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Articles 31 - 50 of 50
Full-Text Articles in Artificial Intelligence and Robotics
Considering The Context To Build Theory In Hci, Hri, And Hmc: Explicating Differences In Processes Of Communication And Socialization With Social Technologies, Andrew Gambino, Bingjie Liu
Considering The Context To Build Theory In Hci, Hri, And Hmc: Explicating Differences In Processes Of Communication And Socialization With Social Technologies, Andrew Gambino, Bingjie Liu
Human-Machine Communication
The proliferation and integration of social technologies has occurred quickly, and the specific technologies with which we engage are ever-changing. The dynamic nature of the development and use of social technologies is often acknowledged by researchers as a limitation. In this manuscript, however, we present a discussion on the implications of our modern technological context by focusing on processes of socialization and communication that are fundamentally different from their interpersonal corollary. These are presented and discussed with the goal of providing theoretical building blocks toward a more robust understanding of phenomena of human-computer interaction, human-robot interaction, human-machine communication, and interpersonal …
Human, Hybrid, Or Machine? Exploring The Trustworthiness Of Voice-Based Assistants, Lisa Weidmüller
Human, Hybrid, Or Machine? Exploring The Trustworthiness Of Voice-Based Assistants, Lisa Weidmüller
Human-Machine Communication
This study investigates how people assess the trustworthiness of perceptually hybrid communicative technologies such as voice-based assistants (VBAs). VBAs are often perceived as hybrids between human and machine, which challenges previously distinct definitions of human and machine trustworthiness. Thus, this study explores how the two trustworthiness models can be combined in a hybrid trustworthiness model, which model (human, hybrid, or machine) is most applicable to examine VBA trustworthiness, and whether this differs between respondents with different levels of prior experience with VBAs. Results from two surveys revealed that, overall, the human model exhibited the best model fit; however, the hybrid …
The Symptom Of Ethics: Rethinking Ethics In The Face Of The Machine, David J. Gunkel
The Symptom Of Ethics: Rethinking Ethics In The Face Of The Machine, David J. Gunkel
Human-Machine Communication
This essay argues that it is the machine that constitutes the symptom of ethics— “symptom” understood as that excluded “part that has no part” in the system of moral consideration. Ethics, which has been historically organized around a human or at least biological subject, needs the machine to define the proper limits of the moral community even if it simultaneously excludes such mechanisms from any serious claim on moral consideration. The argument will proceed in five steps or movements. The first part will define and characterize “the symptom” as it has been operationalized in the work of Slovenian philosopher Slavoj …
Addressing Human-Centered Artificial Intelligence: Fair Data Generation And Classification And Analyzing Algorithmic Curation In Social Media, Amirarsalan Rajabi
Addressing Human-Centered Artificial Intelligence: Fair Data Generation And Classification And Analyzing Algorithmic Curation In Social Media, Amirarsalan Rajabi
Electronic Theses and Dissertations, 2020-2023
With the growing impact of artificial intelligence, the topic of fairness in AI has received increasing attention. Artificial intelligence is observed to have caused unanticipated negative consequences. In this dissertation, we address two critical aspects regarding human-centered artificial intelligence (HCAI), a new paradigm for developing artificial intelligence that is ethical, fair, and helps to improve the human condition. In the first part of this dissertation, we investigate the effect that AI curation of contents by social media platforms has on an online discussions, by studying a polarized discussion in the Twitter network. We then develop a network communication model that …
The Social And Behavioral Influences Of Interactions With Virtual Dogs As Embodied Agents In Augmented And Virtual Reality, Nahal Norouzi
The Social And Behavioral Influences Of Interactions With Virtual Dogs As Embodied Agents In Augmented And Virtual Reality, Nahal Norouzi
Electronic Theses and Dissertations, 2020-2023
