The current stance towards tackling fake news within the Media Industry from the perspective of a startup founder.
Disinformation is misleading information created, presented, and disseminated for economic gain or to intentionally deceive the public. It may have far-reaching consequences, cause public harm, be a threat to democratic political and policy-making processes.
In this article series, I am going to talk about the problems our team faced during the journey towards media content detection from late 2018 until today. My name is Dominik Mate Kovacs, Co-Founder of Defudger.
Defudger offers the one-stop solution for visual content fact-checking: we simplify the…
The struggle of building a product solely based on Machine Learning and the difficulties of Explainable AI within detection algorithms.
In today’s society, fake news is rapidly being produced as a result of information overload and technological tools that enable more advanced manipulations than ever before. To counter the massive amount of content coming into news and media companies, solutions for automated fake news detection must exist. Fake news can be either be visual or linguistic-based. In this article, I am going to focus on visual fake news detection, which includes videos, images, and other types of visual media content.
I work with fake news detection & synthetic media at Defudger and Colossyan. My goal is to ensure technology is not misused, and it brings the most benefits.