Counter-intuitive Design Thinking: Implications for Design Education, Research and Practice

Dr Terence Love
Curtin University, Western Australia
Lancaster University, UK


This paper reports research into recent changes to design practice, research and theory in Art and Design fields. It draws attention to the fact that Art and design practices and research have extended into the territory of complex socio-technical systems design. The analyses suggest these changes imply it is necessary for Art and Design to re-envisage theory, research and practice in light of findings from the field of complex systems design relating to counter-intuitive thinking. The findings broadly challenge many of the traditional claims of design theory, practice, research and education.

Keywords: complex socio-technical systems design, counter-intuitive design thinking, Art and Design, design theory foundations.


The human thinking of design activity is compromised by cognitive biases, biological limitations and fallacies (see, for example, Fernandez-Armesto, 2004; Gilovich, 1993; Klein, 1996; Knight, 1999; Labossiere, 1995; Schacter, 1999; Stroessner & Heuer, 1996; Warren, 1976). These cognitive limitations are grounded in the evolutionary development of human beings (Damasio, 1994, 1999; Fernandez-Armesto, 2004). Human cognitive processes equip us to respond quickly to direct simple causally obvious challenges in which outcomes are close in time and space and the immediate result of obvious causes. They do not equip us to envisage, predict or make judgments about complex situations in which causes of outcomes are complex, multiple and hidden with outcomes and causes are remote in time and location.

There is little evidence design professionals in Art and Design take account of these limitations of human thinking whether in design education, design practice, generating design solutions, design methods and design theory-making.

In contrast, the field of complex systems design (particularly socio-technical systems) has committed extensive effort into addressing these issues and developing specific design methods to address them.

Recently, design practice, research and theory in Art and Design has crossed extensively into the realm of complex socio-technical systems design with new sub-fields such as design strategy, design management, ergonomics, post-modern design, rhetoric, participatory design, user-based design, collaborative design processes, reflexive design, reflective design practice, design evaluation, interactivity, interaction design, mass customization, and open source design.

The above indicates that:

To explain these issues in more detail, this paper focuses on counter-intuitive thinking, a core element of complex systems design. In the longer term, this provides a basis for identifying other aspects of complex systems design important for Art and Design and provides a template for including them into Art and Design.


Until recently, the focus in design in Art and Design has been on form, attractiveness and simple functionality. Design methods and theories of Art and Design have focused on the immediate and close at hand where causes are usually direct: attributes the human brain is evolutionarily well adapted. Design education has aimed at refining these skills.

Design practice in Art and Design, however, has increasingly included creating designs whose influences and effects are remote in time and place and with multiple causal factors often with feedback loops in the socio-technical arena. In addition, many conventional design situations in Art and Design are now increasingly viewed with more sophistication and take into account additional socio-technical design factors with feedback loops. These changes reposition many previously ‘normal’ design issues addressed by Art and Design designers as complex systems design problems to which the findings of the complex systems design field would seem obviously to apply.

A problem, however, is that design practitioners, educators and researchers from Art and Design are presuming the assumptions, concepts theories, design methods and analyses of its earlier eras apply to these new complex systems situations. They do not.

Complex systems designers and researchers have focused on identifying and addressing the specific problems associated with how limitations in human thinking and understanding compromise the development of good design solutions. The above issues are collated under the heading of ‘counter-intuitive thinking’.

Counter-intuition: errors of thought, feelings and intuition in design

To recap, humans throughout our evolution have adapted to be able to deal with situations that are simple, close in time and space, and where causes are directly and obviously linked to outcomes (touch a fire and your finger gets burned). Our brains have also learned to occasionally adapt to forecasting the outcomes of situations with a single feedback loop (room temperature rises, thermostat cuts in and room temperature falls). In terms of feedback loops, the absolute limit of human thinking seems to be to understand situations with two feedback loops. Only the most experienced complex systems practitioners are able to intuitively assess the behaviour of a situation with two feedback loops and then only approximately. These limitations apply to designers as much as non-designers. A simple test: Peter has $1.10 and buys two items. The first item costs $1 more. How much is the second item? Most readers answer 10 cents. This is a simple uncluttered single feedback loop problem. The answer is $1.05 and 5 cents. To test if one can easily understand a double feedback loop situation try .

Most contemporary non-trivial design problems, however, have dozens or hundreds of feedback loops. Traditionally, designers from Art and Design fields have dealt with this problem by defining the bounds of the design context so that it excluded feedback loops; by ignoring the feedback loops by calling the situation ‘wicked’, or by avoiding thinking about the feedback loop issues and using the traditional tools of bodily feelings, intuition and visualisation that are appropriate to non-feedback loop problems. All of these result in faulty or incorrect solutions in design situations involving 2 or more feedback loops.

