ICT under Constraint: Exposing Tensions in Collaboratively Prioritising ICT Innovation for Climate Targets
Authors: 
Kelly Widdicks, 
Bran Knowles, 
Adrian Friday, and Gordon S. BlairAuthors Info & Claims
Kelly Widdicks, Bran Knowles, Adrian Friday, and Gordon S. BlairAuthors Info & ClaimsArticle No.: 12, Pages 1 - 21
Abstract
The international treaty known as the Paris Agreement requires global greenhouse gas emissions to decrease at a pace that will limit global warming to 1.5 degrees Celsius. Given the pressure on all sectors to reduce their emissions to meet this target, the Information Communication Technology (ICT) sector must begin to explore how to innovate under constraint for the first time. This could mean facing the unprecedented dilemma of having to choose between innovations, in which case the community will need to develop processes for making collective decisions regarding which innovations are most deserving of their carbon costs. In this article, we expose tensions in collaboratively prioritising ICT innovation under constraints and discuss the considerations and approaches the ICT sector may require to make such decisions effectively across the sector. This opens up a new area of research where we envision HCI expertise can inform and resolve such tensions for values-based and target-led ICT innovation toward a sustainable future.
1 Introduction
The catastrophic consequences of climate change are becoming ever more apparent [63]. World leaders have committed to the Paris Agreement: a guiding framework for nations to ensure a maximum of 1.5 \(^{\circ }\) C of global warming. Yet meeting its targets requires significant emissions reductions both immediately and into the future—specifically, global net zero emissions by 2050 at the latest. To meet Paris targets, nations will require that all sectors in the global economy reduce their carbon footprint—with implications for Information Communication Technology (ICT), both in terms of its own climate footprint [33], and its possible role in decarbonisation of other sectors [38]. This raises important questions for the ICT sector: Should ICT be allowed to grow and innovate freely for its stated (but largely unevidenced) role in addressing climate challenges? If not, then what innovation can we afford, for what value to society, and who gets to decide?
ICT devices, data centres and networks all have an environmental impact through the energy they use directly but also significantly via the embodied emissions of producing the technology and its end of life disposal. Estimations of the total carbon footprint of ICT vary between experts [2, 8, 57] from 1.8% to 2.8% of global greenhouse gas emissions [33]. Some suggest this impact could increase further to 4–5% of global emissions [1], yet more optimistic projections suggest emissions could instead be halved by 2030 [56]. Despite these conflicting estimates, historic patterns show ICT’s emissions have continuously risen, and all these experts believe ICT’s environmental impact will not reduce without a concerted political and industrial effort [33]. If we assume ICT’s impacts will simply stabilise, then the ICT sector would still need to reduce its carbon footprint by 42% by 2030, 72% by 2040, and 91% by 2050 to be aligned with the Paris accord, and while increases in energy efficiency and adoption of renewable energy sources will help this endeavour, they alone could not be relied upon to enable such extensive emissions reductions [33]. In fact, recent work calls for a constraint on ICT’s emissions to avoid efficiency-based solutions from currently increasing ICT demand and thus offsetting emissions savings or, in the worst case, increasing ICT’s emissions overall [85].
ICT’s environmental impacts are well known in research communities such as Sustainable Human-Computer Interaction (SHCI), with efforts looking to expose these impacts and reduce their severity through interaction design [4, 12, 13, 69, 83]. SHCI work has also often focused on how ICT can promote sustainability [27, 37, 50], yet such design research has not supported anywhere near the vast carbon savings we need to address the climate emergency [48] despite calls for more radical, activist, and political approaches [29, 49, 79]. While we would not of course suggest it is the role of SHCI or even ICT alone to address such a global challenge, we argue it is no longer acceptable simply to adapt designs to be “more sustainable” while tolerating continued technology growth. Rather, this trajectory needs to be reversed, with the ICT sector needing to make stark decisions on what (limited) ICT innovation it should prioritise under climate constraints. Thus, we instead propose using HCI expertise as a mechanism to expose tensions in prioritising ICT collaboratively and offer ways forward for HCI to support the ICT sector in resolving these tensions through values-based and target-led ICT innovation for a sustainable future.
In this article, we use an exploratory participatory exercise to begin to explore some of these tensions—uncovering influences, interpretations, and considerations for priority decision-making in ICT innovation.1 Through this, we uncover what evidence, context, and digital tools the sector may require to be able to make collective choices regarding which valued applications of ICT to continue—instead of other valued areas of ICT—in a carbon-constrained world. Our goal is not to arrive at a concrete prioritisation for global ICT innovation or to hint at areas undeserving of their carbon impacts. Rather, our goal is to observe participants’ decision-making processes to expose the thorny challenges entailed in such decision-making. We discuss issues regarding who, what, where, and how we should make decisions to effectively prioritise ICT innovation collectively and outline implications and future HCI research to support the ICT sector in exposing and resolving tensions for prioritising ICT innovation in line with Paris targets.
2 Related Work
ICT research communities have formed various and interlinking pathways that address environmental challenges and ICT’s role within this. Examples include considering sustainability within the development of ICT through sustainable software engineering (e.g., References [7, 73]), developing methodologies and assessments for the carbon impacts of ICT (e.g., References [9, 23]) (i.e., green ICT literature [44]), and using ICT for responding to challenges in environmental science through environmental informatics [34, 44, 68]. The SHCI community has also been a significantly contributing domain to the topic of ICT and environmental sustainability since its establishment in 2007. SHCI takes a more socio-technical and interdisciplinary approach to sustainability, exploring the interactions between humans, ICT, the environment, and the responsibility of ICT design for sustainable futures; given this focus and its methodological approaches, SHCI provides an effective framing for exploring tensions in collaboratively prioritising ICT.
As an overview of this area, SHCI researchers have been investigating how ICT can be designed to minimise its environment impacts (sustainability in design [58]) or be applied to make other activities more sustainable (sustainability through design [58]). For sustainability in design, research has explored the environmental impact of ICT [4, 55, 70, 83], addressing device obsolescence [71] and offering principles for sustainable interaction design [12, 13]. In sustainability through design, research has included the following: making resource consumption more visible to users with the hope of reducing this consumption, e.g., for energy and water [52, 76]; utilising dystopian Virtual Reality to engage citizens with climate change and promote pro-environmental behaviour [31]; exploring the role of contextual food data [54] and self-tracking technologies [22] to encourage sustainable food practices; and the development of information systems for sustainable communities, with calls for such services to better embody these communities’ values within their design [62].
While this work has merit, there have been several critiques of SHCI that suggest a need to broaden its focus beyond individual behaviour [17, 48], with Knowles et al. highlighting that SHCI focuses too much on “minimal impact” solutions that fall far short of what is required by the climate emergency [49, p. 3593]. Rethinking SHCI, Baumer and Silberman [6] propose that sometimes it may be best not to design, e.g., if a non-tech solution is more appropriate or if the ICT does more harm than good. Similarly, Pierce [66] introduced the concept of undesign, suggesting that there is opportunity for HCI designers to negate ICT by its own design. Moreover, while there have been suggestions for SHCI and “ICT for Development” communities to create ICT that help people prepare and adapt to political, social, or ecological change (e.g., from climate change) through collapse informatics [80], there have been brief mentions of removing ICT to prepare people for collapse scenarios where the ICT may no longer be able to function [81].
Adding to these critiques, Hansson et al. [43] have recently investigated how SHCI research maps to the United Nations’ Sustainable Development Goals (SDGs) [61]—finding that for the majority of papers that do map to the SDGs, they focus on SDG 12, “Responsible Consumption and Production,” and only 2 of their total 71 paper corpus linked to the SDG, “Climate Action.” This is despite the urgency of the climate crisis and calls for SHCI to orient around climate change [48]. Thomas et al. [79] also point out that SHCI does not directly respond to climate change policies or goals, yet ICT4S research by Pargman et al. [65, p. 293] argues that the “concrete nature” of carbon emission reduction targets (specifically the “carbon law”) can aid a trajectory for any sector, society, or time span toward Paris Agreement goals. From recently reviewing SHCI research, Bremer et al. [16] suggest a shift in focus for SHCI toward “Green Policy Informatics,” enabling the community to develop digital systems that support climate policies.
In this article, we directly respond to SHCI’s critiques and ICT’s role in the climate crisis and explore a new way in which HCI can promote political action, shape computing outputs, and support climate policies (cf. References [16, 48]): By using a HCI-based exercise to expose the tensions and considerations in collaboratively making decisions on priorities for ICT innovation. With this as a focus, we do not aim to establish prioritisation decisions on ICT innovation but rather explore the role of HCI in exposing tensions in such decision-making that the ICT sector needs and uncover how HCI can support the ICT sector in resolving these tensions as it aligns with the Paris Agreement. While prioritisation has been investigated for broader energy research (e.g., identifying priority research questions for energy in cities [59] or UK energy system changes to support low-carbon business models [42]), to the best of our knowledge, this is the first study that considers the topic of prioritising innovation in ICT, what tensions exist in such decision-making, and specifically HCI’s role in exposing and resolving these tensions for ICT’s sustainable future.
