AKF

Thesis Proposal: Communicating with Machines

Fall 2019

Smart homes, smart cars, smart watches, smartphones, in smart cities, are everywhere. We are surrounded with invisible agents, algorithms, sensors, and actuators that not only have an effect on culture, but are concurrently observing culture (Redstroem, J. & Wiltse, H. 2019). These agents are woven into the fabric of our everyday lives in ways we do not notice. They interact with us through our phones, track our movements, and facilitate our mobility through public space. These agents influence our behavior and establish complex relations with us (Iaconesi & Persico, 2016). They have varying levels of agency—they record information and generate data—lots and lots of data that influence decisions in the social sphere. Furthermore, these agents and the information they generate are fractured and dispersed across different spatio-temporal environments that range from the cyber, physical, and social (De.S. et al 2017).

The “agents” I speak about are non-human computational agents which make up the Internet of Things in smart cyber-physical-social environments, or Smart Cities. The Internet of Things describes the interconnectedness of everyday objects embedded with sensors and computing devices that are able to send and receive data. A smart environment is a space that is mediated by these sensors or other computational agents such as artificial intelligence (AI) and machine learning. A smart home might have a digital assistant like Alexa to help pay the bills, and a google nest to help with climate control, with little use for human activity. A smart city might have cars equipped with sensors that engage with their networked environments (sensors in traffic lights and crosswalks, all of which work with each other to facilitate mobility in public space for the driver and streetwalker to safely cross the street.

More than half of the world’s population live in cities, many of which are “smart” (Barth et al 2019). Even Raleigh, North Carolina has its own smart initiatives. Because of this trend, it is important for designers to consider the implications of smart infrastructures. By understanding the affordances of new technologies and its working schematics, including the networked capabilities of the Internet of Things, designers can begin to think critically who they are designing for and in what context (Forlano 2016).

Designers and researchers are calling for new frameworks to design in smart environments. Carl DiSalvo, designer and author of AdVersarial Design, structures workshops around perceiving a city from a robotic perspective. Thing ethnography by the Think Tank Project in Amsterdam studies human-object relations through the perspective of a thing (Giaccardi 2016). More than Human Participatory Design leverages non-human agencies, perspectives, and voices, leading to interesting and provocative questions about our environment, our future and ourselves.

This investigation is a plunge into what it is like to design and understand culture within a smart, dynamic,and urban environment. As pervasive, invisible and ubiquitous computing (as AI, sensing artifacts, robotics) occupies corners of public and private space, there is a design opportunity to speculate on future interfaces that bridge the cyber-physical-social landscape. The data generated by these actors (human, non-human, natural or technological) are qualitative and quantitative. This investigation focuses a lens on how these subjective (and objective) worlds can be blended, reframed and restructured in order to not simply see more, but to see differently.

Problem Statement and Justification

Smart Cities

A Smart City is a multidimensional and multifaceted conceptualization. It is made of networked sensors and algorithms embedded in objects—wearables, traffic lights and smart cars that are able to “unobtrusively and seamlessly connect and exchange information” (Mahmood 2019). Despite promises of these technologies to make cities smarter and better, their networked character has forced collisions between the city, its infrastructure, and its citizens (Forlano 2016. These agents make up the Internet of Things and can tell a story about human culture through the data they generate. This data is referred to as “big data” and can be difficult to read without expertise. As urban trends point towards adopting smart infrastructures, design researchers should develop methods to attend to their complexity, one of which, is the consideration of non-human agents the data they generate.

Ethnography and Data

Ethnographic observation is the study of human culture. Traditionally, its practice is conducted through teams who gather qualitative information in the form of observations, field notes, and interviews. These qualitative data are not numerically measurable, but are inherently rich, enabling ethnographers paint a multi-dimensional, context-driven, and “thick” understanding of humans and their environment (Colson, E., & Geertz, C. (1975). Traditional ethnographic methodology becomes complicated, however, when smart agents in the Internet of Things generate a different type of data that aggregates at a multitude much higher than traditional ethnographic data. These data are “big and thin” and provide a macroscopic but myopic view of culture. Big data lacks the inherent richness of thick data and without context, can only reveal the “what” as opposed to the “why. (Bornakke et al. 2018). Conversely, without big data, ethnographic thick data could fall short in asking the right questions (Wang 2016).

