Visible to the public Malicious Design in AIVR, Falsehood and Cybersecurity-oriented Immersive Defenses

TitleMalicious Design in AIVR, Falsehood and Cybersecurity-oriented Immersive Defenses
Publication TypeConference Paper
Year of Publication2020
AuthorsAliman, N.-M., Kester, L.
Conference Name2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)
KeywordsAI, AI Safety, artificial intelligence, composability, Computer crime, cyber physical systems, cybersecurity, Design Fiction, disinformation, HCI, Human Behavior, human factors, Immersive Journalism, immersive systems, Information integrity, Journalism, Media, privacy, psychology, pubcrawl, resilience, Safety, Videos, VR
Abstract

Advancements in the AI field unfold tremendous opportunities for society. Simultaneously, it becomes increasingly important to address emerging ramifications. Thereby, the focus is often set on ethical and safe design forestalling unintentional failures. However, cybersecurity-oriented approaches to AI safety additionally consider instantiations of intentional malice - including unethical malevolent AI design. Recently, an analogous emphasis on malicious actors has been expressed regarding security and safety for virtual reality (VR). In this vein, while the intersection of AI and VR (AIVR) offers a wide array of beneficial cross-fertilization possibilities, it is responsible to anticipate future malicious AIVR design from the onset on given the potential socio-psycho-technological impacts. For a simplified illustration, this paper analyzes the conceivable use case of Generative AI (here deepfake techniques) utilized for disinformation in immersive journalism. In our view, defenses against such future AIVR safety risks related to falsehood in immersive settings should be transdisciplinarily conceived from an immersive co-creation stance. As a first step, we motivate a cybersecurity-oriented procedure to generate defenses via immersive design fictions. Overall, there may be no panacea but updatable transdisciplinary tools including AIVR itself could be used to incrementally defend against malicious actors in AIVR.

DOI10.1109/AIVR50618.2020.00031
Citation Keyaliman_malicious_2020