SoDIS SEPIA - collaborative partnerships in software engineering research

The Centre for Information Technology Research (CITRUS) launched in 2002 had the goal of encouraging collaborative research that is industry and community linked, at regional and national levels within the NACCQ sector. The research programme into Software Development Impact Statements being conducted by the Software Engineering Practice Improvement Alliance, (SoDIS SEPIA) represents one model towards achieving this goal. Initiated in 2001, this programme of research has developed increasing momentum from small beginnings, and is beginning to attract funding and a growing body of research partners committed to its goals. Bootstrapping a research programme from scratch is nonetheless a difficult undertaking. This paper outlines the goals of the programme; the strategies applied to build a collaborative network of researchers in educational and commercial organizations in New Zealand, Australia and the United States; reviews the successes and failures in the process so far; and makes some recommendations for developing successful research partnerships

Being a data professional : give voice to value in a data driven society

Data Analytics needs to have ethical standards. There are numerous examples of why this is so, and the paper cites four particularly egregious ones. The paper offers both reasons why such standards are currently missing or inadequate, and how they might best be introduced, or refined. Some Codes of Ethics, such as the Software Engineering Code of Ethics and Professional Practice, the ACM and IFIP Codes of Ethics, and the Web Analyst’s Code of Ethics are discussed, compared, and contrasted. The paper offers a comparative study, to help inform the process of the drawing up of guidelines where it is best undertaken, within the profession itself

The Code

This Code may be published without permission as long as it is not changed in any way and it carries the copyright notice. Copyright (c) 2018 by the Association for Computing Machinery.Computing professionals' actions change the world. To act responsibly, they should reflect upon the wider impacts of their work, consistently supporting the public good. The ACM Code of Ethics and Professional Conduct ("the Code") expresses the conscience of the profession. The Code is designed to inspire and guide the ethical conduct of all computing professionals, including current and aspiring practitioners, instructors, students, influencers, and anyone who uses computing technology in an impactful way. Additionally, the Code serves as a basis for remediation when violations occur. The Code includes principles formulated as statements of responsibility, based on the understanding that the public good is always the primary consideration. Each principle is supplemented by guidelines, which provide explanations to assist computing professionals in understanding and applying the principle

Addressing Ethical Challenges of Creating New Technology for Criminal Investigation: The VALCRI Project

In developing a semi-automated decision support system using cutting-edge visual technologies to aid police intelligence analysts (the VALCRI project) it was recognised that addressing ethical, privacy and legal issues would need to be considered from the start. From the beginning, experts in these fields were embedded in the project and externally an independent ethics board was established and a number of ethical concerns were identified. Addressing the concerns presented some challenges both in terms of process and product and are the subject of this paper. Insights about these problems can contribute to other research projects beyond the area of crime visualization, for instance addressing concerns such as logging processes for auditing and evidence in other sensitive projects

Dynamic Technology Challenges Static Codes of Ethics

Open access journalWe describe the process of changing and the changes being suggested for the ACM Code of Ethics and Professional Conduct. In addition to addressing the technical and ethical basis for the proposed changes, we identify suggestions that commenters made in response to the first draft. We invite feedback on the proposed changes and on the suggestions that commenters made

Listening to professional voices: draft 2 of the ACM code of ethics and professional conduct

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.For the first time since 1992, the ACM Code of Ethics and Professional Conduct (the Code) is being updated. The Code Update Task Force in conjunction with the Committee on Professional Ethics is seeking advice from ACM members on the update. We indicated many of the motivations for changing the Code when we shared Draft 1 of Code 2018 with the ACM membership in the December 2016 issue of CACMb and with others through email and the COPE website (ethics.acm.org). Since December, we have been collecting feedback and are vetting proposed changes. We have seen a broad range of concerns about responsible computing including bullying in social media, cyber security, and autonomous machines making ethically significant decisions. The Task Force appreciates the many serious and thoughtful comments it has received. In response, the Task Force has proposed changes that are reflected in Draft 2 of the Code. There are a number of substantial changes that require some explanation. In this article, we discuss these, and we explain why we did not include other requested changes in Draft 2. We look forward to receiving your comments on these suggested changes and your requests for additional changes as we work on Draft 3 of the Code. We have provided opportunities for your comments and an open discussion of Draft 2 at the ACM Code 2018 Discussion website [http://code2018.acm.org/discuss]. Comments can also be contributed at the COPE website https://ethics.acm.org, and by direct emails to [email protected]

The moral-IT deck:A tool for ethics by design

This paper presents the design process and empirical evaluation of a new tool for enabling ethics by design: The Moral-IT Cards. Better tools are needed to support the role of technologists in addressing ethical issues during system design. These physical cards support reflection by technologists on normative aspects of technology development, specifically on emerging risks, appropriate safeguards and challenges of implementing these in the system. We discuss how the cards were developed and tested within 5 workshops with 20 participants from both research and commercial settings. We consider the role of technologists in ethics from different EU/UK policymaking initiatives and disciplinary perspectives (i.e. Science and Technology Studies (STS), IT Law, Human Computer Interaction (HCI), Computer/Engineering Ethics). We then examine existing ethics by design tools, and other cards based tools before arguing why cards can be a useful medium for addressing complex ethical issues. We present the development process for the Moral-IT cards, document key features of our card design, background on the content, the impact assessment board process for using them and how this was formulated. We discuss our study design and methodology before examining key findings which are clustered around three overarching themes. These are: the value of our cards as a tool, their impact on the technology design process and how they structure ethical reflection practices. We conclude with key lessons and concepts such as how they level the playing field for debate; enable ethical clustering, sorting and comparison; provide appropriate anchors for discussion and highlighted the intertwined nature of ethics.Comment: Governance and Regulation; Design Tools; Responsible Research and Innovation; Ethics by Design; Games; Human Computer Interaction, Card Based Tool

Exact Bayesian curve fitting and signal segmentation.

We consider regression models where the underlying functional relationship between the response and the explanatory variable is modeled as independent linear regressions on disjoint segments. We present an algorithm for perfect simulation from the posterior distribution of such a model, even allowing for an unknown number of segments and an unknown model order for the linear regressions within each segment. The algorithm is simple, can scale well to large data sets, and avoids the problem of diagnosing convergence that is present with Monte Carlo Markov Chain (MCMC) approaches to this problem. We demonstrate our algorithm on standard denoising problems, on a piecewise constant AR model, and on a speech segmentation problem