IB Digital Society Key Definitions

Honesty and fairness in learning and research, including doing your own work and giving credit for others' ideas. Generative AI strains it, because tools can produce work for a student and reliable detection of AI writing has not proven possible.

The design of digital systems so that people with disabilities can use them, through features like screen readers, captions, and alternative ways to input. Well-designed systems widen inclusion, while poorly designed ones create new barriers.

A component that turns a system's decisions into physical action, such as a motor, wheel, or robotic gripper that moves or manipulates the world.

An approach where software adjusts the content, pace, or difficulty for each learner based on how they are performing, rather than giving everyone the same fixed path. It aims to give more practice where a student struggles and more challenge where they are strong.

Making a physical object by building it up layer by layer from a digital design, allowing goods to be produced on demand close to where they are needed.

The processes of creating goods through agriculture and spreading them to relevant destinations and communities.

The practice of cultivating land and raising animals for food, fiber, and other products.

A chatbot, built on AI, designed to act as a friend, confidant, or romantic partner that remembers a user and is always available. It can offer comfort and reduce loneliness, but only simulates care and can foster dependence or expose vulnerable users to harm.

The laws, rules, standards, and oversight that guide how AI is developed and used. Because it varies widely between countries and is often slower than the technology, governance of AI is uneven and incomplete.

A period when interest and funding in artificial intelligence collapse after inflated promises fail to materialise. AI has gone through several such winters followed by renewed booms.

A finite sequence of clear, unambiguous steps that takes an input and follows a set procedure to produce an output or solve a problem.

The principle that the people and organisations who build and deploy an algorithm are answerable for its effects.

Systematic, unfair outcomes produced by a computer system, often because the data it learned from under-represents some groups or encodes past inequality. In healthcare it can mean a tool works well for some patients and poorly for others.

A systematic error in an algorithm that produces unfair outcomes, often by favouring one group over another.

The use of software and algorithms, rather than human managers, to assign tasks, monitor performance, and make decisions about workers, common on gig and platform work.

Building a picture of a person from their online behaviour, then sorting them into groups to target content and ads. It can infer sensitive traits such as age, ethnicity, or sexuality that were never disclosed, raising concerns about consent, privacy, and discrimination.

A system that represents information as a continuous physical quantity that can take any value, such as a sound wave, a dial, or a mercury thermometer.

The tendency to attribute human traits, feelings, or intentions to a machine. It can make robots easier to interact with, but can also mislead people about what a machine really understands.

A hypothetical AI that could understand, learn, and apply knowledge across any task as flexibly as a human. Also called strong or full AI, it does not yet exist.

A field of computer science dedicated to building systems that can replicate human intelligence and answer complex queries.

The basic unit of an artificial neural network, loosely modelled on a brain cell. It takes in numbers, combines them using weights, and passes on a signal if the combined value is strong enough.

The idea that human attention is a scarce, valuable resource that platforms compete to capture and sell to advertisers, shaping media to be as engaging and hard to put down as possible.

Technology that overlays digital content onto a view of the real world, through a phone screen or glasses, adding to what you see rather than replacing it.

The use of software, often AI, to make or heavily shape decisions about people, such as allocating benefits or flagging fraud, with little or no human involvement. It is fast and consistent but can encode bias and remove the chance to explain or appeal a decision.