Take Care and Design the System

Human Computer Interaction researchers for a very long time have been working on solving issues to support efficiency and efficacy of working environment. With the development of the discipline and introduction of new perspectives, from social sciences and humanities, design studies, the HCI research agenda has changed. Interdisciplinarity of HCI encourages to ask questions that might be difficult to be addressed by other disciplines, and the richness of perspectives within the discipline helps in addressing complex socio-technological field (Star and Ruhleder, 1996).

Perpetration of technologies into every area of our lives also opened the door for researchers to take a wider perspective in their research and look at other areas of social reality and the influence technology has on it. Technology is not only a tool for efficient information processing, but also influences the way we travel (Airbnb), build relationships (Facebook), what we eat and how we dress (Instagram), how we consume news (Twitter), how we shop (Amazon). Of course, any of the previously mentioned examples is not limited to these cases – Twitter also changed the way politics is done, Facebook influenced social activism, Airbnb is a cause for spikes in rental prices, Instagram is presented as a reason for growing number of depressions. These socio-technical infrastructures are complex adaptive systems and require specific research agenda and critical reflection upon everything that research encompasses: framework, tools and communication.

In this blogpost I want to present my understanding of the Digital Civics researcher’s role and Digital Civics agenda. I will draw back on few articles that we have studied in HCI for Digital Civics module and critically reflect on them by comparing strategies for research presented in these pieces with some inspirations from social sciences and humanities.

OPTICS: What we see

None of the theories can explain everything. It simply takes an element of the reality in order to bring the light on it and let researchers, designers and public to work with the new framework on their own way – apply it in their work, operationalize it, see the benefits it brings and its limits, what it leaves beside is frame. But ultimately the way we describe the world shapes our experience of it. Words and language serve as tools that influence the way we perceive our place in the world, describe our possibilities and shape our imaginary: they build a frame for what is in our reach and what is beyond that.

Suchman’s Situated Action brought a new light on the reading of the role of plans in AI (Suchman, 1987, 2007). Once seen as a neutral tool, they became an element of the complex picture. Researchers were proposed with the framework that encouraged them to reflect on the way users interact with plans, how they put them in the context and navigate within constrained information (Duguid, 2012). Suchman presented how to read technology and its interface from the user perspective. She deconstructed what was a neutral, objective plan into an element of a bigger jigsaw and showed how this element works in the messy field of the human–machine interaction. The shift Suchman proposes is important because it changes the design optics fundamentally. We no longer ask if the design is supporting the original mental model of the machine through user’s interaction with the interface, but rather if it manages to make people communicate with the machine effectively on the human level, using the whole vocabulary and repositorium of cultural and social net in which people are immersed (Gaver, Beaver and Benford, 2003). This opens the door to new resources for designing plans and reading interaction between human and machine, once one would like to accept it.

The shift Suchman proposes is a change for plan’s status from intermediary to mediator, using Latour’s language of Actor-Network Theory. His perspective, revolutionary as well, opened the door for reading on agency of non-human elements (Latour, 2005). Plans when read as intermediaries are clean, they transfer the meaning without changing it. In the world messy symbols and connections, this means that something, an element, can go through the reality without changing it and therefore without being noticed by other elements of the reality. On the contrary, when we read them as mediators, we need to be more careful in identifying not only what goes in and what comes out, but also try to describe what is happening inside a symbolical Blackbox. In this case we can study interaction that happens with the plan and the situation that it causes. The framework allows us to identify roles and influences every actor in the interaction brings and trace the connections between them. Also, it allows us to see the whole interaction of connections with understanding and reflection on the instruments and elements present in this phenomenon. What Latour’s perspective can bring to the field of Human-Computer Interaction is the change in defining the status quo of an actor/actant by the number and quality of connections it has within the network, rather than by its self-explained, self-reflected identity or the qualities of the machine. This would mean when describing the use of technology for social goals we would not look for specific, individual elements that make this example original and unique. We would rather look on the situation and try to describe it by what kind of interactions are happening between different actors presented in this situation. We would not study individuals only and their perception of the situation, and we would not study the site by zoomed-out objective criteria. Latour calls the object of a study a collective phenomenon, which is built with individuals, their perceptions and their connections with other actors/actants in the field and with collective that is made with localized data flows and instruments that collect data, connections between instruments and other elements of the phenomenon. Shifting the perspective from personal/social, local/global framework to connections between elements allows us to study more collected phenomena, because there exist as many collected phenomena as there are collective tools. Although it’s so exciting, it needs scrutiny in tracing multiple connections between elements of the network. Trying to combine Latour within HCI is something I am still testing. This is simply my first attempt in describing how I see his theory could inspire HCI research agenda and I’m interested in working on it in the future. I believe that his perspective on sociology as a science of connections is valid framework for Digital Civics researchers who want to design and research complex adaptive systems.

