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Design Paper Outline
Some initial ideas swirl around the metaphysics of design; using the Wikipedia entry, an examination of the fundamental categories into human understanding. (see metaphysics)
If design is fundamentally about a object, process, or system to serve some kind of purpose (see design), within functional, aesthetic, economic, environmental and socio-political goals-constraints, then the possible processes and assumptions which shape and construct the design process-thing-context milieu are important and numerous.
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There has been numerous design approaches for this construction <enumerate a number>. The sheer creativity and number pose both opportunities and challenges for design going forward, especially when considered in the light of recent advancements in artificial intelligence.
The purpose of our paper is to take both a step back and forward by eliciting a number of diverging assumptions about the process and purpose of design, exploring common and competing metaphysical assumptions about the nature of and goals for it.
By metaphysics, we take a Kantian position of exploring a few key fundamental categories of understanding which direct design. These categories are metaphysical in that they cannot be proved with complete empirical knowledge or airtight rational justification. For example, the need to include the users affected by technological design is a metaphysical assumption about what needs to happen (for success), since it posits “users” as a important category, with designers and managers as implied and important other categories. It thus imposes a view of the world onto complicated situations by directing people's attention to particular categories, and with it, particular determinations and actions.
The “users” is also metaphysical in that the empirical justification and rationale for categorizing people in this way and facilitating participation from them is always incomplete. The ebb and flow of its nature, purpose and usefulness to varying design processes and goals, across time is evidence of its metaphysical. For example, users and participation were considered necessary to address unionized workers (and resistance) to large production systems in the 1980s; considered necessary for organizational success through increases in quality-of-working life during the same period through socio-technical design; was necessary to ensure technology acceptance of ERP systems in the 1990s; was a problem throughout the same period because of the perceived expansion and chaos of technology resulting from end-user computing and bring-you-own-devices later on; is no longer useful because of the availability of numerous software apps that can be downloaded and utilized by users themselves.
From just this quick list of approaches to users and participation, there are a diverging set of core metaphysical assumptions about the nature, process and purpose of human participation in technological design.
Our aim in this paper is not to highlight and resolve these tensions, but to illustrate how highlighting and holding these tensions at the same time are helpful and necessary to address complicated design situations. This approach is informed by key ideas from dialectics, postmodern approaches to contradictions, and the possibility for wider vantage points through reflective judgments from experiences across participants.
As examples of this approach for participation: how could the playfulness of the software app approach be possible in the construction of organization-wide systems? Where and how is the development of technology and increased quality-of-working life in harmony and conflict with organizational efficiency? How can systems use be discerned and designed early in design through simulations? How would such simulations assist both the familiarization with and design of emerging technologies? How would people as “work-designers” or “experience-designers” change how we approach participation in design?
These and other approaches have been explored in various ways elsewhere <cite>. Our contribution is in eliciting and juxtaposing a number of key and contradictory metaphysical assumptions which could lead to a richer and human context for design.
In this paper, we illustrate this cross-metaphysical thinking of participation in design by examining important metaphorical assumptions in the design and participation of AI systems. We explore this in detail through the development and use of AI systems to fund at-risk students. Some key points:
the design of the AI system involved two technical design processes that can be informed and misinformed by traditional and singular assumptions about participation, design, and implementation. In this case and in many other AI cases, the projects begin with the selection and use of relatively well-established mathematical methods by experts, developed over many decades, now increasingly used in data analytics. The choice of these algorithms remains largely a specialized endeavour, although attempts to explain and engage a wider public to understand it is on-going. There is also a second algorithm produced by the first, through the patterns in large data sets, typically through statistical weights. These weights are shaped by the first algorithm through supervised (humans dictating the parameters) or unsupervised (letting the algorithm produce patterns without human imposed labels) learning . If the secondary patterns are “supervised”,
then people (experts and possibly government oversights groups and school administrators) were involved in determining how the first algorithm would be guided in its determination of the patterns through the selection of parameters; if unsupervised,
then the patterns emerge under little human influence and guidance. The algorithm develops whatever patterns in the data through various understandable and less-understandable combinations that are strongly correlated. The main site of influence in this unsupervised case would be the data and its initial structure, and the mathematical algorithm, which despites its semi-independent state, is a human construct. In both the supervised and unsupervised cases, the role and nature of humans, machines and decision making has shifted and stretched across time and space, perhaps radically, captured by but also escaping typical metaphysical assumptions about each of them, especially with the term “machine learning”.
