There is much discussion about flaws of ‘democratic’ governance systems, supposedly leading to increasingly threatening crises. Calls for ‘fixing’ these challenges tend to focus on single problems, urging single ‘solutions’. Even recommendations for application of ‘systems thinking’ tools seem to be fixated on the phase of ‘problem understanding’ of the process; while promotions of AI (artificial / augmented intelligence) sound like solutions are likely to be found by improved collection and analysis of data, of information in existing ‘knowledge bases’. Little effort seems devoted to actually ‘connecting the dots’ – linking the different aspects and problems, making key improvements that serve multiple purposes. The following attempt is an example of such an effort to develop comprehensive ‘connecting the dots’ remedies – one that itself arguably would help realize the ambitious dream of democracy, proposed for discussion. A selection (not a comprehensive account) of some often invoked problems, briefly:
“Voter apathy” The problem of diminishing participation in current citizen participation in political discourse and decisions / elections, leading to unequal representation of all citizens’ interests;
“Getting all needed information”
The problem of eliciting and assembling all pertinent ‘documented’ information (‘data’) but also critical ‘distributed’ information especially for ‘wicked problems’, – but:
“Avoiding information overload”
The phenomenon of ‘too much information’, much of which may be repetitive, overly rhetorical, judgmental, misleading (untruthful) or irrelevant;
“Obstacles to citizens’ ability to voice concerns”
The constraints to citizens’ awareness of problems, plans, overview of discourse, ability to voice concerns;
“Understanding the problem”
Social problems are increasingly complex, interconnected, ill-structured, explained in different, often contradicting ways, without ‘true’ (‘correct) or ‘false’ answers, and thus hard to understand, leading to solution proposals which may result in unexpected consequences that can even make the situation worse;
“Developing better solutions”
The problem of effectively utilizing all available tools to the development of better (innovative) solutions;
The problem of conducting meaningful (less ‘partisan’ and vitriolic, more cooperative, constructive) discussion of proposed plans and their pros and cons;
“Better evaluation of proposed plans”
The task of meaningful evaluation of proposed plans;
“Developing decisions based on the merit of discourse contributions”
Current decision methods do not guarantee ‘due consideration’ of all citizens’ concerns but tend to ignore and override as much as the contributions and concerns of half of the population (voting minority);
“The lack of meaningful measures of merit of discourse contributions”
Lack of convincing measures of the merit of discourse contributions: ideas, information, strength of evidence, weight of arguments and judgments;
“Appointing qualified people to positions of power”
Finding qualified people for positions of power to make decisions that cannot be determined by lengthy public discourse — especially those charged with ensuring
“Adherence to decisions / laws / agreements”
The problem of ‘sanctions’ ensuring adherence to decisions reached or issued by governance agencies: ‘enforcement’ – (requiring government ‘force’ greater than potential violators leading to ‘force’ escalation;
“Control of power”
To prevent people in positions of power from falling victim to temptations of abusing their power, better controls of power must be developed.
Some connections and responses:
Details of possible remedies / responses to problems, using information technology, aiming at having specific provisions (‘contribution credits’) work together with new methodological tools (argument and quality evaluation) to serve multiple purposes:
Participation and contribution incentives: for example, offering ‘credit points’ for contributions to the planning discourse, saved in participants’ ‘contribution credit account’ as mere ‘contribution’ or participation markers, (to be evaluated for merit later.)
“Getting all needed information”
A public projects ‘bulletin board’ announcing proposed projects / plans, inviting interested and affected parties to contribute comments, information, not only from knowledge bases of ‘documented’ information (supported by technology) but also ‘distributed, not yet documented information from parties affected by the problem and proposed plans.
“Avoiding information overload”
Points given only for ‘first’ entries of the same content and relevance to the topic
(This also contributes to speedy contributions and assembling information)
“Obstacles to citizens’ ability to voice concerns”
The public planning discourse platform accepts entries in all media, with entries displayed on public easily accessible and regularly (ideally real-time) updated media, non-partisan
“Understanding the problem”
The platform encourages representation of the project’s problem, intent and ‘explanation’ from different perspectives. Systems models contribute visual representation of relationships between the various aspects, causes and consequences, agents, intents and variables, supported by translation not only between different languages but also from discipline ‘jargon’ to natural conversational language.
“Developing better solutions”
Techniques of creative problem analysis and solution development, (carried out by ‘special techniques’ teams reporting results to the pain platform) as well as information about precedents and scientific and technology knowledge support the development of solutions for discussion
While all entries are stored for reference in the ‘Verbatim’ repository, the discussion process will be structured according to topics and issues, with contributions condensed to ‘essential content’, separating information claims from judgmental characterization (evaluation to be added separately, below) and rhetoric, for overview display (‘IBIS’ format, issue maps) and facilitating systematic assessment.
“Better evaluation of proposed plans”
Systematic evaluation procedures facilitate assessment of plan plausibility (argument evaluation) and quality (formal evaluation to mutually explain participants’ basis of judgment) or combined plausibility-weighted quality assessment.
