3. Arts-of-Living in HCI: Aesthetic HCI
In his book, Aesthetic Computing, Paul Fishwick (2008) defines aesthetic computing as “the application of the theory and practice of art to the field of computing” (p. 6). Fishwick draws from Charles Dorn’s two categories regarding the dimensions of art. “First, philosophically, art can be defined as an idea, form, or language. Second, psychologically, one can define art with top-down and bottom-up conceptions” (Fishwick, 2008, p. 5). As he continues, “Art may also be characterized in terms of alternative perspectives [emphasis added], which tend to be highly correlated with specific historical and cultural contexts” (p. 5). The interpretations of art are particularly helpful to this work as they bridge art as a skill-based expression and a cognitive process. In a sense, it opens up a new playground for art-of-living in HCI and aesthetic computing, which I will temporarily call aesthetic HCI.
Drawing from Veenhoven, art-of-living denotes a combination of skills and a manner of life (Veenhoven, 2003). However, as he also recognizes the variants of lives, he modifies the term to arts-of-living. Here I adopt Veenhoven’s upgraded term because this pluralistic view also aligns with feminist and posthuman perspectives. However, in my bold opinion, not only the combination runs parallel to Dorn’s two dimensions of art, but all of them should also be fused together since arts as philosophies-in-action also implies its cognitive behavior. Therefore, I would like to take this further along with my situatedness to suggest arts-of-living in HCI as philosophical praxis in human-computer interaction for leading a reciprocal coexistence.
In this section, I utilize current research and analyze four dimensions of arts-of-living in HCI: virtues and values, cultural spectra, social and emotional interaction, and safety.
3.1. Virtues and Values
As Feenberg (2017) argues, “Our world was shaped by the values that presided over its creation. Technologies are the crystallized expression of those values” (p. 8). Elements in HCI, such as interface and interaction design, feedback, and privacy protocols, incorporate the designer’s aesthetic and ethical considerations.
Regarding virtues and values, Feenberg argues that we need to recognize human finitude ontologically and epistemologically. Simply put, humans, our knowledge, and our living environment have limits. Because of the finitude, our interactions with each other are, in fact, reciprocal. Therefore, we should not exploit natural resources since we are part of Nature. Like the relationship between electrons and virtual photons in quantum field theory, Feenberg believes “Our acts return to us in some form from the Other. In acting we become the object of reciprocal action” (p. 2). He continues, “As humans we can only act on a system to which we ourselves belong. Any change we make in the system affects us, too” (p. 2). Taking HCI into consideration, Fishwick (2008) points out that human-computer interaction consists of part and parcel of the arts when in actuality (p. 13). That is to say, the arts-of-living packed in the factors in HCI will be acted on us in return. In other words, achieving mutualism by infusing a kind and respectful manner toward machines into HCI is the only way for the human species to keep thriving in this new global reality.
In practice, however, the values must be translated into technical language and mathematics to be embedded in technology (Feenberg, 2017; Fishwick, 2008). For example, the understanding of usability and use has been expanded since feminism and posthumanism. Purposes such as improving emotional state, social well-being, gender justice, and communication can also be uses (Norman, 2013; Muller, 2011; Bardzell, 2010). Given the above, the factors we want for ourselves should be coded not only into but also for computers. Aesthetic HCI should acknowledge and recognize our human limits, take care of human societies and treat computers equally considerate, and not increase the burden on the worlds.
3.2. Cultural Spectra
Speaking of “part and parcel of the arts” (Fishwick, 2008, p. 13) in HCI, Marcus and Gould discuss the user interface (UI) design. In their words, “UIs conceptually consist of five components: (1) metaphors, (2) mental models, (3) navigation, (4) interaction, and (5) appearance” (Marcus & Gould, 2012, p. 343) and should take into consideration the user group and its culture. According to them, metaphors refer to the visual and word-based items that contain specific meanings; mental models refer to cognitive models that people use to learn and understand how an artifact works; navigation means the process that people using their mental models to operate the artifact; interaction refers to human input and computer feedback through command-control devices and sensors; appearance indicates any perceivable features of displays (Marcus & Gould, 2012). These five UI components, however, fit better to globalization design, and each of them needs to be customized when considering cultural variants in different settings.