On the other hand, I believe that HCI might also bring answers to some questions that Latour’s theory is posing. Having an experience in tracing various connections, describing multiple factors that influence interaction, having experience in using multiple methods for transferring meanings and setting up publics – HCI is a resource for expertise and reflection that can help face the challenge of a new description.

If we translate Latourian description into the language of design it means that we understand the agency of materiality and we can use it in order to cause specific reactions and situations, or on the contrary: to design objects in a way that they don’t communicate any specific meaning (Gaver, Beaver and Benford, 2003). We perceive materiality as an active participant, a social element, that influences the way we conduct our activities and perform our lives. Materiality shapes the way we collect information, how we process it and distribute. We are connected to the machines and technology, as much as we have always been. In my opinion it’s naïve to see human as someone in reign of technology and technology simply as an oeuvre of human imagination. Neither we are sole creators of it or dependent upon it. Technology design starts within our social imaginary, it roots have been long existing in our literature, theatre, film, mythology before it started to have a material shape or a form of code. It’s not a pure artwork of the intellect and individual labour, or human’s existence is solely dependent on the technological development. In social sciences and humanities there have been multiple researchers and thinkers who try to come up with new re-reading on the relation between human and technology. The perspective of co-relation is presented i.ex. by Bernard Stiegler, Noortje Marres, Adolfo Estalella, Jane Bennett and in my future work I would like to build upon it.

TOOLBOX: What we can do

We know a lot about how to collect data, how to analyse them but most importantly, we also know what kind of knowledge we can build through the use of different research methods.

In the context of discussion on how computational turn may influence research, danah boyd and Kate Crawford, have outlined six provocations for the Big Data phenomenon: its limits and biases, and presented the critical reflection on the consequences of blind use of Big Data in research methodologies (boyd and Crawford, 2012). One of the interesting examples they present is the change in describing social relations, from the moment when sociologists and anthropologist were among those who researched these and conducted their research through surveys, interviews in order to describe notion, quality and values of personal networks, to the moment when our relations started to leave the digital trace in transmission data: who do we contact, how wide is our social network, what are the schemes of our movement. Does setting up “See first” when following someone on Facebook necessarily means that we are in close relation with this person? What does it mean that we call someone often? Or if we only text and not talk over the phone? Quantified data provide us different with type of information, and therefore we can’t say that it’s contradictory to the previous one, it’s just different. Therefor researchers came up with the concepts of ‘articulated networks’ and ‘behavioural networks’, Big Data gave birth to these concepts and allows for researching them. As authors say: “‘Change the instruments, and you will change the entire social theory that goes with them,’ Latour reminds us”.

Tricia Wang comes up with another perspective on the topic. Her 2013 article “Why Big Data Needs Thick Data” started a discussion on the benefits on complementing Big Data with qualitative data (Wang, 2013). She works on quantification bias and points out the problems that comes up when industries use only information generated by quantitative data for their market and development strategies. According to her, it’s not enough, as it doesn’t represent the whole spectrum of social and cultural relations that take places and are performed in relation to any market product. Thick Data is quantitative data enriched with data brought to light using qualitative, ethnographic research methods that uncover people’s emotions, stories, and models of their world. Big Data can provide patterns, but they often lack explanation or, completely opposite, Big Data analyses generates knowledge gaps that can’t be solved by providing more quantitative data.

