Composing with AI

Rhetorical DIKW

Combining traditional DIKW with circulation theory creates a rhetorical approach to DIKW suitable for active pedagogical use, and also helps clarify the writing process of GenAI. Rhetoric involves evaluating ecologies and experiences to facilitate decision-making, active engagement, and the promotion of mobility and equity (Aristotle 2007, Edbauer 2005, Hinks 1940). Since evidence without a human context can be gathered unethically or turn into dogma, rhetoric values both evidence and experiences (Hinks 1940, Katz 1992). Therefore, integrating a distinctly rhetorical dimension into DIKW should emphasize the rhetorical effort required to transform one level into another, rather than just how content moves. Rhetorical DIKW primarily differs from the conventional DIKW by adopting an explicitly future-oriented approach to knowledge creation. It regards wisdom as an ecological impact that writers should aim to envision while navigating all levels effectively, thereby connecting lived experiences, observations, circulation, and the future.

Data

‘Data’ can, simply, be whatever precedes ‘information’ when information is connections between points with meaning beyond those points. Kelleher and Tierney aggregate definitions of data across the information and scientific tradition into data as “abstractions of real-world entities (variable, features, attributes)—not the thing observed itself but a record of the thing” (2018 p. 39). Kitchin highlights purposeful abstraction as the key transformation: data spatiotemporally abstracts the world—selectively cutting something from its time and place—via a capture method (note-taking, photographing, duplicating digitally, etc.) to build information. Salvo (2004) identifies data as the product of analysis, and Buckland describes data as collected records available for processing, in either a virtually or physical place (1991 pp. 353, 354). Therefore, a rhetorical definition of data should emphasize the purposeful transformation that occurs when data is collected, acknowledging the imperfection of abstracting and isolating something from life when it is added to a dataset seeking to represent ‘lived’ reality.

Data: purposefully collected measurements of the world (stored or recorded as measurements, either quantifiable or qualitative)

Data, as a practice of representing the world, may be thought of as using one’s experiences to locate and place dots on a map, like figure 3.

Information

Rhetorically describing information must account for how a document is information when one reads it to entertain a new idea and how the same document becomes rhetorical data when combined with other sources to make a new piece of information (a narrative proposing a new idea/pattern). The Latin and Greek origins of information (informatio, morphe, or plērophoria) connote giving form to ideas to convey them to someone (i.e. design) (Buckland 1991), and information-as-quantified-intelligence refers to bits assembled into a digital document (files, posts, etc.) for circulation, so information distinguishes itself through genre and encounter, say as document or narrative to an audience (Buckland 2017). Data may possess the possibility ‘to inform,’ but it requires processing first; “raw data” is a misnomer, but to say a dataset “informs” without processing labor is disingenuous. Rhetorically, information is data transformed into a meaningful string or pattern, while data is a prospective component one may combine with others to produce information.

Information: data organized to be meaningful or usable (a ‘pattern-making’ process over ‘quantified intelligence’ or a ‘usable unit’)

Information, as a practice of making meaning from specific points, may be thought of as connecting the located dots into a strand of meaning, like figure 4.

Knowledge

Kelleher and Tierney aggregate knowledge definitions for industrial Data Science as ‘information structured to be understood or applied’ (2018 p. 56). Knowledge is the point where information transforms from legible pattern representing the world (believable) into a way of understanding some (all?) of the world (belief). Existence in the world is social, so knowledge implies a social connection around a shared belief in information with the capacity to effect how one views existence. Information known by one person is a belief; knowledge is belief shared with others—something beyond information duplicated in a network (Gleick 2011 p. 409). Knowledge has to be information multiple people share experience of, through belief or other social agreement (citation, etc), enabling them to view the world a certain way together.

