scholarly journals The Language Labyrinth: Constructive Critique on the Terminology Used in the AI Discourse

2021 ◽  
pp. 87-102
Author(s):  
Rainer Rehak

In the interdisciplinary field of artificial intelligence (AI) the problem of clear terminology is especially momentous. This paper claims, that AI debates are still characterised by a lack of critical distance to metaphors like ‘training’, ‘learning’ or ‘deciding’. As consequence, reflections regarding responsibility or potential use-cases are greatly distorted. Yet, if relevant decision-makers are convinced that AI can develop an ‘understanding’ or properly ‘interpret’ issues, its regular use for sensitive tasks like deciding about social benefits or judging court cases looms. The chapter argues its claim by analysing central notions of the AI debate and tries to contribute by proposing more fitting terminology and hereby enabling more fruitful debates. It is a conceptual work at the intersection of critical computer science and philosophy of language.

Author(s):  
Ammu Anna Mathew ◽  
Vivekanandan S.

The recent developments in multi-modular sensor technology for analyzing physiological and psychological activities have brought a breakthrough in the biomedical engineering thereby aiding the real-time monitoring of various vital signals. The monitoring of circadian rhythms and EEG signals keeps a proper observation on sleep and analyzes various sleep disorders. The sleep patterns related to disease and wellness applications can be analyzed with the help of multi-sensor-generated data. Several challenges such as performance evaluation, data storage, processing and integration, modeling, and interpretation as well as curation are to be overcome in this field for expansion of this technology in the future. The digitalization of sleep is an interdisciplinary field of research incorporating neuroscience, bioengineering, epidemiology, clinical medicine, computer science, and electrical engineering. This chapter discusses various sleep disorders, AI, analysis, and applications available. Finally, the challenges and future scope are also discussed followed by the conclusion.


Author(s):  
Francesco Galofaro

AbstractThe paper presents a semiotic interpretation of the phenomenological debate on the notion of person, focusing in particular on Edmund Husserl, Max Scheler, and Edith Stein. The semiotic interpretation lets us identify the categories that orient the debate: collective/individual and subject/object. As we will see, the phenomenological analysis of the relation between person and social units such as the community, the association, and the mass shows similarities to contemporary socio-semiotic models. The difference between community, association, and mass provides an explanation for the establishment of legal systems. The notion of person we inherit from phenomenology can also be useful in facing juridical problems raised by the use of non-human decision-makers such as machine learning algorithms and artificial intelligence applications.


Author(s):  
Gabrielle Samuel ◽  
Jenn Chubb ◽  
Gemma Derrick

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem.


2003 ◽  
Vol 30 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Dafna Fisher-Gewirtzman ◽  
Israel A Wagner

This paper reports on a primary metric tool developed in a collaboration between an architecture researcher and a computer science researcher. The development of this tool emerged from the concept that the spatial openness (SO)—the volume of free space measured from all possible observation points—is an important quality indicator of alternative spatial configurations within given constraints; this concept is based on the idea that the geometry and morphology of the built-up environment influence perception. Previous work showed that comparative SO measurements in alternative spatial configurations are correlated with the comparative perceived density, and in particular that a higher value of SO indicates a lower perceived density. We present a feasible 3D computational method for measuring SO and demonstrate its potential use in the design process. The SO metric is a step towards the development of quantitative comparative evaluation of building shapes and spatial configurations related to the 3D observation of open space.


Janus Head ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 53-66
Author(s):  
Hub Zwart ◽  

This paper subjects Dan Brown’s most recent novel Origin to a philosophical reading. Origin is regarded as a literary window into contemporary technoscience, inviting us to explore its transformative momentum and disruptive impact, focusing on the cultural significance of artificial intelligence and computer science: on the way in which established world-views are challenged by the incessant wave of scientific discoveries made possible by super-computation. While initially focusing on the tension between science and religion, the novel’s attention gradually shifts to the increased dependence of human beings on smart technologies and artificial (or even “synthetic”) intelligence. Origin’s message, I will argue, reverberates with Oswald Spengler’s The Decline of the West, which aims to outline a morphology of world civilizations. Although the novel starts with a series of oppositions, most notably between religion and science, the eventual tendency is towards convergence, synthesis and sublation, exemplified by Sagrada Família as a monumental symptom of this transition. Three instances of convergence will be highlighted, namely the convergence between science and religion, between humanity and technology and between the natural sciences and the humanities.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.


2019 ◽  
Vol 53 (6) ◽  
pp. 759-766
Author(s):  
Mark Mayer ◽  
Angelica Canedo ◽  
Tam Dinh ◽  
Madelyn Low ◽  
Ariel Ortiz ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Kimberly Stowers ◽  
Lisa L. Brady ◽  
Christopher MacLellan ◽  
Ryan Wohleber ◽  
Eduardo Salas

In response to calls for research to improve human-machine teaming (HMT), we present a “perspective” paper that explores techniques from computer science that can enhance machine agents for human-machine teams. As part of this paper, we (1) summarize the state of the science on critical team competencies identified for effective HMT, (2) discuss technological gaps preventing machines from fully realizing these competencies, and (3) identify ways that emerging artificial intelligence (AI) capabilities may address these gaps and enhance performance in HMT. We extend beyond extant literature by incorporating recent technologies and techniques and describing their potential for contributing to the advancement of HMT.


Author(s):  
Susan C. Herring ◽  
Christine Ogan ◽  
Manju Ahuja ◽  
Jean C. Robinson

The “shrinking pipeline” of women who ascend through the ranks in computer science education programs and careers is by now a familiar problem. Women drop out at rates faster than men at all levels of educational and professional advancement, resulting in a gender gap especially pronounced at the highest levels of the computing workforce, and that has not narrowed appreciably at any level in more than 20 years (Camp, 1997; ITAA, 2005; Vegso, 2005). Efforts to move more women into the pipeline at lower levels have met with limited success (cf. the Carnegie Mellon experience as reported by Margolis & Fisher, 2002); girls and women still express less interest than boys and men in studying computer science and pursuing information technology (IT) careers (Bentson, 2000; Vegso, 2005). A reason often cited in the literature is the masculine culture of many computer science programs and IT workplaces, which is perceived by many women as alien and unwelcoming (Bentson, 2000; Spertus, 1991; Turkle, 1988). Even when institutions make efforts to treat women and men equally or accord women special consideration in admissions and hiring decisions, attitudes discouraging women from entering computing persist, both within the institutions and in society at large. Sometimes these attitudes are expressed overtly: Underground “hacker” culture is notoriously antagonistic to women (Gilboa, 1996), and even mainstream computer aficionados respond with resistance and sexist jokes to proposals to recruit more girls and women to study computer science (Slashdot.org, 2005). Moreover, there is a widespread perception that computer experts are socially-isolated “geeks” or “nerds” obsessed with technology, a mode of being that women, who tend to be more socially oriented, find unappealing (Margolis & Fisher, 2002; Turkle, 1988). Fortunately, the situation for computer science does not tell the whole story. In the latter part of the 20th century, the expansion of computing and the Internet fueled the rise of applied IT fields in which technical skills, rather than being developed for their own sake, are increasingly put to use in the service of human needs. Applied fields, such as information science, information systems and instructional technology, have gained strength, and a new interdisciplinary field, informatics, has emerged. At the same time, interest in computer science itself is declining, especially among women (ITAA, 2005; Vegso, 2005). In this article, we explore the possibility that applied IT fields may provide more women-friendly cultures while still focused on technology. The larger question underlying this exploration is: Does applied IT education have the potential to bridge the “gender computing gap”?


Sign in / Sign up

Export Citation Format

Share Document