“Meaningful measures of merit”
The evaluation procedures produce ‘judgment based’ measures of plan proposal merit that guide individual and collective decision judgments. The assessment results also are used to add merit judgments (veracity, significance, plausibility, quality of proposal) to individuals’ first ‘contribution credit’ points, added to their ‘public credit accounts’.
“Decision based on merit”
For large public (at the extreme, global) planning projects, new decision modes and criteria are developed to replace traditional tools (e.g. majority voting)
“Qualified people to positions of power”
Not all public governance decisions need to or can wait for the result of lengthy discourse, thus, people will have to be appointed (elected) to positions of power to make such decisions. The ‘public contribution credits’ of candidates are used as additional qualification indicators for such positions.
“Control of power”
Better controls of power can be developed using the results of procedures proposed above: Having decision makers ‘pay’ for the privilege of making power decisions using their contribution credits as the currency for ‘investments’ in their decision: Good decision will ‘earn’ future credits based on public assessment of outcomes; poor decisions will reduce the credit accounts of officials, forcing their resignation if depleted. ‘Supporters’ of officials can transfer credits from their own accounts to the official’s account to support the official’s ability to make important decisions requiring credits exceeding their own account. They can also withdraw such contributions if the official’s performance has disappointed the supporter.
This provision may help reduce the detrimental influence of money in governance, and corresponding corruption.
“Adherence to decisions / laws / agreements”
One of the duties of public governance is ‘enforcement’ of laws and decisions. The very word indicates the narrow view of tools for this: force, coercion. Since government force must necessarily exceed that of any would-be violator to be effective, this contributes both to the temptation of corruption, — to abuse their power because there is no greater power to prevent it, and to the escalation of enforcement means (weaponry) by enforces and violators alike. For the problem of global conflicts, treaties, and agreements, this becomes a danger of use of weapons of mass destruction if not defused. The possibility of using provisions of ‘credit accounts’ to develop ‘sanctions’ that do not have to be ‘enforced’ but triggered automatically by the very attempt of violation, might help this important task.
The discussion about whether and to what extent Artificial Intelligence technology can meaningfully support the planning process with contributions similar or equivalent to human thinking is largely dominated by controversies about what constitutes thinking. An exploration of the reasoning patterns in the various phases of human planning discourse could produce examples for that discussion, leaving the determination of that definition label ‘thinking’ open for the time being.
One specific example (only one of several different and equally significant aspects of planning):
People propose plans for action, e.g. to solve problems, and then engage in discussion of the ‘pros and cons’ of those plans: arguments. A typical planning argument can be represented as follows:
“Plan A should be adopted for implementation, because
i) Plan A will produce consequences B, given certain conditions C, and
ii) Consequences B ought to be pursued (are desirable); and
iii) Conditions C are present (or will be, at implementation).
Question 1: could such an argument be produced by automated technological means?
This question is usually followed up by question 2: Would or could the ‘machine’ doing this be able (or should it be allowed) to also make decisions to accept or reject the plan?
Can meaningful answer to these questions be found? (Currently or definitively?)
Beginning with question 1: Formulating such an argument in their minds, humans draw on their memory — or on explanations and information provided during the discourse itself — for items of knowledge that could become premises of arguments:
‘Factual-instrumental’ knowledge of the form “FI (A –> X)”, for example (“A will cause X’, given conditions C;
‘Deontic’ Knowledge: of the form “D(X)” or “X ought to be’ (is desirable)”, and
Factual Knowledge of the form “F ( C)” or “Conditions C are given”.
‘Argumentation-pattern knowledge’: Recognition that any of the three knowledge items above can be inserted into an argument pattern of the form
D(A) <– ((A–> X)|C)) & D(X) & F( C)).
(There are of course many variations of such argument patterns, depending on assertion or negation of the premises, and different kinds of relations between A and X.)
It does not seem to be very difficult to develop a Knowledge Base (collection) of such knowledge items and a search-and-match program that would assemble ‘arguments’ of this pattern.
Any difficulties arguably would be more related to the task of recognizing and suitably extracting such items (‘translating’ it into the form recognizable to the program) from the human recorded and documented sources of knowledge, than to the mechanics of the search-and-match process itself. Interpretation of meaning: is an item expressed in different words equivalent to other terms that are appropriate to the other potential premises in an argument?
Another slight quibble relates to the question whether and to what extent the consequence qualifies as one that ‘ought to be’ (or not) — but this can be dealt with by reformulating the argument as follows:
“If (FI(A –> X|C) & D(X) & F( C)) then D(A)”.
(It should be accompanied by the warning that this formulation that ‘looks’ like a valid logic argument pattern is in fact not really applicable to arguments containing deontic premises, and that a plan’s plausibility does not rest on one single argument but on the weight of all its pros and cons.)
But assuming that these difficulties can be adequately dealt with, the answer to question 1) seems obvious: yes, the machine would be able to construct such arguments. Whether that already qualifies as ‘thinking’ or ‘reasoning’ can be left open; the significant realization is equally obvious: that such contributions could be potentially helpful contributions to the discourse. For example, by contributing arguments human participants had not thought of, they could be helping to meet the aim of ensuring — as much as possible — that the plan will not have ‘unexpected’ undesirable side-and-after-effects. (One important part of H. Rittel’s very definition of design and planning.)
