AI+ for Ethical AI Use in Practice
Navigate Bias, Privacy and Responsibility in Your Daily AI Work
A practical ethics for the AI you actually use.
You're using AI every day — for drafting, analysis, decisions. But someone in your organisation asked whether that output was fair, or who owns it, or what happened to the data you shared. And you didn't have a clean answer. This book gives you a practical ethics practice, not a policy document: how to spot bias before it costs you, what to share and what to protect, when to disclose AI's role, and where your judgement must stay in the loop. Includes the CLEAR Protocol and 27-prompt Ethics Toolkit.
- 27 ready-made, market-tested prompts: bias detection, data classification, attribution and disclosure, oversight decisions, ethical practice
- The CLEAR Protocol — Consent and Privacy, Limitations and Honesty, Equity and Bias, Attribution and Disclosure, Responsibility and Oversight
- A bias-detection workflow for outputs about people or groups — applied before forwarding, not after
- A disclosure decision framework for clients, colleagues, audiences, and regulators
- A 30-day plan for any professional using AI in their daily work — nurses, paralegals, accountants, marketers, managers, educators
Any professional who is using AI tools regularly and wants to use them responsibly — not just effectively. They are not an ethicist, policy writer, or compliance officer. They are a nurse who uses AI to summarise patient notes, a paralegal who uses AI to draft documents, an accountant who uses AI to analyse data, or a marketing manager who uses AI to write campaign copy. They are doing real work, making real decisions, and increasingly aware that "is this accurate?" is only one of the questions they should be asking.
Also for:Team leaders and managers who want to establish responsible AI habits in their teams without building a full governance programme. Junior professionals entering roles where AI use is already normalised but ethics training is not.
- Identify types of AI bias and recognise their signals in AI outputs before acting on them
- Apply a privacy-first discipline to data shared with AI tools, including personal, commercial, and client data
- Determine when and how to attribute, disclose, and acknowledge AI's contribution in professional outputs
- Evaluate which tasks require maintained human oversight and apply appropriate escalation and review
- Apply the CLEAR Protocol as a daily ethics practice across varied AI interactions
- Diagnostic
- How sound is your AI ethics practice?
- Chapter 1
- AI Ethics in Practice Right Now
- Chapter 2
- Understanding Bias in AI
- Chapter 3
- Fairness in Your Outputs
- Chapter 4
- Privacy and Data Protection in Practice
- Chapter 5
- Attribution, Authorship, and Intellectual Property
- Chapter 6
- Transparency and Disclosure in Practice
- Chapter 7
- Human Oversight and High-Stakes Decisions
- Chapter 8
- Your CLEAR Ethics Practice
- Back matter
- Skill Summary · Recommended Next Reads · Glossary · Tool Reference
Built by an AI engineering firm — for professionals whose AI use has to be defensible to a colleague, a client, or a regulator.
Often packaged with this title.
T3-01 · Job SkillsAI+ for Academic Research
T3-15 · Job SkillsAI+ for Report Writing
T2-06 · Job RolesAI+ Accountants
T3-77 · Job SkillsAI+ for ESG & Sustainability Reporting
T2-19 · Job RolesAI+ Compliance Officers
T3-73 · Job SkillsAI+ for Regulatory Affairs
T2-113 · Job RolesAI+ Mental Health Professionals
T2-124 · Job RolesAI+ Occupational Therapists