Christoph Becker

Nadia Mariyan Smith, Nils Bonfils, Han Qiao et al.

Permacomputing is a nascent concept and community of practice concerned with developing alternative computing systems grounded in principles of resilience, reuse, sufficiency, and ecological limits. However, research engaging with permacomputing remains in an early stage of development, raising concerns about whether permacomputing can move beyond reflective critique to become a meaningful alternative practice. Through a research-through-design case study, we documented our experience moving a personal website from a data centre in Texas to a self-hosted solar-powered server built from reclaimed electronics. Guided by permacomputing principles and relational aesthesis, we explore what it takes for permacomputing to reconfigure material and perceptual relations. Our findings reveal the frictions of moving away from a maximalist techno-aesthetic while attempting to re-use already existing technologies, potential ways to overcome these challenges through building a community of practice, and the transformative potential of visibilizing and visceralizing digital infrastructures to cultivate more responsible ways of relating to technology. This paper contributes to emerging research on permacomputing and its aesthetics by bringing it into dialogue with theories of non-place and relational aesthesis. Rather than functioning as a purely symbolic gesture, permacomputing practices can cultivate greater collective autonomy, agency, and responsibility in how communities engage and create meaning within digital infrastructures. In the context of socio-ecological crises and anti-colonial transformation, our research offers a situated approach to building and relating to computing technologies in the ashes of dominant technological paradigms.

Harshit Gujral, Eshta Bhardwaj, Dushani Perera et al.

Datacenter expansion under generative AI is increasingly framed as compatible with sustainability because of efficiency gains, cleaner electricity procurement, and improved facility design. Yet these claims often do not show that absolute electricity, water, material, waste, and community-facing burdens are falling. This Perspective addresses that evidentiary gap. Rather than asking whether efficiency gains are real, we ask when such gains are being enlarged into claims of system-wide sustainability to justify continued expansion. We develop a rebound-informed diagnostic framework for evaluating AI and datacenter sustainability narratives across five tests: metric, boundary, reinvestment, burden shifting, and governance. Applied to major AI industry sustainability reporting, the framework shows that firms largely justify continued expansion through efficiency improvements and clean-energy procurement, rather than by demonstrating reductions in absolute resource use. Applied to plateau claims in the literature, we show that many claims establish local or relative improvements while leaving energy rebound, lifecycle burdens, and enforceable limits unresolved. We argue that these sustainable-growth narratives begin to function as greenwashing when they use efficiency improvements to claim sustainability even as absolute energy, water, material, and public health burdens continue to increase. We conclude by positioning digital sufficiency as a burden-of-proof framework for governance: those advocating further datacenter expansion must show that it reduces, rather than merely redistributes or defers, absolute burdens across the full system.

Nils Bonfils, Christoph Becker

The business model of surveillance capitalism, premised on the extraction of behavioral data and its predictive potential for profit, relies on extensive material infrastructure. Such profit is typically driven by practices such as telemetry, user tracking, data analytics, secondary data uses, increased user engagement, and AI model training, as well as large-scale data storage systems that retain personal information for sale or reuse. This paper is motivated by the question: how much of the rising carbon impact of ICT can be attributed to this material infrastructure? Such an inquiry provides a foundation for quantifying the environmental costs of surveillance capitalism by proposing a conceptual framework and research direction that link processes of surveillance with their underlying material realities. To demonstrate the applicability of this framework, we examine the proportion of network traffic caused by surveillance capitalism processes through a comparative case study of a corporate social media platform, X/formerly Twitter, and a decentralized, non-commercial alternative, Mastodon. Our findings highlight the existence of corporate overhead: excess resource consumption driven by corporate social media practices, which is used as an initial proxy for the activities of surveillance capitalism. Our findings further demonstrate how the corporate overhead of X can be used to establish a lower bound in CO2e emissions attributable to for-profit activities that do not contribute to the user experience.

Eshta Bhardwaj, Ciara Zogheib, Christoph Becker

It is prominently recognized that dataset development in machine learning is a value-laden process from problem formulation to data processing, use, and reuse. Structured documentation frameworks such as datasheets, data statements, and dataset nutrition labels have been created to aid developers in documenting how their datasets were produced and, according to the creators of the frameworks, to facilitate reflexivity in dataset development. While reflexivity is a stated goal, it is unclear whether and to what extent these structured dataset documentation frameworks incorporate concepts from reflexivity literature (at FAccT and elsewhere) and whether the use of the frameworks demonstrates reflexivity. Here, we adopt mixed-method thematic analysis and corpus-assisted discourse analysis to explore how reflexivity is incorporated in structured documentation frameworks and their responses. We demonstrate empirically that there is a general lack of engagement with major themes of reflexivity in both dataset documentation frameworks and published applications of these frameworks. We present a codebook of major reflexivity topics, recommend actionable strategies, and propose a set of extended datasheet questions to more effectively incorporate these topics into structured documentation frameworks and in the FAccT literature.

Eshta Bhardwaj, Rohan Alexander, Christoph Becker

The accelerating development and deployment of AI technologies depend on the continued ability to scale their infrastructure. This has implied increasing amounts of monetary investment and natural resources. Frontier AI applications have thus resulted in rising financial, environmental, and social costs. While the factors that AI scaling depends on reach its limits, the push for its accelerated advancement and entrenchment continues. In this paper, we provide a holistic review of AI scaling using four lenses (technical, economic, ecological, and social) and review the relationships between these lenses to explore the dynamics of AI growth. We do so by drawing on system dynamics concepts including archetypes such as "limits to growth" to model the dynamic complexity of AI scaling and synthesize several perspectives. Our work maps out the entangled relationships between the technical, economic, ecological and social perspectives and the apparent limits to growth. The analysis explains how industry's responses to external limits enables continued (but temporary) scaling and how this benefits Big Tech while externalizing social and environmental damages. To avoid an "overshoot and collapse" trajectory, we advocate for realigning priorities and norms around scaling to prioritize sustainable and mindful advancements.

