On the Horizon: Interactive and Compositional Deepfakes

Over a five-year period, computing methods for generating high-fidelity, fictional depictions of people and events moved from exotic demonstrations by computer science research teams into ongoing use as a tool of disinformation. The methods, referred to with the portmanteau of "deepfakes," have been used to create compelling audiovisual content. Here, I share challenges ahead with malevolent uses of two classes of deepfakes that we can expect to come into practice with costly implications for society: interactive and compositional deepfakes. Interactive deepfakes have the capability to impersonate people with realistic interactive behaviors, taking advantage of advances in multimodal interaction. Compositional deepfakes leverage synthetic content in larger disinformation plans that integrate sets of deepfakes over time with observed, expected, and engineered world events to create persuasive synthetic histories. Synthetic histories can be constructed manually but may one day be guided by adversarial generative explanation (AGE) techniques. In the absence of mitigations, interactive and compositional deepfakes threaten to move us closer to a post-epistemic world, where fact cannot be distinguished from fiction. I shall describe interactive and compositional deepfakes and reflect about cautions and potential mitigations to defend against them.Comment: CCC Blue Sky Ideas paper, published at the ACM International Conference on Multimodal Interaction (ICMI '22), November 7-11, 202

A Multi-Party Conversation-Based Effective Robotic Navigation System for Futuristic Vehicle

In response to the growing need for advanced in-car navigation systems that prioritize user experience and aim to reduce driver cognitive workload, this study addresses the research question of how to enhance the interaction between drivers and navigation systems. The focus is on minimizing distraction while providing personalized and geographically relevant information. The research introduces an innovative in-car robotic navigation system comprising three subsystem models: geofencing,personalization, and conversation. The dynamic geofencing model acquires geographic details related to the user's current location and provides information about required destinations. The personalization model tailors suggestions based on user preferences, while the conversation model, employing two virtual robots, fosters interactive multiparty conversations aligned with the driver's interests. The study's scope is specifically confined to interactive conversations centered on nearby restaurants and the driver's dietary preferences. Evaluation of the system indicates a notable prevalence of neutral expressions amongparticipants during interaction, suggesting that the implemented system successfully mitigates cognitive workload. Participants in the experiments express higher usability and interactivity levels, as evidenced by feedback collected at the study's conclusion, affirming the system's effectiveness in enhancing the user experience while maintaining a driver-friendly environment. Keywords: Human-Robot Interaction, Multiparty Conversation, In-Car Navigatio

Peace Revolution as a Three-Dimensional Process: The Israeli-Palestinian Case

The Israeli-Palestinian struggle is a classic case of intractable conflict. Establishing a long-lasting change requires a revolutionary peace process. The paper describes peace revolution as a three-dimensional process—peacemaking, peacebuilding, and peacekeeping. Each of these three components is itself a three-level process. Peacemaking means involving different societal elements (leaders, elites, and people) in the struggle to reach a negotiated peace deal by using political-elite diplomacy, public diplomacy, and people-to-people diplomacy. Peacebuilding means constructing international, bilateral, and domestic frameworks for a stable peace. Peacekeeping means building political, militaristic, and civilian devices to maintain a stable social order

A framework for using humanoid robots in the school learning environment

With predictions of robotics and efficient machine learning being the building blocks of the Fourth Industrial Revolution, countries need to adopt a long-term strategy to deal with potential challenges of automation and education must be at the center of this long-term strategy. Education must provide students with a grounding in certain skills, such as computational thinking and an understanding of robotics, which are likely to be required in many future roles. Targeting an acknowledged gap in existing humanoid robot research in the school learning environment, we present a multidisciplinary framework that integrates the following four perspectives: technological, pedagogical, efficacy of humanoid robots and a consideration of the ethical implications of using humanoid robots. Further, this paper presents a proposed application, evaluation and a case study of how the framework can be used.publishedVersio