The usual design approaches of intuition, visualizing and feeling ones way round a solution do not help when one is unable to fully envisage how the solution will behave. Evidence shows that people intuit the wrong answer whilst believing absolutely (on the basis of their feelings and mental comfort) that they are correct. Meadows (1999) a key author of the seminal book ‘Limits to Growth’ (D. H. Meadows, Meadows, Randers, & Behrens III, 1972) that sparked off much of the present ecological, environmental and green movements, quoted Forrester,

‘Time after time I’ve done an analysis of a company, and I’ve figured out a leverage point-in inventory policy, maybe, or in the relationship between the sales force and productive force, or in personnel policy. Then I’ve gone to the company and discovered there is already a lot of attention to that point. Everyone is trying very hard to push it in the wrong direction!’

It is a significant problem that designers feel and falsely believe they can intuitively understand and predict the behaviour of systems with multiple interlinked feedback loops. That is, erroneously, our minds and bodies both give clear indications that we can understand and predict complex design behaviours with 2 or more feedback loops when we cannot.

The larger problem is that complex multi-feedback loop products ARE designed by designers from Art and Design using the approaches suited to non-feedback loop problems. These products usually fail but the gap in time between the initial production of the product and its failure are typically such that the failures are not attributed to the designers. Commonly, designs function well at first and later when problems emerge due to the actions of the feedback loops, the problems failures are blamed on something else.

In the complex systems design field, the problem of failure of design thinking in situations involving two or more feedback loops is known as ‘counter-intuitive thinking' and the designs are known as counter-intuitive solutions . The counter-intuitive solutions (and the methods for identifying them) are the resolution of the problems avoided in Art and Design by classifying situations as ‘wicked problems’.

In the complex systems arena, the idea of counter-intuitive solutions was raised by Forrester in the realm of industrial dynamics as long ago as 1969 (Forrester, 1971). This area of industrial dynamics later became called system dynamics and is one of the core theory foundations of the complex systems design field. A supporting methodology for bounding the solution space in system design was identified by Zwicky at around the same time (Zwicky, 1969). Forrester, and later Meadows (1999) identified there was an uncommonly large number of instances in which highly competent designers, planners and managers involved in creating complex socio-technical and organisational systems or were asked to intervene in systems, chose interventions that in the longer term resulted in movement away from the intended outcomes rather than towards it. The same issues are found in all areas of design involving two or more feedback loops. For example, in the arenas of manufacturing design and organisational design, Deming (1986, 1993) identified that it was common for designers and managers of manufacturing systems to make similar mistakes when asked to resolve production problems and improve the quality of output. In the environmental design field, designers, planners and managers of third world development of food production suffered similar misguided decision making (Harrison, 1987).

Humorist Henry Mencken is quoted as capturing the essence of this issue,

‘For every complex problem, there is a solution that is simple, neat and wrong.’

To recap, designers and others are unable to predict unaided (either individually or in groups) the behaviours of systems with multiple feedback loops. They also commonly fail to understand and predict the behaviours of single feedback loop design issues using intuition, feelings and guesswork.

The only approach that has proven success is the use of mathematically-based formal representational systems modelling techniques by which the detailed behaviour of designed outcomes in a multi-feedback loop situation can be predicted. Evidence of this counter-intuitive failure phenomenon and the success of the mathematically-based system dynamics models is particularly strong in the design of social and socio-technical systems.

Over the last 50 years or so, in the systems design fields, a range of design and analysis tools have been developed that enable designers to work with design situations involving more than one feedback loop. An example is the use of causal loop modeling shown in Fig 1 below that shows the feedback loops in the analysis of a design for a university research motivation scheme. This model is capable after the inclusion of quantitative details of relationships and calibration to demonstrate the behaviours of the system, including all the actions of the multiple feedback loops. In its present form, it provides a visible basis for designers to start to understand the feedback loop relationships at least to the point that they can infer the direction of likely changes.

Figure 1: Analysis of a multi-feedback loop design of a university motivational information system (Love & Cooper, 2008)

The counter-intuitive issues and the failure of conventional design techniques in complex socio-technical systems design or interventions is particularly significant for new realms of design in Art and Design such as Design Strategy, Design Thinking and participatory/ collaborative approaches to design. The findings and analyses of this research suggest the benefits of these design approaches are likely to be illusory and short term when applied to designing situations involving more than one feedback loop.

If all of the above is so obvious and so significant for design fields and design approaches in Art and Design, one might ask why it is not already mainstream thought in design education process and common to professional design practice. There are several answers, mostly which have a political dimension:

This raises a challenge to a core assumption in professional design practices. Since 1971, the idea of ‘wicked problems’ has been central to defining the boundary of difficulty in design in Art and Design (see, for example, Buchanan, 1992; Coyne, 2005; Rittel, 1971; Rittel & Webber, 1974; Rittel & Webber, 1984). In essence, a ‘wicked problem’ is one with multiple feedback loops. A limitation of the design methods of Art and Design are that ‘wicked problems cannot be satisfactorily addressed by those methods – in part this is the definition of ‘Wicked problems’. In contrast, these are conventional problems to be addressed by the design methods of complex socio-technical systems design. This invites the question whether wicked problems are not wicked at all. Redirecting blame, as in the last point of the above list raises the question as to whether design failures in the case of wicked problems are merely due to lack of competence in designers in applying readily available complex systems design methods. The evidence from complex systems design field as it applies to design fields in Art and Design is that apparently wicked problems can be understood and addressed that this suggests failure to do so lays the responsibility for design failures not on extraneous factors but rather firmly in the hands and bank accounts of designers, design educators and design businesses.

