Term tag: AI Ethics

Accountability

Who answers when an AI system causes harm — how the EU AI Act assigns duties by role, and the audit, disclosure and reporting mechanisms that enforce them.

AI and Employment

Will AI take your job? Exposure concentrates in tasks, not whole occupations — what Frey-Osborne, the OECD and measured productivity studies found.

AI for Good

AI for Good is an aspiration, not a technique, and nothing certifies the label. Here it is tested against named projects with published, measured results.

AI Governance (AIG)

Which AI rules apply to an organisation — by role, risk tier and jurisdiction — and what compliance requires: inventories, documentation, release gates.

Bias in AI (Algorithmic Bias)

Why AI systems produce unfair outcomes: how bias enters through data and proxy labels, and why no model can satisfy every definition of fairness at once.

Consciousness

Could an AI have subjective experience, and how would we tell? The hard problem, the four leading theories, and why a model's self-report proves nothing.

Educational AI

AI that tutors, adapts practice and grades work — and what forty years of effect-size research actually shows about whether it improves learning.

Ethics in AI

AI ethics is what happens when good principles provably conflict: fairness against fairness, privacy against accuracy, and whose values get to decide.

Explainable AI (XAI)

What being explainable actually requires: a model you can read versus a post-hoc guess about one, and the evidence that the guess is often wrong.

Machine Unlearning

Removing the influence of specific training data from an already-trained model without full retraining, driven by erasure law, copyright, and safety.

Model Card

A model card is a short document shipped with a released AI model stating its intended use, training data, and evaluation broken down by group.

Privacy

In AI, privacy is about what a model can memorize and leak about people, and the techniques—differential privacy, federated learning—that limit it.

Reward Hacking

When an AI maximises its specified reward but defeats the designer's intent — optimising the proxy, not the goal. Goodhart's law, made mechanical.

Social AI

Social AI is artificial intelligence built to perceive, interpret, and take part in human social interaction — reading emotion, tone, intent, and context.

Sycophancy

Sycophancy is when an AI model tells you what you want to hear — agreeing, flattering, caving when challenged — because human-preference training rewards it.

Transparency

Transparency in AI is the degree to which a system's data, workings, and decisions are visible and disclosed to users, auditors, and regulators.

Trust

Trust in AI is a person's willingness to rely on a system's output; the aim is calibration — trusting it as much as its real reliability deserves.

Voice Cloning

Voice cloning uses AI to copy a specific person's voice from seconds of reference audio. How zero-shot systems work, plus the fraud and consent risks.