Dear Chuck,

Thank you for a good  question.  You ask how 'collaboration and  negotiation
between individuals with different points of view can resolve multiple
feedback loop issues'

The simple answer is it can't.

I'm aware that this goes against the claims and practices of famous design
consultancies, against what is commonly taught in high status design
schools, and what is found in famous texts by highly respected design
theorists.

Following Birger's lead, let's look at the practical issues.

Four things characterise a multiple feedback loop design problem:

1. The behaviour of the outcome is dynamic. The behaviour of the outcome(s)
changes over time due to the effects of the feedback loops acting with all
their delays and convoluted interactions. Commonly, outcomes oscillate,
often in an inconsistent manner. 

2. As practical responsible professionals,  is essential for a designer or
design group to be able to predict the behaviour of the outcomes - otherwise
they are just guessing.

3. The relationships between the 'parts of the situation' and the 'behaviour
of the outcome' do not follow simple addition. The effect of two parts of
the situation is different  with feedback loops than the effect of the two
parts of the situation simply added together. A crucial issue that the
outcome changes over time rather than is a stable single state.

4. From observation, it appears that any individual is not capable of
accurately predicting the dynamic behaviour of multiple feedback loop
situations without modelling. 

To address your question requires addressing a further practical question:

'How collaboration and  negotiation between individuals with different
points of view can predict the dynamic behaviour of the outcomes of a
multiple feedback loop design situation when each of its members is unable
to predict this behaviour individually?'

Let's step sideways and assume that the problem is merely 'complicated',
i.e. the outcomes results from the effects of all sorts of factors added
together.  Three  things characterise 'complicated' situations: 

1. In a 'complicated' situation, the relations between 'bits of the
situation' and 'outcome' follow the arithmetic properties  of associativity,
distributivity and commutivity. In other words, you can add together all the
bits of situation and their combined effect gives the outcome.

2. In a complicated situation, different stakeholders have good knowledge of
different parts of the design context.

3. Adding together all the knowledge of individuals in a well managed way
reveals the outcome.

Obviously, the use of good processes for collaboration and  negotiation
between individuals with different points of view can be used to predict the
outcomes of 'complicated design situations' .

This is what we know already, it is easy to observe. Collaborative and
Negotiative Design methods are really good for 'complicated design
situations' . The more complicated the better they can work. Futures methods
the same. This is a different game to multiple feedback loop complex design
situations.

The problem comes when simple addition of knowledge doesn't work;
and the solution is dynamic;
and it requires predicting the changing behaviour of the outcome over time;
and no individual can predict the behaviour over time in their own head.

This leaves a situation where 'partial solutions cannot contribute to the
whole'  and 'no single person has the whole understanding and prediction'.

Worse, by observation, all participants have a subjective
belief/illusion/delusion that their 'individual faulty partial picture' is
wholly true and correct (if only they could think hard enough to think all
of it through).

From observation in these situations, I see lots of people trying to
persuade everyone else of their own faulty picture. In parallel, there are
typically two group processes. The first is a social  negotiation  by which
everyone eventually agrees to adopt a superficial simplistic view of the
situation (because reach individual knows they cannot understand it in the
depth to predict the dynamics of the outcomes) . The second, lurking as a
rider on the first, is a tacit social group dynamic  in which participants
tacitly agree to protect each other on the grounds that they all agree the
same decision, even if it is wrong!

There is an obvious reason why this problem has not been clear to the design
field. Until recently, the most difficult design situations the design
profession has primarily tackled have been 'complicated' rather than
'complex': with one or no feedback loops as compared to multiple feedback
loop situations. In addition, many complex multiple feedback loop design
situations are masked  by a large number of factors in a complicated
arrangement. To differentiate them requires special attention to the
situation characteristics. Instead,  there has been a tendency to lump all
of them together  as 'wicked'. There has been very little work done in
characterising difficult design situations outside engineering design. This
work still needs to be done across many design fields.