The same cannot as easily be said about question 2.
The answer to that question hinges on whether the human ‘thinking’ activities needed to make a decision to accept or reject the proposed plan can be matched by ‘the machine’. The reason is, of course, that not only the plausibility of each argument will have to be ‘evaluated’, judged, (by assessing the plausibility of each premise) but also that the arguments must be weighed against one another. (A method for doing that has been described e.g in ‘The Fog Island Argument” and several papers.)
So a ‘search and match’ process as the first part of such a judgment process would have to look for those judgments in the data base, and the difficulty here has to do with where such judgments would come from.
The prevailing answers for factual-instrumental premises as well as for fact-premises — premises i) and iii) — are drawing on ‘documented’ and commonly accepted truth, probability, or validity. Differences of opinion about claims drawn from ‘scientific’ and technical work, if any, are decided by a version of ‘majority voting’ — ‘prevailing knowledge’, accepted by the community of scientists or domain experts, ‘settled’ controversies, derived from sufficiently ‘big data’ (“95% of climate scientists…”) can serve as the basis of such judgments. It is often overlooked that the premises of planning arguments, however securely based on ‘past’ measurements, observations etc, are inherently predictions. So any certainty about their past truth must at least be qualified with a somewhat lesser degree of confidence that they will be equally reliably true in future: will the conditions under which the A –> X relationships are assumed to hold, be equally likely to hold in the future? Including the conditions that may be — intentionally or inadvertently — changed as a result of future human activities pursuing different aims than those of the plan?
The question becomes even more controversial for the deontic (ought-) premises of the planning arguments. Where do the judgments come from by which their plausibility and importance can be determined? Humans can be asked to express their opinions — and prevalent social conventions consider the freedom to not only express such judgments but to have them given ‘due consideration’ in public decision-making (however roundabout and murky the actual mechanisms for realizing this may be) as a human right.
Equally commonly accepted is the principle that machines do not ‘have’ such rights. Thus, any judgment about deontic premises that might be used by a program for evaluating planning arguments would have to be based on information about human judgments that can be found in the data base the program is using. There are areas where this is possible and even plausible. Not only is it prudent to assign a decidedly negative plausibility to deontic claims whose realization contradicts natural laws established by science (and considered still valid…like ‘any being heavier than air can’t fly…’). But there also are human agreements — regulations and laws, and predominant moral codes — that summarily prohibit or mandate certain plans or parts of plans; supported by subsequent arguments to the effect that we all ought not break the law, regardless of our own opinions. This will effectively ‘settle’ some arguments.
And there are various approaches in design and planning that seem to aim at finding — or establishing — enough such mandates or prohibitions that, taken together, would make it possible to ‘mechanically’ determine at least whether a plan is ‘admissible’ or not — e.g. for buildings, whether its developer should get a building permit.
This pattern is supported in theory by modal logic branches that seek to resolve deontic claims on the basis of ‘true/false’ judgments (that must have been made somewhere by some authority) of ‘obligatory’, ‘prohibited’, ‘permissible’ etc. It can be seen to be extended by at last two different ‘movements’ that must be seen as sidestepping the judgment question.
One is the call for society as a whole to adopt (collectively agree upon) moral, ethical codes whose function is equivalent to ‘laws’ — from which the deontic judgment about plans could be derived by mechanically applying the appropriate reasoning steps — invoking ‘Common Good’ mandates supposedly accepted unanimously by everybody. The question whether and how this relates to the principle of granting the ‘right’ of freely holding and happily pursuing one’s own deontic opinions is usually not examined in this context.
Another example is the ‘movement’ of Alexander’s ‘Pattern Language’. Contrary to claims that it is a radically ‘new’ theory, it stands in a long and venerable tradition of many trades and disciplines to establish codes and collections of ‘best practice’ rules of ‘patterns’ — learned by apprentices in years of observing the masters, or compiled in large volumes of proper patterns. The basic idea is that of postulating ‘elements’ (patterns) of the realm of plans, and relationships between these, by means of which plans can be generated. The ‘validity’ or ‘quality’ of the generated plan is then guaranteed by the claim that each of the patterns (rules) are ‘valid’ (‘true’, or having that elusive ‘quality without a name’). This is supported by showing examples of environments judged (by intuition, i.e. needing no further justification) to be exhibiting ‘quality’, by applications of the patterns. The remaining ‘solution space’ left open by e.g. the different combinations of patterns, then serves as the basis for claims that the theory offers ‘participation’ by prospective users. However, it hardly needs pointing out that individual ‘different’ judgments — e.g. based on the appropriateness of a given pattern or relationship — are effectively eliminated by such approaches. (This assessment should not be seen as a wholesale criticism of the approach, whose unquestionable merit is to introduce quality considerations into the discourse about built environment that ‘common practice’ has neglected.)
