Ken, Claus, and all,

This discussion fails to illuminate how abduction might occur in design thinking, to indicate why it is appropriate to designing. or to explain how it might be used to establish an outcome that can be empirically tested. As with “heuristics”, “abduction" is treated as an umbrella word without immediate practical definition or application.

The paper “Building and Using A Theory of Design Thinking” at www.independent.academia.edu/charlesburnette <http://www.independent.academia.edu/charlesburnette> demonstrates how abductive thinking can be applied to produce testable outcomes. Although interpretive correlation is an inductive process. I see no reason for deduction to be called upon. Interpretation and the practical testing of outcomes and assumptions are highly desirable.

"Situated thought” involving the context, background, and circumstances of interest or concern, the identification of “Needs and Desires" within this situated  thought, "Intentional stances" that brings purposeful interpretation to each situation, “Structured Thought" based on scientifically valid findings and practical utility, and an "Iterative Process" of evaluation, assimilation and adaptation are seen as necessary components of an abductive process.  

We need to focus research on the mechanisms of how designers actually think rather than attempt to force design thinking into normative patterns and methods basic to other disciplines.  

Or, so I Believe,
Chuck

> On Mar 11, 2016, at 5:51 AM, Ken Friedman <[log in to unmask]> wrote:
> 
> Dear Claus,
> 
> Thank you for your reply. I had not intended to enter a long thread about this. I have written on this earlier, in different ways, and I was posting my own views with references to deeper articles. I wasn’t summarising or commenting on anything that others have written on the list.
> 
> While I think I understand your response [below], I disagree on your statement of the relationship between abduction and deduction as you phrase them. Deduction requires necessary premisses. An abductive inference does not provide the foundation for necessary premisses.
> 
> What is missing here is a series of steps that show the results of an abductive inference to be valid or necessary. This requires testing. In science, it requires significant testing. One reason for the high prestige given to deductive  inference in physics is the extensive testing of premisses. It has taken a century of careful, repeated, and varied tests to find evidence for gravitation waves, the last major deductive prediction of Einstein’s general theory of relativity.
> 
> Your description of how designers sometimes work is reasonable. Your description of the relationship between abduction and valid hypothetic-deductive inference is only partial. If you are describing a general heuristic approach to design outcomes that *seem* to work, this is one way that things happen.
> 
> The outcome of the normal heuristic design process in developing products and services is far from reliable. Much like the process of evolution in nature, heuristic processes work effectively at a high price in failed developments and extinct lines. The evidence of new product failure is clear. In one study, Mansfield et al. (1971: 57) concluded that once new product ideas move beyond the proposal stage, 57% achieve technical objectives, 31% enter full-scale marketing, and only 12% earn a profit . According to others, over 80% of all new products fail when they are launched, and another 10% fail within five years (Lukas 1998, McMath 1998). 
> 
> Clearly, the world would benefit from better ways to work. At the same time, many designed artefacts form their own tests in the real world — the question is how many tests the world can afford, and how much waste we can still manage. We live in a world where entrepreneurs, companies, inventors — and designers — want to produce things, try them in markets, and test them at scale. Thus we live in a world where 80% of all new products fail on launch, 10% more fail within five years, and only a small fraction of new companies last more than five years. 
> 
> The reason that I point to these statistics is that they are one outcome of the normal process of design and innovation as we have practiced it for the past several centuries. One goal of design research is to achieve better outcomes with less waste. While design is not a science in the sense that physics is, design is a professional practice that can benefit from better thinking. It can, to some degree, benefit from a richer foundation in science, in much the way that medical practice does.
> 
> As with medical practice, design often involves diagnosis to solve problems. Not all design involves solving problems — design sometimes involves invention or pure creation. Even invention or pure creation may involve research or science. For example, skepticism and rigorous testing should be our approach to any product or service based on principles that claim to defeat the laws of physics. Designers invent things that do not yet exist in the world. The iPhone, Google, and the hoverboard are cases in point. The perpetual motion machine is not. 
> 