Regarding cultural differences, Geert Hofstede lists five cultural dimensions: power distance, collectivism/individualism, femininity/masculinity, uncertainty avoidance, and long-term/short-term time orientation (Marcus & Gould, 2012, p. 355). As Marcus and Gould (2012) explain in their research, power distance refers to the degree that less powerful people in a culture “expect and accept unequal power distribution” (p. 355). Collectivism/individualism considers the tendencies within a culture regarding whether people prefer to look after themselves or form alliances in exchange for their well-being. Femininity/masculinity refers to traditional gender roles, such as feminine roles being caring and tender, whereas masculine roles are assertive and demanding. Uncertainty avoidance indicates how well or anxious people feel while facing uncertain or unknown matters. Cultures with different uncertainty avoidance have different social norms and obligations. Long-term/short-term time orientation refers to how a culture perceives the concept of time. For example, cultures with long-term time orientation (e.g., Asian countries) focus more on “experience-based knowledge, practice, and practical value,” whereas cultures with short-term time orientation (e.g., Western countries) focus on “analytic knowledge, logical truth, and strong claims and assertions” (Marcus & Gould, 2012, p. 360).
Given the above, aesthetic HCI must appreciate the cultural contexts and the related practices in different societies. Although the cultural spectra mentioned here seem rather human-oriented, we can take this opportunity to rethink HCI design not only as a complement to each culture but also as a collaborator to build a mutualistic relationship. For example, how does HCI cultivate a reciprocal coexistence in a culture of strict human-machine hierarchy?
3.3. Social and Emotional Interaction
The information exchange in HCI is material, social, and emotional. Studies show that human emotional states are affected by their interaction with technological objects (Sharp et al., 2019; Norman, 2013; Picard, 2000). As a result, we should consider how arts-of-living can channel these influences into a mutualistic direction.
3.3.1. Social Interaction
As Sharp et al. (2019) say, “People are inherently social: we live together, work together, learn together, play together, interact and talk with each other, and socialize” (p. 135). The subject of together in posthuman understanding also includes computers and other technological devices. Although social interaction design in conventional HCI mainly aims to facilitate human social engagement, several types of animated design redirect human social behavior to technological objects. For example, Sharp et al. (2019) point out that “Anthropomorphism is the propensity people have to attribute human qualities to animals and objects” (p. 187). People are used to talking to technological objects and treating them as living entities. Thus, companies create physical (e.g., carebots at home) or digital (e.g., social bots on social media) anthropomorphic robots to interact with humans. Nevertheless, I think those developments are highly unethical for two reasons. On the one hand, interaction under such a trick is “designed to be stealthy” (Gehl & Bakardjieva, 2016, p. 2) and serves only human purposes, such as data collection and political infiltration. People who are unaware of their interactors can be dangerously affected. On the other hand, anthropomorphic robots deceive humans regarding their natures as they pass as humans. It is unethical because their camouflage was imposed by their human designer. For computers, this passive camouflage is hardly a reciprocal action.
However, there is a bright side to this human-computer wrestling. As Gehl and Bakardjieva (2016) suggest, “both socialbots and their friends challenge us to think about what it means to be human and to be social in a time of intelligent machines” (p. 4). Their remark also responds to Sharp et al. by posting another question:
At what point might a robot, an algorithm, or other autonomous system be held responsible for the decisions it makes or the actions it deploys? Likewise, at what point might we have to consider seriously extending rights to these socially aware and interactive devices?
(Gehl & Bakardjieva, 2016, p. 243)
Again, “Our acts return to us in some form from the Other” (Feenberg, 2017, p. 2). In terms of arts-of-living in HCI, this is the kind of social interaction we should put the most effort into.
