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Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016 (Mittelstadt et al. Big Data Soc 3(2), 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative concerns, and to offer actionable guidance for the governance of the design, development and deployment of algorithms.

Recent advances in the capability of digital information technologies—particularly due to advances in artificial intelligence (AI)—have invigorated the debate on the ethical issues surrounding their use. However, this debate has often been dominated by ‘Western’ ethical perspectives, values and interests, to the exclusion of broader ethical and socio-cultural perspectives. This imbalance carries the risk that digital technologies produce ethical harms and lack social acceptance, when the ethical norms and values designed into these technologies collide with those of the communities in which they are delivered and deployed. This special issue takes a step towards broadening the approach of digital ethics, by bringing together a range of cultural, social and structural perspectives on the ethical issues relating to digital information technology. Importantly, it refreshes and reignites the field of Intercultural Digital Ethics for the age of AI and ubiquitous computing.

This article addresses the question of how ‘Country of Origin Information’ (COI) reports—that is, research developed and used to support decision-making in the asylum process—can be published in an ethical manner. The article focuses on the risk that published COI reports could be misused and thereby harm the subjects of the reports and/or those involved in their development. It supports a situational approach to assessing data ethics when publishing COI reports, whereby COI service providers must weigh up the benefits and harms of publication based, inter alia, on the foreseeability and probability of harm due to potential misuse of the research, the public good nature of the research, and the need to balance the rights and duties of the various actors in the asylum process, including asylum seekers themselves. Although this article focuses on the specific question of ‘how to publish COI reports in an ethical manner’, it also intends to promote further research on data ethics in the asylum process, particularly in relation to refugees, where more foundational issues should be considered.

Incidence of human papillomavirus (HPV)-associated oral cancers is on the rise. However, epidemiological data of this subset of cancers are limited. Dental hospital poses a unique advantage in detection of HPV-positive oral malignancies. We assessed the utility of formalin-fixed paraffin-embedded (FFPE) tissues, which are readily available, for evaluation of high-risk HPV infection in oral cancer. For protocol standardization, we used 20 prospectively collected paired FFPE and fresh tissues of histopathologically confirmed oral cancer cases reported in Oral Medicine department of a dental hospital for comparative study. Only short PCRs (~ 200 bp) of DNA isolated using a modified xylene-free method displayed a concordant HPV result. For HPV analysis, we used additional 30 retrospectively collected FFPE tissues. DNA isolated from these specimens showed an overall 23.4% (11/47) HPV positivity with detection of HPV18. Comparison of HPV positivity from dental hospital FFPE specimens with overall HPV positivity of freshly collected oral cancer specimens (n = 55) from three cancer care hospitals of the same region showed notable difference (12.7%; 7/55). Further, cancer hospital specimens showed HPV16 positivity and displayed a characteristic difference in reported sub-sites and patient spectrum. Overall, using a xylene-free FFPE DNA isolation method clubbed with short amplicon PCR, we showed detection of HPV-positive oral cancer in dental hospitals.

Head and neck cancer (HNC) usually arises from squamous cells of the upper aerodigestive tract that line the mucosal surface in the head and neck region. In India, HNC is common in males, and it is the sixth most common cancer globally. Conventionally, HNC attributes to the use of alcohol or chewing tobacco. Over the past four decades, portions of human papillomavirus (HPV)-positive HNC are increasing at an alarming rate. Identification based on the etiological factors and molecular signatures demonstrates that these neoplastic lesions belong to a distinct category that differs in pathological characteristics and therapeutic response. Slow development in HNC therapeutics has resulted in a low 5-year survival rate in the last two decades. Interestingly, HPV-positive HNC has shown better outcomes following conservative treatments and immunotherapies. This raises demand to have a pre-therapy assessment of HPV status to decide the treatment strategy. Moreover, there is no HPV-specific treatment for HPV-positive HNC patients. Accumulating evidence suggests that phytochemicals are promising leads against HNC and show potential as adjuvants to chemoradiotherapy in HNC. However, only a few of these phytochemicals target HPV. The aim of the present article was to collate data on various leading phytochemicals that have shown promising results in the prevention and treatment of HNC in general and HPV-driven HNC. The review explores the possibility of using these leads against HPV-positive tumors as some of the signaling pathways are common. The review also addresses various challenges in the field that prevent their use in clinical settings.

Artificial Intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, which we term AI-Crime (AIC). We already know that AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing law enforcement and policy-makers with a synthesis of the current problems, and a possible solution space.

Parkinson’s disease is perhaps the most well-known neurodegenerative disorder that mainly occurs due to the loss of dopamine-producing neurons and consists of motor/non-motor symptoms. The progression of the symptoms is often varying from one person to another to the diversity of the disease. The condition causes a huge burden both on those affected, as well as their families. Accurate diagnosis is critical and challenging but still, no specific diagnostic process is available. The computer-aided diagnosis techniques of signalling and imaging processing are very helpful in the prediction and classification of PD. This review gives a brief description of different methods of classification for early detection and also highlights the most profitable research directions by focusing on continuous monitoring patterns of daily activities, interactions, and routine that may provide the data on status changes, clinical management, and controlling self-correction

Society is becoming increasingly dependent on data-rich, “Big Tech” platforms and social networks, such as Facebook and Google. But what happens to our data when these companies close or fail? Despite the high stakes involved, this topic has received only limited attention to date. In this article, we use the hypothetical failure of Facebook as a case study to analyse legal and ethical risks related to the closure of data-rich, Big Tech platforms. Focusing on the EU, we argue that existing governance frameworks are inadequate for addressing these risks and make preliminary recommendations with a view to setting an agenda for future research and policymaking on the demise of Big Tech platforms and data-rich companies more broadly.

