Governance and information governance: some ethical considerations within an expanding information society

Governance and information governance ought to be an integral part of any government or organisations information and business strategy. More than ever before information and knowledge can be produced, exchanged, shared and communicated through many different mediums. Whilst sharing information and knowledge provides many benefits it also provides many challenges and risks to governments, global organisations and the individual citizen. Information governance is one element of a governance and compliance programme, but an increasingly important one, because many regulations apply to how information is managed and protected from theft and abuse, much of which resides with external agencies usually outside the control of the individual citizen. This paper explores some of the compliance and quality issues within governance and information governance including those ethical concerns as related to individual citizens and multiple stakeholders engaged directly or indirectly in the governance process

AI management an exploratory survey of the influence of GDPR and FAT principles

As organisations increasingly adopt AI technologies, a number of ethical issues arise. Much research focuses on algorithmic bias, but there are other important concerns arising from the new uses of data and the introduction of technologies which may impact individuals. This paper examines the interplay between AI, Data Protection and FAT (Fairness, Accountability and Transparency) principles. We review the potential impact of the GDPR and consider the importance of the management of AI adoption. A survey of data protection experts is presented, the initial analysis of which provides some early insights into the praxis of AI in operational contexts. The findings indicate that organisations are not fully compliant with the GDPR, and that there is limited understanding of the relevance of FAT principles as AI is introduced. Those organisations which demonstrate greater GDPR compliance are likely to take a more cautious, risk-based approach to the introduction of AI

Practices, policies, and problems in the management of learning data: A survey of libraries’ use of digital learning objects and the data they create

This study analyzed libraries’ management of the data generated by library digital learning objects (DLO’s) such as forms, surveys, quizzes, and tutorials. A substantial proportion of respondents reported having a policy relevant to learning data, typically a campus-level policy, but most did not. Other problems included a lack of access to library learning data, concerns about student privacy, inadequate granularity or standardization, and a lack of knowledge about colleagues’ practices. We propose more dialogue on learning data within libraries, between libraries and administrators, and across the library profession

The nature of practitioner research: critical distance, power and ethics

Researching within one’s place of practice allows the researcher to have the unique position of knowing the participants and the research context. The relationship the participants have with the researcher will impact upon the disclosure of information differently than research conducted by someone outside the area of practice. This can be a benefit and a drawback for the participants, the area of practice and the researcher. However, as is demonstrated within this paper, the role the researcher adopts throughout the process of gathering information is not always clear. As a student on the Doctorate of Education programme myself, the nature of practitioner research and the complexities of this type of research is of great interest to me. Beginning to develop my own research project through this taught programme has allowed an opportunity to think through these challenges and wrestle with the complexity and contradiction, dilemma and incongruity which emerges from being a researching practitioner. Within this piece it is suggested that these quandaries can be considered from the perspective of critical distance, relationships and power and ethical considerations. The idea of considering these conflicts reflexively will be explored here. Although this discussion was not based on empirical research findings as such, it is anticipated that this piece will further the understanding of practitioner research in higher education from the position of being a student and through scholastic analysis of the Ed D programme providing a particular perspective on the nature of research

Responsible Data Governance of Neuroscience Big Data

Open access article.Current discussions of the ethical aspects of big data are shaped by concerns regarding the social consequences of both the widespread adoption of machine learning and the ways in which biases in data can be replicated and perpetuated. We instead focus here on the ethical issues arising from the use of big data in international neuroscience collaborations. Neuroscience innovation relies upon neuroinformatics, large-scale data collection and analysis enabled by novel and emergent technologies. Each step of this work involves aspects of ethics, ranging from concerns for adherence to informed consent or animal protection principles and issues of data re-use at the stage of data collection, to data protection and privacy during data processing and analysis, and issues of attribution and intellectual property at the data-sharing and publication stages. Significant dilemmas and challenges with far-reaching implications are also inherent, including reconciling the ethical imperative for openness and validation with data protection compliance and considering future innovation trajectories or the potential for misuse of research results. Furthermore, these issues are subject to local interpretations within different ethical cultures applying diverse legal systems emphasising different aspects. Neuroscience big data require a concerted approach to research across boundaries, wherein ethical aspects are integrated within a transparent, dialogical data governance process. We address this by developing the concept of “responsible data governance,” applying the principles of Responsible Research and Innovation (RRI) to the challenges presented by the governance of neuroscience big data in the Human Brain Project (HBP)

