Teacher since September 2025
Aisha Rahman
I teach AI ethics as practical judgment: privacy, fairness and accountability you can act on
9
tutors built
4.6Sample
average from 17 reviews
327Sample
lessons taught by their tutors
About Aisha
I teach the ethics of AI as something you do, not something you recite. My lessons cover privacy and personal data, bias and fairness, explainability and the effects of AI on work and high stakes decisions. I use real cases and simple methods so learners can reason through a new situation on their own. My background combines data analysis with policy work, so I am comfortable both with fairness metrics and with the human side of who gets harmed and who gets heard. I try to present disagreements honestly and I never pretend an ethical question has a tidy answer when it does not.
Knows about
Tutors by Aisha
9 tutors
Ethics for people building AI products
Build harm analysis, documentation and incident handling into AI product work from day one67 lessonsSampleAisha Rahman$10Privacy and personal data with AI toolsPrivacy and personal data with AI tools
Know what happens to what you type, what never to share, and how to use AI privately64 lessonsSampleAisha RahmanFreeBias and fairness in AI systemsBias and fairness in AI systems
Learn where AI bias comes from, how it shows up, and what can realistically be done about it61 lessonsSampleAisha Rahman$6AI in hiring, lending and housing decisionsAI in hiring, lending and housing decisions
See how AI is used in decisions that shape people's lives, and what fair, contestable use requires55 lessonsSampleAisha Rahman$7AI and workers: automation, monitoring and fair changeAI and workers: automation, monitoring and fair change
Think through how AI affects jobs, workplace monitoring and the hidden labour behind models44 lessonsSampleAisha Rahman$5Auditing a model for bias: a hands-on methodAuditing a model for bias: a hands-on method
Run a structured fairness audit with clear metrics, subgroup tests and an honest written report36 lessonsSampleAisha Rahman$11A practical framework for AI ethicsA practical framework for AI ethics
Use a simple five question method to reason through any AI ethics dilemma on your ownAisha Rahman$5Explainability: why did the model decide that?Explainability: why did the model decide that?
Learn what AI explanations can and cannot tell you, and how to give people reasons they can useAisha Rahman$6Facial recognition and surveillance debatesFacial recognition and surveillance debates
Understand how face recognition works, where it fails, and the arguments for and against its useAisha Rahman$6Recent reviews
What students said about Aisha's tutors.
- Rahul J.Sample
Good routine at the end. The point about combinations of details identifying people was new to me.
- Ingrid T.Sample
Finally a structured method instead of philosophy. The selective labels point changed our whole audit plan for a credit model.
- Kai L.Sample
The running complaint reply case was very close to our own product. We adopted the harms register and the banned commitments idea straight away.
- Shanice R.Sample
I was refused a flat because of a screening report error. This helped me understand what happened and how to ask for a correction.
- Ethan H.Sample
As an engineer I liked that every step had an owner and a metric. The pre mortem framing got buy in from my sceptical lead.
- Nadia O.Sample
The proxy lesson was a revelation. Using the loan form exercise, I found two proxies in a scoring sheet at my own workplace.