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As many of us in the information retrieval (IR) research community know and appreciate, search is far from being a solved problem. Millions of people struggle with tasks on search engines every day. Often, their struggles relate to the…
Artificial intelligence (AI) ethics has gained significant momentum, evidenced by the growing body of published literature, policy guidelines, and public discourse. However, the practical implementation and adoption of AI ethics principles…
This paper explores the interplay of AI language technologies, sign language interpreting, and linguistic access, highlighting the complex interdependencies shaping access frameworks and the tradeoffs these technologies bring. While AI…
Since its launch in late 2022, ChatGPT has ignited widespread interest in Large Language Models (LLMs) and broader Artificial Intelligence (AI) solutions. As this new wave of AI permeates various sectors of society, we are continually…
As AI systems are increasingly deployed to support decision-making in critical domains, explainability has become a means to enhance the understandability of these outputs and enable users to make more informed and conscious choices.…
Advances in artificial intelligence (AI) present significant risks and opportunities, requiring improved governance to mitigate societal harms and promote equitable benefits. Current incentive structures and regulatory delays may hinder…
Agentic Artificial Intelligence (AI) can autonomously pursue long-term goals, make decisions, and execute complex, multi-turn workflows. Unlike traditional generative AI, which responds reactively to prompts, agentic AI proactively…
Online learning is a familiar problem setting within Machine-Learning in which data is presented serially in time to a learning agent, requiring it to progressively adapt within the constraints of the learning algorithm. More sophisticated…
The autonomy and contextual complexity of LLM-based agents render traditional access control (AC) mechanisms insufficient. Static, rule-based systems designed for predictable environments are fundamentally ill-equipped to manage the dynamic…
The rapid growth in the use of Large Language Models (LLMs) and AI Agents as part of software development and deployment is revolutionizing the information technology landscape. While code generation receives significant attention, a…
The increasing prevalence of Artificial Intelligence (AI) in safety-critical contexts such as air-traffic control leads to systems that are practical and efficient, and to some extent explainable to humans to be trusted and accepted. The…
In recent years we observed rapid and significant advancements in artificial intelligence (A.I.). So much so that many wonder how close humanity is to developing an A.I. model that can achieve human level of intelligence, also known as…
People with visual impairments perceive their environment non-visually and often use AI-powered assistive tools to obtain textual descriptions of visual information. Recent large vision-language model-based AI-powered tools like Be My AI…
Course syllabi are often the first and sometimes only structured artifact that explains how a class will run: deadlines, grading rules, safety procedures, and how to request disability accommodations. For blind and low-vision (BLV) students…
Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to…
Access to mental health support remains limited, particularly in marginalized communities where structural and cultural barriers hinder timely care. This paper explores the potential of AI-enabled chatbots as a scalable solution, focusing…
Despite its significant promise and continuous technical advances, real-world applications of artificial intelligence (AI) remain limited. We attribute this to the "domain expert-AI-conundrum": while domain experts, such as clinician…
This vision paper presents initial research on assessing the robustness and reliability of AI-enabled systems, and key factors in ensuring their safety and effectiveness in practical applications, including a focus on accountability. By…
With recent advancements in AI and computational tools, intelligent paradigms have emerged to enhance fields like shared autonomy and human-machine teaming in healthcare. Advanced AI algorithms (e.g., reinforcement learning) can…
Background: The rapid advancement of large language models (LLMs) has given rise to AI-native applications, a new paradigm in software engineering that fundamentally redefines how software is designed, developed, and evolved. Despite their…