Calling back to researchers’ ethics and responsibility, we should be reflective about the methods we use in research and the kind of reality that they can represent. Feminist Data brings a valid example on how data collecting practices made the case for representation of our actual world: filled with biases and inequalities (D’Ignazio, 2019). As Digital Civics researchers, we should be aware of the fact that technology and technologically collected information is not free of it and try to innovate in our research toolbox with methodologies that will allow to address this problem. As researchers we are in the position that mitigates us to question knowledge practices and support the effort in producing information that builds a just and equitable representation of the world and people we study. An interesting example of how we might approach our research activities comes from ethnography practice that is a base for anthropological reflection. As the fieldwork of ethnography changes and ethnographers more and more often study places like laboratories, news agencies, museums, design studios, the role of ethnographer moved from that of researcher working with people in order to learn about their reality to the one of a partner in an epistemic collaboration that happens during the fieldwork (Estalella, 2018). The partnership in the epistemic collaboration is called joint-problem making. Ethnographers experiment with new methods in their fieldwork (speculative design, arts practice), and therefore fieldworks reminds more often an interface – it links diversity together, different backgrounds of people who create the field i.e., and in the same time unveils this diversity by allowing different clashes that has roots in people’s backgrounds to happen and learn from it. In this sense fieldwork happens in a para-site, because it is not only limited to studying place-based communities, its perspective is more open and includes various actors that interfere with the field.

PERFORMANCE: Complexity scene

Main character of a Weiser’s vision of 21st century life is a single woman named Sal (Weiser, 1991). As her day starts, she is asked about a coffee and answers only by mumbling, like if a question was asked not by a machine, but by a person close to her. In her work no information is lost, she influences the look of her technological workspace. Provided support from technology she is in control of all that happens in her job. It seems like Sal has everything she might need in order to go through her day without any difficulties – information.

Information is gold in Weiser’s world. It is a basic commodity; its existence and use are seamless. Or maybe it’s Weiser’s world that is designed to emphasize the role information has in our everydayness? Even more: an information that is understood within the context of activity management, simply as data provided to serve an execution of a specific task.

In their interactions article Bell, Dourish and Brewer, present the idea of information as cultural category (Bell, Dourish and Brewer, 2005). They state that perspective that comes from cognitive science makes us think of mind as a computer, a calculation device that processes data by electrical operations. As much, as this is true on functional level, there is a danger of limiting the notion of information to data that is simply being sent and stored. Can every situation be translated into electrical operation? Thinking about the role information plays in our lives, I would say that it has a place somewhere between clear, understandable and operational data and a situation that produces only ambiguity, without any justification for it. If we limit the notion of information only to data, we lose factors that build experiences and meanings. What helps us talk to each other and not get lost in the fog of ambiguity is the relevance of cultural code that is used in our communication, code that is developed through shared stories and meanings (Malinowski, 1922). Machines can provide us with operational data, but our existence relies on the use of all spectrum of information and creative application of it in different contexts (Rogers, 2006). Human ubiquity is much more complicated than machines’ one, therefore in terms of respecting the richness of social and cultural dimensions of our lives, we need to evaluate technology against the influence it has on the everyday complexity.

Kevin Salvin writes in his article: “(…) we are no longer just using computers. We are using computers to use the world. The obscured and complex code and engineering now engages with people, resources, civics, communities and ecosystems” (Salvin, 2016) This means that designers are moving form designing for people, from human centred design, to designing systems that work with other systems and influence each other. Designing as participation is acknowledging that from the starting point we – designers, researchers, consultants, coders, activists – are part of the system and our role is to suspend obvious and naïve explanation of the system as something that is supporting our immediate needs, feelings and desires without any change of the status quo, without any cost coming from it. Complex adaptive systems, as our reality for example, produce complex problems. Firstly, this means that such problem can not be solved without considering the whole system in which it is located. Secondly, that solving one usually leads to the creation of a new one. Complex systems are unpredictable and therefore, in order to attempt solving a problem that’s located in such a system, we need to consider the whole system on its own. David Snowden, a theorist of strategy and organisational decision making calls this method ‘probe, sense, and respond’. After first action undertaken, be it deploying a prototype or an instantiation of the service, or other variation of our intervention, we need to learn and observe the results it brings, in order to evaluate and redesign the action itself.

