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Detecting Bot-Generated Text by Characterizing Linguistic Accommodation in Human-Bot Interactions

Project Overview

The document examines the integration of generative AI and language generation models in education, highlighting their promising applications, such as tutoring and information dissemination through chatbots. It underscores the dual nature of these technologies, recognizing both their potential benefits and risks of misuse in educational settings. A significant focus is placed on the dynamics of human-bot interactions, where understanding the nuances of these exchanges can lead to improved chatbot design and efficacy. The paper also addresses the importance of detecting bot-generated text and analyzing linguistic alignment, which can inform better evaluation methods for AI-driven educational tools. Overall, the findings suggest that by enhancing the interaction quality between students and AI, educational outcomes can be positively impacted, paving the way for more personalized and effective learning experiences.

Key Applications

Chatbots for tutoring services

Context: Educational context where chatbots assist students in learning and providing information

Implementation: Chatbots are deployed as tools for answering questions and providing guidance to students.

Outcomes: Improved access to information, personalized learning experiences, and support for students.

Challenges: Potential for misinformation and inadequate responses from bots.

Implementation Barriers

Ethical/Social

Concerns regarding bots being used for misinformation, discrimination, and fraud.

Proposed Solutions: Developing guidelines for ethical bot interactions and enhancing detection methods for harmful bot behavior.

Technical

Challenges in accurately detecting bot-generated text due to similarities with human writing.

Proposed Solutions: Using linguistic accommodation and response patterns in human-bot conversations to improve detection methods.

Project Team

Paras Bhatt

Researcher

Anthony Rios

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Paras Bhatt, Anthony Rios

Source Publication: View Original PaperLink opens in a new window

Project Contact: Dr. Jianhua Yang

LLM Model Version: gpt-4o-mini-2024-07-18

Analysis Provider: Openai

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