Can machines learn? If so, how does this learning compare to and differ from human learning? Have humans ever learned without the aid of other devices? Perhaps at this point, we can ask the machine to give us an answer…. Human influence (as another position of participation) not only differs in how it shapes the first and second algorithms, but also the before, during and after machine learning and it's use. In terms of before, the data collected and used by the algorithm, of many students and from many states, is now an important influence on the patterns. It is these resulting patterns from the data that matter, and less the technology or the software algorithm as was previously the case in the design past. It is this other humans and their resulting data, from students and administrator, generated by them using other technology, that influences the data “before” AI design. Surrounding the before and after is a “during” phase which involves the collection, storage and flow of information through other human-influenced social-technical assemblages that facilitate, change and restrict the flow of data. For example, privacy laws can restrict whether data flows at all, and whether people have a say in opting in or out of their data and how it is prepared, summarized or detailed, and used. Once released, other people are involved in moving and “cleaning” the data for potential use by the first mathematical algorithm, through various human directed tasks to render it possible to use by the mathematical techniques in the first algorithm, to generate patterns which will become the second algorithm. <more> And finally, there is the “after” phase, where the secondary patterns are used in particular situations and cases, producing new data and predictions. These data and predictions are then used by other people to render important judgments and decisions about other people and situations, which then affect and influence other people's lives. The results of these interactions may eventually become days for the next AI design process.
And so for example,
Within and across these approaches,
If we took that to design and participation, then we could argue both the necessity of and “excess” (to use Derrida's term) for some key and fundamental ideas in design.
See Coyne, R. (1995). Designing Information Technology in the Postmodern Age: From Method to Metaphor. The MIT Press. https://doi.org/10.7551/mitpress/2373.001.0001, chapter 3, Deconstruction and Information Technology
See some important thoughts on metaphysics, deconstruction and Derrida at Coyne_1995
Participation and Technological Design: Dominant and Alternative Leaps Across the Who, Where, When and Why
Who, how and where people are invited to discuss (and influence) technological design rests ultimately on varying and competing assumptions about value and values. These assumed values, always-loosely justified leaps to what is valued, prompt various leaps to processes and procedures that will achieve these values, and to human participation. In any case, these values and procedural means also make always-incomplete reference to other ends when asked “why”, through necessarily-thinner elaborations and justifications. In all case, they are both the product of and produce the various semi-material realities of the changing technologies themselves. {need to elaborate – but I think there is a matrix of possibilities here}
We consider these necessarily loose connections across the values of human participation in technological design, in order to consider a range of nascent possibilities toward the future. We also consider these connections across a number of broad differences to the underlying nature of information technologies {list them out? enterprise systems; software apps; artificial intelligence}.
This forging of revised rationales for human participation in technological design also raises the more general argument for the future for participation in technological design.
Two Broad Approaches to Participation: **of** value; as **a** value
We begin with 2 broad approaches to the rationale of participation: participation as of value, and participation as a value.
Broadly speaking, “participation as of value” considers participation in technological design as a means to desired ends - e.g. efficient product-service delivery; product-service customization for customers; and harm reduction, to name a few. The desirability of these ends are necessarily associated with other ends to justify their pursuit, for example: efficiency in order to compete with other organizations in order to avoid organizational decline and death; product-service customization as a different means to the same competitive ends through differentiation (not cost); and the reduction of harm in order to steer within legal constraints and to avoid legal sanctions. In every case, the desirability of an end depends on a number of leaps across a set of “why” answers to justify their pursuit.
In term of the “how” to achieve these ends through technological design, a number of possible and never-purely derived methods and means are possible. Within those means, a number of possible rationales and methods for human participation are also possible, but not always. These possibilities revolve around how answers to the who, what, where, when and why of participation are justified in supporting its value to the desired ends.
For example, if improved organizational efficiency is the goal, there is a possible leap to assumptions that technology and business-process experts should in-charge of selecting and implementing new technologies into the organization. Employees would participate in order to learn how to use and adapt these technologies to achieve these organizational-efficient ends.
Very different means to organizational efficiency have also been proposed and evaluated; for example, socio-technical design and the efficiency produced by letting to coal miners figure out the most efficient practices and technologies. Similar conjectures were considered during the so-called end user computing movement in the 1980s, which radiates through in revised form in today's user-lead technology selection and use of software apps.
In both cases, the values and ends of the project typically drive the processes and means to achieve them. For example, the use of technology for organizational efficiency can prompt efficient design processes; for example, the use of technology experts to select “best of breed software; the “involvement” of people early in design to introduce the project and to get “buy-in”; the selection of representatives from identified groups to simplify deliberation; the categorization of individuals into stakeholder groups with more-or-less well defined interests; a focus on early design and requirements “sign-off”; and the identification of users and desirable use (and “resistance” if some oppose this use). Once infected with the end for design, that end can typically drive the procedures to achieve them.