The relevance of discussing these approaches for the two questions above now becomes clear: If a ‘machine’ (which could of course just be a human, untiringly pedantic bureaucrat assiduously checking plans for adherence to rules or patterns) were able to draw upon a sufficiently comprehensive data base of factual-instrumental knowledge and ‘patterns or rules’, it could conceivably be able to generate solutions. And if the deontic judgments have been inherently attached to those rules, it could claim that no further evaluation (i.e. inconvenient intrusion of differing individual judgments would be necessary.
The development of ‘AI’ tools of automated support for planning discourse — will have to make a choice. It could follow this vision of ‘common good’ and valid truth of solution elements, universally accepted by all members of society. Or it could accept the challenge of a view that it either should refrain from intruding on the task of making judgments, or going to the trouble of obtaining those judgments from human participants in the process, before using them in the task of deriving decisions. Depending on which course is followed, I suspect the agenda and tasks of current and further research and development and programming will be very different. This is, in my opinion, a controversial issue of prime significance.
Levels of assessment depth in planning discourse: A three-tier experimental (‘pilot’) version of a planning discourse support systemPosted: February 4, 2018
Thorbjoern Mann, February 2018
A ‘pilot’ version of a needed full scale Planning Discourse Support System (‘PDSS’)
to be run on current social media platforms such as Facebook
The following are suggestions for an experimental application of a ‘pilot’ version of the structured planning discourse platform that should be developed for planning projects with wide public participation, at scales ranging from local issues to global projects.
Currently available platforms do not yet offer all desirable features of a viable PDSS
The eventual ‘global’ platform will require research, development and integrated programming features that current social media platforms do not yet offer. The ‘pilot’ project is aiming at producing adequate material to guide further work and attract support and funding a limited ‘pilot’ version of the eventual platform, that can be run on currently available platforms.
Provisions for realization of key aims of planning: wide participation;
decisions based on merit of discourse contribution;
recognition of contribution merit;
presented as optional add-on features
leading to a three-tier presentation of the pilot platform
One of the key aims of the overall project is the development of a planning process leading to decisions based on the assessed merit of participants’ contributions to the discourse. The procedural provisions for realizing that aim are precisely those that are not supported by current platforms, and will have to be implemented as optional add-on processes (‘special techniques’) by smaller teams, outside of the main discourse. Therefore, the proposal is presented as a set of three optional ‘levels’ of depth of analysis and evaluation. Actual projects may choose the appropriate level inconsideration of the project’s complexity and importance, of the degree of consensus or controversy emerging during the discourse, and the team’s familiarity with the entire approach and the techniques involved.
1 General provisions
2 Basic structured discourse
3 Structured discourse with argument plausibility assessment
4 Assessment of plausibility-adjusted Quality assessment
5 Sample ‘procedural’ agreements
6 Possible decision modes based on contribution merit
7 Discourse contribution merit rewards
1 General Provisions
Main (e.g. Facebook) Group Page
Assuming a venue like Facebook, a new ‘group’ page will be opened for the experiment. It will serve as a forum to discuss the approach and platform provisions, and to propose and select ‘projects’ for discussion under the agreed-upon procedures.
Project proposals and selection
Group members can propose ‘projects’ for discussion. To avoid project discussions being overwhelmed by references to previous research and literature, the projects selected for this experiment should be as ‘new’ (‘unprecedented’) and limited in scope as possible. (Regrettably, this will make many urgent and important issues ineligible for selection.)
Separate Project Page for selected projects
For each selected project, a new group page will be opened to ensure sufficient hierarchical organization options within the project. There will be specific designated threads within each group, providing the basic structure of each discourse. A key feature not seen in social media discussions is the ‘Next step’ interruption of the process, in which participants can choose between several options of continuing or ending the process.
‘Participants’ in projects will be selected from the number of ‘group members’ having signed up, expressing an interest in participating, and agree to proceed according to the procedural agreements for the project.
Main Process and ‘Special Techniques’
The basic process of project discourse is the same for all three levels; the argument plausibility assessment and project quality assessment procedures are easily added to the simple sequence of steps of the ‘basic’ versions described in section 2.
In previous drafts of the proposal, these assessment tools have been described as ‘special techniques’ that would require provisions of formatting, programming and calculation. For any pilot version, they would have to be conducted by ‘special teams’ outside of the main discourse process. This also applies to the proposed three-level versions and the two additional ‘levels’ of assessment presented here. Smaller ‘special techniques teams’ will have to be designated to work outside of the main group discussion, (e.g. by email); they will report their results back to the main project group for consideration and discussion.
For the first implementation of the pilot experiment, only two such special techniques: the technique of argument plausibility assessment, and the evaluation process for plan proposal ‘quality’ (‘goodness’) are considered; they are seen as key components of the effort to link decisions to the merit of discourse contributions.
2 Basic structured discourse
Project selection Group members post suggestions for projects (‘project candidates) on the group’s main ‘bulletin board’. If a candidate is selected, the posting member will act as its ‘facilitator’ or co-facilitator. Selection is done by posting an agreed-upon minimum of ‘likes’ for a project candidate. By posting a ‘like’, group members signal their intention to become ‘project participants’ and actively contribute to the discussion.
Project bulletin page, Project description
For selected projects, a new page serving as introduction and ‘bulletin board’ for the project will be opened. It will contain a description of the project (which will be updated as modifications are agreed upon). For the first pilot exercise, the projects should be an actual plan or action proposals.
