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Ethical and Responsible AI Use
Role Play
57 students
Ethical and Responsible AI Use
Master AI fairness, bias, privacy, transparency, and responsible use policies for the modern workplace.
Created byFortivance Academy
Last updated 3/2026
English
What you'll learn
- Identify AI bias in workplace tools and take practical steps to reduce unfair or discriminatory outcomes across hiring, healthcare, and financial decisions.
- Apply responsible AI principles — fairness, transparency, accountability, and privacy — to your daily use of AI tools at work.
- Protect sensitive data and intellectual property when using generative AI, and know exactly what you should never share with consumer AI tools.
- Recognise automation bias and over-reliance on AI, and confidently decide when to trust, question, or override an AI recommendation.
- Understand key AI regulations and frameworks — including the EU AI Act and NIST AI RMF — and how they translate into your organisation's AI policies.
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Course content
11 sections • 23 lectures • 1h 37m total length
Requirements
- No technical background required — the course is designed for all employees, managers, and leaders regardless of their role or industry.
- A basic familiarity with everyday workplace tools (email, internet, productivity software) is all you need to get started.
Description
This course contains the use of artificial intelligence.
AI is transforming how we work — but are we using it responsibly? From biased hiring algorithms to privacy violations and opaque decision-making, the risks of unchecked AI use are real and growing. This course gives you a practical, jargon-free foundation in ethical AI — so you can use AI tools confidently, fairly, and in line with your organisation's expectations.
Whether you work in HR, legal, compliance, operations, finance, marketing, or any other function, this course explains AI ethics in plain language and connects every concept to situations you're likely to encounter on the job.
What This Course Covers
What AI is, how it works, and how it's already influencing decisions in your workplace and daily life
The core pillars of responsible AI — fairness, transparency, accountability, privacy, and safety
How to identify and respond to AI bias in tools used for hiring, healthcare, financial services, and more
Global AI frameworks including the EU AI Act and NIST AI RMF — and what they mean for your role
How to apply your organisation's AI use policies and avoid the consequences of non-compliance
The "black box" problem — why AI decisions are hard to explain and when human review is essential
Do's and don'ts of using AI tools at work, including how to avoid automation bias and over-reliance
What data you should never enter into consumer AI tools — and how to protect sensitive information
Intellectual property and copyright risks when using generative AI outputs
Privacy by design, data minimisation, and how to report privacy incidents involving AI
Who Will Benefit
Employees and managers in any industry beginning to use AI tools in their daily work
HR, legal, compliance, and operations professionals managing AI-related risk and policy
Business leaders who need a non-technical but informed perspective on responsible AI governance
No technical background is required. This course is built for professionals across all functions and seniority levels — not just IT or data teams.
By the end of this course, you will have a clear understanding of your responsibilities when using AI, the ability to spot and flag ethical risks, and the confidence to contribute to a responsible AI culture in your organisation — wherever your role sits.
Who this course is for:
- Employees, managers, and team leads in any industry who use — or are expected to use — AI tools as part of their day-to-day work
- HR, legal, compliance, and operations professionals who need to understand AI risks, bias, and data privacy obligations within their organisation.
- Business leaders and decision-makers seeking a practical, non-technical grounding in responsible AI to support informed governance and policy decisions.