Design of Ethical AI Systems, built into the lifecycle.
A working course on ethical AI for the people designing the systems, not just the people writing about them. Covers the business case for ethical AI, design choices that shape ethical risk, the regulatory landscape (including the EU AI Act) and the established frameworks for putting responsible AI and trustworthy AI into research and product practice. A natural home for teams meeting the EU AI Act Article 4 AI literacy duty.
How to take this course
Commission it for your cohort.
ORBIT paid courses are delivered bespoke for groups: cohort size, dates, exercises and case studies are tailored before delivery. We do not sell individual seats. Tell us what you are planning and we will reply within one working day with a suggested fit and a fixed quote.
Have an access code?
If your organisation has already commissioned this course and given you an ORBIT access code, you can open your lessons straight away. No account, no sign-up - the code unlocks the courses chosen for you.
Lost your code? Email contact@orbit-rri.org.What the workshop delivers.
The course works through ethical AI as a design discipline: the choices that shape ethical risk across a system's lifecycle, the regulatory and legal landscape now coming into force for AI in the UK and EU, training-data risk and bias mitigation, and the recognised ethical AI frameworks researchers and developers can use as scaffolding.
Learning outcomes
- 01Articulate the business and research case for ethical AI in language stakeholders, funders and senior leaders understand.
- 02Incorporate ethical principles across the full lifecycle of an AI system, not just at deployment.
- 03Navigate the major regulatory frameworks shaping responsible AI in the UK, the EU and other jurisdictions.
- 04Curate datasets with diversity and representativeness in mind, and recognise the limits of bias mitigation in technical work.
- 05Apply established ethical AI frameworks to a real project, with a working understanding of when each one fits.
Who the course is for.
Built for academic AI research groups, for industry R and D teams and for mixed cohorts of researchers and developers. Particularly useful for CDTs working in AI, robotics, autonomous systems, data science and adjacent disciplines, plus the engagement leads inside research offices managing institutional AI strategy.
Format and pricing.
One day, in person, at your institution, up to fifteen participants. Tailored to your discipline before delivery. Bespoke pricing scoped to the cohort. Talk to us to start.
Common questions.
What is the difference between AI ethics and responsible AI?
AI ethics is the discipline that studies the moral, social and political questions raised by AI. Responsible AI is the practice of acting on that thinking inside research and product development. Our training spans both, with a clear bias toward practice.
Is this a course for AI researchers, or for product teams?
Both. We run the course for academic AI research groups, for industry R and D teams and for mixed cohorts. The frameworks are the same; the worked examples shift with the audience.
How does this course relate to the AREA framework?
AREA gives us the scaffolding for thinking about responsibility across the life of a project. The Ethical AI course applies that scaffolding to AI, robotics and big data specifically, and adds the technical and regulatory material those systems need.
Pair with.
Talk to us about your AI cohort.
Tell us the cohort, the topics you need covered and rough timing. We reply within one working day.