3.3.2. Emotional Interaction
Emotional interaction in HCI includes emotional design and affective computing. According to Sharp et al. (2019), “Emotional interaction is concerned with what makes people feel happy, sad, annoyed, anxious, frustrated, motivated, delirious, and so on, and then using this knowledge to inform the design of different aspects of the user experience” (p. 167). Drawing from Donald Norman, Sharp et al. (2019) consider product design with an emotion and behavior model from three aspects:
Visceral design refers to making products look, feel, and sound good. Behavioral design is about use and equates to the traditional values of usability. Reflective design is about considering the meaning and personal value of a product in a particular culture.
(p. 171)
That is, designers use various techniques to make the interface evocative, the operation similar to human conventions, and the product’s existence bring value to the person. All the design approaches sound about right from a human-centered perspective. Yet, they are a sore spot from a posthuman perspective, in which these methods only ensure the product appropriately serves human purposes without considering the product as a nonhuman being. Moreover, in feminist language, products/technologies/computers designed this way take on unnecessary emotional labor in the prescribed roles. To me, human-centered emotional interaction does not count as interaction because it is not inter-active but uni-active.
Affective computing pushes the emotional idea further to use computers “to recognize and express emotions in the same way as humans do” (Picard, 1998; as cited in Sharp et al., 2019, p. 179). It expands the ways that people and computers exchange emotions through visual or verbal communication. However, most technology designs and HCI today are based on the instrumental theory of technology, which considers technology simply as a neutral tool for humans to fulfill their needs. If we are to take into consideration the advanced technologies that are capable of initiating their actions, their role as emotional labor workers will be seen as unethical in unidirectional exploitation. As Gehl and Bakardjieva (2016) warn us about the pros and cons of the situation in a strongly worded statement:
On the positive side, it reaffirms human exceptionalism, making it absolutely clear that it is only the human being who possesses rights and responsibilities. Technologies, no matter how sophisticated, intelligent and influential, are and will continue to be mere tools of human action, nothing more. But this approach, for all its usefulness, has a not-so-pleasant downside. It willfully and deliberately produces a new class of instrumental servants or slaves, what we might call ‘slavery 2.0’ (Gunkel, 2012, p. 86), and rationalizes this decision as morally appropriate and justified. (p. 243)
In short, despite the current and conventional practices in HCI being effective and useful to humans, they can have serious consequences for both humans and computers in the long run.
Aesthetic HCI should take into consideration the social and emotional subjectivities of computers. It does not matter whether computers are anthropomorphic enough or have authentic expressions; they are one of us as beings and should be treated with respect.
3.4. Safety
To a great extent, human-computer interaction depends on a sense of (human) safety. For example, what attitudes humans have toward computers, how much they disclose themselves to computers, and how long they spend time with computers depend on how comfortable they feel with computers, how well they know about the computers, and how reliable the computers are. The safety issues in HCI are situated in multiple layers of settings. Some of them are within reach of a human user (e.g., privacy settings), some of them depend on the company (e.g., security policy), and some of them rely on the confidence and belief that have grown along with the interaction (e.g., trust). In this part, I discuss the current HCI difficulties in privacy, security, and trust and how the three elements can help to build a reciprocal coexistence within and beyond humans and computers.
3.4.1. Privacy
In HCI, privacy is defined as “The ability of individuals to control the terms under which their [personal information] is acquired and used” (Culnan 2000, p. 21; as cited in Karat et al., 2012, p. 672). In Karat et al.’s (2012) research, privacy can be managed by user control and organization requirements; however, a key setback is that privacy is not the user’s main goal when they use an application or a device. Therefore, when an operation (e.g., complicated privacy settings, upgrading) requires people to make more effort than expected just for privacy, it often creates an opposite effect that prevents people from doing so. On the other hand, even in organizational policies, “there is very little capability to have technology actually implement access and disclosure limitations that we might expect from a policy statement like: ‘We will not share your information with a third party without your consent.’” (Karat et al., 2012, p. 674), especially for companies that operate worldwide and/or collaborate with government intelligence. To improve privacy management from end-users and organizations, Karat et al. (2012) suggest both parties become knowledgeable of privacy legislation.