On a separate thread, a ‘default’ version of procedural agreements will be posted. They may be modified in response to project conditions and expected level of depth, ideally before the discussion starts. The agreements will specify the selection criteria for issues, and the decision modes for reaching recommendations or decisions on the project proposals. (See section 5 for a default set of agreements).
General discussion thread (unstructured)
A ‘General discussion’ thread will be started for the project, inviting comments from all group members. For this thread, there are no special format expectation other than general ‘netiquette’.
On a ‘bulletin board’ subthread of the project intro thread, participants can propose ‘issue’ or ‘thread’ candidates, about questions or issues that emerge as needing discussion in the ‘general discussion’ thread. Selection will be based on an agreed-upon number of ‘likes, ‘dislikes’ or comments about the respective issue in the ‘general discussion’ thread.
Issue threads: For each selected issue, a separate issue thread will be opened. The questions or claims of issue threads should be stated more specifically in the expectation of clear answers or arguments, and comments should meet those expectations.
It may be helpful to distinguish different types of questions, and their expected responses:
– “Explanatory” questions (Explanations, descriptions, definitions);
– “Factual’ questions (‘Factual’ claims, data, arguments)
– “Instrumental questions” (Instrumental claims” “how to do …”)
– “Deontic” (‘Ought’- questions) (Arguments pro / con proposals)
Links and References thread
Comments containing links and references should provide brief explanations about what positions the link addresses or supports; the links should also be posted on a ‘links and references’ thread.
Visual material: diagrams and maps
Comments can be accompanied by diagrams, maps, photos, or other visual material. Comments should briefly explain the gist of the message supported by the picture. (“What is the ‘argument’ of the image?) For complex discussions, overview ‘maps’ of the evolving network of issues should be posted on the project ‘bulletin’ thread.
Anytime participants sense that the discussion has exhausted itself or needs input of other information or analysis, they can make a motion for a ‘Next step?’ interruption, specifying the suggested next step:
– a decision on the main proposal or a part,
– call for more information, analysis;
– call for a ‘special technique’ (with or without postponement of further discussion)
– call for modifying the proposal, or
– changing procedural rules;
– continuing the discussion or
– dropping the issue, ending the discussion without decision.
These will be decided upon according to the procedural rules ‘currently’ in force.
Decision on the plan proposal
The decision about the proposed plan — or partial decisions about features that should be part of the plan — will be posted on the project’s ‘bulletin board’ thread., together with a brief report. Reports about the process experience, problems and successes, etc. will be of special interest for further development of the tool.
3 Structured discourse with argument plausibility assessment
The sequence of steps for the discourse with added argument plausibility assessment is the same as those of the ‘basic’ process described in section 2 above. At each major step, participants can make interim judgments about the plausibility of the proposed plan, (for comparison with later, more deliberated judgments). At each of these steps, there also exists the option of responding to a ‘Next step?’ motion with a decision to cut the process short, based on emerging consensus or other insights such as ‘wrong question’ that suggest dropping the issue. Without these intermediate judgments, the sequence of steps will proceed to construct an overall judgment of proposal plausibility ‘bottom-up-fashion’ from the plausibility judgments of individual argument premises.
Presenting the proposal
The proposal for which the argument assessment is called, is presented and described in as much detail as is available.
(Optional: Before having studied the arguments, participants make first offhand, overall judgments of proposal plausibility Planploo’ on a +1 / -1 scale, (for comparison with later judgments). Group statistics: e.g. GPlanploo’ are calculated (Mean, range…) and examined for consensus or significant differences. )
Displaying all pro/con arguments
The pro / con arguments having been raised about the issue , displayed in the respective ‘issue’ thread, are displayed and studied, if possible with the assistance of ‘issue maps’ showing the emerging network of interrelated issues. (Optional:) Participants assign a second overall offhand plan plausibility judgment: Planploo”, GPlanploo”)
Preparation of formal argument display and worksheets
For the formal argument plausibility assessment, worksheets are prepared that list
a) the deontic premises of each argument (goals, concerns), and
b) the key premises of all arguments ((including those left unstated as ‘taken for granted’)
Assignment of ‘Weights of Relative Importance’ w
Participants assign ‘weights of relative importance’ w to the deontics in list (a), such that 0 ≤ wi ≤ 1, and ∑wi = 1, for all i arguments.
Assignment of premise plausibility judgments prempl to all argument premises
Participants assign plausibility judgments to all argument premises, on a scale of -1 (totally implausible) via 0 –zero – (don’t know) to +1 (totally plausible)
Calculation of Argpl Argument plausibility
For each participant and argument, the ‘Argument plausibility’ Argpl is calculated from the premises plausibility judgments. E,g. Argplod = ∏ (premplj) for all j premises of the argument.
Calculation of Argument Weight Argw
From the argument plausibility judgment s and the weight of the deontic premise for that argument, the ‘weight of the respective argument Argw is calculated. E.g. Argwi = Argplod * wi.