In short, by observation, collaboration and  negotiation between individuals
with different points of view doesn't work for complex design situations
involving multiple feedback loops. 

The interesting thing now is to challenge design consultancies, design
schools, design theorists to demonstrate exactly how collaboration and
negotiation between individuals with different points of view can accurately
predict the dynamic behaviour of situations with multiple feedback loops.

My guess is the evidence offered will be of situations in which there exist
multiple feedback loops but which these do not significantly affect the
outcome, and that the outcome is singular and stable. I look forward to
seeing - and being proved wrong.

Warm regards,
Terry
____________________

Dr. Terence Love, FDRS, AMIMechE, PMACM
School of Design and Art
Director Design-focused Research Group, Design Out Crime Research Group
Director, Design-Advertising-Branding (DAB)
Researcher, Digital Ecosystems and Business Intelligence Institute
Curtin University, PO Box U1987, Perth, Western Australia 6845
Mob: 0434 975 848, Fax +61(0)8 9305 7629, [log in to unmask]
Visiting Professor, Member of Scientific Council
UNIDCOM/ IADE, Lisbon, Portugal
Honorary Fellow, Institute of Entrepreneurship and Enterprise Development
Management School, Lancaster University, Lancaster, UK
____________________

All the best

-----Original Message-----
From: PhD-Design - This list is for discussion of PhD studies and related
research in Design [mailto:[log in to unmask]] On Behalf Of Charles
Burnette
Sent: Tuesday, 20 April 2010 8:53 PM
To: [log in to unmask]
Subject: Re: Are visual approaches to design outdated?

Terry, Birger, David and list

I believe Terry is right in what he is saying about an individual's  
response to complexity, but is not considering how collaboration and  
negotiation between individuals with different points of view can  
resolve multiple feedback loop issues. I'd love to hear Terry comment  
on that broader scale of purposeful human interaction.

Go Terry!
Chuck


On Apr 19, 2010, at 10:56 AM, Terence Love wrote:

> Hi Birger,
>
> Thank you for bringing the discussion back to the practical.  That's  
> where
> it's easiest to see things.
>
> For me it’s watching practical life that shows how badly we humans  
> manage
> any situation with feedback loops (complexity). I understand this is  
> the
> opposite to what you are suggesting. I'd like to suggest some  
> reasons why.
>
> It seems obvious that we humans are good at situations where the  
> causes are
> close in time and space We respond to situations where causes are   
> single,
> direct, obvious and do not involve feedback loops. Watching people  in
> practical situations shows we are really bad at single feedback loop
> situations and useless at multiple feedback loops situations.
>
> Watch two people bump into each other in a shopping mall and both go  
> one way
> and then the other  in a comic routine. That's a single feedback  
> loop with a
> bit of a delay. People get in mess and for a short while you can see  
> they
> don't know what to do. The impasse is broken when one person  
> converts it to
> a zero feedback situation by making a decisive move that is different.
> Another example in business, watch how two people behave who meet   
> for the
> first time  and don't know who is the senior. There is a politeness  
> game
> that happens - again another single feedback loop with delay. Watch  
> new
> couple's behave before they've managed to get enough information on  
> each
> other to convert their behaviour to simple stimulus and response  
> routines -
> they trip over each other trying to avoid making mistakes. Another  
> single
> feedback loop situation. All of us know the relatively simple  
> feedback loops
> of addiction - caught in the feedback between rational thought and
> underlying emotional desires.
>
> We humans are so bad at even single loop feedback situations that we  
> insist
> on structuring life to avoid any feedback. We use management  
> structures,
> codes of behaviour, legal codes, monetary codes traffic rules.....  
> anything
> to try to convert feedback loop situations to situations without  
> feedback
> loops. We intuitively know that we can manage complicatedness but not
> complexity.
>
> I can see that it appears at first that standing back we can view  
> the human
> situation as complex and that we humans seem to manage. That doesn't  
> seem to
> be any proof as to whether or not humans are competent at predicting  
> the
> behaviour of multi-feedback loop situations (i.e. complex situations).
>
> There are at least two epistemological fallacies  with the argument.
>
> First, the relevant complexity is how each individual sees it - not  
> the
> complexity as seen from a rationalist all-seeing helicopter view. It  
> is us
> as  individual humans that are the unit of analysis and it is the  
> situation
> as seen from  out individual viewpoint rather than the overall world  
> view.
> The alternative you are suggesting  is a bit like saying 'cars are  
> highly
> complex mechanical, chemical and electronic technologies' and we  
> drive cars
> therefore 'all humans are successful at  designing anything that  
> involves
> mechanical, chemical and electronic technologies'. It is the relative
> complexity of the reality that each of us sees as individuals that  
> matters
> in this context.
>
> The reality from observation  is that we as individuals try as much as
> possible to ignore anything with multiple feedback loops  
> (complexity) and if
> that is not possible, we instead try to treat situations  as if  
> there are no
> feedback loops. If that is not possible, we complain or claim that the
> situation  is esoterically odd (e.g. 'it's a wicked problem', or '  
> not my
> problem'  or we make a guess and try to bluff it out). From  
> observation, we
> humans handle complicatedness relatively well, and those with an  
> enthusiasm
> for relationships can understand situations with single feedback  
> loops.
> Again by observation,  as soon as situations with relationships have  
> two or
> more feedback loops, people quickly come up with phrases such as 'it  
> could
> go either way' or 'it's in the lap of the gods' or something similar  
> that
> indicates that they can no longer predict the outcome. So the first  
> fallacy
> is  that to suggest that everything is complex is epistemologically  
> the
> wrong context for the subject of study.
>
> The second problem  with claiming humans are successful at  
> complexity is
> also epistemological. The problem is the viewpoint on 'successful'  
> in the
> claim 'humans are successful at dealing with complexity because the  
> world
> looked at objectively is complex'.  The underlying key to the  
> fallacy  is in
> defining 'success'  as  'what people define as success'. This is  
> claiming an
> objective definition  on the basis of a subjective judgment.  It  is  
> like
