Journal of responsible technology最新文献

Software engineering, as a central practice of digitalization, needs to become accountable for sustainability. In light of the ecological crises and the tremendous impact of digital systems on reshaping economic and social arrangements - often with negative side-effects - we need a sustainability transformation of the digital transformation. However, this is a complex and long-term task. In this article we combine an analysis of accountability arrangements in software engineering and a model of sustainability transformations to trace how certain dynamics are starting to make software engineering accountable for sustainability in the technological, cultural, economic and governance domains. The article discusses existing approaches for sustainable software engineering and software engineering for sustainability, traces emerging discourses that connect digitalization and sustainability, highlights new digital business models that may support sustainability and shows governance efforts to highlight “green and digital” policy problems. Yet, we argue that these are so far niche dynamics and that a sustainability transformation requires a collective and long-lasting effort to engender systemic changes. The goal should be to create varied accountability arrangements for sustainability in software engineering which is embedded in complex ways in society and economy.

Over the past decades, the field of interaction design has shaped how people interact with digital technology, both through research and practice. Interaction designers adopted human-centred design to ensure that the interactive products they design meet the needs and desires of end consumers. However, there is surmounting evidence that placing the end consumer at the centre of the design process creates unintended consequences, damaging global systems that are essential to human well-being. This article reviews emerging paradigms that provide a more holistic perspective, such as value-sensitive design, more-than-human participation and life-centred design. Based on this review, the article introduces a practical framework for life-centred design consisting of principles, actionable methods and a model for responsible innovation. The article discusses how interaction designers can use the framework to balance human-centred considerations with environmental and ethical concerns when designing interactive products.

Data protection risks play a major role in data protection laws and have shown to be suitable means for accountability in designing for usable privacy. Especially in the legal realm, risks are typically collected heuristically or deductively, e.g., by referring to fundamental right violations. Following a user-centered design credo, research on usable privacy has shown that a user-perspective on privacy risks can enhance system intelligibility and accountability. However, research on mapping the landscape of user-perceived privacy risks is still in its infancy. To extend the corpus of privacy risks as users perceive them in their daily use of technology, we conducted 9 workshops collecting 91 risks in the fields of web browsing, voice assistants and connected mobility. The body of risks was then categorized by 11 experts from the legal and HCI-domain. We find that, while existing taxonomies generally fit well, a societal dimension of risks is not yet represented. Discussing our empirically backed taxonomy including the full list of 91 risks, we demonstrate roads to use user-perceived risks as a mechanism to foster accountability for usable privacy in connected devices.

Most engineers work within social structures governing and governed by a set of values that primarily emphasise economic concerns. The majority of innovations derive from these loci. Given the effects of these innovations on various communities, it is imperative that the values they embody are aligned with those societies. Like other transformative technologies, artificial intelligence systems can be designed by a single organisation but be diffused globally, demonstrating impacts over time. This paper argues that in order to design for this broad stakeholder group, engineers must adopt a systems thinking approach that allows them to understand the sociotechnicity of artificial intelligence systems across sociocultural domains. It claims that value sensitive design, and envisioning cards in particular, provides a solid first step towards helping designers harmonise human values, understood across spatiotemporal boundaries, with economic values, rather than the former coming at the opportunity cost of the latter.

States are increasingly turning to automated decision-making systems to increase efficiency in program and service delivery. While automation offers several desirable benefits, great care must be given to establishing and increasing the accountability of automated decision-making systems in the public sector. This paper focuses on accountability in automated decision-making systems in migration management. A key issue is what the impact of automated decision-making is on accountability in migration management? This paper seeks to explore this question by evaluating the accountability mechanisms established by the Canadian government in the use of automated decision-making systems to triage Temporary Resident Visa immigration applications. This paper begins with an explanation of the interaction between public administration and digital governance, with a particular focus on the human decision-making component of public administration and a review of accountability in the public sector. What follows is an explanation of how decision-making in Canada's Temporary Resident Visa Application stream traditionally occurs. A brief review of the Canadian Algorithmic Impact Assessment Tool introduces a thorough explanation of the Canadian government's Temporary Resident Visa (TRV) eApps Advanced Analytics Pilot to showcase changes between the traditional human decision-making process and the more recent experiment engaging automated decision-making in this particular immigration stream. The paper concludes by posing a question on what accountability amounts to for the Canadian government and whether the accountability measures introduced in Canada's TRV Pilot are sufficient.