Calculation of Plan plausibility Planpld
The Argument weights Argw of all arguments pro and con are aggregated into the deliberated plan plausibility score Planplod for each participant. E.g. Planpld = ∑(Argwi) for all i arguments.
Calculating group statistics of results
Statistics of the Plan plausibility judgment scores across the group (Mean, Median, Range, Min /Max) are calculated and discussed. Areas of emerging consensus are identified, as well as areas of disagreements of lack of adequate information. The interim judgments designated as ‘optional’ above can serve to illustrate the learning process participants go through.
Argument assessment team develops recommendations for decision or improvement of proposed plan
The argument assessment team reports its findings and analysis, makes recommendations to the entire group in a ‘Next Step?’ deliberation.
4 Assessment of plausibility-adjusted plan Quality
Assigning quality judgments
Because pro / con arguments usually refer to the deontic concerns (goals, objectives) in qualitative terms, they do not generally generate adequate information about the actual quality or ‘goodness’ that may be achieved by a plan proposal. A more fine-grain assessment is especially important for the comparison of several proposed plan alternatives. It should be obvious that all predictions about the future performance of plans will be subject to the plausibility qualifications examined in section 3 above. So a goodness or quality assessment may be grafted onto the respective steps of the argument plausibility assessment. The following steps describe one version of the resulting process.
Proposal presentation and first offhand quality judgment
(Optional step:) Upon presentation of a proposal, participants can offer a first overall offhand goodness or quality judgment PlanQoo, e.g. on a +3 / -3 scale, for future comparison with deliberated results.
Listing deontic claims (goals, concerns)
From the pro / con arguments compiled in the argument assessment process (section 3) the goals, concerns (deontic premises) are assembled. These represent ‘goodness evaluation aspects’ against which competing plans will be evaluated.
Adding other aspects not mentioned in arguments
Participants may want to add other ‘standard’ as well as situation-specific aspects that may not have been mentioned in the discussion. (There is no guarantee that all concerns that influence participants’ sense of quality of a plan will actually be brought up and made explicit in a discussion).
Determining criteria (measures of performance) for all aspects
For all aspects, ‘measures of performance’ will be determined that allow assessment about how well a plan will have met the goal or concern. These may be ‘objective’ criteria or more subjective distinctions. For some criteria, ‘criterion functions’ can show how a person’s ‘quality’ score depends on the corresponding criterion.
Example: plan proposals will usually be compared and evaluated according to their
expected ‘cost’; and usually ‘lower cost’ is considered ‘better’ (all else being equal)
than ‘higher cost’. But while participants may agree that ‘zero cost’ would be
best so as to deserve a +3 (couldn’t be better’) score, they can differ significantly
about what level of cost would be ‘acceptable’, and at what level the score should
become negative: Participant x would consider a much higher cost to be still
‘so/so’, or acceptable, than participant o.
-3 ——————————————————- ($∞ would be -3 ‘couldn’t be worse’)
$0 | | | | | | | | | > Cost criterion function.
“Weighting’ of aspects, subaspects etc.
The ‘weight’ assignments of aspects (deontics) should correspond to the weighting of deontic premises in the process of argument assessment. However, if more aspects have been added to the aspect list, the ‘weighting’ established in the argument assessment process must be revised: Aspects weights are on a zero to +1 scale, 0 ≤ w ≤ 1 and ∑wi = +1 for all i aspects. For complex plans, the aspect list may have several ‘levels’ and resemble an ‘aspect tree’. The weighing at each level should follow the same rule of 0 ≤ w ≤ 1 and ∑w=1.
Assigning quality judgment scores
Each participant will assign ‘quality’ or ‘goodness’ judgments, on a +3 to -3 scale (+3 meaning ‘could not possibly be better’, -3 ‘couldn’t possibly be worse’, with zero (0) meaning ‘so-so’ or ‘can’t decide’, not applicable) to all aspects / subaspects of the evaluation worksheet, for all competing plan proposals.
Combining quality with plausibility score for a ‘weighted plausibility-adjusted quality score Argqw
Each (partial) quality score q will be combined with the respective argument plausibility score Argpl from the process in section 3, resulting in a ‘weighted plausibility-adjusted quality score’ Argqplwi = Argpli * qi * wi .
Aggregating scores into Plan quality score PlanQ
The weighted partial scores can be aggregated into overall plan quality scores: e.g. :
PlanQ = ∑i (Argqplwi) for all n aspects. or
PlanQ = Min (Argqplw) or
PlanQ = ∏ (Argqpli +3)wi -3
(The appropriateness of these functions for a given case must be discussed!)
Group statistics: GArgqpl and GPlanQ
Like the statistics of the plausibility assessments, statistical analysis of these these scores can be calculated. Whether a resulting measure such as Mean (PlanQ) should be accepted as a ‘group judgment’ is questionable, but such measures can become helpful guides for any decisions the group will have to make. Again, calculation of interim results can provide information about the ‘learning process of team members, ‘weaknesses’ of plans that are responsible for specific poor judgment scores, and guide suggestions for plan improvements.
Team reports results back to main forum
A team report should be prepared for presentation back to the main discussion.