Recent advances in the capability of digital information technology — particularly due to advances in artificial intelligence (AI) — have invigorated the debate on the ethical issues surrounding their use. However, this debate has often been dominated by ‘Western’ ethical perspectives, values and interests, to the exclusion of broader ethical and socio-cultural perspectives. This imbalance carries the risk that digital technologies produce ethical harms, and lack social acceptance, when the ethical norms and values designed into these technologies collide with those of the communities in which they are delivered and deployed. This special issue takes a step towards broadening the approach of digital ethics, by bringing together a range of cultural, social and structural perspectives on the ethical issues relating to digital information technology. Importantly, it refreshes and reignites the field of Intercultural Digital Ethics for the age of AI and ubiquitous computing.

Society is becoming increasingly dependent on data-rich, “Big Tech” platforms and social networks, such as Facebook and Google. But what happens to our data when these companies close or fail? Despite the high stakes involved, this topic has received only limited attention to date. In this article, we use the hypothetical failure of Facebook as a case study to analyse legal and ethical risks related to the closure of data-rich, Big Tech platforms. Focusing on the EU, we argue that existing governance frameworks are inadequate for addressing these risks and make preliminary recommendations with a view to setting an agenda for future research and policymaking on the demise of Big Tech platforms and data-rich companies more broadly.

Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime (AIC). AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space.

Recent advances in machine learning (ML) and Big Data techniques have facilitated the development of more sophisticated, automated consumer credit scoring models — a trend referred to as 'algorithmic credit scoring' in recognition of the increasing reliance on computer (particularly ML) algorithms for credit scoring. This chapter, which forms part of the 2018 collection of short essays 'Autonomous Systems and the Law', examines the rise of algorithmic credit scoring, and considers its implications for the regulation of consumer creditworthiness assessment and consumer credit markets more broadly. The chapter argues that algorithmic credit scoring, and the Big Data and ML technologies underlying it, offer both benefits and risks for consumer credit markets. On the one hand, it could increase allocative efficiency and distributional fairness in these markets, by widening access to, and lowering the cost of, credit, particularly for 'thin-file' and 'no-file' consumers. On the other hand, algorithmic credit scoring could undermine distributional fairness and efficiency, by perpetuating discrimination in lending against certain groups and by enabling the more effective exploitation of borrowers. The chapter considers how consumer financial regulation should respond to these risks, focusing on the UK/EU regulatory framework. As a general matter, it argues that the broadly principles and conduct-based approach of UK consumer credit regulation provides the flexibility necessary for regulators and market participants to respond dynamically to these risks. However, this approach could be enhanced through the introduction of more robust product oversight and governance requirements for firms in relation to their use of ML systems and processes. Supervisory authorities could also themselves make greater use of ML and Big Data techniques in order to strengthen the supervision of consumer credit firms. Finally, the chapter notes that cross-sectoral data protection regulation, recently updated in the EU under the GDPR, offers an important avenue to mitigate risks to consumers arising from the use of their personal data. However, further guidance is needed on the application and scope of this regime in the consumer financial context.

This article addresses the question of how ‘Country of Origin Information’ (COI) reports — that is, research developed and used to support decision-making in the asylum process — can be published in an ethical manner. The article focuses on the risk that published COI reports could be misused and thereby harm the subjects of the reports and/or those involved in their development. It supports a situational approach to assessing data ethics when publishing COI reports, whereby COI service providers must weigh up the benefits and harms of publication based, inter alia, on the foreseeability and probability of harm due to potential misuse of the research, the public good nature of the research, and the need to balance the rights and duties of the various actors in the asylum process, including asylum seekers themselves. Although this article focuses on the specific question of ‘how to publish COI reports in an ethical manner’, it also intends to promote further research on data ethics in the asylum process, particularly in relation to refugees, where more foundational issues should be considered.

By definition, the company is an association of persons coming together with pooling of resources for economic motives with pooling of resources. Its managers need to be ethical in dealing and managing other persons' resources. The accountability is there towards investors and other stake holders but still there have been many issues in governance of companies in India. The present paper is an attempt to take an over view of corporate governance practices in India. In the private sector, the Satyam case has resulted in eye opening shortcomings of in the corporate functioning. The greed and negligence of related parties, independent directors, auditors, bankers and others have led to this manipulation by the Managing Director Raju for many years. This has brought out many changes in the Indian Companies Act. The clause 49 has been improved, and the responsibilities of Key Managerial Personnel have been introduced in a serious manner. The fiduciary responsibilities of directors have become the focal point of all debates on the topic. The study seeks to sum up recent changes in Indian regulatory system governing the companies especially Indian Companies Act, 2013.