In contrast, a company involved in the generation of new and novel electronic games could emanate from very different ends to technological design and participation: e.g. the freedom of individuals to explore and find generic software applications to select and customize for individual, group and collective needs. In this case, a marketplace of numerous app providers with numerous products serves as a ready source of supply for users to find and shape their digital space. Whether this generative context is an entirely new form of human participation in technological design, or whether it is sits on top of or beside the efficiency goals of production (e.g. the need for github and other software design systems to manage coding teams), it provides an alternative means-end reason for particular forms of participation in technology design, and its ends.
In any of these “participation as of value” cases, despite the broad range of ends and processes, people's participation in design is towards the production of value.
In contrast, and still depending on a loose but different set of relationships to means, is participation “as a value”. Participation as a value considers participation as end in itself, irrespective of any external ends. Participation is itself “good”, in whatever form it takes.
To be clear, there are possible cross-overs into the “participation as of value”, both to support and critique it. But participation as a value is good for itself, without focusing or pushing it as a means to other ends.
Despite this assumed independence from other ends, its justification depends on other higher ends to answer “why” for “its own sake”: e.g. individual rights to shape the technologies that they use and are affected by; the joy of humans shaping their own tools and work environment; seeing each and every person as offering a unique and important vantage point from individual experiences; seeking diverse perspectives on work and individual experiences in shaping technological design and use (but as a secondary end); the striving for limited or zero harm to people's quality-of-working life. {some of these are still ends driven, and so will need further work}.
Broader values about participation as a value may support a view that all organizations and technology should be driven by all humans interests, and not by the goals of other non-human things/means; markets, organizations (survival), technology for technology sake, artificial intelligence to see if we can replicate human intelligence, shareholders (a subset of human interests), or any other goals.
Participation as a value can also provide a critique of the assumed relationships across means and ends in participation as of value, for example the restriction of participation to “buy in” in order to efficiently produce efficient systems that address only shareholder value; the possibility of shrinking consumer demand if work is lost to automation; the loss of the natural environment making life unlivable.
Technology
In addition to participation of value and a value, various loose connections are made to the handling of the semi-material realities of new and changing information technologies. We use the term “loose” because they are neither the inductively-proven results of experiment, nor deductively-derived proofs from theoretical concepts, so must always remain more-or-less, conjectures about the processes and possibilities for realizing values.
In terms of information technology, we consider 3 broad social and material natures of it over time, all now operating in the present in 3 semi-independent spheres.
Large and cross-department technologies, custom-built initially in the 1970s and and 80s, and now evident in enterprise systems requiring more or less customization to achieve enterprise-wide results, are our first or three social and material natures to IT.
It is typically in this particular social and material sphere that we encounter some of the earliest discussions of employee participation, at work. As such, the who, what, where, when and why questions of participation were typically answered in the 70s and 80s, as a means to particular ends:
- why: to increase organizational efficiency, typically focused on quickening and streamlining inter-organizational processes through transactional processing and the semi-automation of production.
- what: the determination of requirements (and non-requirements) in designing a new technology.
- who: employees as users, managers as project holders, and designer-programmers as technology coders
- where and when: with customization, participation by employees was typically done early through meetings
- why: in order to produce the requirements for what the system should do.
- who: Typically unstated as participants were the designers who had continual access to shaping the emerging technologies, and managers who had the final say on whether certain requirements became required (or not).
- how: through designer lead conversations,
- how: in many industrial cases, the threat of industrial action if employee input was ignored or neglected tended to surround the focal how.
In contrast and at the same time, other configurations of the questions were organized through socio-technical logic:
- why: to increase organizational efficiency, typically focused on quickening and streamlining inter-organizational processes through transactional processing and the semi-automation of production.
- what: the determination of new work and technical arrangements through continuous conversation and adjustment
- who: across employees as work participants, independent of managers; drawing upon designer-programmers directly to build emerging technologies
- where and when: continuous participation and discernment across employees throughout
- why: employees have the local understanding and expertise to make change
- how: through self-organized teams
An enterprise systems emerged in the 1990s to dominate enterprise-wide systems development, we find a switch back to the first chain-of-reasoning, with alternative logics and new participants:
- why: to increase organizational efficiency, typically focused on quickening and streamlining inter-organizational processes through transactional processing (less semi-automation of production)
- what: the determination of requirements (and non-requirements) for a new technology;
- what: the selection of a “best fit” enterprise system, using its preexisting structures to change organizational processes.