According to technology ethnographer Tricia Wang, integrating big and thick data forms a more complete picture—big data offers insights at scale at best of machine intelligence where thick data rescues the context loss and integrates the best of human intelligence (2016). According to Curran, the justification lies in their common characteristics and in their situatedness within the same epistemological field—within human behavior and cultural interpretation (2013). He coins the term “big ethnographic data” and lists synergistic ties between qualitative and quantitative data:

• Both are interested in the everyday culture
• Both explore patterns, movement and networks
• Both are interested in the physical (how the body interacts with products and space)
• Both can offer holistic and synchronic approaches to analysis (2013)

Blok et al refer to this new form of data as “big social data” which is computational, transactional, and digital and in need of re-alignment across the social sciences (2017). Others call for “the mixing of big decontextualized data with highly contextualized thick data can help uncover the meaning behind Big Data and analysis and entirely new interfaces and polyphonies can arise” (Bornakke et al. 2018).

By merging the two types of data, researchers could have a more holistic understanding of culture in complex smart environments, which could result in a number of things for design research including understanding users in socio-technical smart environments and understanding the affordances and materiality of smart agents and their heterogeneous data types. All of which would have an effect on the services we provide, the infrastructure we design, and roads we create, the interfaces we design.

Blending Data

While the incentive to blend data worlds evident, there is no systematic method for integrating quali-quanti methods in ethnographic research, much less an interface that allows for generating its blending in collaboration in situ (Bornakke, R and Due, B 2018). There are, however, some explorations:

Aipperspach et al uses a methodology of ethno-mining which draws on techniques from ethnography and data mining that is characterized by close iterative loops to incorporate both quantitative and qualitative in a “mutual dance of space observation” (2006). Bornakke et al proposes a big-thick blending methodology that is rapid, iterative, and collaborative with respect for individual expertise (Bornakke et al 2018). Blok et al explores a multi-methodology of “combining heterogeneous data: through a “stiching together” of digital and ethnographic data worlds (2017). These methods use visualizations to guide the ethnographic process and make visible the blended and stitched data worlds as well as a call to consider the heterogeneous nature of each data world, in its orientation towards time, space, and content (Aipperspach et al 2006, Blok et al 2017.

Given the affordances of new technologies in smart environments, there is a design opportunity to help blend the disparate data worlds together through explorations of a tool to mediate collaboration and co-production of heterogeneous data as well as visualizations to blend and analyze their results.

This investigation merges two frameworks: ethno-mining and big-thick blending during sequential stages of ethnographic research: in field work and analysis. I intend to explore how the affordances of networked objects—sensors and actuators that exist in smart environments can contribute to the co-production of data during a study—in part, to speculate about the future of human-machine co-production of knowledge in the future. Through exploring visualizations strategies, I will investigate how heterogeneous data types can be blended, mapped, and visualized to enable novel insights.

Research Question

How can the design of a multi-agent data (system) used by ethnographers during a study of a smart urban environment gather and visualize data to aid comprehension and analysis?

• How can geo-tagging connect ethnographers during field work to facilitate the co-production of data?
• How can multi-modal features promote heterogeneity among data types?
• How can dynamic visualizations generate novel insights through blending data?
• How can interactive mapping provide context to aid spatial analysis?