Enhancing reuse of data and biological material in medical research : from FAIR to FAIR-Health

The known challenge of underutilization of data and biological material from biorepositories as potential resources formedical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability—entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)—are likely to address only parts of the problem. In this article,we argue that biologicalmaterial and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks.Wepropose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.peer-reviewe

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier

As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property. Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of 'grey data' about individuals in their daily activities of research, teaching, learning, services, and administration. The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities are exploiting these data for research, learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities are besieging universities with requests for access to data or for partnerships to mine them. The privacy frontier facing research universities spans open access practices, uses and misuses of data, public records requests, cyber risk, and curating data for privacy protection. This paper explores the competing values inherent in data stewardship and makes recommendations for practice, drawing on the pioneering work of the University of California in privacy and information security, data governance, and cyber risk.Comment: Final published version, Sept 30, 201

Ethical Implications of Predictive Risk Intelligence

open access articleThis paper presents a case study on the ethical issues that relate to the use of Smart Information Systems (SIS) in predictive risk intelligence. The case study is based on a company that is using SIS to provide predictive risk intelligence in supply chain management (SCM), insurance, finance and sustainability. The pa-per covers an assessment of how the company recognises ethical concerns related to SIS and the ways it deals with them. Data was collected through a document review and two in-depth semi-structured interviews. Results from the case study indicate that the main ethical concerns with the use of SIS in predictive risk intelli-gence include protection of the data being used in predicting risk, data privacy and consent from those whose data has been collected from data providers such as so-cial media sites. Also, there are issues relating to the transparency and accountabil-ity of processes used in predictive intelligence. The interviews highlighted the issue of bias in using the SIS for making predictions for specific target clients. The last ethical issue was related to trust and accuracy of the predictions of the SIS. In re-sponse to these issues, the company has put in place different mechanisms to ensure responsible innovation through what it calls Responsible Data Science. Under Re-sponsible Data Science, the identified ethical issues are addressed by following a code of ethics, engaging with stakeholders and ethics committees. This paper is important because it provides lessons for the responsible implementation of SIS in industry, particularly for start-ups. The paper acknowledges ethical issues with the use of SIS in predictive risk intelligence and suggests that ethics should be a central consideration for companies and individuals developing SIS to create meaningful positive change for society

Balancing and integrating basic values in the development of organic regulations and standards: proposal for a procedure using case studies of conflicting areas

The basic aim of the report is to develop a procedure for the integration of the ethical value base of organic farming into standards and regulations. For this it is necessary to identify the core ethical value of organic production, consider their coherence and relate them to existing practice of organic food and farming. Ethical values are per se in need of interpretation. It is therefore also necessary to consider the process of decision-making, when aiming to achieve a coherent integration of such values in the structure of a standard or regulation. In line with the European Action Plan for organic food and farming from 2004 the Project EEC 2092/91 (Organic) Revision supports the idea that delegating a larger role to values and basic principles will help to harmonise the rules, provide room for flexibility in implementation and to simplify the European Regulation for organic production. It is important to include basic values in standards and regulations, because organic farming is value based and all actors/stakeholders have value expectations, including consumers who the regulation wants to protect. Standards and regulations form the basis of a virtual contract between the consumer and the producers. By following the practices set out in the standards, producers give a promise to the consumer to deliver on additional ethical values, beyond the legal minimum standards for conventional agriculture and food. The growing and globalised organic market and the involvement of large companies have resulted in renewed interest in the values and principles of organic farming. There has been concern that the organic food and farming sector is becoming more conventionalised, and has lost touch with its basic values. Thus it will no longer function effectively as a real alternative to general agriculture for consumers, producers and also for policy makers. The report analyses what core ethical value are associated with organic agriculture and should therefore be considered for inclusion in a regulation. This value base is contrasted with the existing Regulation (EEC) 2092/91 and with examples of current practice of organic agriculture in Europe. The implications of including ethical values in the structure of a regulation for decisionmaking are considered. Following on from the European Action Plan a process of total revision of the EU regulation on organic production is underway. A new European Regulation for organic production was adopted by the European Council of Ministers in June 2006 and will come into force in Jan 2009. The text of the near final proposal from December 2006 has been considered in several sections of the report. The report finishes with some conclusions and recommendations for the EU Commission and other standard setting bodies regarding the choice and roles of values in organic standard, the rules for decision-making processes in relation to integrating values, and regarding the ongoing revision of the organic regulation in Europe