Integrating Human Factors into AI for Fake News Prevention: Challenges and Opportunities

Tutorial Presented at AAAI 2019, Honolulu, Hawaii

Date: Monday, 28th January, 2019

Time: 1:30 PM - 5:30 PM

Venue: South Pacific 2, Upper level

Abstract

This tutorial aims to sketch the shape of an interdisciplinary approach involving artificial intelligence (AI) and cognitive psychology for fake news prevention on social media platforms. One objective is to illustrate how representations of human behavior can lead to realistic models/algorithms which address different aspects of the fake news problem, e.g., characterization, detection, and mitigation of fake news. Another is to emphasize the importance of understanding/characterizing the interactions between humans and these AI-aided systems.

The tutorial consists of three parts. In the two parts, we will present summaries of the latest work in the AI and cognitive psychology communities for fake news prevention, respectively. In the third part, we will propose an approach of integrating AI & cognitive psychology to alleviate the limitations of prior research. We will point out tangible research questions that would arise from this integration, and propose possible solutions.

This tutorial is geared toward graduate students, AI researchers, and practitioners, who are interested in fake news detection and prevention but do not have much background in human factors, and want to learn about principles of human information processing and apply those principles for AI algorithms to detect and prevent fake news.

Topics

The main topics of the tutorial will be:

• Prelude
  • The Rising Problem of Fake News, its Impact on Society
  • An Age-old Problem: A History of Fake News
  • What is Fake News? Definitions and Terminology
• AI Research for Fake News
  • A Three Tiered Pipeline for AI Research in Fake News: Introduction
  • AI Research for Disincentivizing Creation of Fake News
  • AI Research for Detection of Fake News
  • AI Research for Mitigation of Fake News
• Human Factors and Cognitive Psychology Research for Fake News
  • A Three Tiered Pipeline for Human Factors Research in Fake News: Introduction
  • Perception in Humans: Key Results and Discussion
  • Cognition in Humans: Key Results and Discussion
  • Action in Humans: Key Results and Discussion
• Integrating AI and Human Factors Research
  • Possible Future Directions
• Closing Comments

Presentation Slides

AI and Human Factors Research for Tackling the Fake News Problem

Presenters

Amulya Yadav	Aiping Xiong

Amulya Yadav is an Assistant Professor in the College of Information Sciences and Technology at Penn State University. His research interests include Artificial Intelligence, Multi-Agent Systems, Computational Game-Theory and Applied Machine Learning.

Aiping Xiong is an Assistant Professor in the College of Information Sciences and Technology at Penn State University. Her research has focused on examining decision making and human action selection within various cyber security and privacy contexts, including phishing, password generation, app selection, and autonomous driving.