Instruction

This course asks you to make art that explains artificial intelligence and medicine. That is hard, because the most important parts of both are invisible: a model’s statistics, a patient’s blood pressure, the flow of data through a hospital. Designers have faced this problem for a long time, and they have left us methods.

Florence Nightingale (1858). Nightingale is remembered as a nurse, but she was also a statistician. After the Crimean War she published polar-area diagrams showing, month by month, how many British soldiers died of wounds and how many died of preventable diseases in the army hospitals. Each month is a wedge; the area of each colored segment shows the number of deaths. The design decision was the argument: the disease segments are so much larger than the wound segments that a reader sees at once that sanitation, not battle, was the main killer. She was designing to change policy.

Charles Joseph Minard (1869). Minard’s map of Napoleon’s 1812 campaign into Russia draws the army as a band whose width is the number of soldiers. The band narrows as it moves toward Moscow and shrinks further on the retreat, with a temperature line beneath it. One image carries size, place, direction, time and temperature.

Otto Neurath and Isotype (1920s-1930s). Working in Vienna with the designer Gerd Arntz and with Marie Neurath, Neurath built a system of simple, repeatable pictograms in which one symbol always stands for a fixed quantity. Instead of one big figure for a big number, you see more figures. The rule makes comparisons honest and readable across languages.

Three moves to borrow. First, encoding: each visual variable (length, area, color, position) stands for one piece of data, consistently. Second, hierarchy: the most important comparison is the most visible thing on the page. Third, sequence: the reader’s eye is led through the explanation in order.

What do we mean by AI? You will explain AI to others, so you need precise words. Narrow AI performs a specific task, such as flagging a possible diabetic eye disease in a retinal photograph, transcribing speech or recommending a video. Every AI system in use today, in medicine or anywhere else, is narrow. Artificial general intelligence (AGI) is a hypothetical system that could learn and perform the wide range of intellectual tasks a person can. Researchers disagree sharply about whether and when it could be built. Superintelligence is a further hypothetical: a system far beyond human ability in nearly every domain, discussed by philosophers such as Nick Bostrom. When a headline says a product is “thinking”, ask which of these it means. The honest answer is almost always a narrow system doing one task well under particular conditions.

Why this matters for design. Images of glowing brains and humanoid robots suggest AGI when the product is a narrow classifier. Nightingale persuaded by showing the data honestly. Your first responsibility as a designer of AI media is the same: make the reader see what the system actually does.

Formative check

Work through these before moving on. They are not graded — they tell you, and your teacher, whether the standard below has landed yet.