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Full-Text Articles in Computer Engineering
When Ai Moves Downstream, Frances S. Grodzinsky, Keith W. Miller, Marty J. Wolf
When Ai Moves Downstream, Frances S. Grodzinsky, Keith W. Miller, Marty J. Wolf
School of Computer Science & Engineering Faculty Publications
After computing professionals design, develop, and deploy software, what is their responsibility for subsequent uses of that software “downstream” by others? Furthermore, does it matter ethically if the software in question is considered to be artificial intelligent (AI)? The authors have previously developed a model to explore downstream accountability, called the Software Responsibility Attribution System (SRAS). In this paper, we explore three recent publications relevant to downstream accountability, and focus particularly on examples of AI software. Based on our understanding of the three papers, we suggest refinements of SRAS.
Human Tracking Function For Robotic Dog, Andrew Sharkey
Human Tracking Function For Robotic Dog, Andrew Sharkey
Williams Honors College, Honors Research Projects
With the increase the increase in automation and humans and robots working side by side, there is a need for a more organic way of controlling robots. The goal of this project is to create a control system for Boston dynamics robotic dog Spot that implements human tracking image software to follow humans using computer vision as well as using hand tracking image software to allow for control input through hand gestures.
Research On The Issues Of Next Generation Wargame System Model Engine, Yubo Tang, Bilong Shen, Shi Lei, Yi Xing
Research On The Issues Of Next Generation Wargame System Model Engine, Yubo Tang, Bilong Shen, Shi Lei, Yi Xing
Journal of System Simulation
Abstract: Aiming at the more and more complex war systems, widely used artificial intelligence technology is needed to make up the human deficiencies in future wargame deduction, which is necessary for the next generation wargame system model engine. To address these challenges, a framework prototype of the next generation wargame model engine based on the experience of the long-term development and application is proposed. The decoupling method for the complexity of structure and computation is researched. The human-computer integration architecture on digital twinning technology is studied. Some new modeling techniques which the threshold of model development is reduced and the …
Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree
Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree
Browse all Theses and Dissertations
In almost every field, there is a need for strong interpersonal skills. This is especially true in fields such as medicine, psychology, and education. For instance, healthcare providers need to show understanding and compassion for LGBTQ+ and BIPOC (Black, Indigenous, and People of Color), or individuals with unique developmental or mental health needs. Improving interpersonal skills often requires first-person experience with expert evaluation and guidance to achieve proficiency. However, due to limited availability of assessment capabilities, professional standardized patients and instructional experts, students and professionals currently have inadequate opportunities for expert-guided training sessions. Therefore, this research aims to demonstrate leveraging …
Administrative Law In The Automated State, Cary Coglianese
Administrative Law In The Automated State, Cary Coglianese
All Faculty Scholarship
In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Doctoral Dissertations
Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …
Transparency And Algorithmic Governance, Cary Coglianese, David Lehr
Transparency And Algorithmic Governance, Cary Coglianese, David Lehr
All Faculty Scholarship
Machine-learning algorithms are improving and automating important functions in medicine, transportation, and business. Government officials have also started to take notice of the accuracy and speed that such algorithms provide, increasingly relying on them to aid with consequential public-sector functions, including tax administration, regulatory oversight, and benefits administration. Despite machine-learning algorithms’ superior predictive power over conventional analytic tools, algorithmic forecasts are difficult to understand and explain. Machine learning’s “black-box” nature has thus raised concern: Can algorithmic governance be squared with legal principles of governmental transparency? We analyze this question and conclude that machine-learning algorithms’ relative inscrutability does not pose a …