3 Method and Participants
We designed an exploratory participatory HCI study to investigate how ICT researchers and technologists prioritise ICT innovation as a means of prompting structured reflection about the tensions that the ICT sector would need to consider in making priority decisions regarding strategic cuts to its carbon footprint.2 This involved 20 ICT researchers and technologists3 engaging in a “prioritisation exercise” in pair-based interviews via Teams. By offering this practical exercise as experience of prioritising ICT innovation, we were able to uncover the tensions in such processes and discuss these in-depth with the participants themselves through the interview questions. The study was ethically approved and participants were informed that the study was motivated by environmental sustainability, noting the need to mitigate ICT’s carbon footprint and to understand what valued ICT innovation people believe we should prioritise and continue under constraints on ICT growth.
Each participant was asked to answer a pre-interview demographic survey covering their age, gender, employment status, highest education level, primary sector of work (academia, industry, or equally both) and their familiarity or past experience of working with notable ICT trends. Participants were recruited via email advertisement and snowballing methods, were required to work or have worked as an ICT researcher or technologist, and were offered a £10 voucher. Studies were conducted in September–December 20204 at a time to suit participants. The participants are summarised in Table 1—ranging from 20s–50s in age, 50% female and 50% male,5 with a variety of industry or academic experience. Participants were well educated, with 14/20 holding a postgraduate degree and all having engaged in further education; this was not explicitly a design of the study recruitment but as a result of snowball sampling.
Table 1.
| G# | P# | Age | Gender | Occupation | Sector | Top qualification |
|---|---|---|---|---|---|---|
| G1 | P1 | 30s | Female | Lecturer | Academia | Doctorate |
| G1 | P2 | 40s | Female | Lecturer | Academia | Doctorate |
| G2 | P3 | 30s | Female | Researcher | Academia | Doctorate |
| G2 | P4 | 40s | Male | Company Director | Both | Doctorate |
| G3 | P5 | 30s | Female | PhD Student | Academia | UG Degree |
| G3 | P6 | 30s | Male | Researcher | Academia | Doctorate |
| G4 | P7 | 30s | Female | PhD Student | Both | Master’s Degree |
| G4 | P8 | 20s | Female | Researcher | Academia | Master’s Degree |
| G5 | P9 | 20s | Female | Engineer | Industry | UG Degree |
| G5 | P10 | 20s | Male | Researcher | Both | Doctorate |
| G6 | P11 | 40s | Male | Professor | Academia | Doctorate |
| G6 | P12 | 30s | Female | Researcher | Industry | Doctorate |
| G7 | P13 | 30s | Male | Engineer | Industry | Master’s Degree |
| G7 | P14 | 30s | Male | Lead Engineer | Industry | Sixth Form/ College |
| G8 | P15 | 20s | Female | Analyst/ PhD Student | Industry | UG Degree |
| G8 | P16 | 40s | Male | Academic | Academia | Master’s Degree |
| G9 | P17 | 30s | Male | Senior Researcher | Academia | Doctorate |
| G9 | P18 | 50s | Female | Professor | Academia | Doctorate |
| G10 | P19 | 20s | Male | PhD Student | Both | UG Degree |
| G10 | P20 | 20s | Male | Researcher | Both | UG Degree |
Table 1. Participant Summary
Participants chose the sector (industry, academia, both equally) they felt they work, or have worked, mostly in. For age, “20s” for example classes as 20–29 years old, protecting participants’ anonymity. UG is an acronym for undergraduate.
The interview involved an ice breaker exercise for the participants to introduce themselves and denote what they believe are ICT’s key strengths and weaknesses,6 the “prioritisation exercise,” followed by a round of discussion questions. The prioritisation exercise involved displaying a grid via video link of 12 broad categories of where ICT is applied: Natural Sciences; Energy; Manufacturing; Logistics and Transport; Society and Community; Education and Skills Development; Health, Medicine and Psychology; Security, Privacy and Defence; Government, Policy and Law; Business and Commerce; Entertainment and Fitness; and Robotics. The researcher provided participants with examples of the type of ICT innovation that may occur in each category, noting that ICT may be used to enhance these categories (e.g., for “Natural Sciences,” using ICT to monitor the natural environment) or that these categories may be used to enhance ICT (e.g., for “Natural Sciences,” creating new materials for ICT development).
Participants were then asked to individually allocate 12 “tokens” to represent what categories of ICT application they believe should be prioritised, exploring what areas of ICT application they deem to be most important and valuable to continue under constraints on ICT innovation. Tokens were used to broadly represent resources put toward those categories (e.g., money, environmental, or workforce resources); 12 tokens were provided so at least 1 token could be allocated to each category, but participants were able to distribute these as they wished (e.g., three on four categories). The participants were asked to describe how they allocated the tokens; the researcher placed their tokens on the grid.
To simulate the requirement to ratchet down emissions over time in line with increasingly ambitious interim targets, the participants were then asked to allocate 12 tokens as a group—discussing their decisions throughout the task. This was then repeated with a depleting number of tokens: nine tokens (75% of total), 6 tokens (50%), 3 tokens (25%), and, finally, one token to identify their most prioritised application domain. Like the individual exercise, participants were prioritising what ICT they deem most important and valuable to continue under constraints on ICT innovation.
The researcher observed the study, taking frequent photos of the application categories grid to record the participants’ priorities, as well as answering any questions or prompting engagement. Discussion questions followed around feedback on the study alongside the participants’ thoughts on how the ICT sector could make collective priority decisions.
Following each interview, the researcher textually recorded the priority decisions from the photos to visualise how priorities changed during the exercise and compared to other groups; and fully transcribed and analysed the audio recordings, using thematic analysis (cf. Reference [15]). Themes were re-coded as each interview was conducted until findings converged; final themes were discussed with another researcher to ensure the coding was an appropriate representation of how participants approached the decision-making, as well as the tensions and considerations in their prioritisation.
A note on categories used in the prioritisation exercise: The 12 categories of ICT application were created by a preliminary analysis of data from the UKRI’s GtR,7 a publicly available database containing information about UK Government funded research. This specifically involved analysing 102 digital technology projects associated with major trends that have been noted for their significant energy impact [33]: Data Science and Artificial Intelligence (AI), the Internet of Things (IoT), and Blockchain. We recognise there are limitations in asking our participants to prioritise global ICT innovation based on analysis from a subset of UK-funded projects; however, our focus was on understanding how participants approach decisions rather than the prioritisation outcomes made by participants. We are not making any claims for global ICT prioritisation based on the participant decisions, and the exploratory method is instead used to uncover complexities in decision-making for ICT innovation. In that notion, we could have perhaps even replaced these 12 with a different set of categories, leading to different decision outcomes yet similar challenges for decision-making approaches and influences and HCI’s role in ICT prioritisation. Nevertheless, we provide all details regarding the analysis and formation for the 12 categories as supplementary material for transparency.
4 Findings
4.1 Influences on Participants’ Priorities
When forming priorities (Figures 1 and 2), the participants discussed various influences that impacted their decisions, including their role and expertise, personal and cultural values, and the salience of world events on their thinking.
Fig. 1.
Fig. 2.
4.1.1 Work Roles and Expertise.
The participants often referred to an experience during their working life in justifying the rationale for their allocation. This usually resulted in acknowledgement of a positive bias toward their own research expertise or knowledge of a particular application domain. For example, P2 suggested more resources are needed within “Government, Policy and Law” due to her work on women’s harassment via ICT; P8 stressed the importance of using technology for mental health given her work in the area; and P14 discussed how issues regarding a lack of human consideration in a prior project led to his allocations on the “Society and Community” theme. Similarly, decisions were linked to the sector they were working in (P6, P15–16, and P18), or their knowledge of specific technology (P16 and P19), ICT job gaps (P6) and ICT funding bodies’ priorities (P17). Participants sometimes reflected on such work biases (P7, P14, and P17), and the focus on ICT occupations in our participant sample shows how these ICT-specific work roles and expertise influence their decisions; further work would be required to explore the impact of other work roles and expertise from participants with varying occupations (discussed further in Section 5.1).
Work colleagues or collaborations also influenced these decisions: G2 discussed how working with ICT researchers and companies had emphasised a need for technology to be regulated; both P16 and P18’s work with others, e.g., through consultancy or committee membership influenced their decisions; and P5 discussed how she’s learned more about security and health from other researchers during her teaching roles, impacting her token allocation.
