Abstract
Keywords: Fake news, Article generation, LSTM, RNN, Language model, Machine learning, AI, Media art, Internet art, Web, Blog, Human-AI Co-Creation
While the purpose of most fake news is misinformation and political propaganda, our team sees it as a new type of myth that is created by people in the age of internet identities and artificial intelligence. Seeking insights on the fear and desire hidden underneath these modified or generated stories, we use machine learning methods to generate fake articles and present them in the form of an online news blog. This paper aims to share the details of our pipeline and the techniques used for full generation of fake news, from dataset collection to presentation as a media art project on the internet.
- Vít Ružicka received his B.Sc. and M.Sc. with Honors in Computer Sciences with specialization in Machine Learning, Computer Graphics and Interaction from the Czech Technical University in Prague, Czech Republic in 2017. He spent nearly two exciting years of research internships at the Electrical and Computer Engineering department of Carnegie Mellon University in USA (September 2017 May 2018) and at the EcoVision lab of the Photogrammetry and Remote Sensing group at ETH Zu¨rich in Switzerland (January 2019
July 2019). His research interest are Machine Learning, its application to other disciplines, Computer Vision, Creative AI and the intersections of Machine Learning and Art. - Eunsu Kang is a Korean media artist who creates interactive audiovisual installations and AI artworks. Her current research is focused on creative AI and artistic expressions generated by Machine Learning algorithms. Creating interdisciplinary projects, her signature has been seamless integration of art disciplines and innovative techniques. Her work has been invited to numerous places around the world including Korea, Japan, China, Switzerland, Sweden, France, Germany, and the US. All ten of her solo shows, consisting of individual or collaborative projects, were invited or awarded. She has won the Korean National Grant for Arts three times. Her researches have been presented at prestigious conferences including ACM, ICMC, ISEA, and NeurIPS. Kang earned her Ph.D. in Digital Arts and Experimental Media from DXARTS at the University of Washington. She received an MA in Media Arts and Technology from UCSB and an MFA from the Ewha Womans University. She had been a tenured art professor at the University of Akron for nine years and is currently a Visiting Professor with emphasis on Art and Machine Learning at the School of Computer Science, Carnegie Mellon University.
- David Gordon is an interdisciplinary artist and engineer living in the Los Angeles area, USA. He has a specialty in simulation for autonomous systems, and currently works in NVIDIA’s autonomous driving simulation division. He received a BCSA (Bachelors in Computer Science and Arts) from Carnegie Mellon University in 2019.
- Manzil Zaheer earned his Ph.D. degree in Machine Learning from the School of Computer Science at Carnegie Mellon University, USA, under the able guidance of Prof Barnabas Poczos, Prof Ruslan Salakhutdinov, and Prof Alexander Smola. He is the winner of Oracle Fellowship in 2015. His research interests broadly lie in representation learning. He is interested in developing large-scale inference algorithms for representation learning, both discrete ones using graphical models and continuous with deep networks, for all kinds of data. He enjoy learning and implementing complicated statistical inference, data-parallelism, and algorithms in a simple way.
- Jacqui Fashimpaur, Carnegie Mellon University, USA
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