The Case for Generative AI in Scholarly Practice

The Case for Generative AI in Scholarly Practice
Author: Chris Berg
Publisher:
Total Pages: 0
Release: 2023
Genre:
ISBN:

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This paper defends the use of generative artificial intelligence (AI) in scholarship and argues for its legitimacy as a valuable tool for contemporary research practice. It uses a emergent property rights model of writing to shed light on the evolution of scholarly norms and practices in academic practice. The paper argues that generative AI extends the capital-intensive nature of modern academic writing. The paper discussing three potential uses for AI models in research practice: AI as a mentor, AI as an analytic tool, and AI as a writing tool. The paper considers how the use of generative AI interacts with two critical norms in scholarship: norms around authorship attribution and credits for contributions, and the norm against plagiarism. It concludes that the effective use of generative AI is a legitimate research practice for scholars seeking to experiment with new technologies that might enhance their productivity.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
Total Pages: 385
Release: 2020-06-21
Genre: Computers
ISBN: 0128184396

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Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Constructivism in Mathematics, Vol 1

Constructivism in Mathematics, Vol 1
Author: A.S. Troelstra
Publisher: Elsevier Science
Total Pages: 355
Release: 1988-07-15
Genre: Mathematics
ISBN: 9780444702661

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These two volumes cover the principal approaches to constructivism in mathematics. They present a thorough, up-to-date introduction to the metamathematics of constructive mathematics, paying special attention to Intuitionism, Markov's constructivism and Martin-Lof's type theory with its operational semantics. A detailed exposition of the basic features of constructive mathematics, with illustrations from analysis, algebra and topology, is provided, with due attention to the metamathematical aspects. Volume 1 is a self-contained introduction to the practice and foundations of constructivism, and does not require specialized knowledge beyond basic mathematical logic. Volume 2 contains mainly advanced topics of a proof-theoretical and semantical nature.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: David Riaño
Publisher: Springer
Total Pages: 431
Release: 2019-06-19
Genre: Computers
ISBN: 303021642X

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This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Topics in General Topology

Topics in General Topology
Author: K. Morita
Publisher: Elsevier
Total Pages: 761
Release: 1989-08-04
Genre: Mathematics
ISBN: 0080879888

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Being an advanced account of certain aspects of general topology, the primary purpose of this volume is to provide the reader with an overview of recent developments.The papers cover basic fields such as metrization and extension of maps, as well as newly-developed fields like categorical topology and topological dynamics. Each chapter may be read independently of the others, with a few exceptions. It is assumed that the reader has some knowledge of set theory, algebra, analysis and basic general topology.

Case Study Research in Practice

Case Study Research in Practice
Author: Helen Simons
Publisher: SAGE Publications
Total Pages: 201
Release: 2009-06-05
Genre: Social Science
ISBN: 076196424X

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Case Study Research in Practice explores the theory and practice of case study research. Helen Simons draws on her extensive experience of teaching and conducting case study to provide a comprehensive and practical account of how to design, conduct and communicate case study research. It addresses questions often raised by students and common misconceptions about case research. In four sections the book covers - Rationale, concept and design of case study research - Methods, ethics and reflexivity in case study - Interpreting, analyzing and reporting the case - Generalizing and theorizing in case study research Rich with 'tales from the field' and summary memos as an aide-memoire to future action, the book provides fresh insights and challenges for researchers to guide their practice of case study research. This is an ideal text for those studying and conducting case study research in education, health and social care, and related social science disciplines. Helen Simons is Professor Emeritus of Education University of Southampton

Deploying Machine Learning

Deploying Machine Learning
Author: Robbie Allen
Publisher: Addison-Wesley Professional
Total Pages: 99998
Release: 2019-05
Genre: Computers
ISBN: 9780135226209

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Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.

Advanced Applications of Generative AI and Natural Language Processing Models

Advanced Applications of Generative AI and Natural Language Processing Models
Author: Obaid, Ahmed J.
Publisher: IGI Global
Total Pages: 505
Release: 2023-12-21
Genre: Computers
ISBN:

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The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.

Unfreeze: How to Create a High Growth Economy After the Pandemic

Unfreeze: How to Create a High Growth Economy After the Pandemic
Author: Dr Darcy W.E. Allen
Publisher: American Institute for Economic Research
Total Pages: 165
Release: 2020-05-01
Genre: Business & Economics
ISBN: 1630692034

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We spell out the policy settings necessary for the rapid adaptation and market re-coordination that is required to resuscitate the economy. We explain why a return to business as usual is simply not enough to get everyone working again. A period of high growth prosperity will be imperative to deal with the costs of the freeze. This book tackles the tough questions and fills some of the current void of ideas and thinking about economic recovery. We develop a framework and principles for an institutional re-build, presenting a path to recovery based on the ideas of private governance, permissionless innovation, and entrepreneurial dynamism. “Economies are not like video games that can be paused and then unpaused with no effect. Freezing an economy causes systematic problems, and unfreezing it requires systematic solutions. This book is a much needed well-researched study on what it will take to get the world up and running again." ~ Jason Brennan The American Institute for Economic Research in Great Barrington, Massachusetts, was founded in 1933 as the first independent voice for sound economics in the United States. Today it publishes ongoing research, hosts educational programs, publishes books, sponsors interns and scholars, and is home to the world-renowned Bastiat Society and the highly respected Sound Money Project. The American Institute for Economic Research is a 501c3 public charity.

AI and education

AI and education
Author: Miao, Fengchun
Publisher: UNESCO Publishing
Total Pages: 50
Release: 2021-04-08
Genre: Political Science
ISBN: 9231004476

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Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]