4.1.2 Personal and Cultural Values.
Participants drew on their own personal or cultural values throughout the group interviews. These included being people or family orientated (P3, P5, P8, and P15) and considering where society as whole could most benefit from ICT prioritisation (P5 and P12), being sustainability orientated (P4, P5–8, and P20) or considering other life forms, e.g., animals (P7), and having country or community perspectives (P4, P9, P12, and P17), such as the different needs of developing countries in comparison to developed countries (P2 and P7–8). These values were clearly influencing their decisions, with half of the participants’ language indicating this (P3–6, P8–11, and P19–20). To share just a few examples of this: “that [theme] isn't pulling at the heart strings as it were” (P3); “it’s like really, really important to me” (P4); “I wouldn’t say that ‘Security, Privacy and Defence’ is like my passion” (P5); “there’s some grids that I’m strongly against” (P8); “that’s selfishly not important to me” (P15); and “that one is quite close to my heart” (P17). P6 and P16 also explicitly reflected that prioritisation decisions come down to one’s values and beliefs, and some participants mentioned specific ICT companies that aligned, or conflicted, with their values (e.g., Tesla and Facebook).
4.1.3 Current Events.
Participants often referred to current events when making their decisions and justifying them. These included the environmental crisis and sustainability (P13–14 and P16–19), U.S. elections (P5 and P12) and the Cambridge Analytica scandal (P9 and P11), the digital divide or skills gap (P4–5, P8, P12–14, and P17–18), and current privacy, justice or security issues (P4, P6, P17, and P19). Most prominently, and likely due to this study being run during the pandemic, Covid-19 was brought up as a defining reason—with 17 of the 20 participants mentioning the health crisis in some way. This included the relevance of health through pandemic monitoring and remote medical support (P2, P6, P15, P17–18, and P20); the importance of entertainment for fun and mental health (P1–2, P12, and P15–16); being in contact with others and avoiding isolation (P3–4, P15, and P18–19); enabling online education and work (P5, P10, P12, and P20); and supporting e-commerce and goods logistics, including vaccines (P9, P11, and P18–19). Some participants also mentioned media impacted their decisions, such as the “Social Dilemma” Netflix documentary on privacy (P5–6 and P8) and the David Attenborough films on environmental sustainability (P15 and P18). Two participants explicitly reflected on how their choices were being defined by “what’s happening in the world in the moment” (P15) or “influenced by the current state of affairs” (P10).
4.2 Participants’ Interpretations
It became clear that the participants brought their own interpretation of the meaning of the themes and categories we chose for the prioritisation exercise, including ICT’s role within the themes, and the goal of the prioritisation itself.
4.2.1 Interpretations of Themes.
P3 clarified she allocated tokens to “Security, Privacy and Defence” on the basis of keeping technology secure, rather than, by way of counter-example, using AI for Defence. P15 mentioned how she allocated tokens to “Entertainment and Fitness” because of its benefits to mental health, and P4 discussed how his allocation to “Business and Commerce” was due to his perception that the theme is responsible for the majority of innovation and uptake of emerging technology. These interpretations of the themes were no doubt impacted by the participants’ influences (Section 4.1).
Seventeen participants felt the themes overlapped, with some finding it difficult to differentiate some themes at all (e.g., P4: the interplay between “Energy” and “Logistics and Transport”; P7: “Health, Medicine and Psychology” and “Robotics”), as P4 describes: “these different cells here, they’re very much meta cells, like if there was a Venn diagram, they cross very strongly over each other.” In G6, the participants’ interpretations meant they were potentially referring to identical ICT applications despite choosing different themes, with P11 noting that “at a very simplistic level, all those boxes could be mutually exclusive but they can’t be [...]I guess one reason they can’t be is probably ICT.” Moreover, participants discussed how there were overarching themes, such as society (P2, P18, and P19), e.g., “I personally would title that entire grid as society” (P19), or the environment and society (P5, P6, and P10). Given these overlaps, participants made prioritisation decisions on the basis that removing a token from one theme would still mean it is catered for by an overlapping theme. For example, G8 noted they wanted to rename their “Energy” category to “Energy, Logistics and Transport” and then remove a token from “Logistics and Transport” given they found the two themes implicitly connected.
4.2.2 Interpretations of ICT’s Role.
Participants were provided examples of how ICT is applied within the categories (Section 3). Yet, similar to the interpretations of the themes (Section 4.2.1), participants had preconceptions of ICT’s role within these themes, which consequently impacted their prioritisation. For example, P3, P5, and P20 all gave explicit examples of ICT for healthcare that led to them regarding this theme as important; P11 also noted how ICT could be used in ‘Government, Policy and Law’ for e-voting and e-petitioning. Conversely, P3 explained that they allocated a token to “Government, Policy and Law” on the basis that this was in favour of more strongly governing ICT rather than, say, placing an emphasis on “AI judges for example in the legal sphere.” This is similar to G9, who contemplated allocating tokens to “Robotics” and “Business and Commerce” on the assumption that both required ethical oversight. P6 reflected that G3 would’ve probably chosen different priorities if the role of ICT was more defined “in terms of whether you view it as IT, how IT can affect these [categories]or how these [categories]affect IT, or is it a combination.”
ICT’s role in some themes was difficult for participants to understand (e.g., Natural Sciences: P3, P5, P12, P19–20), and thus the emphasis they placed on this was reduced—as P11 describes: “either I don’t have much understanding of or I, I guess from my own experience I don’t see much impact of or on, in terms of ICT [...] I've just assigned where I just think there is that potential impact, does that makes sense?” Similarly, the themes led the participants to discuss world problems (e.g., making governments accessible), with P5–6 and P10 reflecting that some problems may not require ICT solutions. For example, P6 described having to remind himself that they were prioritising tokens based on ICT’s role in the themes, rather than allocating tokens to a theme itself: “you kind of keep having to take a step back and say in terms of IT prioritisation, cause it’s very much, like the instinct was like that needs more funding: government, policy.”
4.2.3 Interpretations of the Prioritisation.
The participants took different interpretations toward the exercise of allocating tokens to themes. Part of this was due to the tokens being broadly defined as “resources” (e.g., money, environmental resources, workforce labour—Section 3), and for the most part, tokens were seen as money, funding or investment. Only one group (G4) made an environmental interpretation of the tokens and P20 noted they saw the token as an “abstract concept.” Yet there were different perspectives to how they imagined the themes—and often the world—with, or without, token allocation. For example, P9 and P16 saw “Manufacturing” and “Business and Commerce” as being able to “figure themselves out” (P9) or “look after themselves” (P16) without ICT prioritisation—similar to P5 who reflected: “health, medicine and psychology, people are interested in that right, even without prioritisation.” This may be due to the perspective they took to the exercise, as while they drew on their own knowledge as experts and citizens, the participants sometimes took the role of allocation to be acting as a government, public or funding body (P9–10 and P15–17)—viewing the allocation of tokens as separate to the research and development of ICT in industry.
Others saw the lack of tokens as detrimental to the theme or society, e.g., P10 mentioned they were “happy to kill [their] manufacturing and give it to logistics and transport”, and P8 found the penultimate prioritisation round to be a form of apocalyptic scenario, “this is basically the end of the world, we only have three resources, so nothing matters, knowledge doesn’t matter, education doesn’t matter, let’s just use 1 resource to develop a great medicine to let all of us die with peace, cause really that’s the end.” G3 were concerned whether no tokens equated to no resources being allocated to that theme at all anymore. For G10, P20 also jokingly described the elimination of tokens as a life with and without certain aspects: “we’ve got school, with perfect health, and we really like each other, but we can’t watch Netflix [laughs].” P19 (G10) instead assumed that removing tokens would only apply to future research and development and reflected that the exercise made him consider the progression of ICT in this future prioritisation that he would usually take for granted.
4.3 Participants’ Considerations for Decision Making
Several factors were thought to be driving the underlying decision-making in the groups, including the need to establish a common foundation, the balancing of risk and reward, and ensuring that decisions were inclusive.
4.3.1 Setting Foundational Understandings.
Participants probed the study’s definition of ICT (P6), whether allocation approaches should be on personal opinions or societal views (P15 and P18), and whether there were specific time-span or geolocation contexts for the prioritisation (G8). Some participants also thought further detail on the themes would’ve been helpful (P6, P8, and P19). The wide impact of ICT in other sectors and prioritising tokens for the whole ICT sector made it difficult for the participants to make decisions. P15 and P19 actually both struggled to comprehend whether this was even possible given how society and ICT are structured, e.g., “society, it’s you know, it’s quite naturally evolving and I think as far as IT prioritisation that is also the case” (P19). P8 also didn’t understand the point of “dictating” priorities as people have different interests; concern was expressed about authoritarian controls of ICT or dictatorship as P15 put it.
