AI ethics in February 2022

Abstract Artificial intelligence (AI) governance is required to reap the benefits and manage the risks brought by AI systems. This means that ethical principles, such as fairness, need to be translated into practicable AI governance processes. A concise AI governance definition would allow researchers and practitioners to identify the constituent parts of the complex problem of translating AI ethics into practice. However, there have been few efforts to define AI governance thus far. To bridge t

Post-acute sequelae of COVID (PASC), usually referred to as 'Long COVID' (a phenotype of COVID-19), is a relatively frequent consequence of SARS-CoV-2 infection, in which symptoms such as breathlessness, fatigue, 'brain fog', tissue damage, inflammation, and coagulopathies (dysfunctions of the blood coagulation system) persist long after the initial infection. It bears similarities to other post-viral syndromes, and to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Many regulatory

Abstract Research on sustainable development is significantly influenced by the trade‐off between the economic, social and environmental performance of businesses. Industry 4.0 development is a key business priority due to the promise of exponential increase in productivity, time efficiencies and cost reduction. However, Industry 4.0 development has been slow. Notably, human actors remain central to Industry 4.0, while the social responsibility component of sustainable development is a key prero

Importance: To better understand the emerging role of artificial intelligence (AI) in surgical training, efficacy of AI tutoring systems, such as the Virtual Operative Assistant (VOA), must be tested and compared with conventional approaches. Objective: To determine how VOA and remote expert instruction compare in learners' skill acquisition, affective, and cognitive outcomes during surgical simulation training. Design, Setting, and Participants: This instructor-blinded randomized clinical trial

Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020, indicating an increase of more than 50% since 2018. With the average cyber insurance claim rising from USD 145,000 in 2019 to USD 359,000 in 2020, there is a growing necessity for better cyber information sources, standardised databases, mandatory reporting and public awareness. This research analyses the extant academic and industry literature on cybersecurity and cyber risk management with a particular f

Explainability for artificial intelligence (AI) in medicine is a hotly debated topic. Our paper presents a review of the key arguments in favor and against explainability for AI-powered Clinical Decision Support System (CDSS) applied to a concrete use case, namely an AI-powered CDSS currently used in the emergency call setting to identify patients with life-threatening cardiac arrest. More specifically, we performed a normative analysis using socio-technical scenarios to provide a nuanced accoun

Artificial intelligence (AI)-synthesized text, audio, image, and video are being weaponized for the purposes of nonconsensual intimate imagery, financial fraud, and disinformation campaigns. Our evaluation of the photorealism of AI-synthesized faces indicates that synthesis engines have passed through the uncanny valley and are capable of creating faces that are indistinguishable-and more trustworthy-than real faces.

This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our study finds that most LA dashboards merely employ surface-level descriptive analytics, while only few go beyond and use predictive analytics. In response

Abstract This paper aimed to provide a holistic view of research that investigated online learning in higher education around the globe during COVID‐19 utilizing a bibliometric analysis. The researchers used co‐citation analysis and text mining afforded by VOSviewer to document and analyze research patterns and topics reported in peer‐reviewed documents published between January 2020 and August 2021. Findings of this study indicated that scholars from 103 countries or regions from the Global Nor

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill data into relevant information. We argue that animal ecologists can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge. Incorporating machine learning into ecological workflows could i

COVID-19 restrictions significantly affected SMEs, which have faced many challenges to their sustainability within this fragile new environment. This study proposes a holistic framework of sustainable performance by interrelating factors showing robust associations to produce this effect' for achieving sustainable performance in SMEs, through integrating the Technology Organisation Environment (TOE) and Resource Based View (RBV) models, to test how sustainable green practices can process the TOE

Abstract Companies increasingly deploy artificial intelligence (AI) technologies in their personnel recruiting and selection process to streamline it, making it faster and more efficient. AI applications can be found in various stages of recruiting, such as writing job ads, screening of applicant resumes, and analyzing video interviews via face recognition software. As these new technologies significantly impact people’s lives and careers but often trigger ethical concerns, the ethicality of the

A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transformation led by AI. Despite a growing interest in AI ethics, implementing AI-related technologies and initiatives responsibly in healthcare settings remains a challenge. In response to this topical chall