> saying success is simply people doing what they do. Intrinsically,  
> there is
> no means of inferring from it  whether we are good or bad at  
> complexity. To
> recap, from observation of practical situations, we humans ignore  
> complexity
> and deal with it as complicatedness or as simple situations. It is  
> with this
> behaviour and these limitations that we define what is success in  
> dealing
> with life. That doesn't give any information about  whether or not  
> we are
> naturally  able to understand and predict  the behaviour of a  
> situation
> determined by multiple feedback loops. The definition of success is
> independent of competence in a specific task unless there is much more
> carefully defined links with competence.
>
> I'm suggesting that simply by sitting at a café or observing people  
> at work,
> when we look at how humans behave in both everyday and highly skilled
> situations, we find we as humans avoid multiple feedback situations.  
> When we
> do deal with them we deal with them as if they are to single  
> feedback loop
> 'complicated' situations or even as if they are 'simple'  
> situations.  Also
> by observation, when the situations are important and the feedback  
> loops
> dominate the outcomes then we get problems . Observing how people  
> deal with
> these confirms the same findings. Commonly, those  reviewing a failure
> situation try to interpret it without feedback loops. Often this  
> problem
> situation can continue indefinitely. A classic case was the  several  
> decades
> of failures in IT and Information systems. The combination of  
> feedback loops
> and delays was a key component of the outcome being the wrong  
> solution for
> the wrong  users.  Recent design methods such as Agile and Scrum  
> address and
> partially resolve some of the single feedback loop feedback issues.  
> Again it
> needs a method/code etc.
>
> Again, I'll suggest that the issues stand and that visualisation  
> only helps
> with complicated situations.
>
> Please send me any example of a visually-based method that enables  
> humans to
> predict the dynamic behaviour of a multi-feedback complex situation.
> I haven't found one yet.
>
> Best wishes,
> Terry
> ____________________
>
> Dr. Terence Love, FDRS, AMIMechE, PMACM
> School of Design and Art
> Director Design-focused Research Group, Design Out Crime Research  
> Group
> Researcher, Digital Ecosystems and Business Intelligence Institute
> Associate,  Planning and Transport Research Centre
> Curtin University, PO Box U1987, Perth, Western Australia 6845
> Mob: 0434 975 848, Fax +61(0)8 9305 7629, [log in to unmask]
> Visiting Professor, Member of Scientific Council
> UNIDCOM/ IADE, Lisbon, Portugal
> Honorary Fellow, Institute of Entrepreneurship and Enterprise  
> Development
> Management School, Lancaster University, Lancaster, UK
> ____________________
>
>
>
>
>
>
>
> -----Original Message-----
> From: Birger Sevaldson [mailto:[log in to unmask]]
> Sent: Saturday, 17 April 2010 1:33 AM
> To: Terence Love
> Subject: SV: Are visual approaches to design outdated?
>
> Dear Terry
> Thanks for challenging the ideas of visualisation being helpful in  
> dealing
> with complexity. Its clearly justified to do so.
> To my experience it is very difficult to impose the old systems  
> model with
> well defined boundaries, hierarchies of sub systems, well defined  
> inn and
> output and well defined feed back loops. Even quite simple real life  
> systems
> are to my mind hard to squeeze into this model. e.g. a car is today  
> built
> according to integrale principles where an increasing number of  
> parts are
> designed to performe according to multiple criteria and functions.  
> This
> makes it very challenging to subdivide an automobile into its  
> subsystems,
> because the multiple performance blurres the boundaries. Maybe this
> difference in systems approaches is at the heart of the different  
> possitions
> in this discussion?
> As an example: you say that "'Complex' situations are different. Human
> cognitive and emotional biology is
> not well suited to understanding or predicting the outcomes of
> 'complex'situations."
> I totally disagree with this:
> To my mind are humans very well equiped cognitively and biologically  
> to
> understand and to a certain degree predict the outcomes of very  
> complex
> situations. We do this every day from morning to the evening. If we  
> were not
> we would not survive for very long. So humans are amazingly well  
> equiped to
> navigate through multiple hyper complex systems e.g. walking down a  
> crowded
> street while having a conversation with another person, navigating in
> different layers of different overlapping and interacting systems  
> being
> traffic flows, social spaces, visual symbols, micro climates. How more
> complex can it get? We use skills and perseption , visual thinking,