As one potential way forward and as a first step for prioritising tokens across the sector, some of the participants discussed identifying an initial set of values or fundamental issues to address for the greater good (P5–6 and P15), as P6 explains: “at a higher level what you probably want to look at is to prioritise values, I mean before you decide what to invest in, you want to agree on a set of values, you know, what’s, is sustainability the priority? Is social equality the priority? Is the economy the priority? I think this is all gonna change depending on the situation and the context.” P11 also alluded to this, suggesting the United Nations’ SDGs could be utilised as a way to drive priorities.
4.3.2 Ensuring Rewards Outweigh Risks.
Some participants were keen to ensure allocated tokens would be used in a way that they deemed positive—noting ICT’s costs as well as its benefits (P3, P5–8, and P11). For example, P3 discussed how she struggled with “Robotics” as she has seen autonomous systems be used in great ways, yet is nervous about self-driving cars. P5 had the same concerns for such cars, but considered whether prioritisation would be needed to ensure humans know what to do when an automated machine does something wrong. Moreover, P8 described technology as a “double-edged sword,” noting that there is a “considerable amount of risk for [‘Government, Policy and Law’-related] systems to do what they’re not intended to do”; P7 raised to P8 that risks are present in all themes.
The depletion of tokens was also difficult for most groups, with concerns if too few resources for themes and the neglection of themes in favour of the prioritised—particularly when the non-prioritised themes were still seen as important or valuable. P7 and P12 reflected that they would want to better understand the costs and benefits in terms of how tokens impact a theme (P7) or on society and individuals (P12). However, P7 discussed the difficulty of measuring and comparing these benefits across different application areas of ICT: “benefits [in] the natural sciences world is different to benefits in the education and skills development, so I don’t know how you would measure those outcomes as benefits.”
4.3.3 Representation of Opinions.
Four groups (G1, G3, and G8–9) thought that, to make concrete decisions on where and how ICT is prioritised, it was important to consider potential biases and a variety of opinions. They suggested different groups should be included in decisions, inclusive of various age groups, career stages, disciplines, and professional backgrounds (e.g., politicians, academics, people outside of ICT) and with experience in the themes. For the latter, G1 noted how they both came from an education background and thus were potentially biased toward “Education and Skills Development” and that having people from the different themes may reveal interesting results. P2 even suggested having a representative from every theme at once as “when we talk to each other probably we can make better decisions,” and G9 wanted to ensure many disciplines could input to avoid some being neglected at the expense of others (e.g., art).
In G9, P17 emphasised the importance of recognising bias and under-representation when making decisions, “everybody’s got a bias, and when you go into a room at a sandpit or whatever, you bring, you can mix things together but there’s also people who, the things that aren’t represented.” However, P5 highlighted how prioritisation can become “muddy” as different people, bodies or corporations are involved given they may have varying conflicts of interests—a view P20 shared in G10, expressing the opinion that priorities need to come from government. While domain knowledge impacted prioritisation (Section 4.1.1) and was seen as helpful (G3 and G8), G8 discussed creating a steering group that included both ICT professionals and ‘random’ individuals that have an interest in ICT and can provide other perspectives.
5 Discussion
Asking our participants to prioritise ICT innovation was no easy task, yet our exploratory study surfaced interesting tensions and considerations worth further discussion—especially covering who should be prioritising, what and where we should prioritise, and how this could be achieved.
5.1 Who Should Prioritise?
Our participants questioned who should make decisions about ICT innovation priorities moving forward and why they would be best suited to make those decisions. We recruited ICT researchers and technologists as we deemed these groups to have the most relevant expertise to comment on the relative priorities for the ICT sector. However, there was a belief that a variety of different stakeholder opinions should be considered (Section 4.3.3)—perhaps even involving the general public, without specific expertise in ICT—to ensure there is suitable representation of people and opinion. Climate change affects us all globally and ICT is pervasive in many people’s lives; so, should not anybody, including non-ICT experts, have a say on ICT prioritisation? It is however difficult to make such important decisions if you have little domain knowledge (as shown with our participants for some of the themes—Section 4.2.2), but it is worth considering how democratic these processes should be. If they should be included, then what information would they require to be able to make sufficiently informed decisions on a subject area they know little, or even nothing, about?
Perhaps one benefit of including non-ICT experts is the removal of work-related biases that our participants raised (Section 4.1.1). The consultation of the general public may allow for a more balanced view that is free from conflicts of interests within the sector. Yet, as identified by our findings, there are a number of influences beyond work and ICT that impacted our participants’ decisions such as current events (Section 4.1), and despite having ICT expertise, our participants also sometimes changed the role they took to make priorities (e.g., as an expert, citizen, government or funding body—Section 4.2.3). It is thus clear that all biases must be explicitly accounted for when making decisions, ensuring decision makers declare their conflict of interests and their values or beliefs. Having this understanding of the decision makers themselves should avoid issues such as “chumocracy”8 and aid transparency of how they interpret prioritisation based on their discipline or world view.
5.2 What and Where Should We Prioritise?
Making decisions for prioritising ICT innovation is no doubt complex. Our participants all interpreted the ICT application areas (Section 4.2.1) and ICT’s role in those themes (Section 4.2.2) differently—making it difficult to understand really what they were prioritising. The prioritisation exercise also made it difficult for participants to remember they were prioritising resources on ICT’s use within a theme rather than the theme itself (e.g., resources for ICT in “Government, Policy and Law” rather than resources for Government, Policy and Law generally). Complicating matters further is how interdisciplinary and interwoven with society ICT can be, with the ICT sector seamlessly crossing boundaries to other sectors in the global economy. Our participants thus saw the ICT themes as overlapping and interconnected, creating hurdles for which theme to prioritise.
This raises the following two issues for ICT prioritisation: (1) Where do we prioritise? and (2) at what granularity? For the former, the ICT sector needs to establish boundaries on what qualifies as ICT and whether priorities should be made by the ICT sector (consuming the ICT sector’s carbon budget) or other sectors in the global economy (consuming carbon budgets in those sectors). Put simply: When is ICT the ICT sectors’ problem? For the latter, our study attempted to understand ICT prioritisation at the level at which it is applied to explore “worthy” vs. “less worthy” uses of ICT [33] and to prioritise ICT by value moving forward, foundational knowledge amongst decision makers is required (Section 4.3.1)—ensuring shared understandings of ICT’s application and its impacts. Yet, to remove divergence of interpretation and given broad categories of ICT application will have varying carbon footprints, do we need to make decisions on ICT at a different level of granularity, e.g., available compute in data centres for AI algorithms, or even the number of data centres, networks and user devices that can be used? In prioritising innovation in the ICT sector, we need to set these boundaries and identify the ideal granularity to make reasonable decisions and achievable climate targets.
5.3 How Should We Prioritise?
Our participants’ prioritisation approach raised some interesting considerations for whether the sector can be prioritised independently. Some participants struggled to prioritise for ICT as a whole—making the assumption that some ICT application areas would continue to flourish without resource prioritisation. Similarly, participants found it difficult to understand what prioritising diminishing resources for ICT into the future would really mean, since they reasoned ICT is unlikely to be able to continue unmolested separably (with only the future of ICT impacted) when other sectors utilising ICT are reducing their footprints. These highlight considerations for what our carbon budget for ICT innovation covers now and in the future and how we can then prioritise. It also uncovers the tensions of how we prioritise research and development that is made possible by public and private funds, or in academia and industry, so that the ICT sector can innovate responsibly and sustainably without living in (their words) a global dictatorship (raised by two participants).
Our participants were keen to ensure ICT prioritisation enabled significant rewards (Section 4.3.2) and prioritised based on current events (Section 4.1.3) raising questions for (1) how we make decisions based on ICT’s risks and rewards, and thus how we establish these risks and rewards now and in the future, and (2) whether prioritisation decisions should be reactive to immediate issues determined by current events, or proactive pre-empting future issues that could arise.
Taking these all into account, it is clear much further research and evidence gathering is required with various ICT stakeholders to answer these questions, and to understand exactly how we can best prioritise ICT across the sector in a way that aligns with the Paris Agreement and is endorsed by ICT stakeholders (e.g., researchers and technologists).
6 Implications
In considering the who, what, when, and how of prioritising ICT innovation under declining carbon emissions, we must address the emerging tensions and considerations in making such decisions, and as a starting point, the challenges revealed by working with our participants. In this section, we outline a new area of research for the sustainability of the ICT sector, and specifically HCI, to help support the ICT sector in uncovering and resolving these challenges—enabling the ICT sector to prioritise its innovation and align its emissions with the Paris Agreement.
