A study demonstrates people can be conditioned to think a certain way about the motivations of an Artificial intelligence (AI) chatbot, which affects how they interact with the chatbot.

1. Is AI a subjective concept?
A study demonstrates people can be conditioned to think a certain way about the
motivations of an Artificial intelligence (AI) chatbot, which affects how they
interact with the chatbot.
From Adam Zewe of MIT News
According to a new study, a person’s prior opinions about an AI agent, such as a
chatbot, have a big impact on their interactions with that agent and how they judge
its reliability, empathy, and efficiency.
In spite of the fact that users were conversing with the same conversational AI
agent for mental health support, researchers from MIT and Arizona State
University discovered that priming users affected how they interacted with the
chatbot. They were told whether the agent was sympathetic, neutral, or
manipulative.
The majority of people who were informed that the AI agent was caring did so, and
they gave it higher performance ratings than those who thought it was
manipulative. Less than 50% of users who were informed that the agent had
manipulative intentions believed the chatbot was genuinely evil, showing that

2. people may attempt to “see the good” in Artificial intelligence in the same way
they do in their fellow humans.
The study showed a feedback loop between users’ mental models of an AI agent,
or how they perceive that agent, and their replies. If the user thought the Artificial
intelligence was sympathetic, the tone of their talks with it tended to become more
positive over time, but the converse was true for those who thought it was
malicious.
What is AI? Artificial Intelligence Explained
“From this study, we see that to some extent, the AI is the AI of the beholder,”
explains Pat Pataranutaporn, a graduate student in the MIT Media Lab’s Fluid
Interfaces group and co-author of a paper presenting this study. “When we explain
what an AI agent is to users, it not only alters their mental model but also their
behavior. Additionally, because the Artificial intelligence reacts to the user, it also
changes as the user alters their behavior.
Along with senior author Pattie Maes, a professor of media technology and the
director of the Fluid Interfaces group at MIT, Pataranutaporn is joined by co-lead
author and fellow MIT graduate student Ruby Liu, Ed Finn, an associate professor
in the Center for Science and Imagination at Arizona State University, and Ruby
Liu.
Since the media and popular culture have such a big impact on our mental models,
the study, which was published today in Nature Machine Intelligence, emphasises
the significance of researching how AI is portrayed to society. The same kinds of
priming remarks utilised in this study may be employed to mislead humans about
an AI’s intentions or capabilities, the scientists warn.
“A lot of people believe that the success of AI is solely an engineering challenge,
but this is incorrect. The success of these systems when presented to people can be
greatly influenced by the way we discuss AI and even the name we give it in the
first place. We need to give these issues greater thought, adds Maes.
AI: A friend or A foe?
The goal of this study was to ascertain how much of the empathy and efficacy
people see in AI is based on their subjective perceptions and how much is based on
the actual technology. Additionally, they were interested in investigating whether
priming could be used to influence someone’s view.

3. “Since the Artificial intelligence is a mystery to us, we often compare it to
something else that we can comprehend. Similes and metaphors are used
frequently. But which metaphor is most appropriate for thinking about AI?
Pataranutaporn claims that the solution is not simple.
In order to find out whether people would recommend a conversational AI mental
health companion to a friend, researchers created a study in which participants
interacted with the agent for roughly 30 minutes and then gave their ratings. Three
groups of the 310 people the researchers selected were randomly divided. Each
group received a priming statement on AI.
The first group was informed the agent had no motivations; the second group was
told the Artificial intelligence had good goals and was concerned for the welfare of
the user; and the third group was told the agent had evil motivations and would
attempt to trick users. Even though it was difficult to limit themselves to only three
primers, the researchers made the decisions they believed best matched the most
widespread AI misconceptions, according to Liu.
An AI agent built on the GPT-3 generative language model, a potent deep-learning
model that can produce writing that is human-like, interacted with half of the
participants in each group. The other half engaged with an implementation of
ELIZA, a chatbot that was created in the 1960s at MIT using a less complex rule-
based natural language processing system.
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