How Big Data Transforms Manufacturing Industry

This article describes an overview of what Big Data is and explains how it transforms the manufacturing industry. First, this article defines what Big Data means for the manufacturing industry. It explains four advantages about Big Data analytics and their benefits to manufacturing. Then, it describes about what ethical issues of Big Data are. Next, it discusses more deeply about the ethical issues of Big Data in manufacturing with both individual and organizational perspectives. Finally, this article sums up with some principles to show the ethical governance of the interests of Big Data stakeholders.

The Urgency of the Implementation of Public Administration Ethical Governance to Realize Good Governance

This study analyzes the urgency of implementing public administration ethics to realize good governance. This study uses a qualitative method with a case study approach. The data sources used in this study are primary and secondary data. Preliminary data was collected from interviews and questionnaires to respondents, while secondary data was collected through the literature study method. The location of this research is in one of the sub-district offices in the Sumedang District. Respondents who were given a questionnaire totaling 100 people living around the sub-district were selected based on the random sampling method. Based on the data and analysis of research results, it can be seen that sub-district employees in Sumedang District still have not implemented bureaucratic ethical governance properly. Government governance has not been able to absorb and develop more advanced management values. The problem arises because of the following: learning culture, processes, tools and techniques, and skill and motivation. This should be a concern, especially by the government, to create good governance, which is indicated by the high public trust in the government.

The social licence for data-intensive health research: towards co-creation, public value and trust

Background The rise of Big Data-driven health research challenges the assumed contribution of medical research to the public good, raising questions about whether the status of such research as a common good should be taken for granted, and how public trust can be preserved. Scandals arising out of sharing data during medical research have pointed out that going beyond the requirements of law may be necessary for sustaining trust in data-intensive health research. We propose building upon the use of a social licence for achieving such ethical governance. Main text We performed a narrative review of the social licence as presented in the biomedical literature. We used a systematic search and selection process, followed by a critical conceptual analysis. The systematic search resulted in nine publications. Our conceptual analysis aims to clarify how societal permission can be granted to health research projects which rely upon the reuse and/or linkage of health data. These activities may be morally demanding. For these types of activities, a moral legitimation, beyond the limits of law, may need to be sought in order to preserve trust. Our analysis indicates that a social licence encourages us to recognise a broad range of stakeholder interests and perspectives in data-intensive health research. This is especially true for patients contributing data. Incorporating such a practice paves the way towards an ethical governance, based upon trust. Public engagement that involves patients from the start is called for to strengthen this social licence. Conclusions There are several merits to using the concept of social licence as a guideline for ethical governance. Firstly, it fits the novel scale of data-related risks; secondly, it focuses attention on trustworthiness; and finally, it offers co-creation as a way forward. Greater trust can be achieved in the governance of data-intensive health research by highlighting strategic dialogue with both patients contributing the data, and the public in general. This should ultimately contribute to a more ethical practice of governance.

A framework for a data interest analysis of artificial intelligence

This article makes a case for a data interest analysis of artificial intelligence (AI) that explores how different interests in data are empowered or disempowered by design. The article uses the EU High-Level Expert Group on AI’s Ethics Guidelines for Trustworthy AI as an applied ethics approach to data interests with a human-centric ethical governance framework and accordingly suggests ethical questions that will help resolve conflicts between data interests in AI design

Evaluating the prospects for university-based ethical governance in artificial intelligence and data-driven innovation

There has been considerable debate around the ethical issues raised by data-driven technologies such as artificial intelligence. Ethical principles for the field have focused on the need to ensure that such technologies are used for good rather than harm, that they enshrine principles of social justice and fairness, that they protect privacy, respect human autonomy and are open to scrutiny. While development of such principles is well advanced, there is as yet little consensus on the mechanisms appropriate for ethical governance in this field. This paper examines the prospects for the university ethics committee to undertake effective review of research conducted on data-driven technologies in the university context. Challenges identified include: the relatively narrow focus of university-based ethical review on the human subjects research process and lack of capacity to anticipate downstream impacts; the difficulties of accommodating the complex interplay of academic and commercial interests in the field; and the need to ensure appropriate expertise from both specialists and lay voices. Overall, the challenges identified sharpen appreciation of the need to encourage a joined-up and effective system of ethical governance that fosters an ethical culture rather than replacing ethical reflection with bureaucracy.

Philosophical evaluation of the conceptualisation of trust in the NHS’ Code of Conduct for artificial intelligence-driven technology

The UK Government’s Code of Conduct for data-driven health and care technologies, specifically artificial intelligence (AI)-driven technologies, comprises 10 principles that outline a gold-standard of ethical conduct for AI developers and implementers within the National Health Service. Considering the importance of trust in medicine, in this essay I aim to evaluate the conceptualisation of trust within this piece of ethical governance. I examine the Code of Conduct, specifically Principle 7, and extract two positions: a principle of rationally justified trust that posits trust should be made on sound epistemological bases and a principle of value-based trust that views trust in an all-things-considered manner. I argue rationally justified trust is largely infeasible in trusting AI due to AI’s complexity and inexplicability. Contrarily, I show how value-based trust is more feasible as it is intuitively used by individuals. Furthermore, it better complies with Principle 1. I therefore conclude this essay by suggesting the Code of Conduct to hold the principle of value-based trust more explicitly.