The question of how to design would be still present, no matter if we decide to design for publics or systems. The most valuable example of designing was for me presented by Ann Light and Yoko Akama in their concept of politics of care in participatory design (Light and Akama, 2014). This approach is characterised by intervening from within communities, through understanding their resources and context, it values and uses social and cultural complexity as a resource in the ongoing design process that is oriented towards sustaining and flourishing relations rather than designing a final product that is offered with or as a service. It supports the process of becoming “with” communities, through embracing their values and possibilities, their localized context and therefore builds resilience that will allow to act and perform within the system this community is located.

In my opinion it would be interesting to see Digital Civics researchers engaged with work on complex adaptive systems. I would argue that this perspective might bring new methodologies and directions in the Digital Civics research agenda.

Conclusion

As Digital Civics researchers we change our hats often, we are involved in the process of technology design and development, we work with social movements, through our activities we design and shape publics. Navigating between these roles is difficult on its own, but I believe that once we have a clear understanding on the scene we position our actions, we know what our optics are and what kind of tools we have in our hands, we will be able to use them wisely and efficiently.

 

 

 

References:

Bell, G., Dourish, P. and Brewer, J. (2005) ‘Information as a Cultural Category’, Interactions, pp. 31–33.

boyd, d. and Crawford, K. (2012) ‘Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon’, Information Communication and Society, 15(5), pp. 662–679. doi: 10.1080/1369118X.2012.678878.

D’Ignazio, Christina., Klein, Lauren (2019) Data Feminism, https://bookbook.pubpub.org/data-feminism (publication draft available for comments and feedback)

Duguid, P. (2012) ‘On rereading. Suchman and Situated Action’, Le Libellio AEGIS, 8(1), p. 6.
Latour, B. (2006) Reassembling the Social, Politica y Sociedad. doi: 10.1163/156913308X336453.

Estalella, A., Sanchez Criado, T. (2018) Experimental Collaborations: Ethnography through Fieldwork Devices. Berghahn Books.

Gaver, W. W., Beaver, J. and Benford, S. (2003) ‘Ambiguity as a resource for design’, Proceedings of the conference on Human factors in computing systems – CHI ’03, (5), p. 233. doi: 10.1145/642651.642653.

Light, A. and Akama, Y. (2014) ‘Structuring Future Social Relations : The Politics of Care in Participatory Practice’.

Malinowski, B. (1922) Argonauts of the Western Pacific. G. Routledge & Sons.

Rogers, Y. (2006) ‘Moving on from Weiser’s Vision of Calm Computing: Engaging UbiComp Experiences’, pp. 404–421.

Salvin, K. (2016) ‘Design as participation’, https://jods.mitpress.mit.edu/pub/design-as-participation (access 10.01.2019)

Suchman, L. (2007) Human-Machine Reconfigurations: Plans and Situated Actions. Cambridge University Press.

Snowden, David https://cognitive-edge.com

Star, S. L. and Ruhleder, K. (1996) ‘Steps Toward an Ecology of Infrastructure : Design and Access for Large Information Spaces’, Information Systems Research, 7(1), pp. 111–134.

Wang, T. (2013) ‘Big Data Needs Thick Data’, Ethnography Matters, http://ethnographymatters.net/blog/2013/05/13/big-data-needs-thick-data/

Weiser, M. (1991) ‘The Computer for the 21st Century’, Scientific American, pp. 94–104.


Author: Agata Jałosińska

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