5 Sample procedural agreements
The proposed platform aims at facilitating problem-solving, planning, design, policy-making discussions that are expected to result in some form of decision or recommendation to adopt plans for action. To achieve decisions in groups, it is necessary to have some basic agreements as to how those decisions will be determined. Traditional decision modes such as voting are not appropriate for any large asynchronous online process with wide but unspecified participation (Parties affected by proposed plans may be located across traditional voting eligibility boundaries; who are ‘legitimate’ voters?). The proposed approach aims at examining how decisions might be based on the quality of content contributions to the discourse rather than the mere number of voters or supporters.
The following are proposed ‘default’ agreements; they should be confirmed (or adapted to circumstances) at the outset of a discourse. Later changes should be avoided as much as possible; ‘motions’ for such changes can be made as part of a ‘Next step’ pause in the discussion; they will be decided upon by a agreed upon majority of participants having ‘enlisted’ for the project, or agreements ‘currently’ in place.
Members of the Planning Discourse FB group (Group members) can propose ‘projects’ for discussion on the Main group’s ‘Bulletin Board’ Thread. Authors of group project proposals are assumed to moderate / facilitate the process for that project. Projects are approved for discussion if an appropriate number __ of group members ‘sign up for ‘participation’ in the project.
Project participants are assumed to have read and agreed to these agreements, and expressed willingness to engage in sustained participation. The moderator may choose to limit the number of project participants, to keep the work manageable.
Project discussion can be ‘started’ with a Problem Statement, a Plan Proposal, or a general question or issue. The project will be briefly described in the first thread. Another thread labeled ‘Project (or issue) ___ General comments’ will then be set up, for comment on the topic or issue with questions of explanation clarification, re-phrasing, answers, arguments and suggestions for decisions. Links or references should be accompanied by a brief statement of the answer or argument made or supported by the reference.
Participants and moderator can suggest candidate issues: potentially controversial questions about which divergent positions and opinions exist or are expected, that should be clarified or settled before a decision is made. These will be listed in the project introduction thread as Candidate Issues. There, participants can enter ‘Likes’ to indicate whether they consider it necessary to ‘raise’ the issue for a detailed discussion. Likely issue candidates are questions about which members have posted significantly different positions in the ‘General comments’ thread; such that the nature of the eventual plan would significantly change depending on which positions are adopted.
Issue Candidates receiving an agreed upon number of support (likes, or opposing comments, are accepted and labeled as ‘Raised’. Each ‘raised’ issue will then become the subject of a separate thread, where participants post comments (answers, arguments, questions) to that issue.
It will be helpful to clearly identify the type of issue or question, so that posts can be clearly stated (and evaluated) as answers or arguments: for example:
– Explanations, definitions, meaning and details of concepts to ‘Explanatory questions’;
– Statements of ‘facts’ (data, answers, relationship claims) to Factual questions;
– Suggestions for (cause-effect or means to ends) relationships, to Instrumental questions;
– Arguments to deontic (ought-) questions or claims such as ‘Plan A should be adopted’, for example:
‘Yes, because A will bring about B given conditions C , B ought to be pursued, and conditions C are present’).
‘Next step?’ motion
At any time after the discussion has produced some entries, participants or moderator can request a ‘Next Step?’ interruption of the discussion, for example when the flow of comments seems to have dried up and a decision or a more systematic treatment of analysis or evaluation is called for. The ‘Next step’ call should specify the type of next step requested. It will be decided by getting agreed-upon number of ‘likes’ of the total number of participants. A ‘failed’ next step motion will automatically activate the motion of continuing the discussion. Failing that motion or subsequent lack of new posts will end discussion of that issue or project.
Decisions (to adopt or reject a plan or proposition) are ‘settled’ by an agreed-upon decision criterion (e.g. vote percentage) total number of participants. The outcome of decisions of ‘next step?’ motions will be recorded in the Introduction thread as Results, whether they lead to an adoption, modification, rejection of the proposed measure or not.
As indicated before, traditional decision modes such as voting, with specified decision criteria such as percentages of ‘legitimate’ participants, are going to be inapplicable for large (global’) planning projects whose affected parties are not determined by e.g. citizenship or residency in defined geometric governance entitites. It is therefore necessary to explore other decision modes using different decision criteria, with the notion of criteria based on the assessed merit of discourse contributions being an obvious choice to replace or complement the ‘democratic’ one-person, one-vote’ principle, or the principle of decisions made by elected representatives (again, by voting.)
Participants are therefore encouraged to explore and adopt alternative decision modes. The assessment procedures in sections 3 and 4 have produced some ‘candidates’ for decision criteria, which cannot at this time be recommended as decisive alternatives to traditional tools, but might serve as guidance results for discussion:
– Group Plan plausibility score GPlanpl;
– Group Quality assessment score GPlanQ
– Group plausibility-adjusted quality score GPlnQpl;
The controversial aspect of all these ‘group scores is the method for deriving these from the respective individual scores.
