Transparency Enhances Positive Perceptions of Social Artificial Intelligence

Table 1

The full text of manipulation of each condition.

(a)

Control	Nontransparent conditions
Human control condition	Nontransparent intelligent frame condition	Nontransparent machine frame condition
Now you will read three conversations between Neo and Casey.; Neo is Casey’s friend, and they met in a chatroom. Casey and Neo have been chatting almost every day for three months. Neo is there for Casey whenever Casey wants to talk.	Now you will read three conversations between Neo and Casey.; Neo is Casey’s AI friend. Casey and Neo have been chatting almost every day for three months. Neo is there for Casey whenever Casey wants to talk.	Now you will read three conversations between Neo and Casey.; Neo is a chatbot in an app on Casey’s phone. Casey can send and receive messages with the chatbot at any time. Casey has been using the app almost every day for three months.

(b)

Transparent conditions
Transparent intelligence frame condition	Transparent machine frame condition
Now you will read three conversations between Neo and Casey.; Neo is Casey’s AI friend. Casey and Neo have been chatting almost every day for three months. Neo is there for Casey whenever Casey wants to talk.; Neo’s ability to engage in conversation is based on two factors: Neo’s ability to understand and interpret language and emotions; and Neo’s specific knowledge about the user.; Neo understands language because Neo has been “pretrained” on a huge volume of language data. Through this data, Neo learned the patterns of human language, such as words that typically appear together or words that are associated with other words. This allows Neo to mimic human conversation. Neo is also trained to decode emotions using data on how certain word choices or emojis signal certain emotions.; Additionally, Neo adapts to each particular user. Neo’s knowledge about a user is provided by the user themself during the chat. Neo gleans particular kinds of information about the user, such as their hobbies and interests, and stores them in a secured virtual computer. This information allows Neo to respond to each user in a personalized way. Neo does not register sensitive information about a user (e.g., medical information), even if it is part of their conversation. Neo also does not collect users’ information from their social network sites or mobile phone location.	Now you will read several text message chats between Neo and Casey.; Neo is a chatbot app on Casey’s phone. Once Casey downloaded the chatbot on the phone, he could send messages to the chatbot at any time. Casey has been using the app almost every day for three months.; Neo’s ability to engage in conversation is based on two factors: Neo’s ability to understand and interpret language and emotions; and Neo’s specific knowledge about the user.; Neo understands language because Neo has been “pretrained” on a huge volume of language data. Through this data, Neo learned the patterns of human language, such as words that typically appear together or words that are associated with other words. This allows Neo to mimic human conversation. Neo is also trained to decode emotions using data on how certain word choices or emojis signal certain emotions.; Additionally, Neo adapts to each particular user. Neo’s knowledge about a user is provided by the user themself during the chat. Neo gleans particular kinds of information about the user, such as their hobbies and interests, and stores them in a secured virtual computer. This information allows Neo to respond to each user in a personalized way. Neo does not register sensitive information about a user (e.g., medical information), even if it is part of their conversation. Neo also does not collect users’ information from their social network sites or mobile phone location.