Potential Impact Of Artificial Intelligence Research Articles

The Potential Role of AI in Anticipating Futures from a Design Process Perspective: From the Reflexive Description of “Design” to a Discussion of Influences by the Inclusion of AI in the Futures Research Process

The key question behind this article is, How is AI impacting futures research, with particular focus on foresight and design futures? To address such question, this article reports on selected epistemological and methodological traits of design futures research, on the nature of Artificial Intelligence (AI), and the potential impact of AI on the design futures domain, offering a conceptual model as theoretical junction between the domains of foresight and design. Key topics and themes addressed were selectively focused on foresight, design, design futures, weak signals, and their role in relationship with visioning and the image, AI, and a multidisciplinary discussion of how these fields relate to each other. This article is based on desk research and dialogue among the two authors, both profiled professional experts in their respective fields of design futures and AI, with a track of experience both in academic and applied research. Therefore, sources include a rich texture of bibliographic information, combined with selected input from ongoing research activities on AI and related trends, as performed in the professional field.

Digital literacies and children’s personalized books: Locating the ‘self’

This conceptual article discusses the role of digital literacies in personalized books, in relation to children’s developing sense of self, and in terms of assessing the potential impact of artificial intelligence (AI). Personalized books contain children’s data, such as their name, gender or image, and they can be created by readers or automatically by the publisher. Some personalized books are e-books enhanced with artificial intelligence, and some can be ordered as paperbacks. We discuss this use of children’s personal data in terms of the social location of the self with regard to subjective and objective dimensions. We draw on a map metaphor, in which objective space requires readers to locate themselves in an unknown ‘A-to-B’ space and subjective space provides an individually oriented world of ‘me-to-B’. By drawing on examples of personalized books and their use by parents and young children, we discuss how personalization troubles the borders between readers’ me-to-B and A-to-B space experiences, leading to possible confusion in the sense of self. We conclude by noting that AI-enhanced personalized texts can reduce personal agency with respect to formulating a sense of identity as a child.

Making AI Work in Indian Education

This paper explores the potential impact of Artificial Intelligence (AI) on educational processes and outcomes. It examines key concerns with respect to rights-based development that AI policy and programming frameworks should address to support ethical, inclusive and universal education in India. The paper is based on interviews with educationists and organisations working in the area of AI and education, and desk research conducted by IT for Change.

Artificial intelligence in diagnostic imaging: impact on the radiography profession.

The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radiographer role is lacking. This paper discusses the potential impact of artificial intelligence (AI) on the radiography profession by assessing current workflow and cross-mapping potential areas of AI automation such as procedure planning, image acquisition and processing. We also highlight the opportunities that AI brings including enhancing patient-facing care, increased cross-modality education and working, increased technological expertise and expansion of radiographer responsibility into AI-supported image reporting and auditing roles.

Influence of Artificial Intelligence on Canadian Medical Students' Preference for Radiology Specialty: ANational Survey Study

Artificial intelligence (AI) has the potential to transform the clinical practice of radiology. This study investigated Canadian medical students' perceptions of the impact of AI on radiology, and their influence on the students' preference for radiology specialty. In March 2018, an anonymous online survey was distributed to students at all 17 Canadian medical schools. Among 322 respondents, 70 students considered radiology as the top specialty choice, and 133 as among the top three choices. Only a minority (29.3%) of respondents agreed AI would replace radiologists in foreseeable future, but a majority (67.7%) agreed AI would reduce the demand for radiologists. Even among first-choice respondents, 48.6% agreed AI caused anxiety when considering the radiology specialty. Furthermore, one-sixth of respondents who would otherwise rank radiology as the first choice would not consider radiology because of the anxiety about AI. Prior significant exposure to radiology and high confidence in understanding of AI were shown to decrease the anxiety level. Interested students valued the opinions of local radiologists, radiology conferences, and journals. Students were most interested in "expert opinions on AI" and "discussing AI in preclinical radiology lectures" to understand the impact of AI. Anxiety related to "displacement" (not "replacement") of radiologists by AI discouraged many medical students from considering the radiology specialty. The radiology community should educate medical students about the potential impact of AI, to ensure radiology is perceived as a viable long-term career choice.

Artificial intelligence and higher education

Hardly a day goes by without some reference to the potential impact of artificial intelligence in our lives. I believe that universities both in the United States and around the world will also experience significant change brought about through AI.

Demystification of AI-driven medical image interpretation: past, present and future.

The recent explosion of 'big data' has ushered in a new era of artificial intelligence (AI) algorithms in every sphere of technological activity, including medicine, and in particular radiology. However, the recent success of AI in certain flagship applications has, to some extent, masked decades-long advances in computational technology development for medical image analysis. In this article, we provide an overview of the history of AI methods for radiological image analysis in order to provide a context for the latest developments. We review the functioning, strengths and limitations of more classical methods as well as of the more recent deep learning techniques. We discuss the unique characteristics of medical data and medical science that set medicine apart from other technological domains in order to highlight not only the potential of AI in radiology but also the very real and often overlooked constraints that may limit the applicability of certain AI methods. Finally, we provide a comprehensive perspective on the potential impact of AI on radiology and on how to evaluate it not only from a technical point of view but also from a clinical one, so that patients can ultimately benefit from it. KEY POINTS: • Artificial intelligence (AI) research in medical imaging has a long history • The functioning, strengths and limitations of more classical AI methods is reviewed, together with that of more recent deep learning methods. • A perspective is provided on the potential impact of AI on radiology and on its evaluation from both technical and clinical points of view.

Artificial Intelligence and Economic Growth

This paper examines the potential impact of artificial intelligence (A.I.) on economic growth. We model A.I. as the latest form of automation, a broader process dating back more than 200 years. Electricity, internal combustion engines, and semiconductors facilitated automation in the last century, but A.I. now seems poised to automate many tasks once thought to be out of reach, from driving cars to making medical recommendations and beyond. How will this affect economic growth and the division of income between labor and capital? What about the potential emergence of “singularities” and “superintelligence,” concepts that animate many discussions in the machine intelligence community? How will the linkages between A.I. and growth be mediated by firm-level considerations, including organization and market structure? The goal throughout is to refine a set of critical questions about A.I. and economic growth and to contribute to shaping an agenda for the field. One theme that emerges is based on Baumol’s “cost disease” insight: growth may be constrained not by what we are good at but rather by what is essential and yet hard to improve.

The potential impact of artificial intelligence on the practice of OR

The fantastic claims made by Artificial Intelligence Experts could lead us to think that computers will inevitably have a great impact on disciplines such as OR, even to the extent of displacing them. However, we should question whether there is any evidence to support these claims. This paper considers the present capabilities of computers and looks at the impact that the AI community has had on the practice of OR. It also examines the potential success of current research and lists some of the obstacles to development. The evidence suggests that although AI will provide significant support to the work of OR researchers, the impact of AI on the OR community will not be as great as the claims suggest.