Nanotechnology in food and agriculture (nano-agrifoods) may provide numerous benefits to society. At the same time, previous experiences have demonstrated the importance of innovating responsibly. This study reports on stakeholder-identified actions to address concerns about nano-agrifoods and actions to ensure their responsible innovation (RI). We find stakeholders largely supported actions to address risk and safety, followed by governance actions, the examination of ‘need,’ and identification of clear benefits. Participants also indicated no actions would address their concerns in several cases, largely for nano-in food products without a clear ‘need’ and risk/benefit comparisons. We conclude by highlighting four best practices to foster RI of nano-agrifoods, with relevancy for other novel agrifood technologies, including the institutionalization of RI, education and training next generation of researchers and innovators, use of tiered approaches to implement RI principles at different levels and degrees, and incorporation of monitoring and learning systems to improve RI practices.

Sustainability is high on the agendas of public and private organizations. Governments are setting targets for reducing the use of virgin raw materials in products and to eliminate waste. To accelerate the transition towards a Circular Economy (CE) policymakers are launching instruments. However, policy instruments, such as financial incentives or new regulatory guidelines, are prone to manipulations when the stakes for the involved stakeholders are high. Therefore, policymakers and government authorities need a solid system to monitor and control the implementation and effectiveness of their CE measures. To this end, digital technologies are key to enabling visibility and monitoring of materials flows. They allow governments and other stakeholders to use data to steer the transition towards a CE. However, data from different materials supply chains reside in a diversity of digital platforms used by a diversity of stakeholders involved. Blockchain-based platforms can support the required visibility by combining data from different stakeholders across different materials supply chains. But connecting all data for CE visibility throughout the entire materials flows into one singular platform is unlikely. With the growing number of blockchain-based platforms that each covers parts of data on CE flows, there is a need to assess the level of visibility they offer and to determine which data is lacking to monitor full CE flows. In this article, the development of a framework to evaluate blockchain-enabled information systems on their ability to act as monitoring systems for CE purposes is presented. The design science research approach was followed to develop the framework. Insights provided by academic literature as well as empirical data from three extant blockchain-enabled platforms were used (i.e., TradeLens, FoodTrust, and Vinturas). The evaluation framework can be deployed by public and private actors (e.g., governments and banks) for monitoring purposes, but also by IT providers to offer CE visibility solutions.

This study aims to map digitally mediated injustice and to understand how judicial versus non-judicial bodies contextualize and translate such harm into human rights violations. This study surveys judicial and quasi-judicial cases and case reports by non-judicial bodies, mainly civil society organizations, international organizations, and media. It divides digitally mediated harms identified through the survey into three categories: direct, structural, and hybrid harm. It then examines how these three forms of harm are represented and articulated in judicial judgments and case reports. To differentiate between the three forms of digitally mediated harm, the study uses Iris Young's political philosophy of structural injustice and Johan Galtung's account of structural violence in peace studies. The focus of this study is understanding the forms of injustices that are present but rendered invisible because of how they are contextualized. Therefore, the epistemology of absence is applied as the theoretical approach, that is, interpretation of absence and invisibility. The epistemology of absence facilitates the identification of structural and intersectional injustices that are not articulated in the same way they are experienced in society. The assessment reveals four observations. (1) Structural injustice is rarely examined through a conventional adjudicatory process. (2) Harms of structural quality examined by courts are narrowly interpreted when translated into rights violations. (3) The right to privacy, often presented as a gateway right, addresses structural injustice only partially, as this right has a subject-centric narrow interpretation currently. (4) There are limitations to the mainstream way of seeing and representing risks and injustices in the digital space, and such a view yields metonymic reasoning when framing digitally produced harms. As a result, the conventional way of contextualization is blind to unconventional experiences of vulnerability, which renders structural and intersectional injustices experienced by marginalized communities invisible.

As AI-based models take an increasingly central role in our lives, so does the concern for fairness. In recent years, mounting evidence reveals how vulnerable AI models are to bias and the challenges involved in detection and mitigation. Our contribution is three-fold. Firstly, we gather name disparity tables across protected groups, allowing us to estimate sensitive attributes (gender, race). Using these estimates, we compute bias metrics given a classification model’s predictions. We leverage only names/zip codes; hence, our method is model and feature agnostic. Secondly, we offer an open-source Python package that produces a bias detection report based on our method. Finally, we demonstrate that names of older individuals are better predictors of race and gender and that double surnames are a reasonable predictor of gender. We tested our method on publicly available datasets (US Congress) and classifiers (COMPAS) and found it to be consistent with them.