Skip to content

How KM Can Team Up With AI to Fight Fake News

In a post-truth world, objective facts have less influence on opinions and decisions than emotions and personal beliefs. People deliberately select those facts and data that support their preferred conclusions and classify any information that contradicts their beliefs as “false news..” This is not a recent problem but the Internet and social media allow information sharing at an incredible speed (practically real-time) and over a much greater geographic range (almost worldwide).

There is also increasingly a crowd-sourcing approach to gathering information as most people read news through their social networks rather than independent news reports. How can knowledge management and AI technologies help in a post-truth world? Newer technologies such as artificial intelligence improve the efficiency and effectiveness of fact checking (e.g. through a news filtering agents that identify false news much as we identify junk email).

We need to better educate our students and train our professionals so that they have the full range of literacies or meta-literacy needed to navigate in a post-truth world There is an interesting intersection of human (manual) methods to address post-truth (such as information literacy workshops and legal or policy changes to deter the spread of misinformation online) and a more automated, machine/AI-based approach (e.g. an algorithm that detects fake news dissemination patterns in social media).

This webinar will bring together the different disciplines and research approaches to provide a comprehensive and effective toolkit to deal with information and knowledge in the post-truth era. KM can work in synergy with AI to help users navigate in this convoluted world of increasingly complex and dubious content. The only uncontested prediction is that the volume will only increase making its validation even more challenging.


Dr. Kimiz Dalkir is an Associate Professor and Director of the School of Information Studies at McGill University with a Ph.D. in Educational Technology, MBA and a B.Sc. in Human Genetics.

Dr. Dalkir wrote Knowledge Management in Theory and Practice (MIT Press, 3rd Ed published 2017), which has had an international impact on KM education and on KM practice. She has also published Intelligent Learner Modeling in Real-time and co-edited Utilizing Evidence-Based Lessons Learned for Enhanced Organizational Innovation (with S. McIntyre) and Change as well as the more recent Navigating Fake News, Alternative Facts and Misinformation in a Post-Truth World (with R. Katz).

Dr. Dalkir’s research focuses tacit knowledge sharing and organizational learning. Prior to joining McGill, Dr. Dalkir was Global Practice Leader KM for Fujitsu Consulting and she worked in the field of knowledge transfer and retention for 17 years with clients in Europe, Japan and North America.