Intelligent virtual agents (IVAs) have been researched for years and recently many of these IVAs have become commercialized and widely used by many individuals as intelligent personal assistants. The majority of these IVAs are anthropomorphic, and many are developed to resemble real humans entirely. However, real humans do not interact only with other humans in the real world, and many benefit from interactions with non-human entities. A prime example is human interactions with animals, such as dogs. Humans and dogs share a historical bond that goes back thousands of years. In the past 30 years, there has been a great …
Unsupervised Meta-Learning, Siavash Khodadadeh
Unsupervised Meta-Learning, Siavash Khodadadeh
Electronic Theses and Dissertations, 2020-2023
Deep learning has achieved classification performance matching or exceeding the human one, as long as plentiful labeled training samples are available. However, the performance on few-shot learning, where the classifier had seen only several or possibly only one sample of the class is still significantly below human performance. Recently, a type of algorithm called meta-learning achieved impressive performance for few-shot learning. However, meta-learning requires a large dataset of labeled tasks closely related to the test task. The work described in this dissertation outlines techniques that significantly reduce the need for expensive and scarce labeled data in the meta-learning phase. Our …
Visual Learning Beyond Human Curated Datasets, Muhammad Abdullah Jamal
Visual Learning Beyond Human Curated Datasets, Muhammad Abdullah Jamal
Electronic Theses and Dissertations, 2020-2023
The success of deep neural networks in a variety of computer vision tasks heavily relies on large- scale datasets. However, it is expensive to manually acquire labels for large datasets. Given the human annotation cost and scarcity of data, the challenge is to learn efficiently with insufficiently labeled data. In this dissertation, we propose several approaches towards data-efficient learning in the context of few-shot learning, long-tailed visual recognition, and unsupervised and semi-supervised learning. In the first part, we propose a novel paradigm of Task-Agnostic Meta- Learning (TAML) algorithms to improve few-shot learning. Furthermore, in the second part, we analyze the …
Reviving Mozart With Intelligence Duplication, Jacob E. Galajda
Reviving Mozart With Intelligence Duplication, Jacob E. Galajda
Honors Undergraduate Theses
Deep learning has been applied to many problems that are too complex to solve through an algorithm. Most of these problems have not required the specific expertise of a certain individual or group; most applied networks learn information that is shared across humans intuitively. Deep learning has encountered very few problems that would require the expertise of a certain individual or group to solve, and there has yet to be a defined class of networks capable of achieving this. Such networks could duplicate the intelligence of a person relative to a specific task, such as their writing style or music …
Secure And Trustworthy Hardware And Machine Learning Systems For Internet Of Things, Shayan Taheri
Secure And Trustworthy Hardware And Machine Learning Systems For Internet Of Things, Shayan Taheri
Electronic Theses and Dissertations, 2020-2023
The advancements on the Internet have enabled connecting more devices into this technology every day. This great connectivity has led to the introduction of the internet of things (IoTs) that is a great bed for engagement of all new technologies for computing devices and systems. Nowadays, the IoT devices and systems have applications in many sensitive areas including military systems. These challenges target hardware and software elements of IoT devices and systems. Integration of hardware and software elements leads to hardware systems and software systems in the IoT platforms, respectively. A recent trend for the hardware systems is making them …
Implication Of Manifold Assumption In Deep Learning Models For Computer Vision Applications, Marzieh Edraki
Implication Of Manifold Assumption In Deep Learning Models For Computer Vision Applications, Marzieh Edraki
Electronic Theses and Dissertations, 2020-2023
The Deep Neural Networks (DNN) have become the main contributor in the field of machine learning (ML). Specifically in the computer vision (CV), there are applications like image and video classification, object detection and tracking, instance segmentation and visual question answering, image and video generation are some of the applications from many that DNNs have demonstrated magnificent progress. To achieve the best performance, the DNNs usually require a large number of labeled samples, and finding the optimal solution for such complex models with millions of parameters is a challenging task. It is known that, the data are not uniformly distributed …
From Ai With Love: Reading Big Data Poetry Through Gilbert Simondon’S Theory Of Transduction, Andrew Klobucar