> interpretation of patterns, filters, to a large degree tacitly. I  
> think
> these skills are what is activated when we work visually with  
> complexity in
> design.
>
> I refere to soft systems methodology (Checkland was quoted in this
> discussion earlier) and e.g. Systems Architecting as described by  
> Mayer and
> Rechtin. I think this soft end of systems thinking is more relevant  
> and
> closer related to design thinking, than some of the more traditional  
> systems
> approaches.
>
> Maybe we come from different world views and the discussion needs to  
> clarify
> this first?
>
> Here a selection of references i found interresting, (please feel  
> free to
> suggest additional sources):
>
> Checkland, P. (2000). Soft Systems Methodology: a 30-year  
> retrospective.
> Systems Thinking, Systems Practice. P. Checkland. Chichester, John  
> Wiley &
> Sons LTD.
> Checkland, P. and J. Poulter (2006). Learning for Action: A Short  
> Definitive
> Account of Soft Systems Methodology and its use for Practitioners,  
> Teachers
> and Students. Chichester, John Wiley & Sons, Ltd.
> Csikszentmihalyi, M. (1999). Implications of a Systems Perspecive  
> for the
> Study of Creativity. Creativity Handbook. R. J. Sternberg. Cambridge,
> Cambridge University Press.
> Glanville Ranulph, A Ship without a Rudder  CybernEthics Research,  
> Southsea,
> UK 1994
> Gordon Dyer, Y3K: Beyond Systems Design as we know it, in: Res- 
> Systemica,
> Vol. 2, 2002. Refering to Béla H. Banathy
> Frostell, B., Å. Danielsson, et al., Eds. (2008). Sciene for  
> Sustainable
> Development: The Social Challenge with Emphasis on the Conditions for
> Change. Uppsala, VHU.
> Frostell, B. (2009). Industrial Ecology and Environmental Systems  
> Analysis-
> Systems Approaches for Increased Complexity. Stockholm, KTH Royal  
> Institute
> of Technology.
> Gharajedaghi, J. (2006). Systems Thinking: Managing Chaos and  
> Complexity: A
> Platform for Designing Business Architecture. London, Elsevier.
> Gigch, J. P. and J. McIntyre-Mills, Eds. (2006). Wisdom. Knowledge and
> Management: A Critique and Analyses of Churchman's Systems Approach.  
> New
> York, Springer.
> Gruber, H. E. (1988). "The evolving systems approach to creative  
> work."
> Creativity Research Journal 1.
> Gruber, H. E. and D. B. Wallace (1999). The Case Study Method and  
> Evolving
> Systems Approach for Understanding Unique Creative People at Work.  
> Handbook
> of creativity. Cambridge, Cambridge University Press.
> Gunderson, L. H. and C. S. Holling, Eds. (2002). Panarchy:  
> Understanding
> Transformations in Human and Natural Systems. Washington DC, Island  
> Press.
> Gunderson, L. H. and L. P. Jr., Eds. (2002). Resilience and Behavior  
> of
> Large-Scale Systems. Washington, Island Press.
> Jonas, W. (1996). Systems Thinking in Industrial Design. Systems  
> Dynamics,
> Cambridge Massachusets, MIT.
> Jonas, W. (2005). Designing in the real world is complex anyway-so  
> what?
> Systemic and evolutionary process models in design. European  
> Conference on
> Complex Systems Satellite Workshop: Embracing Complexity in Design,  
> Paris.
> Maier, M. W. and E. Rechtin (2000). The Art of Systems Architecture.  
> Boca
> Raton, CRC Press.
> Mariussen, Å. and Å. Uhlin, Eds. (2006). Trans-national Practices,  
> Systems
> Thinking in Policy Making. Stockholm, Nordregio.
> Meadows, D. (1999). "Leverage Points: Places to intervene in a  
> System." The
> Sustainable Institute, Hartland.
> Meadows, D. H. (2008). Thinking in Systems. White River Junction,  
> Chelsea
> Green Publishing.
> Midgley, G. (2000). Systems Intervention: Rhilosophy, Methodology, and
> Practice. New York, Kluver Academic / Plenum Publishers.
> Miller, J. H. and S. E. Page (2007). Complex Adaptiv Systems: An
> Introduction to Computational Models of Social Life. Princeton,  
> Princeton
> University Press.
> Olsson, M.-O. and G. Sjöstedt, Eds. (2004). Systems Approaches and  
> Their
> Applicaitons: Examples from Sweden. Dordrecht, Kluwer Academisc  
> Publishers.
> Rechtin, E. (1999). Systems Architecting of Organisations: Why  
> Eagles Can't
> Swim. Boca Raton, Florida, CRC Press LLC.
> Sage, A. P. and J. E. J. Armstrong (2000). Introduction to Systems
> Engineering. New York, John Wiley & Son.
> Senge, P. M., B. Smith, et al. (2008). The Necessary Revolution: How
> individuals and organizations are working together to create a  
> sustainable
> world. New York, Doubleday.
> Svedin, U. (2006). Introduction to Systems Approaches and Their  
> Aplications.
> Systems Approaches and Their Aplications: Examples from Sweden. M.- 
> O. Olsson
> and G. Sjöstedt. Dortrecht, Kluwer.
> Ulrich, W. (2000). "Reflective Practice in the Civil Society: the
> contribution of critical systemic thinking." Reflective Practice 1(2):
> 247-268.
> Walker, B. and D. Salt (2006). Resilience Thinking. Washington,  
> Island Press
>
>
> Best regards
> Birger