Related papers: Constitutive vs. Corrective: A Causal Taxonomy of …
We use the notion of oracle machines and reductions from computability theory to formalise different Human-in-the-loop (HITL) setups for AI systems, distinguishing between trivial human monitoring (i.e., total functions), single endpoint…
Agentic AI systems, powered by Large Language Models (LLMs), offer transformative potential for value co-creation in technical services. However, persistent challenges like hallucinations and operational brittleness limit their autonomous…
Human-in-the-loop (HIL) systems have emerged as a promising approach for combining the strengths of data-driven machine learning models with the contextual understanding of human experts. However, a deeper look into several of these systems…
Artificial intelligence (AI) is increasingly utilized in synthesizing visuals, texts, and audio. These AI-based works, often derived from neural networks, are entering the mainstream market, as digital paintings, songs, books, and others.…
Developing and deploying AI applications in organizations is challenging when human decision authority and oversight are underspecified across the system lifecycle. Although Human-in-the-Loop (HITL) and Human-Centered AI (HCAI) principles…
AI agents are increasingly deployed to execute tasks and make decisions within agentic workflows, introducing new requirements for safe and controlled autonomy. Prior work has established the importance of human oversight for ensuring…
Rapid advances in Machine Learning (ML) have triggered new trends in Autonomous Vehicles (AVs). ML algorithms play a crucial role in interpreting sensor data, predicting potential hazards, and optimizing navigation strategies. However,…
As Artificial Intelligence (AI) technologies continue to advance, protecting human autonomy and promoting ethical decision-making are essential to fostering trust and accountability. Human agency (the capacity of individuals to make…
A Human-in-the-Loop (HITL) approach leverages generative AI to enhance personalized learning by directly integrating student feedback into AI-generated solutions. Students critique and modify AI responses using predefined feedback tags,…
Large language models (LLMs) are increasingly embedded in computer science education through AI-assisted programming tools, yet such workflows often exhibit objective drift, in which locally plausible outputs diverge from stated task…
Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for…
This paper considers the motion control and task planning problem of mobile robots under complex high-level tasks and human initiatives. The assigned task is specified as Linear Temporal Logic (LTL) formulas that consist of hard and soft…
Although browser-using agents (BUAs) show promise for web tasks and automation, most BUAs terminate after executing a single instruction, failing to support users' complex, nonlinear browsing with ambiguous goals, iterative decision-making,…
Plain Language and Easy-to-Read formats in text simplification are essential for cognitive accessibility. Yet current automatic simplification and evaluation pipelines remain largely automated, metric-driven, and fail to reflect user…
AI has revolutionized the processing of various services, including the automatic facial verification of people. Automated approaches have demonstrated their speed and efficiency in verifying a large volume of faces, but they can face…
Artificial intelligence systems increasingly operate in decision-critical environments where probabilistic outputs and Human-in-the-Loop (HITL) interactions reshape user engagement. Traditional user experience (UX) frameworks, designed for…
While the role of humans is increasingly recognized in machine learning community, representation of and interaction with models in current human-in-the-loop machine learning (HITL-ML) approaches are too low-level and far-removed from…
Information systems increasingly leverage artificial intelligence (AI) and machine learning (ML) to generate value from vast amounts of data. However, ML models are imperfect and can generate incorrect classifications. Hence,…
As the global population ages, effective rehabilitation and mobility aids will become increasingly critical. Gait assistive robots are promising solutions, but designing adaptable controllers for various impairments poses a significant…
Artificial Intelligence (AI) techniques, particularly machine learning techniques, are rapidly transforming tactical operations by augmenting human decision-making capabilities. This paper explores AI-driven Human-Autonomy Teaming (HAT) as…