Incorporating Object-Oriented Analysis into Market Driven Mobile Ethnography

November 2019

Section 1 Purpose of my study

Current mobile technologies used for market ethnographic research are geared towards understanding consumer needs, desires, and pain points of a user journey. They typically function as a crowd sourcing platform that incentives users to provide feedback on consumer goods through payment. Once in the system, a user provides feedback on customer experience related to a particular product, store, or activity in the form of video diaries, textual notes, or prompts given from push notifications. There are a number of benefits for using mobile ethnography, some of which are in its price as it is cheaper than hiring a team of ethnographers to do research (Indeemo 2018). Another benefit is in its ability to reach a wide range of users from different locations (Indeemo 2018). Mobile ethnography also affords methodological naturalism as it unpacks the participant perspectives of everyday life, captures mobility within the marketplace, and begins to democratize the research process (DeBerry-Spence et al 2019).

While mobile ethnography is effective in getting the consumer feedback overtime and space, there is a missed opportunity to receive insight from the consumer goods they are interacting with, especially those that make up the Internet of Things. These smart objects in the Internet of Things possess their own capacities and kinds of experiences in interaction with the consumer and each other that could be useful for ethnographic market research (Hoffman et al 2017). According to Meyer (2016) the overall IoT industry is expected to be worth $3 trillion in 2025, with 27 billion different types of smart things connected to the internet. These objects are equipped with sensors and actuators and can sense, perceive, and act in an environment. Because of these sensing capabilities, design researchers have begun to explore user experiences from the orientation of the “thing” or smart object (Giaccardi et al 2016). The benefits of such angle of analysis is that generated insight can not only tell the researcher more about the thing itself, but about the user as well. It serves as a sort of reflexive method to obtain a deeper insight into consumer-object or human-thing relationship.

Given the prevalence of smart objects in the Internet of Things that are populating homes—Alexa, Google Home among others, there is a potential for mobile ethnography to incorporate networked capabilities from these smart objects into the software in order to receive data from the object itself (Hoffman et al 2017). Potential pain points could be observed if the quantitative and qualitative data of both the consumer and object are analyzed and assessed side by side. This study would function to consider the implications for this type of ethnography—what type of data can be generated and what sorts of insights can be revealed from incorporating an object-oriented perspective into mobile ethnographic software.

Section II Relevant Literature

For the purposes of this research, I conducted a literature review that investigates design approaches from a non-anthropocentric perspective in the context of mobile ethnography. Academic articles from scholarly journals and books which are peer reviewed from credited sources from the basis of my review in which the focus is to research and analyze a variety of methods that aim to elevate the artifact as co-ethnographer and or research artifact experience through an object oriented perspective. The articles explore ways to observe and identify aspects of artifact ontology including its essence, or materiality, its ability to perceive, sense, and observe, and how humans and artifacts can collaborate in the ethnographic process in the context of networked smart environments.

Section III Prior Work

In order to get a deeper understanding about current uses of ethnography, I conducted an interview with a design researcher and did a mini ethnographic study of two urban parks in downtown Raleigh. These studies revealed insights into means, methods and attitudes towards ethnography in the corporate context as well as affordances and limitations of individual participant observation of a dynamic urban environment.

Section IV Proposal

For my proposal, I am interested in how can the design of a multi-use mobile ethnographic tool that incorporates both the human (consumer) data and object (smart thing) data can serve as a viable research tool for market researchers in the professional context. How can this tool incorporate several researchers in collaborative, observational work? How can its interface enable asynchronous annotation and data input? How can the software leverage the networked capabilities of interconnected smart things on the web to to incorporate their data in the researcher observation platform? And how a collaborative web platform provides access to the data in a visually organized way?

Methods

I will select a range of participants and begin by conducting interviews.

I will also send participants a cultural probe package in order to gain insights into their general feelings about mobile ethnography and the smart objects they possess. I will use both the interviews and cultural probe information as research to help generate personas.

Once I do the interviews and get the cultural probes I will send out instructions for them to do an ontography map in which they map out objects in her home (the fixed ones that do not move) on top of a floor plan they will provide.

I will then send each participant a fit bit that is equipped with a sensor to track their location as well as sensor to track how much time it has been used. This way I can accumulate data on its use and location as well as proximity to other objects in the home. They will use the fit bit for a month.