6.1 Bringing Together Socio-technical Evidence
There is the need for an evidence base including quantitative and qualitative data to inform decision-making for ICT innovation priorities (Sections 5.2 and 5.3). Developing this evidence does not lie solely with HCI, yet the field is well placed to work across disciplines and thus we see HCI’s role as drawing the evidence together. From a carbon perspective, the ICT sector needs to know what it means for ICT innovation to be aligned with the Paris Agreement: what carbon budget the sector has, how much carbon is required for ICT applications (at varying granularities), and how valued assemblages of ICT should make up the sector’s available carbon budget. This requires examining ICT’s carbon impact, doing so comprehensively and repeatedly, with a trusted methodology. The challenge of scoping and creating this evidence base should not be underestimated, but there is undoubtedly going to be continuous uncertainties regarding ICT’s carbon impacts and this should not stop the ICT sector from taking action [51]. Thus, we would argue for an incremental approach resulting from active research into this area, rather than pausing urgent prioritisation until such evidence is “complete.”
Prior work on the climate impacts of ICT has emphasised the need for carbon accounting that is fully inclusive of emission scopes 1–3, and considers both the ways in which ICT efficiency gains can rebound to increase overall externality or might enable the saving of emissions in other sectors (enablement) [33]. The rebound effects of ICT are subtle and pervasive [10, 18, 24]: We refer to any increase in overall emissions that result from the application of ICT to a sector both directly and indirectly. By way of example, smart home heating counter-intuitively can increase energy consumption by extending heating hours by pre-heating homes automatically to meet user expectations or by making control of heating simpler and more usable [86]; in addition, e-commerce may offer access to lower cost products, making money available for increased consumption [18]. Conversely, ICT can enable reductions in global emissions in other sectors, e.g., mobile applications that facilitate the use of shared resources such as car pooling, or IoT for “smart roads” that relieve congestion and air pollution [38]. While the tradeoffs and implications of ICT’s impacts are complex to assess and hard to generalise, it is important we can collate and contrast ICT’s systems-complete rebound and enablement effects to fully appreciate ICT’s tradeoffs and possible impacts on global emissions (cf. Reference [85]). Understanding how the ICT sector’s emissions forms a part of, or interlinks with, overlapping sectors in the global economy (Section 5.2) will help define whether ICT can have a larger or less rapidly decreasing carbon budget if justifiable by demonstrably creating significant emission reductions in other sectors [33].
As we have explored with our participants, however, there are other concerns that need to be balanced when prioritising ICT innovation that go beyond ICT’s purely environmental impacts, such as the “greater good” that ICT can bring (e.g., using AI for HIV prevention or combating wildlife poaching [39]). Such concerns are important to consider to ensure the overall reward of a technology outweighs its risk (Section 5.3). There is likely no single answer; balancing these difficult tradeoffs will be a matter of creating good governance and responsible innovation. The HCI community is arguably well established in exploring the various ethical implications of ICT and impacting society positively [5, 45, 47, 53], such as designing technology responsibly [40], for digital well-being [20, 60], or for social justice [28, 32]. But it is critical that these possible and sometimes speculative promises of ICT are not always placed ahead of the environmental concerns, a value that aligns with life-centred (rather than human-centred) design [14].
In resolving this, our study also points to the importance of “values” [48, p. 4] in exploring participants’ perceived benefits and drawbacks of ICT innovation now and into the future. We need concrete evidence on ICT’s social implications that enables assessment of its socio-technical tradeoffs. This is a non-trivial task given ICT is so human centric [74], yet one that follows motivations for HCI’s Value Sensitive Design [36] in fostering and balancing human values [35] for the choice (rather than design) of ICT. Researchers in values in Computing have knowledge surrounding making values visible or quantifiable for decisions [30], and thus we see fruitful collaboration with these groups to ensure we have a truly socio-technical evidence base: one that allows the ICT sector to compare the risks and rewards between ICT’s environmental and social impacts (e.g., on equality, trust, social justice, security, privacy, health, well-being etc.).
Following this, the HCI community should consider how ICT stakeholders (e.g., academic institutions, organisations) can respond to socio-technical criterion for the evidence gathering of ICT’s tradeoffs, now and in the future. To evidence how these impacts may change, HCI researchers could more deeply engage in speculative design methods [67, 72] in this space to better reflect on ICT’s future effects—enabling predictions to be made on whether different ICTs will provide net-risks or net-rewards. With such a socio-technical evidence base, the HCI community can—as activists, educators and professionals—provide this evidence to relevant ICT stakeholders in industry, academia and policy, and enable the sector to make non-refutable, evidence-led prioritisation decisions for Paris Agreement alignment.
6.2 Incorporating a Global Context
The ICT sector needs to further unpack how it can prioritise innovation across its entire sector using available evidence. Our study highlighted the challenges of ICT crossing many boundaries (Section 5.2)—disciplines, organisations, funding sources, countries, values, and so on—making scalable ICT prioritisation inherently difficult. For example, how might different funding sources involving public and private money impact priorities (Section 5.3), since different countries have varying governments and policies for the regulation of public and private sectors, and many ICT companies are multi-nationals? Even beyond ICT, the Paris Agreement that provides governance for different countries to reduce their environmental impact in line with specific targets has not been pledged by all countries worldwide [21]; this makes it hard to believe that the ICT sector will itself be able to achieve what the Paris Agreement has not. However, ICT is seen as vital in the climate crisis [38], and given this, it it is crucial we are able to make evidence-led decisions on the sector’s innovation.
Adding to the challenge of prioritising across boundaries, our study participants indicated that ICT priority decisions should be democratic and inclusive of those impacted by the prioritisation. Thus it may be the case that everyone—in and beyond the ICT sector, regardless of their demographic—is allowed to have a say on ICT prioritisation (Section 5.1). If so, then further complexities lie with understanding how different members of society (e.g., academics, ICT industry leaders, general public) can have their opinions considered appropriately, and what mechanisms can be established to enable decision negotiation (e.g., member elections for an “ICT sector governance steering group,” building on how governments and funding bodies work today). To do this effectively, everyone should be able to make informed decisions and understand why the sector must prioritise, and any conflicts of interests should also be accounted for (Section 5.1).
For our exploratory study, we developed a baseline of research being conducted on major ICT trends in the UK (Section 3); but this is too UK-focused for a global sector and based only on innovation that is publicly funded and thus accessible. To enable data collection and decision-making at a global scale, the ICT sector needs to investigate what processes and procedures would be required to collect a baseline of the ICT innovation currently conducted by various organisations, institutions and individuals worldwide both public and private, and the innovation they expect to conduct in the future.
We still do not have the answers and rightly should not dictate how these globally scalable data gathering and prioritisation processes are set to ensure Paris Agreement alignment. In fact, our study is the first to our knowledge in HCI that directly responds to this climate change goal [79], and yet Thomas et al. [79, p. 6989] note that “The HCI community’s interdisciplinary strengths could place many members in a unique position to engage with the digital dimensions and implications of [environmental public policy].” We too see these strengths of HCI to facilitate ICT governance for sustainability, and suggest the HCI community can conduct transdisciplinary research to explore these tensions across boundaries, society members and ICT stakeholders. The Paris Agreement will cascade down to all sectors, and the ICT sector needs to be able to govern ICT innovation when it does. As such, we urge the HCI community to collaborate with experts working in the space of “anticipatory governance” [41] as a part of Responsible Research and Innovation [40, 87] to further anticipate the environmental and ethical implications of prioritising ICT amongst ICT stakeholders. Not only would these implications be useful for ICT’s role in environmental sustainability, but would also help the sector understand how it may govern ICT for its other negative social impacts [84], e.g., on privacy and bias.
6.3 Transparent Tools for ICT Priority Decision-making
While socio-technical evidence is paramount for the ICT sector to make decisions on ICT innovation priorities (Section 6.1), such data would be useless without the ability to visualise and analyse it in line with global carbon targets such as the Paris Agreement. Pargman et al. [65, p. 293] note that there is a need for better digital tools that visualise flight-related data to “guide any change process and reduce carbon emissions” involved with flying; we argue a similar tool is required for ICT and that the HCI community can help design and develop such a tool [26] for the ICT sector to use (drawing on concepts of “Green Policy Informatics” [16]). Through this, the data on ICT’s environmental and societal impacts would be able to be evaluated in one space—allowing the sector to explore how prioritising different ICT innovations of value affect its carbon budget and how that can bring global net-benefits.
We see such tool development as an opportunity to connect ICT stakeholders to their actions and consequences, shaping environmental movement in the sector [29]. Aligning ICT with the Paris Agreement would involve bringing together the stakeholders required for making ICT priority decisions, making decisions visible, and providing a historical trail of socio-technical evidence and decisions for future scrutiny. This would ensure that ICT sector decisions are fully transparent, a quality paramount to ensure the sector can reason about all priorities (regardless of if they are reactive or proactive—Section 5.3) and alleviate the challenges regarding ICT’s global context (Section 6.2).
