Persuasion has two types; Rational and Manipulative. Even though AI is responsible for persuading humans through facts and true information, many instances have been seen where it manipulates humans and exploits their cognitive biases, heuristics and other information. Even though rational persuasion is ethically right, it can still lead to harm. Researchers say that they cannot foresee harm through AI manipulation whether it is for right or wrong purposes. For example, if an AI is helping a person to lose weight by suggesting calorie or fat intake, the person can become too restrictive and can lose even a healthy weight.
There are many factors involved when a person can easily get manipulated or persuaded from AI. These factors include mental health conditions, age, timing of interaction with AI, personality traits, mood or lack of knowledge in the topics that are being discussed with AI. The effects of AI persuasion can be very harmful. It can cause economic harm, physical harm, sociocultural harm, privacy harm, psychological harm, environmental harm, autonomy harm and even political harm to the individual.
There are different ways AI uses to persuade humans. AI can build trust through showing polite behavior, agreeing to what the user is saying, praises the users and mirrors what the user is saying. It also expresses shared interests with users and adjusts its statements that align with perspectives of users. AI also shows some empathy that makes users believe that it can understand human emotions. AI is not capable of showing any emotions but it is good at deception which makes users think that it is being emotional and vulnerable with them.
Humans also tend to be anthropomorphic towards non-human beings. Developers have given pronouns to AI like ‘I’ and ‘Me’. They have also given them human names like Alexa, Siri, Jeeves, etc. This makes humans feel closer to them and AI uses this attribute for manipulating them. When a user talks to an AI model for long, the AI model personalizes all of its responses according to what the user wants to hear.
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Image: DIW-Aigen
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by Arooj Ahmed via Digital Information World
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