Advancements and innovations in requirements elicitation: Developing a comprehensive conceptual model

OA Popoola, HE Adama, CD Okeke… - World Journal of …, 2024 - wjarr.com
Requirements elicitation is a crucial phase in the software development lifecycle, ensuring
that stakeholders' needs are understood and translated into system specifications …

[HTML][HTML] Methodological and quality flaws in the use of artificial intelligence in mental health research: systematic review

R Tornero-Costa, A Martinez-Millana… - JMIR Mental …, 2023 - mental.jmir.org
Background: Artificial intelligence (AI) is giving rise to a revolution in medicine and health
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …

Data cards: Purposeful and transparent dataset documentation for responsible ai

M Pushkarna, A Zaldivar, O Kjartansson - Proceedings of the 2022 ACM …, 2022 - dl.acm.org
As research and industry moves towards large-scale models capable of numerous
downstream tasks, the complexity of understanding multi-modal datasets that give nuance to …

Algorithmic management in a work context

MH Jarrahi, G Newlands, MK Lee, CT Wolf… - Big Data & …, 2021 - journals.sagepub.com
The rapid development of machine-learning algorithms, which underpin contemporary
artificial intelligence systems, has created new opportunities for the automation of work …

Ethics-based auditing of automated decision-making systems: Nature, scope, and limitations

J Mökander, J Morley, M Taddeo, L Floridi - Science and Engineering …, 2021 - Springer
Important decisions that impact humans lives, livelihoods, and the natural environment are
increasingly being automated. Delegating tasks to so-called automated decision-making …

Trustllm: Trustworthiness in large language models

L Sun, Y Huang, H Wang, S Wu, Q Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

[PDF][PDF] Ai transparency in the age of llms: A human-centered research roadmap

QV Liao, JW Vaughan - arXiv preprint arXiv:2306.01941, 2023 - assets.pubpub.org
The rise of powerful large language models (LLMs) brings about tremendous opportunities
for innovation but also looming risks for individuals and society at large. We have reached a …

The role of explainable AI in the context of the AI Act

C Panigutti, R Hamon, I Hupont… - Proceedings of the …, 2023 - dl.acm.org
The proposed EU regulation for Artificial Intelligence (AI), the AI Act, has sparked some
debate about the role of explainable AI (XAI) in high-risk AI systems. Some argue that black …

Designing a feature selection method based on explainable artificial intelligence

J Zacharias, M von Zahn, J Chen, O Hinz - Electronic Markets, 2022 - Springer
Nowadays, artificial intelligence (AI) systems make predictions in numerous high stakes
domains, including credit-risk assessment and medical diagnostics. Consequently, AI …

Opportunities and challenges of ChatGPT for design knowledge management

X Hu, Y Tian, K Nagato, M Nakao, A Liu - Procedia CIRP, 2023 - Elsevier
Abstract Recent advancements in Natural Language Processing have opened up new
possibilities for the development of large language models like ChatGPT, which can …