152,265 research outputs found
Communities of knowledge and knowledge of communities: An appreciative inquiry into rural wellbeing
This article offers a retrospective examination of the use of appreciative inquiry (AI) in a study on rural wellbeing. It provides a reflection on the rationale for choosing AI as a suitable methodology, critiques the application of AI in rural settings and considers its suitability for this inquiry into individual and community wellbeing. The article also considers the value of AI as a participatory research approach for community-university partnerships. A review of the literature on AI is distilled to examine the limitations as well as the utility of AI. Through an effective use of AI, communities of knowledge can be fostered and the knowledge of communities can be valued and harvested to enhance the wellbeing of rural communities.Keywords: appreciative inquiry, wellbeing, rural community, community-university partnership
Competitor Collaboration Before a Crisis: What the AI Industry Can Learn
Overview: For artificial intelligence (AI) technology to impact society positively, the major AI companies must coordinate their efforts and agree on safe practices. The social legitimacy of AI development depends on building a consensus among AI companies to prevent its potentially damaging downsides. Consortia like the Partnership on AI (PAI) aim to have AI competitors collaborate to flag risks in AI development and create solutions to manage those risks. PAI can apply valuable lessons learned from other industries about how to facilitate collective action but do so proactively rather than after the fact. The Dynamic Capabilities Framework of “sensing, seizing, and transforming” provides a process map for the AI industry to create processes to reduce the risk of a major disaster or crisis
Improving Traffic Safety Through Video Analysis in Jakarta, Indonesia
This project presents the results of a partnership between the Data Science
for Social Good fellowship, Jakarta Smart City and Pulse Lab Jakarta to create
a video analysis pipeline for the purpose of improving traffic safety in
Jakarta. The pipeline transforms raw traffic video footage into databases that
are ready to be used for traffic analysis. By analyzing these patterns, the
city of Jakarta will better understand how human behavior and built
infrastructure contribute to traffic challenges and safety risks. The results
of this work should also be broadly applicable to smart city initiatives around
the globe as they improve urban planning and sustainability through data
science approaches.Comment: 6 pages; LaTeX; Presented at NeurIPS 2018 Workshop on Machine
Learning for the Developing World; Presented at NeurIPS 2018 Workshop on AI
for Social Goo
Opening the black box of artificial intelligence technologies: unveiling the influence exerted by type of organisations and collaborative dynamics
Until now, the management literature on Artificial Intelligence (AI) focuses mostly on the diverse applications of this technology, while its development has attracted only limited attention. To partially fill this research gap, the present paper analyses a large sample of AI
patents and investigates the potential determinants of their technological impact. We show how University-Industry (UI) collaborations seem to be less able to develop high-impact AI patents, compared to other types of partnership based on the involvement of either universities or companies. This result contrasts with the previous literature on the inventing process of other generalpurpose technologies (GPT), thus clarifying how the development of AI may be significantly affected by the peculiar characteristics of this technology. Thereby, our findings not only shed further light on the inventing process of AI solutions but may also stimulate the debate on the development of other GPTs strongly imbued with scientific knowledge
AI for CSI Feedback Enhancement in 5G-Advanced
The 3rd Generation Partnership Project started the study of Release 18 in
2021. Artificial intelligence (AI)-native air interface is one of the key
features of Release 18, where AI for channel state information (CSI) feedback
enhancement is selected as the representative use case. This article provides
an overview of AI for CSI feedback enhancement in 5G-Advanced. Several
representative non-AI and AI-enabled CSI feedback frameworks are first
introduced and compared. Then, the standardization of AI for CSI feedback
enhancement in 5G-advanced is presented in detail. First, the scope of the AI
for CSI feedback enhancement in 5G-Advanced is presented and discussed. Then,
the main challenges and open problems in the standardization of AI for CSI
feedback enhancement, especially focusing on performance evaluation and the
design of new protocols for AI-enabled CSI feedback, are identified and
discussed. This article provides a guideline for the standardization study of
AI-based CSI feedback enhancement.Comment: 8 pages, 4 figures, 2 table. This work has been submitted to the IEEE
for possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
Chatbots in Drug Discovery: A Case Study on Anti-Cocaine Addiction Drug Development with ChatGPT
The birth of ChatGPT, a cutting-edge language model chatbot developed by
OpenAI, ushered in a new era in AI, and this paper vividly showcases its
innovative application within the field of drug discovery. Focused specifically
on developing anti-cocaine addiction drugs, the study employs GPT-4 as a
virtual guide, offering strategic and methodological insights to researchers
working on generative models for drug candidates. The primary objective is to
generate optimal drug-like molecules with desired properties. By leveraging the
capabilities of ChatGPT, the study introduces a novel approach to the drug
discovery process. This symbiotic partnership between AI and researchers
transforms how drug development is approached. Chatbots become facilitators,
steering researchers towards innovative methodologies and productive paths for
creating effective drug candidates. This research sheds light on the
collaborative synergy between human expertise and AI assistance, wherein
ChatGPT's cognitive abilities enhance the design and development of potential
pharmaceutical solutions. This paper not only explores the integration of
advanced AI in drug discovery but also reimagines the landscape by advocating
for AI-powered chatbots as trailblazers in revolutionizing therapeutic
innovation
Technologies and Applications for Big Data Value
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems
ID.8: Co-Creating Visual Stories with Generative AI
Storytelling is an integral part of human culture and significantly impacts
cognitive and socio-emotional development and connection. Despite the
importance of interactive visual storytelling, the process of creating such
content requires specialized skills and is labor-intensive. This paper
introduces ID.8, an open-source system designed for the co-creation of visual
stories with generative AI. We focus on enabling an inclusive storytelling
experience by simplifying the content creation process and allowing for
customization. Our user evaluation confirms a generally positive user
experience in domains such as enjoyment and exploration, while highlighting
areas for improvement, particularly in immersiveness, alignment, and
partnership between the user and the AI system. Overall, our findings indicate
promising possibilities for empowering people to create visual stories with
generative AI. This work contributes a novel content authoring system, ID.8,
and insights into the challenges and potential of using generative AI for
multimedia content creation
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