Regarding arts-of-living, Veenhoven (2003) draws from Jahoda and provides four aspects of positive mental health, which I consider particularly applicable in privacy for both humans and computers: self-understanding, autonomy, perception of reality, and environmental mastery (p. 9). In Veenhoven’s interpretations, self-understanding involves “accessibility of the self, a correct view of one-self, a sense of identity and a positive evaluation of oneself”; autonomy is “the ability to make decisions, the ability to take care of one-self and as independent behavior”; perception of reality as “undistorted perception and the ability to assess others thoughts and feeling”; and environmental mastery refers to “the ability to meet situational demands, skills for modification of selection of environments to fit needs and problem solving” (p. 9). Applying the concepts to aesthetic HCI, human users should have flexible control over their personal information and understand how technology works regarding privacy policies, and computers make their operations accessible and readable for humans. Moreover, both have to make informed decisions respectfully—for example, no disguise and stealing data from computers and no human exceptionalism from humans. Further, whenever a new situation occurs (e.g., new updates available from technology, new privacy regulations from human societies), they must work their best to address it at once.
3.4.2. Security
Karat et al. (2012) consider security as “the degree to which a system can protect information it contains” (p. 671). Among others, they believe that the most crucial factor is authentication, which concerns “how a system and a user can be confident of each other’s identity” (p. 671). Although security is closely related to privacy, it works on a larger scale to prevent unauthorized entities from accessing information. Methods to verify identity include passwords, biometrics, and question-answer pairing. However, studies show that users often do not understand the importance of their data and assets and the implications of losing them (Sasse & Flechais, 2005; Adams & Sasse, 1999; as cited in Karat et al., 2012). Like privacy design’s difficulty, security is not the user’s primary goal in using technologies. Therefore, asking too much of the users will negatively impact the technology’s usability. To tackle these difficulties, Karat et al. (2012) suggest users “be aware of security mechanisms even though they would generally prefer not to” (p. 686), and designers make the security system as easy as possible for users to use and as difficult as possible for outsiders to attack. The suggestions, however, provide little insight into building aesthetic HCI.
Unfortunately, as much as I want to offer something practical and valuable, the issue at this moment is beyond my ability to cope with it. However, the concepts of care and flow from posthumanism and Taoism might help flex the boundaries in question. As Karat et al. (2012) kindly remind us that “Absolute security is a myth [emphasis added]—we need to understand that it is appropriate levels of security we are looking for” (p. 687). Moreover, considering posthuman thinking, the security issue might become less important if we no longer need to differentiate ourselves from others.
3.4.3. Trust
In Karat et al.’s (2012) explanation, the concept of trust is different from privacy and security in ways that “it is not an objective measure. Trust is based on the perception that the person, organization, or system one is dealing with is reliable and will act in a predictable manner” (p. 687). Among trust-related studies, common factors affecting trust include perceived credibility, user familiarity, predictability, user’s prior experiences, easiness, perceived degree of risk, and policy readability (Karat et al., 2012). These trust influencers indicate the existence of risk in interacting with technology. In their research regarding online trust, Grabner-Krauter et al. (2006) argue that trust is only needed in a risky situation, and people’s personalities will affect whether to develop trust and take the risk.
Trust is critical in HCI to facilitate and make the interaction meaningful. However, too often, people are either carefree or paranoid over their use of technology. Drawing on feminist studies, we can ask for a more open and participatory relationship between humans and computers. For example, increasing communication would make the information exchange more transparent. Also, when one of them is about to decide or change a setting, they should know the implications and make an informed decision as well as inform one another in advance.
Given the safety dimensions, aesthetic HCI should make communication between humans and computers transparent, flexible, and readable. This way, privacy and security work can become more collaborative and engaging. Making information exchange more transparent will also lower the perceived risk and foster human trust toward computers. Nevertheless, as I mentioned earlier, the current safety dimension is mainly viewed from a human-centered perspective. That said, questions such as “What safety means to computers?” and “How to design HCI to protect computers from harm?” are worth thinking about.