> Serious research and richer research training will hopefully help us to reduce waste and create a better world. This is definitely the case when designers work with complex socio-technical systems (see, f.ex., Norman and Stappers 2016). To a great degree, much of what designers do will involve trials in a real world governed by imperfections, hurried managers, deadlines, and inadequate resources. The goal of research in the university system is to pursue responsible, valid answers without respect to the commercial pressures that designers face in the workplace. 
> 
> My reason for posting my notes on abduction, induction, and deduction was to clarify a research issue. Again, heuristics work — or seem to — because that’s often all we have time for in design practice. It’s also the reason for the massive failure rates we face in design practice. I posted a note to clarify an issue in an ideal sense. Understanding the nature of abduction, induction, and deduction won’t help you to overcome the difficulties and challenges of design practice when you face the constraints of industry and business — but this kind of understanding will help you to think better and more effectively, so understanding these issues thoroughly will give you a modest edge.
> 
> The better designers still have their failures. Products and services fail for a great many reasons. What I suspect, however, is that some designers get their failure rates down from 80% plus 10% to 60% and 5%. Some do even better. Over a lifetime of designing products and services, that adds up to a real difference.
> 
> Achieving this difference is one reason for design research. Compare the failure rates in medical practice in 1890 or 1915 against our failure rates today. You can also measure these differences in actuarial rates and human longevity, and you can measure them in the diseases that no longer exist. I’d like to think that we can achieve similar improvements in design practice — I doubt that we can make equally massive gains, but we can make useful gains.
> 
> To do this, designers need some fundamental thinking skills and research skills, much as physicians do when they take their pre-med sequence. One set of thinking skills involves understanding the difference between rigorous, valid logic and workable heuristics. 
> 
> Heuristics work. Everyone uses them, just as we all use rules of thumb and we all use abduction. We must nevertheless recognise the differences between different modes of logic, what they mean, and how to use them. 
> 
> One cannot transform an abductive conclusion to a deductive premise and then expect the deductive conclusion to be *necessarily* valid.  
> 
> Yours,
> 
> Ken
> 
> Ken Friedman, PhD, DSc (hc), FDRS | Editor-in-Chief | 设计 She Ji. The Journal of Design, Economics, and Innovation | Published by Tongji University in Cooperation with Elsevier | URL: http://www.journals.elsevier.com/she-ji-the-journal-of-design-economics-and-innovation/
> 
> Chair Professor of Design Innovation Studies | College of Design and Innovation | Tongji University | Shanghai, China ||| University Distinguished Professor | Centre for Design Innovation | Swinburne University of Technology | Melbourne, Australia
> 
> —
> 
> References
> 
> Lukas, Paul. 1998. “The Ghastliest Product Launches.” Fortune 16 March 1998, p. 44.
> 
> Mansfield, Edwin, J. Rapaport, J. Schnee, S. Wagner, and M. Hamburger. 1971. Research and Innovation in Modern Corporations. New York: Norton.
> 
> McMath, Robert. 1998. What Were They Thinking? Marketing Lessons I’ve Learned from Over 80,000 New Product Innovations and Idiocies. New York: Times Business.
> 
> Norman, Donald A. and Pieter Jan Stappers. 2016. "DesignX: Complex Sociotechnical Systems.” She Ji: The Journal of Design, Economics, and Innovation. [Uncorrected Proof.] doi:10.1016/j.sheji.2016.01.002
> http://www.sciencedirect.com/science/article/pii/S240587261530037X
> 
> —
> 
> Claus Cramer-Petersen wrote:
> 
> —snip—
> 
> "In my interpretation, in design activity, the reasoning types enter into a three step process involving: (1) an abduction that leads to a certain framing, explicitly or implicitly from some constraints, followed by (2) deductions that concretise and predict a solution or effect under the conjectured framing, and finally (3) an inductive reference to principles or accepted facts (possibly 'outside' the framing) that evaluates and tests, leading to a new iteration if the result is not satisfactory. Hence, the deduction following an abduction is arguably 'valid' in the sense that it develops and supports the argument proposed by the abduction, and the induction that follows tries to amend or evaluate the abduction through the deductive 'prediction'." 
> 
> This three step process is very similar to several models of design activity as well as heuristic processes and makes it relevant to perceive reasoning as a sequential process. In this process, the deductive reasoning (and to some extent the inductive reasoning) helps to explore and clarify the consequences of e.g. the abductively inferred hypothesis. Consequently, the definition of deduction stated as "a valid inference from necessary premises" underlines that deduction to explore or simulate the consequences of the premise (i.e. the abductive hypothesis or framing), making it one 'truth' amongst many possible. The latter evaluation is inductive and determines both whether the abduction (the hypothesis) or the deduction (a solution to the hypothesis) is valid. 
> 
> —snip—
> 
> 
> 
> 
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