From Ai With Love: Reading Big Data Poetry Through Gilbert Simondon’S Theory Of Transduction, Andrew Klobucar
Electronic Literature Organization Conference 2020
Computation initiated a far-reaching re-imagination of language, not just as an information tool, but as a social, bio-physical activity in general. Modern lexicology provides an important overview of the ongoing development of textual documentation and its applications in relation to language and linguistics. At the same time, the evolution of lexical tools from the first dictionaries and graphs to algorithmically generated scatter plots of live online interaction patterns has been surprisingly swift. Modern communication and information studies from Norbert Weiner to the present-day support direct parallels between coding and linguistic systems. However, most theories of computation as a model of …
Why Are We Like This?: Exploring Writing Mechanics For An Ai-Augmented Storytelling Game, Max Kreminski, Melanie Dickinson, Michael Mateas, Noah Wardrip-Fruin
Why Are We Like This?: Exploring Writing Mechanics For An Ai-Augmented Storytelling Game, Max Kreminski, Melanie Dickinson, Michael Mateas, Noah Wardrip-Fruin
Electronic Literature Organization Conference 2020
Why Are We Like This? (WAWLT) is a playful, co-creative, AI-augmented, improvisational storytelling game in which one or more players explore and influence an ongoing simulation which they then glean for narrative material. It uses the recently developed simulation technology of story sifting (the recognition of microstories in a chronicle of simulation events), via the Felt library, to afford a new kind of playful, social, and creative writing experience. In this paper, we discuss our primary design goals: (1) using computation and interaction design to support casual player creativity, and (2) foregrounding character subjectivity as a driver for …
Towards Robust Artificial Intelligence Systems, Sunny Raj
Towards Robust Artificial Intelligence Systems, Sunny Raj
Electronic Theses and Dissertations, 2020-2023
Adoption of deep neural networks (DNNs) into safety-critical and high-assurance systems has been hindered by the inability of DNNs to handle adversarial and out-of-distribution input. State-of-the-art DNNs misclassify adversarial input and give high confidence output for out-of-distribution input. We attempt to solve this problem by employing two approaches, first, by detecting adversarial input and, second, by developing a confidence metric that can indicate when a DNN system has reached its limits and is not performing to the desired specifications. The effectiveness of our method at detecting adversarial input is demonstrated against the popular DeepFool adversarial image generation method. On a …
Analysis Literatures Of Machine Learning And Neural Networks For Real Time Scheduling, Phong Nguyenho, Mark Nguyen
Analysis Literatures Of Machine Learning And Neural Networks For Real Time Scheduling, Phong Nguyenho, Mark Nguyen
Recent Advances in Real-Time Systems
Real time scheduling problems are present in every aspect of software development. An optimized real time scheduling scheme would determine the performance of an operating system. There are many different approaches that real time scheduling researchers developed to tackle scheduling problems in many computer systems that have great important roles in keeping our modern society running smoothly. Neural-network real time scheduling is one of those approaches that can solve many computer scheduling problems. As computing technology advanced, more and more real time scheduling problems arise that need new solutions to keep up with the demand of faster computer systems. In …
Transparency And Communication Patterns In Human-Robot Teaming, Shan Lakhmani
Transparency And Communication Patterns In Human-Robot Teaming, Shan Lakhmani
Electronic Theses and Dissertations
In anticipation of the complex, dynamic battlefields of the future, military operations are increasingly demanding robots with increased autonomous capabilities to support soldiers. Effective communication is necessary to establish a common ground on which human-robot teamwork can be established across the continuum of military operations. However, the types and format of communication for mixed-initiative collaboration is still not fully understood. This study explores two approaches to communication in human-robot interaction, transparency and communication pattern, and examines how manipulating these elements with a robot teammate affects its human counterpart in a collaborative exercise. Participants were coupled with a computer-simulated robot to …