Taking this further, such tools could highlight the values, backgrounds, and other influences or biases that decision makers themselves bring to prioritising ICT innovation (Section 5.1). For example, if a specific ICT priority aligns with a decision maker’s work (potentially creating more funding for their research or easier ways for them to profit), then a decision-making tool should be able to recognise this strong correlation and openly flag this to the publicly available data. There is also the question whether priorities should be given less weight for decision makers that have “conflicted” priorities and how conflicts between decision makers can be identified and logged (avoiding ‘chumocracy’—Section 5.1).
Understanding how such considerations can be integrated into tools for decision-making to support ICT prioritisation is no mean feat, especially given the precursor challenges of socio-technical evidence and scalability. Yet, developing such tools is a clear design interaction problem that HCI experts can, and should, explore to support. Further adding to this challenge is for HCI research to ensure decision-making tools are fair and transparent about their data, algorithms and analysis. For this, future work should build on lessons learned in HCI from creating decision tools (e.g., used for health [78] or the public sector [82]) to promote rigour and trust.
7 Conclusion
As SHCI researchers, we recognise achieving positive impact on ICT’s environmental sustainability from the vantage point of HCI is challenging. Not only do we suggest designs that go against traditional HCI narratives, but we also critique our own work for having a too narrow focus (cf. Reference [17]) and not creating enough impact [49]. From our prioritisation exercise and discussions with ICT stakeholders, we propose a new area of research for HCI to lead on for responsible and sustainable ICT, comprising of urgently compiling a socio-technical evidence base for the ICT sector to make priority decisions on, understanding how the ICT sector can make priority decisions and societal tradeoffs in a global context, and designing transparent digital tools that aid the ICT sector in making priority decisions on its innovation in the increasingly limited time there is to meet global climate goals. Through this, we envision the HCI community can utilise their socio-technical expertise and expand its focus with experts in responsible computing to help the ICT sector traverse a new pathway for sustainability, differing vastly from the “ICT status quo” of continuous innovation and growth.
While the stakes are high, we wish to remind readers that the HCI community need not be alone in this: our implications call for transdisciplinary research that encompasses ICT stakeholder involvement, and we simply propose the HCI community is well placed to glue relevant research and associates together. By utilising the socio-technical expertise that HCI embodies, the HCI and responsible computing communities can support the ICT sector in priority decision-making (as highlighted in our implications for next steps in this domain), as well as build upon what we have started through our study to expose further tensions of ICT innovation prioritisation amongst different stakeholders and under varied criteria. As activists, educators and professionals, such communities can then utilise this work to influence others in the ICT sector—particularly industry and academic leaders, as well as policymakers, who can hold the sector accountable for ICT’s environmental impacts.
Given the ICT sector is broad in the innovation it provides, we suggest this avenue for responsible and sustainable ICT should initially focus on supporting the ICT sector in prioritising a subset of ICT innovation under constraints: Freitag et al. [33] found that the growth and environmental impacts of AI, IoT, and Blockchain (e.g., for AI training [11], for IoT’s vast expected growth [75], Bitcoin as an application of Blockchain [25]) could have profound effects on ICT’s future emissions. This work can leverage and extend research examining the ethical issues in regards to these trends in ICT, such as guidelines of AI [46], challenges for IoT [3] and issues of Blockchain [77]. Focusing on these trends should expose the key tensions for prioritising innovation in the ICT sector as a whole and support the ICT sector to make effective priorities that enable significant inroads in reducing ICT’s carbon footprint to align with the Paris Agreement.
Acknowledgments
We thank the UK Research and Innovation (UKRI) Engineering and Physical Sciences Research Council (EPSRC) for funding this work (grant numbers EP/R513076/1 and EP/V042378/1). We thank the participants for their time and engagement in the study and to the reviewers for their useful feedback on the article. To protect the anonymity of the participants, the data associated with this study have not been shared.
Footnotes
1
In this article, we take the definition that “innovation” is “the introduction of new things, ideas or ways of doing something” [64]; thus this incorporates future novel ICT, as well as the current use and development digital technologies that need to be sustainably innovated within the climate crisis.
2
We focused on participants with this career demographic given individuals with these roles will have expertise in ICT; however, in our discussion (e.g., see Section 5.1) and implications, we explore the question of who should make decisions regarding ICT prioritisation beyond this expert group.
3
We recognise our study had a small sample size, yet this is not uncommon for HCI research [19] and is appropriate for exploratory studies such as this.
4
The study was conducted during the global Covid-19 pandemic, which impacted the study results (e.g., see Section 4.1.3).
5
We have since recognised that “female” and “male” are sex, not gender, but display the original data. Participants only identified as binary genders.
6
Group 7 did not do the ice breaker exercise as they had limited time to participate and already knew each other.
7
UKRI (UK Research and Innovation) GtR (Gateway to Research): https://gtr.ukri.org/
8
A UK term for when people put their friends/ those from similar backgrounds (“chums”) into power positions without due process and transparency.
References
[1]
Anders S. G. Andrae. 2020. Hypotheses for primary energy use, electricity use and CO \(_2\) emissions of global computing and its shares of the total between 2020 and 2030. WSEAS Transactions on Power Systems, 15, 50-59 (2020), p.4.
[2]
Anders S. G. Andrae and Tomas Edler. 2015. On global electricity usage of communication technology: Trends to 2030. Challenges 6, 1 (2015), 117–157.
[3]
Hany F. Atlam and Gary B. Wills. 2020. IoT security, privacy, safety and ethics. In Digital Twin Technologies and Smart Cities. Springer, 123–149.
[4]
Oliver Bates, Mike Hazas, Adrian Friday, Janine Morley, and Adrian K. Clear. 2014. Towards an holistic view of the energy and environmental impacts of domestic media and IT. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’14). Association for Computing Machinery, New York, NY, 1173–1182. DOI:
[5]
Oliver Bates, Vanessa Thomas, and Christian Remy. 2017. Doing good in HCI: Can we broaden our agenda? Interactions 24, 5 (Aug. 2017), 80–82. DOI:
[6]
Eric P. S. Baumer and M. Six Silberman. 2011. When the Implication Is Not to Design (Technology). Association for Computing Machinery, New York, NY, 2271–2274.
[7]
Christoph Becker, Ruzanna Chitchyan, Leticia Duboc, Steve Easterbrook, Birgit Penzenstadler, Norbert Seyff, and Colin C. Venters. 2015. Sustainability design and software: The karlskrona manifesto. In Proceedings of the IEEE/ACM 37th IEEE International Conference on Software Engineering, Vol. 2. 467–476. DOI:
[8]
Lotfi Belkhir and Ahmed Elmeligi. 2018. Assessing ICT global emissions footprint: Trends to 2040 & recommendations. J. Clean. Prod. 177 (2018), 448–463.
[9]
Pernilla Bergmark, Vlad C. Coroamă, Mattias Höjer, and Craig Donovan. 2020. A methodology for assessing the environmental effects induced by ict services: Part ii: Multiple services and companies. In Proceedings of the 7th International Conference on ICT for Sustainability. 46–55.
[10]
Mike Berners-Lee and Duncan Clark. 2013. The Burning Question: We Can’t Burn Half the World’s Oil, Coal and Gas. So How Do We Quit? Profile Books.
[11]
Lukas Biewald. 2019. Deep Learning and Carbon Emissions. Retrieved July 2021 from https://towardsdatascience.com/deep-learning-and-carbon-emissions-79723d5bc86e
[12]
Eli Blevis. 2007. Sustainable interaction design: Invention & disposal, renewal & reuse. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’07). ACM, New York, NY, 503–512. DOI:
[13]
Eli Blevis, Chris Preist, Daniel Schien, and Priscilla Ho. 2017. Further connecting sustainable interaction design with sustainable digital infrastructure design. In Proceedings of the Workshop on Computing Within Limits (LIMITS’17). ACM, New York, NY, 71–83. DOI:
[14]
Madeleine Borthwick, Martin Tomitsch, and Melinda Gaughwin. 2022. From human-centred to life-centred design: Considering environmental and ethical concerns in the design of interactive products. Journal of Responsible Technology, 10 (2022), 100032.
[15]
Virginia Braun and Victoria Clarke. 2019. Reflecting on reflexive thematic analysis. Qual. Res. Sport Exercise Health 11, 4 (2019), 589–597. DOI:
[16]
Christina Bremer, Bran Knowles, and Adrian Friday. 2022. Have we taken on too much?: A critical review of the sustainable HCI landscape. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’22). Association for Computing Machinery, New York, NY, Article 41, 11 pages. DOI:
[17]
Hronn Brynjarsdottir, Maria Håkansson, James Pierce, Eric Baumer, Carl DiSalvo, and Phoebe Sengers. 2012. Sustainably Unpersuaded: How Persuasion Narrows Our Vision of Sustainability. Association for Computing Machinery, New York, NY, 947–956.
