptable AI use.
  2. Model Responsible Use: Demonstrate ethical AI integration.
  3. Support Student Development: Teach AI literacy and critical evaluation.

Reflection Questions​

🤔 Evaluate Your AI Use

  • Accountability: Can you explain and justify every instance of AI use in your work?
  • Learning: Is AI enhancing or replacing your learning process?
  • Competence: Are you developing the clinical skills needed for safe practice?
  • Integrity: Would you be comfortable disclosing your AI use to patients, mentors, or examiners?
  • Balance: Are you maintaining skills that don't rely on AI?

Next: Explore Cost to the Environment to understand the sustainability implications of AI use.