- who: employees still as users, managers as project holders, business consultants to consider current and changed organizational practices, designer-programmers their to implement and customize the software.
- where and when: participation by employees is done throughout, but emphasis is on training and accommodation, and the identification of gaps needing either software customization or work-related change
- why: in order to change what the system will do or what the employee will need to learn.
- who: as before, unstated participants include the technology (STS), the consultants, the designers who have reduced access to shaping the emerging technologies, and managers who had the final say on project outcomes.
- how: through consultant-designer lead conversations with users throughout
- how: in many industrial cases, the threat of industrial action is no longer present. Nevertheless, so-called problems with employee resistance in post-implementation use remain.
Beginning with end-user computing and the rise of personal computing in the 1980s, extending into the internet era, we see another social and material ensemble emerge, which we call participant-lead computing, in an effort to explain in a phrase, the form of participation it encouraged. Whether through spreadsheets and word processor in the 1980s, internet browsers and e-mail in the 90s, social-computing in the 00s, or personalized productively apps in the 10s, the plethora of software available for download and use encourages a very different set of answers to our questions about participation:
- why: a range of responses, but generally the end is the production of useful software through participant-lead selection, exploration and use of software for personalized productivity: writing, deciding, and communicating
- what: the availability of numerous software apps to meet an ever-increasing appetite for functionalities that inform, delight, communicate –
- who: employees and citizen revealed demands; software app producers and social medial companies meeting and exceeding the want.
- where and when: participation is continuous and through society-wide use, within and beyond the organization; app companies meet or create the demands (or not) for their products
- how: through user forums and customer experiences; producing or reducing market demand
In many respects, the participant-lead computing looks like the dominant answer to the production of useful software, the diversity of human needs, and the inclusion of diverse perspectives into technological design. However, its ideal rests on a number of important assumptions that are not immediately closed to critical questions:
- enterprise systems development still dominates most people's experiences of technological design in work.
- the challenges of scaling individually-selected software into group and enterprise-wide coordination is difficult (but not impossible) to imagine.
- given the previous point, the conditions and possibilities for participant-lead computing may be minor compared with other social and material conditions
- the meeting of any particular individual demands still rests on the market availability of software to meet demand. If there isn't enough of a market for a particular function, individual needs remain unmet.
- with any downloadable software, there is still often considerable time and expertise required in order to shape the software towards individual needs and productivity. It may thus be only possible for those who are in jobs and organizations where such resources and time are available.
Our third social and material setting, while more recent but sitting beside and often drawing upon the second setting, is another social and material ensemble which we call data-revealed computing. Whether through spreadsheets and word processor in the 1980s, internet browsers and e-mail in the 90s, social-computing in the 00s, or personalized productively apps in the 10s, the plethora of software available for download and use encourages a very different set of answers to our questions about participation:
Implications of Big ("Efficient") and Small ("Artisanal") Ends on Participation in Design
On the questions of participation in design, it may be that addressing the question, “is participation in design even possible”, entails a tension from two different design scenarios, which may have some common roots (and technologies) … and, to be determined … some common ways to address. These scenarios/tension are not new but have been gaining ground at least since the industrial revolution.
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One class of scenarios are the designs of systems that automate and make ever more efficient and “human labor free” transactional and operational systems. These scenarios entail standardization of the products and the processes of human productive systems, e.g., historically, the springfield rifle case. As these design scenarios spread across human economic and social practices, they often spur productivity and allow for diffusion of innovation, the “generative” effects that Yoo et al like to talk about. And more and more activities are drawn into the maw of the automation efficiency scenario. e.g., the history of customer service is to separate CS from production, standardize scripts, then automate the interactions first with automated “menus” and increasingly with AI chatbots that emulate some sort of responsiveness (but fail IMO). In these scenarios the whole technosystem – the technology, the markets, the administrative systems are all subject to the same technological code.
The other class of design scenarios are, as you say, artisanal, with flexible, adaptable technologies, though also some highly specialized technology tools (or perhaps those are locally constructed?). This may be the domain of “shadow IT” in terms of organizational systems. Artisanship may be expanding as more “talented amateurs” share insights, ideas, technology advances, etc. Think of Youtube (or I image, Tik Tok) to share experiences and uses of technology! While the artisan tool user has some constraints that are imposed by distanced technology design, and certainly technology platforms try to capture these designers/users in their platform spider web, there is significant room to navigate, innovate, locally customize and apply.
