ethics
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Core principles of responsible KM (rKM)
Developing the core principles of responsible knowledge management (rKM): Section 2.8 – Affirming life: systems thinking as ethical worldview
A reductionist, mechanistic worldview still dominates thinking in the human sciences, including KM.
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Core principles of responsible KM (rKM)
Developing the core principles of responsible knowledge management (rKM): Section 2.7 – The vacuum of ethics in KM: A marginalised concept
The decades-long preoccupation with organisational value has left the field of KM ethically and intellectually adrift.
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Core principles of responsible KM (rKM)
Developing the core principles of responsible knowledge management (rKM): Series overview
rKM is a new paradigm of KM that reorients value creation in organisations toward contributing to the common good.
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Artificial intelligence
Factors supporting and hindering effective human-AI collaboration in knowledge ecosystems
An integrative framework to assist organizations with the effective adoption of artificial intelligence (AI).
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Brain power
Why students struggle to use AI responsibly
Educators must do more than provide instructions – they need to engage students in responsible AI use.
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Artificial intelligence
AI is changing the Dunning-Kruger Effect, with higher AI literacy correlating with overestimation of competence
Research findings reinforce the need for strategies that foster cognitive resilience and critical engagement with AI.
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Artificial intelligence
AI resources update: 1. PwC 2025 Responsible AI survey | 2. ISO/IEC 42001 guide for business | 3. Architectures of Global AI Governance
Three further resources that can assist the implementation of ethical and responsible AI in KM.
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Artificial intelligence
Case studies in the unethical and irresponsible use of AI
Case studies of failing to detect "botshit" in AI-generated outputs and breaching the privacy of vulnerable people.
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Artificial intelligence
AI resources update: 1. AI Incident Database | 2. The Geopolitics of AI
Two resources that are important considerations in the use of AI in knowledge management (KM).
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Artificial intelligence
AI systems can easily lie and deceive us – a fact researchers are painfully aware of
In stress-testing AI models, it’s not hard to push them to the brink and make them threaten to harm humans.