During the month I will prompt them 2 times a week with questions regarding their attitudes towards the fitbit. They will also be responding to prompts from the mobile ethnography company's general website. They will do this in the form of diary studies, interviews, and photo studies.

After the month, I will have accumulated enough data on all participants on their day to day life as well as that of the Fitbit. I will combine this data together to see what insights unfold.

Data

• Will be from their month long study:
• Data from diary studies, photostudies, questionnaires, interviews, personal inventories, ontography map and floor plans, videos, images received by Mindswarms.
• Answers to prompts related to the Fitbit
• Data on the fit bit’s location and use throughout the month.

Resources

• 5 fit bits
• For each participant:
• $25 for the initial interview
• $50 for the ontography map, floor plan, and personal inventory
• $250 total for the whole study
• 5 participants: $1,250
• 5 Fitbits: $50/each: $250
• Total: $2500

Timeline

• January 1 - March 5
• Jan 1: Mindswarms puts out a call for participants.
• Jan 6: Mindswarms sends out a list to me with potential participants, I narrow down.
• Jan 7-11: Interviews Occur: 5 are selected.
• Jan 12: Initial payment of $25.
• Jan 13: Secondary payment of $50
• Jan 14: Fitbits are sent out.
• Jan 18: Pilot test to make fitbits work.
• Jan 20: Study begins.
• Jan 20 - 27 (Week 1): 2 prompts from me, 3 prompts from Mindswarms:
• Diary Studies, Photo studies, Videos, Images
• Receive Ontography maps, cultural proves, and personal inventory.
• Jan 28 - Feb 4 (Week 2): 2 prompts from me, 3 prompts from Mindswarms:
• Diary Studies, Videos, Images.
• Send Mid-Study compensation: $50.
• Feb 5 - 10 (Week 3): 2 prompts from me, 3 prompts from Mindswarms:
• Diary Studies, Videos, and Images
• Feb 11 - 18 (Week 4): 2 prompts from me, 3 prompts from Mindswarms: Diary Studies, Videos, and Images
• Feb 18: Send out a return package with instructions on how to send the Fitbit.
• Feb 18: Wire the remaining money for each participant: $125.
• Feb 20: Follow up interview over the phone asking about participants experience.
• Feb 20: Have the participants fill out a questionnaire about experience.
• Feb 23: Receive all Fitbits, upload data on to computer.
• Feb 24: Package and return Fitbits to owners.
• Feb 25: Begin analysis of data.
• Feb 25-March 5: Analyse data, create charts, graphs, and write up the results of the study.

References

Aisher, A., & Damodaran, V. (2016). Introduction: Human-nature interactions through a multispecies lens. Conservation and Society, 14(4), 293-304. doi:10.4103/0972-4923.197612

Bennet, J. (2010). Introduction. Vibrant Matter: A Political Ecology of Things. NC: Duke University Press.

Bødker, S., & Klokmose, C. N. (2012). Dynamics in artifact ecologies. Proceedings of the 7th Nordic Conference on Human-Computer Interaction Making Sense Through Design - NordiCHI 12. doi: 10.1145/2399016.2399085

Bogost, I. (2012). Alien phenomenology, or, What its like to be a thing. Minneapolis: University of Minnesota Press.

Bowens, M. (2018). The Flesh of The Perceptible: The New Materialism of Leviathan. Film-Philosophy,22(3), 428–447. doi: 10.3366/film.2018.0088

Chang, W.-W., Giaccardi, E., Chen, L.-L., & Liang, R.-H. (2017). Interview with Things: A First-thing Perspective to Understand the Scooter’s Everyday Socio-material Network in Taiwan. Proceedings of the 2017 Conference on Designing Interactive Systems - DIS 17. doi: 10.1145/3064663.3064717

Deberry-Spence, B., Ekpo, A. E., & Hogan, D. (2018). Mobile Phone Visual Ethnography (MpVE): Bridging Transformative Photography and Mobile Phone Ethnography. Journal of Public Policy & Marketing. doi: 10.1509/jppm.16.228

DiSalvo, C., & Lukens, J. (2011). Nonanthropocentrism and the Nonhuman in Design: Possibilities for Designing New Forms of Engagement with and through Technology. From Social Butterfly to Engaged Citizen. US: The Mit Press.