Christoph Becker

Behavioral research can provide important insights for SE practices. But in performing it, many studies of SE are committing a normative fallacy - they misappropriate normative and prescriptive theories for descriptive purposes. The evidence from reviews of empirical studies of decision making in SE suggests that the normative fallacy may is common. This article draws on cognitive psychology and behavioral economics to explains this fallacy. Because data collection is framed by narrow and empirically invalid theories, flawed assumptions baked into those theories lead to misleading interpretations of observed behaviors and ultimately, to invalid conclusions and flawed recommendations. Researchers should be careful not to rely solely on engineering methods to explain what people do when they do engineering. Instead, insist that descriptive research be based on validated descriptive theories, listen carefully to skilled practitioners, and only rely on validated findings to prescribe what they should do.

Leticia Duboc, Curtis McCord, Christoph Becker et al.

The design of software systems inevitably enacts normative boundaries around the site of intervention. These boundaries are, in part, a reflection of the values, ethics, power, and politics of the situation and the process of design itself. This paper argues that Requirements Engineering (RE) require more robust frameworks and techniques to navigate the values implicit in systems design work. To this end, we present the findings from a case of action research where we employed Critical Systems Heuristics (CSH), a framework from Critical Systems Thinking (CST) during requirements gathering for Homesound, a system to safeguard elderly people living alone while protecting their autonomy. We use categories from CSH to inform expert interviews and reflection, showing how CSH can be simply combined with RE techniques (such as the Volere template) to explore and reveal the value-judgements underlying requirements.

Fabian Fagerholm, Christoph Becker, Alexander Chatzigeorgiou et al.

Background: Many decisions made in Software Engineering practices are intertemporal choices: trade-offs in time between closer options with potential short-term benefit and future options with potential long-term benefit. However, how software professionals make intertemporal decisions is not well understood. Aim: This paper investigates how shifting time frames influence preferences in software projects in relation to purposefully selected background factors. Method: We investigate temporal discounting by replicating a questionnaire-based observational study. The replication uses a changed-population and -experimenter design to increase the internal and external validity of the original results. Results: The results of this study confirm the occurrence of temporal discounting in samples of both professional and student participants from different countries and demonstrate strong variance in discounting between study participants. We found that professional experience influenced discounting. Participants with broader professional experience exhibited less discounting than those with narrower experience. Conclusions: The results provide strong empirical support for the relevance and importance of temporal discounting in SE and the urgency of targeted interdisciplinary research to explore the underlying mechanisms and their theoretical and practical implications. The results suggest that technical debt management could be improved by increasing the breadth of experience available for critical decisions with long-term impact. In addition, the present study provides a methodological basis for replicating temporal discounting studies in software engineering.

Christoph Becker, Fabian Fagerholm, Rahul Mohanani et al.

Technical Debt management decisions always imply a trade-off among outcomes at different points in time. In such intertemporal choices, distant outcomes are often valued lower than close ones, a phenomenon known as temporal discounting. Technical Debt research largely develops prescriptive approaches for how software engineers should make such decisions. Few have studied how they actually make them. This leaves open central questions about how software practitioners make decisions. This paper investigates how software practitioners discount uncertain future outcomes and whether they exhibit temporal discounting. We adopt experimental methods from intertemporal choice, an active area of research. We administered an online questionnaire to 33 developers from two companies in which we presented choices between developing a feature and making a longer-term investment in architecture. The results show wide-spread temporal discounting with notable differences in individual behavior. The results are consistent with similar studies in consumer behavior and raise a number of questions about the causal factors that influence temporal discounting in software engineering. As the first empirical study on intertemporal choice in SE, the paper establishes an empirical basis for understanding how software developers approach intertemporal choice and provides a blueprint for future studies.

Birgit Penzenstadler, Stefanie Betz, Colin C. Venters et al.

We report on a summer school course on Software Engineering for Sustainability (SE4S). We provide a detailed blueprint of the contents taught and its evaluation with the instruments that were used.

Christoph Becker, Dawn Walker, Curtis McCord

When making choices in software projects, engineers and other stakeholders engage in decision making that involves uncertain future outcomes. Research in psychology, behavioral economics and neuroscience has questioned many of the classical assumptions of how such decisions are made. This literature review aims to characterize the assumptions that underpin the study of these decisions in Software Engineering. We identify empirical research on this subject and analyze how the role of time has been characterized in the study of decision making in SE. The literature review aims to support the development of descriptive frameworks for empirical studies of intertemporal decision making in practice.

Christoph Becker, Ruzanna Chitchyan, Leticia Duboc et al.

Sustainability is a central concern for our society, and software systems increasingly play a central role in it. As designers of software technology, we cause change and are responsible for the effects of our design choices. We recognize that there is a rapidly increasing awareness of the fundamental need and desire for a more sustainable world, and there is a lot of genuine goodwill. However, this alone will be ineffective unless we come to understand and address our persistent misperceptions. The Karlskrona Manifesto for Sustainability Design aims to initiate a much needed conversation in and beyond the software community by highlighting such perceptions and proposing a set of fundamental principles for sustainability design.