Knowledge-making invokes concern for futurity and power whether it is always acknowledged. Foucault argues that Enlightenment moving truth (via knowledge) from the domain of monarchs to the domain of (more) people made it social (Foucault 1984 p. 37, Foucault 1975 p. 174, Foucault 1975 p. 192, Foucault 1978 p. 265). Buckland differentiates information from knowledge as an idea that is solely the possession of one person’s mind, like a belief or opinion (1991 p. 351, p. 352). Therefore, information becomes knowledge when more than one person socially shares it (not the same as information replicated in a network) (Gleick 2011 pp. 76, 416). Information that multiple people share experiences of—that they can rely on and defend (Merrill 2002 p. 50) because of its legibility and alignment with information or knowledge they already possess—is the rhetorical transformation of information into knowledge. Citation, for example, signifies that information aligns with other experiences. Building communities around these practices is part of institutionalization. Composition and PTC are integral to sharing experiences, whether through researching and synthesizing arguments about life and the world, document and interface design, or through theories of audience and the systems that shape data collection, pattern-making, and experience-sharing. Regardless of the approach, Composition and PTC are part of the labor of collecting and making data, information, and knowledge, visibly or hidden (Star and Strauss 1999). The labor of knowledge-making, therefore, makes a reasonable organizing concept for writing classes because it accounts for disciplinary concerns of Rhetoric and Composition and PTC while directly invoking active learning principles of Merrill’s first principles while teaching skills relevant in industries and other cultural institutions.

Knowledge: shared experience of information, through communication or application

Knowledge, as a shared experience of information forming joint belief, may be thought of as information strands overlapping and binding together into social bonds, like figure 5.

Wisdom

Wisdom completes the feedback loop of knowledge-making wherein people apply or practice their shared knowledge, either in an institution or part of a distributed community. Wisdom invokes futurity and implies ethics, making it an ideological minefield. Kelleher and Tierney aggregate wisdom definitions into, succinctly, "knowledge applied appropriately" (2018 p. 56). Wisdom is where data-driven fields like Data Science acknowledge their role in shaping the future beyond wrangling data into usable, informative units. The appeal of fields like GenAI and Data Science that rely on large datasets, high-performance computing, and novel applications, is that they present ‘wisdom’ (the future-tense) as a data-driven product more efficiently produced with machines (Kelleher and Tierney 2018 p. 56, Zuboff 2019 p. 14). Bluntly, industrial data uses empiricism to argue the future can be planned, so next questions are ‘by and for whom?’

Wisdom, in other words, has to do with the why of knowledge-production: what ends and material effects on ecology and living knowledge-work should pursue. This confirms the rhetoricity of previous levels: the nature of the data and the form and meaning of the information effect the knowledge underpinning wisdom. Therefore, conscious consideration for the trajectory of thought into action is an essential rhetorical concern of wisdom as a process. Because Rhetoric emphasizes decisions, mobility, and ecological awareness, future-oriented application of knowledge promoting democracy, justice, and survival is the rhetorical transformation of knowledge into wisdom.

Survival, as imagining a future and ability to live in it, reminds us that people need tangible futures (Kohn 2013 p. 194). Inability to imagine a future can empirically indicate insecurity and unsafety, something debilitating or traumatic depending on how long it lasts. DIKW and AI alone produce a privately-owned and technocratic certainty that is anti-rhetorical (Zuboff 2019 p. 40, Johnson, Salvo, and Zoetewey 2007). Democracy and justice refer to tireless and rigorous actualization of symmetry for people’s ecological relationships intersectional by identifying the greatest power asymmetries and applying appropriate asymmetrical responses to remedy them (Crenshaw 1989 p. 167). Survival, justice, and democracy are ultimately political, human problem dealing with human-made institutions, power, and the nature of humans-in-the-world (Kohn 2013 pp. 194–95) coming about through planning and cooperation. Rhetorically presenting DIKW can illustrate for students that cooperation with machines always has human ends and results that they have to consciously craft, with or without machines.

Wisdom: future-oriented application of knowledge promoting democracy, justice, and survival

Wisdom, as action based on a shared worldview, may be thought of as people’s knowledge strands set on a three-dimensional plane spatiotemporally persisting to form parts of a new map, like figure 6.