Haptic Visions. Valerie Hanson
or shading (Stoll 72). About the color choices in one image, one scientist explains,
It [color] certainly can help to clarify the presentation because you can accentuate contrast in regions . . . which contain the point you’re trying to make rather than have the reader be distracted by contrast related to things that you aren’t worried about right now . . . . [In this image, for example,] you see all these lines here for atomic steps on the surface. So, if you look at that in black and white, your colors, your gray-scale has to be stretched to accommodate all those steps, and these steps are actually larger than any of the usual features on the surface. So some kind of stretching of the scale of the image has to be done in order to see the fine features that generally you’re interested in. . . . So, if you look at the image just in gray-scale, it doesn’t appear so clear because all the contrast is taken out by the steps rather than by the little bumps on the surface that you want to study.43
Adding color to STM images helps viewers grasp slight variations in value; Russ explains that human eyes can only pick out about twenty to forty shades of gray in an image, but can differentiate between hundreds of colors (35). Russ also observes that colors help humans verbally refer to parts of an image through different colors, as opposed to different shades of gray (35). Color allows viewers to not only distinguish differences in value, but also to import the value differences into language—another medium.
While added color helps viewers verbally and visually distinguish an image’s particular characteristics, and so eases the entry of the presented value into scientific discourse, the researcher cannot rely on a color correspondence or order while choosing colors to use. Edward Tufte explains, “Despite our experiences with the spectrum in science books and rainbows, the mind’s eye does not readily give a visual ordering to colors, except possibly for red to reflect higher levels than other colors” (154). Therefore, adding color to an image is dependent on the user’s or group’s decisions and previous associations with color. In his study of the digital image production of astronomers, Lynch explains that the dependence on individual or group associations to assign meanings to colors can lead to the user’s reinforcement of her or his expectations of the sample through color choice: “Color becomes iconic when used for color enhancement or when signifying intensity or red shift. That is, the code is selected intuitively to suggest properties the object should have” (“Lab” 71).
In images of the nanoscale, the question of whether color correspondences exist is unsettled. Science studies scholars Arie Rip and Martin Ruivenkamp observe that color choices are not fully determined in the nano-researcher community: Some researchers see some colors as commonly used for certain features or attributes and cite, for example, the default colors in imaging software (29). Figuring out color schemes involves the researcher’s preferences. One scientist I interviewed commented, “[Y]eah, so there’s some playing that goes on with false coloring and just looking at what highlights the features that you want to show. Those [colors] aren’t—of course, those aren’t real.”44 Another commented that he would try out different colors and would make a file of those images, images he would later return to, and choose a version he liked best.45 Using color, then, engages STM image-creators in another set of interactions to determine how to best present the data to users. Like other filtering techniques, choosing color extends the process of interacting through the GUI; choosing color engages the user in practices that also include scientific and extra-scientific cultural elements and conventions. By changing the appearance of the data and the image, chosen colors can also affect how data is read.46 As color choices are not based on a predetermined order whose meaning viewers will immediately understand, but instead are based on previous (and most likely unexamined) color associations as well as the experience of color in the image, color choices affect the viewer’s response to the image and his or her perceptions of what the image depicts.
Habituated Interactions: Coordinated Dynamic Effects
The operating dynamics of electron tunneling, movement in x, y, and z directions, and GUI use are separately identifiable in STM operations as well as in the dynamics of other visualization technologies. In the STM, however, the coordinated contributions of electron tunneling, movement in x, y, and z directions, and GUI use allow an intensification of the kinds of multi-directional interactivity and manipulability afforded individually by each dynamic. In the process of operating, these three dynamics constitute an instrument that encourages manipulability and interaction—interaction with and through images and data (as one might expect with GUI) , but also with atomic phenomena. As part of the coordinated dynamic of interaction, the user’s involvement intensifies, allowing for an increase in the user’s feelings of engagement (Rafaeli and Sudweeks). The affordances created by the coordinated dynamics of electron tunneling, movement in x, y, and z directions, and GUI in turn create rhetorical possibilities that are, in part, fueled by the feeling of engagement: manipulation and interaction themselves become rhetorical. Thus, manipulation and interaction form a strand of persuasive possibility that helps structure a user’s experience within the STM, and also engagement with other technologies whose dynamics may operate similarly.
The increased engagement encouraged by the operating dynamics of the STM resonates with the last type of human computer interaction, “flow,” further explaining how rhetorical experience with the STM is structured. As mentioned above, flow tends to include participation from both sides so that neither computer nor user occupies the positions of “sender” or “receiver.” “Flow” may most accurately describe how the human user interacts with the screen and microscope apparatus because users engage in repeated interactions as they manipulate the sample and the image—interactions that build on responses from the sample, user, and image, and also take on a playful quality. Researchers’ descriptions of using the STM echo the characterization of flow. Scientist Gimzewski and artist Victoria Vesna explain in a collaborative article, “through images constructed from feeling atoms with an STM, an unconscious connection to the atomic world quickly becomes automatic to researchers who spend long periods of time in front of their STMs. This inescapable reaction is much like driving a car—hand, foot, eye and machine coordination becomes automated” (11). In describing the experience of using an STM to someone who has never used the microscope, one scientist I interviewed responded by making an explicit link to computer games:
Well, it’s kind of like a late-seventies video game . . . . You’re looking at a computer screen and you see little blobs on the screen which correspond to, you know, typically will correspond to a single atom or molecule on the surface that you’re looking at, and you know, on good days you can manipulate these atoms or molecules, and then it becomes a lot more like a video game because you actually—most software interfaces are mouse based. If you want to manipulate something, that involves usually moving the mouse and clicking and then moving it somewhere else and clicking again. So that’s almost like, you know, Ms. Pac Man or something like that . . . . So it can be quite fun.47
Another respondent answered, “it’s hypnotic, I would say . . . . You go in and you’re exploring a part of the world that nobody has seen because of that scale and you often don’t know what you’re gonna find and you usually don’t understand what you’re seeing.”48 Other scientists, such as Eigler, remark on the playful qualities of exploration with the STM and also on some of the excitement they feel as they manipulate atoms (Eigler, “From the Bottom Up” 425; also see Chapter 4). For these users, the hypnotic, game-like effects of using the STM may not only influence their perceptions of what they are doing (e.g., making STM use more “fun”), but also how the researchers perceive themselves and the instrument. As N. Katherine Hayles explains about her experience with virtual reality:
I can attest to the disorienting, exhilarating effect of the feeling that subjectivity is dispersed throughout the cybernetic circuit. In these systems, the user learns, kinesthetically and proprioceptively, that the relevant boundaries for interaction are defined less by the skin than by the feedback loops connecting body and simulation in a technobio-integrated circuit. (How We Became Posthuman 27)
Whether or not users experience feedback loops, as Hayles describes, or a merging with the machine, Hayles’s comment shows how users may attune themselves to operating beyond the confines of what is considered the boundary of the body and, in a transformative, prosthetic relation, merge or fuse—physically and mentally—amidst the dynamic