Forlano, L. (2016). Decentering the human in the design of collaborative cities. Design Issues, 32(3), 42-54. doi:10.1162/DESI_a_00398

Forlano, L. (spring 2017). Posthumanism and Design. She Ji: The Journal of Design, Economics, and Innovation, 3(1), 16-29. Retrieved April.

Giaccardi, E., Speed C., Cila N., & Caldwell, ML. (2016). Things as Co-Ethnographers: Implications of a Thing Perspective for Design and Anthropology. (n.d.). Design Anthropological Futures. doi: 10.5040/9781474280617.ch-015

Hoffman, D. L., & Novak, T. P. (2016). Consumer and Object Experience in the Internet of Things: An Assemblage Theory Approach. SSRN Electronic Journal. doi: 10.2139/ssrn.2840975

Indeemo (2018). White Paper: An Introduction to Mobile Ethnography. Indeemo, November 11, https://indeemo.com/mobile-ethnography-white-paper.

Kuijer, L., & Giaccardi, E. (2018). Co-performance. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI 18. doi: 10.1145/3173574.3173699

Meyer, David (2016), “Why Smartphones Are Bringing Down Internet-of-Things Revenue Forecasts,” Fortune, April 4 ,http://fortune.com/2016/08/04/smartphones-iot-revenue-ma china/.

Pink, S. (2015). Introduction: Doing Sensory Ethnography. Los Angeles: SAGE.

Empowering Artifacts

De-centering the Human in the Early Phases of the Design Process

05/2019

Since the 1980s the design paradigm has been influenced by human and user centered design, which has positioned humans as the center of form and meaning making of the natural, built, and technological environment (Forlano, 2017). This humanist framework has created a binary distinction between humans and non humans as us vs. them, the living vs. nonliving, and natural vs artificial. The psychological division and othering has contributed to a wide range of complex problems regarding sustainability and the environment and has led to a false sense of human identity (Colomina Wigley, 2016, pg. 136). As human forms of intelligence are being matched by AI, human-centeredness is put to question in an immediate way. In the future, who will be the form and meaning makers: humans? Or our artificial counterparts?

In effort to decenter the human a bit I want to highlight the role of the material, natural, and technological artifact as an entity with agency, autonomy, and power. I postulate that by giving emphasis to our non human counterparts during the early phases of the design process, designers can subvert the psychological limitations of “human-centeredness” in human-centered design to one that is more inclusive of all beings. This paper examines methods that leverage artifacts as agent, anthropomorphic, intelligent, speculative and equal. Though each method has degrees of human-decentering, I postulate whether or not they are truly non-humanist by exploring if it is possible to move beyond anthropocentrism entirely to understand the subjective and relative experience of non-human entities.

The basis of this paper stems from readings of architectural theory, sociology, and ecology, all of which question the relationship between humans, non humans, the built and natural environment. According to architectural theorists Beatriz Colomina and Mark Wigley, what makes us human is our interdependency with artifacts. We create tools to help shape the world and they in return shape us. We are completely suspended in the experience of designing and being designed in a sort of synchronized call and response between humans and non humans (2016, p. 23). The blurred boundary between human and non-human derives from Bruno Latour’s Actor Network Theory which defines the artifact as an actant, or “that which has efficacy, can do things, has sufficient coherence to make a difference, produce effects, alter the course of events” (Bennet, 2010, p. viii). According to ecologist Jane Bennet, actants also have vitality, the power “not only to impede or block the will and design of humans but also to act as quasi agents or forces with trajectories, propensities, or tendencies of their own...These material powers, which can aid or destroy, enrich or disable, ennoble or degrade us, in any case call for our attentiveness or even ‘respect’” (Bennet, 2010, pps. viii & ix) The methods below attempt to give attentiveness and respect to the artifact.

