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Publication Details

How to trick AI - Examining users' coping strategies and mental models to avoid profiling by intelligent algorithms

BA/MA

Status open
Advisor Sarah Theres Völkel
Professor Prof. Dr. H. Hußmann

Task

Description

A growing body of research shows that personality traits can be automatically inferred from users' digital texts, e.g. conversations with chat bots or social media posts. Like other personal data, we think that users' personality data might be captured in the future without users' knowledge and out of their control. This raises, in our opinion, ethical and privacy concerns and might potentially lead to misuse. We assume that depending on the context, users might not be comfortable with being profiled and its potential consequences. Together with you, we want to find out, which coping strategies users would employ to avoid being profiled by intelligent algorithms, i.e. how they try to ``trick'' the algorithm.

Tasks

The thesis comprises of the following tasks:
  • Conduct an extensive survey of related research with a focus on personality assessment and attitude towards data sharing.
  • Design a suitable online survey based on previous research to collect coping strategies
  • Recruit n = 300 participants, who fill out the online survey
  • Evaluate the findings using qualitative and quantitative research analysis methods.

Keywords

Chatbots, Conversational Agents, Personality, Big 5, User control, Personality profile, artificial intelligence, AI, Survey
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