AI ETHICS TOOLKIT

PIONEERING ARTIFICIAL INTELLIGENCE IN NURSING

There are many complex ethical issues related to using artificial intelligence based models and tools in healthcare such as privacy and trust, transparency, accountability and more. The AI Nurses Network will be launching the world's first AI ethics toolkit for nurses here very soon!

AI Ethics Toolkit

Coming soon....

We have recently completed a large systematic review (220 studies) examining the ethical dimensions of artificial intelligence (AI) in nursing and midwifery practice (i.e., education, clinical practice/patient care and research). The pre-print manuscript is available online here.

Based on the results of these scientific studies we are building a practical online toolkit to help nurses understand the key ethical issues with using AI and some of the governance and other strategies that are needed to work with AI tools in professional practice. As soon as our AI ethics toolkit is ready we will post it here and share it on our social media!!

Theme 1: Preserving humanity

Care ethics in AI-mediated nursing and midwifery practice

1.1 Relational care under threat

1.2 Value alignment as ethical imperative

1.3 The authenticity dilemna

Theme 2: Beyond technical reliability

Safety as an ethical and relational imperative

2.1 Premature deployment risks

2.2 Misinformation as patient harm

2.3 Risk mitigation and navigation

Theme 3: Autonomy, authority and accountability

Governance challenges and solutions

3.1 Patient autonomy, rights and dignity

3.2 The accountability - authority - capability gap

3.3 Governance gaps and solutions

Theme 4: Beyond transparency

Privacy, disclosure and earning trust

4.1 Privacy threats and relational harm

4.2 Building trust requires more than transparency

4.3 Nurses and midwives' information governance roles

Theme 5: Justice in development and deployment

From bias to equitable implementation

5.1 Algorithmic bias as structural inequality

5.2 Systematic exclusion of nurses and midwives

5.3 Inequitable AI deployment concentrates risks

5.4 Equitable implementation

Theme 6: Workforce preparation and deployment challenges

From education to practice integration

6.1 Capacity gaps and training requirements

6.2 Critical thinking and ethical awareness

6.3 Academic integrity and competency

6.4 Implementation barriers