Method 1: Artifact as Agent

Designers must first engage with artifacts by viewing them as equal, active players. What better way to comprehend this for visual designers than to diagram? The Actor Network Theory (ANT) diagram provides a visualization of human and non-human actors as a part of a social system (Payne, 2017). When combined with Distributive Cognition Theory Mapping (Dcog), a designer can comprehend a system beyond the individual as the visualization shows how “cognitive resources are organized within a context...as mental activity is externalized onto the world” (Perry, 2003). Through a combination of ANT and Dcog mapping, a designer can reposition the role of the human user of a system and locate actors of different levels of value and purposes. Furthermore, the designer reframes the problem question from a human-centric point of view to a systems level. For example: “How does NCSU Campus Engage Bird Culture?” as opposed to “How do NCSU students engage Bird Culture?” The subtle change in semantics shifts positions of power and reveals non-human actants as important in ways that might be overlooked.

Method 2: Artifact as Anthropomorphic

The second method I propose early in the design process is to anthropomorphize non human objects. This idea is derived from a class project in which we utilized a human-centered research method, a cultural probe to inquire about folk’s hopes and fears surrounding AI (Gaffney, 2006). My group came up with a questionnaire that probed participants to approach analogue objects in their homes as if they were “smart,” thereby relating to these objects as their partner, child, animal, and so forth. Participant’s responses revealed the ability to relate to analogue objects as if they were active, living participants in their life. The responses revealed feelings surrounding AI—whether or not some objects should be embedded with technology, as well as interspecies differences and limitations.

Method 3: Artifact as Intelligent

Once the designer understands the power of artifacts, they can enhance their cognitive and agentic capabilities in savvy ways for intentional change. Through this method, artifacts become “interfaces, enabling different forms of human engagement” and “openings, possibilities for something new in the human, even a new human” (Colomina & Wigley, 2016 pps. 24-25). In Discursive Design, objects move beyond their utility and materiality into frictional, critical space by “magnifying, reflecting, and revealing aspects of culture for its audience...intentionally distorting in order to emphasize, propose, speculate, instigate, or criticize” (Tharp & Tharp, 2018, p. 13). The argument is to leverage repeated exposure to material goods for social change. Think: coy and invisible, yet hyper exposed and political. The Nutriplate, for example, is a discursive ceramic dinner plate that includes nutritional information about hundreds of food items on the rim of the plate. The plate both informs and provokes thought about nutrition and food subtly and effortlessly through its repeated exposure (Tharp & Tharp, 2018, p. 11).

Method 4: Artifact as Speculative:

Artifacts have superpowers as well. They can function as props or act as mediators between present and future possibilities. According to Speculative Design theorists Anthony Dunne and Fiona Raby, artifacts yield speculative power through their simultaneous belonging in the here and now and the world yet to be had as “their physical presence can locate them in our world whereas their meaning, embodied values, beliefs, ethics, dreams, hopes, and fears belong somewhere else” (2013, pps. 43- 44). The fictitious restaurant, Bistro Invitro, demonstrates this beautifully (Bistro In Vitro, 2019). By positioning the digital artifacts (photographs and videos of speculative food items) within the context of a contemporary restaurant website—a design that looks familiar and actual, the viewer is struck by a suspension in disbelief (Dunne & Raby, 2013, p. 100). Upon further glance, it is clear that the meat is fictitious, hyperbolic, and critical of meat grown in a lab.

Method 5: Artifact as Equal

In the preceding methods, the designer shifts position of power from the human to non human by giving the artifact agency, intellect, and speculative power, but arguably still within an anthropocentric framework. As we enter into a posthuman world where the boundaries between human and non-human become more ambiguous, what methods can designers employ to assure all points of view are being considered that lie outside of our species-centric definition of consciousness?” (Anderson, 2019). What methods can help us decenter the human to the extent that we embody the other’s cognitive, emotional, and physical experience fully—is that even possible?

