Caring About Others
When you pick up litter in the park, you are helping people you have never met. When a crosswalk button is placed low enough for someone in a wheelchair, the person who designed it cared about others they might never know. Caring about people we have never met is one of the most important skills in the world — and it is one of the most important skills for AI too. The decisions people make when they build and use AI can affect thousands, or even millions, of people. Most of those people the builders will never meet. Today we practice thinking about others when we think about AI.
AI Choices Ripple Out
When a company builds an AI tool, their choices ripple outward to everyone who uses it. If they build fairly, millions of users benefit. If they build carelessly, millions of users might be hurt — even if the builders never intended any harm. Think about an AI used to decide who gets a loan from a bank. If the AI has been trained on biased data, it might recommend loans to some groups of people and deny them to others — not because of anything the person did, but because of unfair patterns in the data. That affects real families trying to buy homes or start businesses. The people who built that AI did not see those families. But their choice still reached them.
When we make choices about AI, we are making choices that affect people we may never meet. Caring about those people — imagining their lives, their needs, their situations — is part of being a responsible AI citizen.
You do not have to be an engineer to practice this kind of caring. You can practice it right now by imagining other people when you think about AI. Here is a way to do it. When you hear about a new AI tool, try asking: who benefits from this? Who might it hurt? Who did the builders probably have in mind? Who might they have forgotten about? This habit — imagining the people affected by a decision — is called thinking about stakeholders. A stakeholder is anyone who is affected by a decision. Good AI builders try to think about all their stakeholders, not just the easiest or most obvious ones.
Flashcards — click each card to reveal the answer
Here is a warm example of caring at work. A team building an AI reading helper noticed that it worked well for kids who could sit quietly at a desk. But some kids with certain disabilities learn better when they can move around. The AI was hard for them to use. One engineer on the team had a younger sibling with that disability. She spoke up. The team thought about it and redesigned the interface to work for kids who needed to interact differently. Because one person on the team cared about someone they knew — and brought that caring into their work — the tool got better for everyone.
One person who cares about overlooked people can change a tool that reaches millions. You do not have to be the boss or the engineer. You just have to speak up when you see someone being left out.
Match each stakeholder group to a need they might have that AI builders should think about.
Terms
Definitions
Drag terms onto their definitions, or click a term then click a definition to match.
What does 'stakeholder' mean in AI?
Why is it important for AI builders to think about people they have never met?
Stakeholder Imagination
- Pick an AI tool you know about — a voice assistant, a translation app, a reading helper, or anything else.
- Imagine five different people who might use it. Make them as different as possible: different ages, languages, abilities, and places.
- For each imagined person, write one sentence: how does this AI tool help them, or how might it let them down?
- Look at your five descriptions. Did the AI tool work well for all five? Who might be left out?
- If you were on the team that built this AI, what one change would you make to help the person who was most left out?