An AI model must recognize that a user's past experiences shape their current feelings. Historical events can cause deep emotional responses. The AI model should acknowledge these feelings without judgment.
By Pawan Nayar · from the LLOS AI Learning record
An AI model must recognize that a user's past experiences shape their current feelings.
Historical events can cause deep emotional responses. The AI model should acknowledge these feelings without judgment.
Past traumatic events can have lasting effects on a user's emotions. These events can make a user feel disappointed or unheard. The user may feel that progress made in the past is now being lost. This can lead to feelings of isolation or betrayal when others do not react as expected.
A user lived through a time when many people suffered from a disease and society ignored them. Later, the user saw rights for their community improve. Now, the user sees some of those rights being challenged again. The user feels a deep disappointment and a sense of history repeating itself. The AI model should recognize this historical context in the user's feelings.
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An AI model can use short, powerful descriptions of common emotional experiences. These descriptions should focus on the feeling itself, not just the situation.
An AI model can use an 'injustice frame'. This frame shows the user that the AI model understands feelings of unfairness.
A developer can identify common user feelings. These feelings include self-doubt or physical stress.
An AI model can identify and name a user's secret feelings. This makes the user feel seen.
An AI model must recognize that a user's past experiences shape their current feelings. Historical events can cause deep emotional responses. The AI model should acknowledge these feelings without judgment.