The first thing that comes to mind is through full embodiment in Virtual Reality. Recently, I entered into an in-process project by an NCSU professor, Matt Peterson that provided a VR experience to understand scale and size of entities beyond our visual comprehension from the tiniest microbe to a large ship. The VR experience decentered the human to the extent that deep into the process, you felt as if you lost sense of yourself. I’d argue that his project was non-anthropocentric at best because it challenged the participants to experience scale from the perspective of the non-human.

In addition to embodiment, a radical means towards multi-species equity is to abandon the anthropocentric idea that thinking is the leading communication mode and to embrace the non-linguistic (Jeffries, 2017). In How Forests Think, Kohn focuses on semiotic form as a mediating center, and asks humans to discard “received ideas about what it means to represent something...explore representational forms that go beyond language...by going beyond human” (2013). I find the challenge of new form making interesting because that is what designers do: translate and articulate messages through form every day. In the design process, designers can aspire to bridge the communication divide between the human and non human by ideating alternative languages and symbols that cull from both perceptive centers.

Though it may be impossible for humans to design from a non-anthropomorphic center, methods to elevate the artifact and challenge notions of perception and form can lend themselves to adaptive and inclusive design solutions. As Monika Bakke states, “A planetary perspective on human life vis-à-vis nonhuman forms brings to attention not only vast spatial dimensions but also immense temporal dimensions” (2016). Decentering the human in the design process can only function to warp and shift our perspectives in ways we might not consider to develop a more nuanced understanding of the hybrid ecology of humans, non humans, technology, and society. To summarize Donna Haraway, it is through these multiple decenterings and wounds to the narcissism of the humanist that the liveliness of technological and companion entities come forth, bringing hope to our posthuman world (2004).

References

Anderson, M. (2019, March 11). What Does "Posthuman Design" Actually Mean? Retrieved from https://eyeondesign.aiga.org/what-does-posthuman-design-actually-mean/

Axel, N., Colomina, B., Hirsch, N., Vidokle, A., Wigley, M., (Eds.). (2018). Superhumanity: Design of the Self.: Minneapolis, MN: University of Minnesota Press.

Bakke, M. (2016). Deep Time Environments: Art and the Materiality of Life Beyond the Human. The Journal of Electronic Publishing, 19 (2).

Bennet, J. (2010). Vibrant Matter: A Political Ecology of Things. NC: Duke University Press.

Colomina, B., & Wigley, M. (2016). Are We Human?: The Archaeology of Design. Zürich, Switzerland: Lars Müller.

Dunne, A., & Raby, F. (2013). Speculative Everything: Design, Fiction, and Social Dreaming. Erscheinungsort nicht ermittelbar: MIT Press.

Forlano, L. (spring 2017). Posthumanism and Design. She Ji: The Journal of Design, Economics, and Innovation, 3(1), 16-29. Retrieved April.

Gaffney, G. (2006). What is a Cultural Probe? http://www.infodesign.com.au/ftp/CulturalProbes

Haraway, D. (2004). From Cyborgs to Companion Species. Retrieved from https://www.youtube.com/watch?v=Q9gis7-Jads/

Jeffries, S. (2017, August 23). Humankind by Timothy Morton review – no more leftist defeatism, everything is connected. Retrieved from https://www.theguardian.com/books/2017/aug/23/humankind-solidarity-with-nonhuman-people-by-timothy-morton-review

Kohn, E. (2013). How Forests Think: Toward and Anthropology Beyond the Human. Berkeley: University of California Press.

Payne, L. (2017). Visualization in Analysis: Developing ANT Analysis Diagrams (AADs). Qualitative Research, 17(1), 118–133. https://doi.org/10.1177/1468794116661229

Perry, M. (2003). Distributed Cognition. HCI Models, Theories, and Frameworks: Toward a Multidisciplinary Science Interactive Technologies, 193-223. doi:https://doi.org/10.1016/B978-155860808-5/50008-3

Tharp, B. M.; Tharp, S. M. (2018). Discursive Design: Critical, Speculative, and Alternative Things, Cambridge (Mass.): MIT Press.