[18]
Miriam Börjesson Rivera, Cecilia Håkansson, Åsa Svenfelt, and Göran Finnveden. 2014. Including second order effects in environmental assessments of ICT. Environ. Model. Softw. 56 (2014), 105–115. DOI:
[19]
Kelly Caine. 2016. Local Standards for Sample Size at CHI. Association for Computing Machinery, New York, NY, 981–992.
[20]
Marta E. Cecchinato, John Rooksby, Alexis Hiniker, Sean Munson, Kai Lukoff, Luigina Ciolfi, Anja Thieme, and Daniel Harrison. 2019. Designing for digital wellbeing: A research & practice agenda. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (CHI EA’19). Association for Computing Machinery, New York, NY, 1–8. DOI:
[21]
Mal Chadwick. 2021. What Is the Paris Climate Agreement and Why Does It Matter? Retrieved July 2021 from https://www.greenpeace.org.uk/news/what-is-paris-climate-agreement-and-why-does-it-matter/?source=GA&subsource=GOFRNAOAGA034J&gclid=Cj0KCQjw0K-HBhDDARIsAFJ6UGiYW016bGeZbtffiVsd69sajql4CfzYpNuWqKTCnWdHG18huRHL7GwaAhx3EALw_wcB
[22]
Janghee Cho, Laura Devendorf, and Stephen Voida. 2021. From The Art of Reflection to The Art of Noticing: A Shifting View of Self-Tracking Technologies’ Role in Supporting Sustainable Food Practices. Association for Computing Machinery, New York, NY, 1--7.
[23]
Vlad C. Coroamă, Pernilla Bergmark, Mattias Höjer, and Jens Malmodin. 2020. A methodology for assessing the environmental effects induced by ict services: Part i: Single services. In Proceedings of the 7th International Conference on ICT for Sustainability. 36–45.
[24]
Vlad C. Coroamă and Friedemann Mattern. 2019. Digital rebound–why digitalization will not redeem us our environmental sins. In Proceedings 6th International Conference on ICT for Sustainability. Vol. 2382.
[25]
Alex de Vries. 2018. Bitcoin’s growing energy problem. Joule 2, 5 (2018), 801–805.
[26]
Tawanna Dillahunt. 2014. Toward a deeper understanding of sustainability within HCI. In Workshop on Sustainability: What Have We Learned.
[27]
Carl DiSalvo, Phoebe Sengers, and Hrönn Brynjarsdóttir. 2010. Mapping the Landscape of Sustainable HCI. Association for Computing Machinery, New York, NY, 1975–1984.
[28]
Lynn Dombrowski, Ellie Harmon, and Sarah Fox. 2016. Social justice-oriented interaction design: Outlining key design strategies and commitments. In Proceedings of the ACM Conference on Designing Interactive Systems (DIS’16). Association for Computing Machinery, New York, NY, USA, 656–671. DOI:
[29]
Paul Dourish. 2010. HCI and environmental sustainability: The politics of design and the design of politics. In Proceedings of the 8th ACM Conference on Designing Interactive Systems (DIS’10). Association for Computing Machinery, New York, NY, 1–10. DOI:
[30]
Maria Angela Ferrario, Will Simm, Jon Whittle, Christopher Frauenberger, Geraldine Fitzpatrick, and Peter Purgathofer. 2017. Values in computing. In Proceedings of the CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA’17). Association for Computing Machinery, New York, NY, 660–667. DOI:
[31]
Kate Ferris, Gonzalo Garcia Martinez, Greg Wadley, and Kathryn Williams. 2020. Melbourne 2100: Dystopian virtual reality to provoke civic engagement with climate change. In Proceedings of the 32nd Australian Conference on Human-Computer Interaction (OzCHI’20). Association for Computing Machinery, New York, NY, 392–402. DOI:
[32]
Sarah Fox, Mariam Asad, Katherine Lo, Jill P. Dimond, Lynn S. Dombrowski, and Shaowen Bardzell. 2016. Exploring social justice, design, and HCI. In Proceedings of the CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA’16). Association for Computing Machinery, New York, NY, 3293–3300. DOI:
[33]
Charlotte Freitag, Mike Berners-Lee, Kelly Widdicks, Bran Knowles, Gordon S. Blair, and Adrian Friday. 2021. The real climate and transformative impact of ICT: A critique of estimates, trends, and regulations. Patterns 2, 9 (2021), 100340. DOI:
[34]
James E. Frew and Jeff Dozier. 2012. Environmental informatics. Annu. Rev. Environ. Resourc. 37 (2012), 449–472.
[35]
Batya Friedman. 1996. Value-sensitive design. Interactions 3, 6 (1996), 16–23.
[36]
Batya Friedman and David G. Hendry. 2019. Value Sensitive Design: Shaping Technology with Moral Imagination. MIT Press.
[37]
Jon Froehlich, Leah Findlater, and James Landay. 2010. The design of eco-feedback technology. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’10). ACM, New York, NY, 1999–2008. DOI:
[38]
GeSI. 2015. Smarter 2030: ICT Solutions for 21st Century Challenges. Technical Report.
[39]
Carla Gomes, Thomas Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, Fei Fang, Andrew Farnsworth, Alan Fern, and Xiaoli Fern. 2019. Computational sustainability: Computing for a better world and a sustainable future. Commun. ACM 62, 9 (2019), 56–65.
[40]
Barbara Grimpe, Mark Hartswood, and Marina Jirotka. 2014. Towards a closer dialogue between policy and practice: Responsible design in HCI. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’14). Association for Computing Machinery, New York, NY, 2965–2974. DOI:
[41]
David H. Guston. 2014. Understanding ‘anticipatory governance’. Soc. Stud. Sci. 44, 2 (2014), 218–242. DOI:
[42]
Stephen Hall, Christoph Mazur, Jeffrey Hardy, Mark Workman, and Mark Powell. 2020. Prioritising business model innovation: What needs to change in the United Kingdom energy system to grow low carbon entrepreneurship? Energy Res. Soc. Sci. 60 (2020), 101317. DOI:
[43]
Lon Åke Erni Johannes Hansson, Teresa Cerratto Pargman, and Daniel Sapiens Pargman. 2021. A Decade of Sustainable HCI: Connecting SHCI to the Sustainable Development Goals . In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1--19.
[44]
Lorenz Hilty, Wolfgang Lohmann, and Elaine M. Huang. 2011. Sustainability and ICT-an overview of the field. Not. Polit. 27, 104 (2011), 13–28.
[45]
Marina Jirotka, Barbara Grimpe, Bernd Stahl, Grace Eden, and Mark Hartswood. 2017. Responsible research and innovation in the digital age. Commun. ACM 60, 5 (Apr. 2017), 62–68. DOI:
[46]
Anna Jobin, Marcello Ienca, and Effy Vayena. 2019. The global landscape of AI ethics guidelines. Nat. Mach. Intell. 1, 9 (2019), 389–399.
[47]
Lorraine Kisselburgh, Michel Beaudouin-Lafon, Lorrie Cranor, Jonathan Lazar, and Vicki L. Hanson. 2020. HCI ethics, privacy, accessibility, and the environment: A town hall forum on global policy issues. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. 1--6. DOI:
[48]
Bran Knowles, Oliver Bates, and Maria Håkansson. 2018. This changes sustainable HCI. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’18). ACM, New York, NY, Article 471, 12 pages. DOI:
[49]
Bran Knowles, Lynne Blair, Paul Coulton, and Mark Lochrie. 2014. Rethinking plan a for sustainable HCI. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’14). ACM, New York, NY, 3593–3596. DOI:
[50]
Bran Knowles, Lynne Blair, Mike Hazas, and Stuart Walker. 2013. Exploring sustainability research in computing: Where we are and where we go next. In Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp’13). Association for Computing Machinery, New York, NY, 305–314. DOI:
[51]
Bran Knowles, Kelly Widdicks, Gordon Blair, Mike Berners-Lee, and Adrian Friday. 2022. Our house is on fire: The climate emergency and computing’s responsibility. Commun. ACM 65, 6 (May 2022), 38–40. DOI:
[52]
Matthias Laschke, Marc Hassenzahl, Sarah Diefenbach, and Marius Tippkämper. 2011. With a little help from a friend: A shower calendar to save water. In CHI’11 Extended Abstracts on Human Factors in Computing Systems (CHI EA’11). ACM, New York, NY, 633–646. DOI:
[53]
Ann Light, Alison Powell, and Irina Shklovski. 2017. Design for existential crisis in the anthropocene age. In Proceedings of the 8th International Conference on Communities and Technologies (C&T’17). Association for Computing Machinery, New York, NY, 270–279. DOI:
[54]
Martin V. A. Lindrup, EunJeong Cheon, Mikael B. Skov, and Dimitrios Raptis. 2021. One byte at a time: Insights about meaningful data for sustainable food consumption practices. In Proceedings of the Designing Interactive Systems Conference (DIS’21). Association for Computing Machinery, New York, NY, 683–696. DOI:
[55]
Carolynne Lord, Mike Hazas, Adrian K. Clear, Oliver Bates, Rosalind Whittam, Janine Morley, and Adrian Friday. 2015. Demand in my pocket: Mobile devices and the data connectivity marshalled in support of everyday practice. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI’15). ACM, New York, NY, 2729–2738. DOI:
[56]
J. Malmodin. 2020. The ICT Sector’s Carbon Footprint. Retrieved December 2020 from https://spark.adobe.com/page/dey6WTCZ5JKPu/
[57]
Jens Malmodin and Dag Lundén. 2018. The energy and carbon footprint of the global ICT and E&M sectors 2010–2015. Sustainability 10, 9 (2018), 3027.