Collaborative Artificial Intelligence Algorithms For Medical Imaging Applications, Naji Khosravan
Collaborative Artificial Intelligence Algorithms For Medical Imaging Applications, Naji Khosravan
Electronic Theses and Dissertations
In this dissertation, we propose novel machine learning algorithms for high-risk medical imaging applications. Specifically, we tackle current challenges in radiology screening process and introduce cutting-edge methods for image-based diagnosis, detection and segmentation. We incorporate expert knowledge through eye-tracking, making the whole process human-centered. This dissertation contributes to machine learning, computer vision, and medical imaging research by: 1) introducing a mathematical formulation of radiologists level of attention, and sparsifying their gaze data for a better extraction and comparison of search patterns. 2) proposing novel, local and global, image analysis algorithms. Imaging based diagnosis and pattern analysis are "high-risk" Artificial Intelligence …
Exploring Natural User Abstractions For Shared Perceptual Manipulator Task Modeling & Recovery, Senglee Koh
Exploring Natural User Abstractions For Shared Perceptual Manipulator Task Modeling & Recovery, Senglee Koh
Electronic Theses and Dissertations
State-of-the-art domestic robot assistants are essentially autonomous mobile manipulators capable of exerting human-scale precision grasps. To maximize utility and economy, non-technical end-users would need to be nearly as efficient as trained roboticists in control and collaboration of manipulation task behaviors. However, it remains a significant challenge given that many WIMP-style tools require superficial proficiency in robotics, 3D graphics, and computer science for rapid task modeling and recovery. But research on robot-centric collaboration has garnered momentum in recent years; robots are now planning in partially observable environments that maintain geometries and semantic maps, presenting opportunities for non-experts to cooperatively control task …
Environmental Physical-Virtual Interaction To Improve Social Presence With A Virtual Human In Mixed Reality, Kangsoo Kim
Environmental Physical-Virtual Interaction To Improve Social Presence With A Virtual Human In Mixed Reality, Kangsoo Kim
Electronic Theses and Dissertations
Interactive Virtual Humans (VHs) are increasingly used to replace or assist real humans in various applications, e.g., military and medical training, education, or entertainment. In most VH research, the perceived social presence with a VH, which denotes the user's sense of being socially connected or co-located with the VH, is the decisive factor in evaluating the social influence of the VH—a phenomenon where human users' emotions, opinions, or behaviors are affected by the VH. The purpose of this dissertation is to develop new knowledge about how characteristics and behaviors of a VH in a Mixed Reality (MR) environment can affect …
Complex Affect Recognition In The Wild, Behnaz Nojavanasghari
Complex Affect Recognition In The Wild, Behnaz Nojavanasghari
Electronic Theses and Dissertations
Artificial social intelligence is a step towards human-like human-computer interaction. One important milestone towards building socially intelligent systems is enabling computers with the ability to process and interpret the social signals of humans in the real world. Social signals include a wide range of emotional responses from a simple smile to expressions of complex affects. This dissertation revolves around computational models for social signal processing in the wild, using multimodal signals with an emphasis on the visual modality. We primarily focus on complex affect recognition with a strong interest in curiosity. In this dissertation,we ?rst present our collected dataset, EmoReact. …
Online Path Planning And Control Solution For A Coordinated Attack Of Multiple Unmanned Aerial Vehicles In A Dynamic Environment, Juan Vega-Nevarez
Online Path Planning And Control Solution For A Coordinated Attack Of Multiple Unmanned Aerial Vehicles In A Dynamic Environment, Juan Vega-Nevarez
Electronic Theses and Dissertations
The role of the unmanned aerial vehicle (UAV) has significantly expanded in the military sector during the last decades mainly due to their cost effectiveness and their ability to eliminate the human life risk. Current UAV technology supports a variety of missions and extensive research and development is being performed to further expand its capabilities. One particular field of interest is the area of the low cost expendable UAV since its small price tag makes it an attractive solution for target suppression. A swarm of these low cost UAVs can be utilized as guided munitions or kamikaze UAVs to attack …