Unisys to Research Use of Artificial Intelligence and Machine Learning to Detect Deceitful and Persuasive Writing for Australia's Defence and National Security Communities
Unisys Corporation (NYSE: UIS) has received research funding from the Artificial Intelligence (AI) for Decision Making Initiative to explore AI and Machine Learning (ML) applications for identifying deceitful writing. This initiative is a collaboration with Australia's Office of National Intelligence and Department of Defence, focusing on enhancing AI capabilities relevant to national security. Unisys aims to develop solutions that could potentially assist in forensic analysis and cybersecurity, with expected results to be presented in early 2021.
- Awarded research funding to investigate AI and ML for detecting deceitful writing, indicating confidence from Australia's national security agencies.
- Partnership with key Australian government bodies enhances Unisys's reputation and potential for future contracts.
- Research focus may not yield immediate financial returns for Unisys in the short term.
- Dependence on government contracts could pose risks if funding priorities change.
SYDNEY and BLUE BELL, Pa., Jan. 20, 2021 /PRNewswire/ -- Unisys Corporation (NYSE: UIS) today announced that the Artificial Intelligence (AI) for Decision Making Initiative has awarded Unisys research funding to investigate using AI and Machine Leaning (ML) to detect deceitful and persuasive writing.
The AI for Decision Making Initiative is a collaboration between the Office of National Intelligence (ONI) and Department of Defence, to develop AI and ML expertise and capability in areas of significant importance to the Australian Defence Force and national security community. It is delivered nationally through the Defence Science Centre, Defence Science Institute, Defence Innovation Network and Defence Innovation Partnership.
Unisys chose from 23 challenges set by the initiative, and applied to develop an AI and ML-based solution to detect deceitful or persuasive writing in a collection of documents by the same author. With the research funding awarded in November 2020, Unisys will experiment, prototype and demonstrate the proposed approach using publicly available data, in a detailed technical paper and oral presentation in the first quarter of 2021.
"Ultimately we want to be able to detect if an author's writing style has changed in documents making exaggerated claims. Real world applications could potentially include forensic analysis to determine who is the true author of a written piece for legal purposes; identify if emails or text messages are written by imposters such as hackers or phishers; or even detect fraudulent of fake statements on Twitter or other public information platforms designed to confuse media or the public," said Dr. Xin Xu, practice lead for Artificial Intelligence, Machine Learning & Data Science for Unisys Asia Pacific.
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