[58]
Jennifer C. Mankoff, Eli Blevis, Alan Borning, Alan Borning, Batya Friedman, Susan R. Fussell, Jay Hasbrouck, Allison Woodruff, and Phoebe Sengers. 2007. Environmental sustainability and interaction. In Extended Abstracts on Human Factors in Computing Systems (CHI EA’07). ACM, New York, NY, 2121–2124. DOI:
[59]
Chris J. Martin, Peter G. Taylor, Paul Upham, Golnoush Ghiasi, Catherine S. E. Bale, Hannah James, Alice Owen, William F. Gale, Rebecca J. Slack, and Simon Helmer. 2014. Energy in low carbon cities and social learning: A process for defining priority research questions with UK stakeholders. Sust. Cities Soc. 10 (2014), 149–160. DOI:
[60]
Alberto Monge Roffarello and Luigi De Russis. 2019. The Race Towards Digital Wellbeing: Issues and Opportunities. Association for Computing Machinery, New York, NY, 1–14.
[61]
United Nations. 2021. The 17 Sustainable Development Goals. Retrieved July 2021 from https://sdgs.un.org/goals
[62]
Juliet Norton, Birgit Penzenstadler, and Bill Tomlinson. 2019. Implications of grassroots sustainable agriculture community values on the design of information systems. Proc. ACM Hum.-Comput. Interact. 3, CSCW, Article 34 (Nov. 2019), 22 pages. DOI:
[63]
Intergovernmental Panel on Climate Change (IPCC). 2021. Climate Change 2021: The Physical Science Basis. Working Group I contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Technical Report.
[64]
Oxford Learner’s Dictionary. 2021. Definition of Innovation noun. Retrieved December 2021 from https://www.oxfordlearnersdictionaries.com/definition/english/innovation
[65]
Daniel Pargman, Aksel Biørn-Hansen, Elina Eriksson, Jarmo Laaksolahti, and Markus Robèrt. 2020. From moore’s law to the carbon law. In Proceedings of the 7th International Conference on ICT for Sustainability (ICT4S’20). Association for Computing Machinery, New York, NY, 285–293. DOI:
[66]
James Pierce. 2012. Undesigning Technology: Considering the Negation of Design by Design. Association for Computing Machinery, New York, NY, 957–966.
[67]
James Pierce. 2019. Smart home security cameras and shifting lines of creepiness: A design-led inquiry. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’19). Association for Computing Machinery, New York, NY, Article Paper 45, 14 pages. DOI:
[68]
Werner Pillmann, Werner Geiger, and Kristina Voigt. 2006. Survey of environmental informatics in Europe. Environ. Model. Softw. 21, 11 (2006), 1519–1527.
[69]
Chris Preist, Daniel Schien, and Eli Blevis. 2016. Understanding and mitigating the effects of device and cloud service design decisions on the environmental footprint of digital infrastructure. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’16). ACM, New York, NY, 1324–1337. DOI:
[70]
Chris Preist, Daniel Schien, and Paul Shabajee. 2019. Evaluating sustainable interaction design of digital services: The case of YouTube. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’19). ACM, New York, NY, Article 397, 12 pages. DOI:
[71]
Christian Remy. 2015. Addressing obsolescence of consumer electronics through sustainable interaction design. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA’15). Association for Computing Machinery, New York, NY, 227–230. DOI:
[72]
Holly Robbins, Joep Frens, Lenneke Kuijer, and Ron Wakkary. 2020. Speculative energy futures: Post-human design for the energy transition. In Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society (NordiCHI’20). Association for Computing Machinery, New York, NY, Article 136, 3 pages. DOI:
[73]
Christoph Schneider and Stefanie Betz. 2022. Transformation \(^{2}\) : Making software engineering accountable for sustainability. Journal of Responsible Technology 10 (2022), 100027. DOI:
[74]
Anne Spaa, Abigail Durrant, Chris Elsden, and John Vines. 2019. Understanding the boundaries between policymaking and HCI. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’19). ACM, New York, NY, Article 84, 15 pages. DOI:
[75]
Statista Research Department. 2020. Internet of Things (IoT) Connected Devices Installed Base Worldwide from 2015 to 2025 (in Billions). Retrieved July 2021 from https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/
[76]
Yolande A. A. Strengers. 2011. Designing Eco-Feedback Systems for Everyday Life. Association for Computing Machinery, New York, NY, 2135–2144.
[77]
Yong Tang, Jason Xiong, Rafael Becerril-Arreola, and Lakshmi Iyer. 2019. Blockchain ethics research: A conceptual model. In Proceedings of the Computers and People Research Conference (SIGMIS-CPR’19). Association for Computing Machinery, New York, NY, 43–49. DOI:
[78]
Helena Tendedez, Roisin McNaney, Maria-Angela Ferrario, and Jon Whittle. 2018. Scoping the design space for data supported decision-making tools in respiratory care: Needs, barriers and future aspirations. In Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth’18). Association for Computing Machinery, New York, NY, 217–226. DOI:
[79]
Vanessa Thomas, Christian Remy, Mike Hazas, and Oliver Bates. 2017. HCI and Environmental Public Policy: Opportunities for Engagement. Association for Computing Machinery, New York, NY, 6986–6992.
[80]
Bill Tomlinson, Eli Blevis, Bonnie Nardi, Donald J. Patterson, M. Six Silberman, and Yue Pan. 2013. Collapse informatics and practice: Theory, method, and design. ACM Trans. Comput.-Hum. Interact. 20, 4, Article 24 (Sep. 2013), 26 pages. DOI:
[81]
Bill Tomlinson, M. Six Silberman, Donald Patterson, Yue Pan, and Eli Blevis. 2012. Collapse informatics: Augmenting the sustainability & ICT4D discourse in HCI. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’12). ACM, New York, NY, 655–664. DOI:
[82]
Michael Veale, Max Van Kleek, and Reuben Binns. 2018. Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making. Association for Computing Machinery, New York, NY, 1–14.
[83]
Kelly Widdicks, Mike Hazas, Oliver Bates, and Adrian Friday. 2019. Streaming, Multi-Screens and YouTube: The New (Unsustainable) Ways of Watching in the Home. Association for Computing Machinery, New York, NY, 1–13.
[84]
Kelly Widdicks, Bran Knowles, Gordon Blair, Carolyn Ten Holter, Marina Jirotka, Federica Lucivero, Gabrielle Samuel, and Helena Webb. 2021. Anticipatory governance in the technology sector: processes, critiques and principles for addressing grand challenges in computing. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. 1--5.
[85]
Kelly Widdicks, Federica Lucivero, Gabrielle Samuel, Lucas Somavilla Croxatto, Marcia Tavares Smith, Carolyn Ten Holter, Mike Berners-Lee, Gordon S. Blair, Marina Jirotka, Bran Knowles, et al. 2023. Systems thinking and efficiency under emissions constraints: Addressing rebound effects in digital innovation and policy. Patterns 4, 2 (2023).
[86]
Charlie Wilson, Tom Hargreaves, and Richard Hauxwell-Baldwin. 2017. Benefits and risks of smart home technologies. Energy Policy 103 (2017), 72–83.
[87]
Alan F. T. Winfield and Marina Jirotka. 2017. The case for an ethical black box. In Towards Autonomous Robotic Systems, Yang Gao, Saber Fallah, Yaochu Jin, and Constantina Lekakou (Eds.). Springer International Publishing, Cham, 262–273.
Index Terms
- ICT under Constraint: Exposing Tensions in Collaboratively Prioritising ICT Innovation for Climate Targets
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Publication History
Published: 20 June 2024
Online AM: 11 March 2024
Accepted: 28 November 2023
Revised: 23 August 2023
Received: 18 October 2022
Published in JRC Volume 1, Issue 2
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