The implications of all of the above reach deeply into and challenge many contemporary practices in design education and professional design practices in Art and Design.


To recap, at its simplest, the findings from complex systems design are when humans, designers or not, try to understand complex systems unaided, they will typically be confident about the most critical points of the design and their solutions. However, they will produce solutions that emerge as faulty or suggest design improvements in the opposite direction from those necessary those that will produce the intended design behaviours.

Experience shows most system outcomes involving two or more feedback loops are counter-intuitive. To address these systems in design terms requires the designer to understand that:

In addition, the findings suggest that the majority of tools and theories relating to design, particularly in the areas of design cognition and design thinking, are deeply flawed in ways that are not, or have been not, obvious to students, Art and Design educators, design theorists and design practitioners.

Part of this blindness, as identified in the complex system design realm is that designers, design educators and design researchers will feel good about what they do, and feel that it is correct what they do, and designs will appear initially to function. After handoff of a design, however, as the implications and effects of multiple feedback loops operate the designs will fail or will produce outcomes that are different or even opposite to those intended (see, for example, the iPod example above).

Implications of these understandings for design fields in Art and Design include:

·         It will be important to teach designers to be aware of counter-intuitive relationships where there are two or more feedback loops in a design situation.

·         It is important to educate designers, and for designers in practice to be aware, that designing solutions involving systems with two or more feedback loops cannot be thought through, inferred or successfully undertaken by intuition or feeling-based design methods.

·          It is important to be able to distinguish between complex systems involving two or more feedback loops and merely complicated design situations, where ‘complicated’ means design situations with a lot of simple non-feedback factors, as distinct from complex situations with multiple feedback loops (and perhaps less design factors).

·         It is likely impotent to understand that feelings and intuition are typically a handicap rather than a main skill in designs involving multiple feedback loops. Traditional design expertise in being able to intuitively feel one’s way around a design is mistaken in these types of situations. Designers cannot feel their way around a solution and identify correct solutions by feelings because emotion-based designerly judgement is false in situations involving two or more feedback loops. Solution will be either wrong or sub-optimal. In the case of interventions in designed systems, designers’ feelings and intuition-based skills are likely to suggest interventions that will move the solution in the opposite or a different direction from that which they intend in spite of the fact that they will feel happy with the solution at the time of designing.

·         It suggests an important aspect of design education and design practice is for designers to be able to identify when they are designing in realms where the design or the context involves more than one feedback loop.

·         It is likely to be important for designers to be aware in their design practice that the designed system’s BEHAVIOUR is the primary issue, and that explicitly understanding how and why a design behaves the way t does is essential to being able to design successfully in a compete and comprehensive manner. Craft-based design methods that do not require this depth of explicit understanding of behaviour do not result in the solutions that designers intend in design activity involving multiple feedback loops.

·         It is likely to be important that designers use specific tools from complex systems design fields that describe and model behaviours of the design and its feedback loops. Typical and appropriate complex systems design tools are ‘System Dynamic ,modelling’ and ‘Causal Loop modelling’

·         It is important for designers and educators of designers to be aware that there are two main classes of systems tools: information-gathering systems design tools and behaviour-modelling system design tools. Most systems tools identify information about system parameters and boundary conditions of specific responses. All of this information is necessary in preparation for using behaviour modelling system design tools. They are different from the relatively small group of system design tools used to model and predict system behaviours. Designers who only use information-gathering systems design tools such as soft systems methods will not be able to understand or predict the behaviour of a designed system using these tools. They will face identical design problems to those that do not use any systems tools because they will be depended only on traditional design approaches such as feelings, intuition, group discussion responses as in participative design. As described earlier, these and similar design approaches fail in complex systems because of the limitations of all human brains in situations involving two or more feedback looks.


This paper described research reviewing the insights from complex systems design field to Art and Design. It draws attention to the way findings of the field of complex systems design apply to recent developments in Art and Design. It identifies implications of the use of traditional design methods and theories in complex socio-technical systems arenas and suggests they will consistently result in faulty design outcomes, and that a range of socially-based deceptions are used to deflect criticism of these failures.

The analyses suggest changes are needed within design practices and design education in Art and Design towards more sophisticated systems understanding and prediction of outcomes of multiple feedback loops through the use of mathematically-based complex systems tools to address counter-intuitive behaviours relating to usability, emotions, user participation, interactions with other design objects, platform designs, design strategy, and design thinking.


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