In the first class of scenarios, technology futures are directed and constrained by participation-limited design occuring at a distance, guided by certain technical codes, logics. Yet the distanced/top down design makes technology (and teh technosystem) fragile when implemented locally. In the second class of scenarios, scaling is problematic as design is highly localized/contextually customized – if scaling aka diffusion of innovation is desirable. Welfare that could result from technology innovation is limited, if only localized.
It would seem that the first scenario necessarily wins the future, because “big is powerful” vs “small is beautiful”. Yet I think we could argue that the future(s) that emerge will depend on both scenarios, and how the tensions and interactions between them evolve.
So back to participation generally, and reflective judgements specifically, Where and how can contextualized artisanship pierce the integrated technosystem “machine” of design, and how can the advantages of the technosystem machine support diffusion of contextually developed innovation without injesting it into the “maw” of automation?
There are common technological roots – even with today's GenAI tools, they can be applied in either class of scenarios. But are flexible technologies the answer, an answer? I would guess not alone, for sure, as we see in the irst statement about GenAI.
The Design of Design -- Feenberg, Arendt and Reflective Judgment
1. Is participatory design still possible in a meaningful way in this age of large IT firms, AI, and packages?
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- This question is the result of a problem with overall distanciation in the design, implementation and use of technology, divorced from the contexts of production and use.
- Evident in Feenberg and his (now) drawing upon Foucault and Latour is the codification of practices in technosystems by remote and absent specialists in very-different contexts, which is then brought to and implemented in new contexts.
- These technologies are often presented as universal rationalities and fait d’acommplis (i.e. take it or leave it), but depends on the span of the technology (e.g. enterprise systems cast the organizations mechanistically, while personalized apps cast people as artisans).
- If you consider that many organization-wide technologies are driven by the goals of labour displacement, typically argued as necessary for “organizational survival” through efficiency and profitability, then participation in any form is severely curtailed as unnecessary.
- Typically, the customer, who benefits or not from the technology, is often absent from these conversations, despite having to deal with for example, how frustratingly limited technology-automated agents are in answering their questions.
- In any and all cases, technosystems design and effects are shaped and infused by the social and political contexts around them.
- Acknowledging that technologies also have semi-independent realities independent of those contexts (i.e. Latour).
- And so they can produce very different outcomes under different social and practical contexts, as so they are is ambiguous as per Feenberg and social construction suggest.
- Feenberg and Arendt argue that any and all “experiences” from diverse participants using or affected by technology are important for participation (taking part and part-taking)…
- This won’t happen in a boardroom around a table, talking conceptually about a technology that isn’t yet built or implemented
- It is only later on, when it is allowed by certain methodologies of design, and certainly too late to matter after the technology is cement, that the important experiences for participation are ignored.
- The response will be simply that the truncation of participation to only those legitimized and restricted experiences, and early in design, truncated by simple and shallow language, such as “efficiency” and “effectiveness”, are closed designs, or designs
- Perhaps it is only when more generic technology is put in front of users to play with for individual use that the problems of distanciation and the imposition of technology on work is reduced – although their may be other secondary uses that fall into the restricted cases; e.g. the use of the same systems to monitor and sanction work.
- Given there are very few experiences with technology in earlier design phases, perhaps the experiences people can speak to are with the good, bad and ugly of current technologies, work, and the effects
- These experiences can include managers and other senior executives and their distant experiences with profitability and other grander outcomes….
2. Is PD still even useful and important or is technology so powerful and configurable that we all can make technology do what we want? 3. Is PD more important for some contexts (eg organizational IS) vs personal IS or is it it important everywhere but in different ways? 4. How do philosophical views of design and technosystem help us to sort this out? 5. What are some of the underlying tensions and conflicts that are not yet solved? 6. Is consensus possible? How do we pay attention to the others, and to what degree? 7. What are the rights and duties of participants in design?
What are the key concepts we want to draw out and rely on? 1. Technosystem 2. Determinant judgments 3. Distributed justice 4. Reflective judgments
Pragmatic vs idealistic
Hypocritters
Rick Mercer's alley rant about Stockwell Day, a fundamentalist Christian politician:
“He believes in Capital Punishment and Jesus. Is there a version of Jesus that I don't remember?”
Hypocritical: Behaving in a way that contradicts one's beliefs. From “hypo” (low) and “critical” (as having knowledge to pass judgment). So hypocritical is low or poor judgment.
This is the only excuse for those Christians who voted for Voldemort in the US elections in early November - a lack of judgment. While believing in Jesus and that he was evil, a Trump presidency would do the work of God; which is at least a God who who would be pleased by the roll-back of progressive laws and case precedent for women, LGTBQ+, blacks, migrants, religious freedoms. To Make America Pray (to Jesus) Again (MAPTJA).