These measures also provide the opportunity for measuring the degree of improvement achieved by a proposed plan over the ‘initial’ problem situation a plan is expected to remedy: leading to possible decision rules such as that rejecting plans that do not achieve adequate improvement for some participants (people being ‘worse off ‘after plan implementation) or selecting plans that achieve the greatest degree of improvement overall. This of course requires that the existing situation be included in the assessment, as the basis for comparison.
In the ‘basic’ version of the process, no special analysis, solution development, or evaluation procedures are provided, mainly because the FB platform does not easily accommodate the formatting needed. The goal of preparing decisions or recommendations based on contribution merit or assessed quality of solutions may make it necessary to include such tools – especially more systematic evaluation than just reviewing pro and con arguments. If such techniques are called for in a ‘Next step?’ motion, special technique teams must be formed to carry out the work involved and report the result back to the group, followed by a ‘next step’ consideration. The techniques of systematic argument assessment (see section 3) and evaluation of solution ‘goodness’ or ‘quality’ (section 4) are shown as essential tools to achieve decisions based on the merit of discourse contributions above.
Special techniques teams will have to be designated to work on these tasks ‘outside’ of the main discourse; they should be limited to small size, and will require somewhat more special engagement than the regular project participation.
Other special techniques, to be added from the literature or developed by actual project teams, will be added to the ‘manual’ of tools available for projects. The role of techniques for problem analysis, solution idea generation, as well as that of systems modeling and simulation (recognizing the fact that the premise of ‘conditions’ under which the cause-effect assumption of the factual-instrumental premise of planning arguments can be assumed to hold, really will be the assumed state of the entire system (model) of interrelated variables and context conditions; an aspect that has not been adequately dealt with in the literature nor in the practice of systems consulting to planning projects.)
6 Decision modes
For the smaller groups likely to be involved in ‘pilot’ applications of the proposed structured discourse ideas described, traditional decision modes such as ‘consensus’, ‘no objection’ to decision motion, or majority voting may well be acceptable because familiar tools. For large scale planning projects spanning many ordinary ‘jurisdictions’ (deriving the legitimacy of decisions from the number of legitimate ‘residents, these modes become meaningless. This calls for different decision modes and criteria: an urgent task that has not received sufficient attention. The following summary only mentions traditional modes for comparison without going into details of their respective merit or demerits, but explores potential decision criteria that are derived from the assessment processes of argument and proposal plausibility, or evaluation of proposal quality, above.
Proposals receiving an agreed-upon percentage of approval votes from the body of ‘legitimate’ voters. The approval percentages can range from simple majority, to specified plurality or supermajority such as 2/3 or 3/4 to full ‘consensus’ (which means that a lone dissenter has the equivalent of veto power.) Variations: voting by designated bodies of representatives, determined by elections, or by appointment based on qualifications of training, expertise, etc.
Decision based on meeting (minimum) qualification rules and regulations.
Plans for building projects will traditionally receive ‘approval’ upon review of whether they meet standard ‘regulations’ specified by law. Regulations describe ‘minimum’ expectations mandated by public safety concerns or zoning conventions but don’t address other ‘quality’ concerns. They will lead to ‘automatic’ rejection (e.g. of a building permit application) if only one regulation is not met.
Decision based on specified performance measures
Decision-making groups can decide to select plans based on assessed or calculated ‘performance’. Thus, real estate developers look for plan versions that promise a high return on investment ratio (over a specified) ‘planning horizon’. A well known approach for public projects is the ‘Benefit/Cost’ approach calculating the Benefit minus Cost (B-C) or Benefit-Cost ration B/C (and variations thereof).
Plan proposal plausibility
The argument assessment approach described in section 3 results in (individual) measures of proposal plausibility. For the individual, the resulting proposal plausibility could meaningfully serve as a decision guide: a proposal can be accepted if its plausibility exceeds a certain threshold – e.g. the ‘so-so’-value of ‘zero’ or the plausibility value of the existing situation or ‘do nothing’ option. For a set of competing proposals: select the one with the highest plausibility.
It is tempting but controversial to use statistical aggregation of these pl-measures as group decision criteria; for example, the Mean group plausibility value GPlanpld. For various reasons, (e.g. the issue of overriding minority concerns), this should be resisted. A better approach would be to develop a measure of improvement of pl-conditions for all parties compared to the existing condition, with the proviso that plans resulting in ‘negative improvement’ should be rejected (or modified until showing improvement for all affected parties).
Plausibility-adjusted ‘Quality’ assessment measures.
Similar considerations apply to the measures derived from the approach to evaluate plans for ‘goodness or ‘quality’ but adjust the implied performance claims with the plausibility assessments. The resulting group statistics, again, can guide(but should not in their pure form determine) decisions, especially efforts to modify proposals to achieve better results for all affected parties (the interim results pinpointing the specific areas of potential improvement.
7 Contribution merit rewards
The proposal to offer reward points for discourse contributions is strongly suggested for the eventual overall platform but one difficult to implement in the pilot versions (without resorting to additional work and accounting means ‘outside’ of the main discussion). Its potential ‘side benefits’ deserve some consideration even for the ‘pilot’ version.
Participants are awarded ‘basic contribution points’ for entries to the discussion, provided that they are ‘new’ (to the respective discussion) and no mere repetition of entries offering essentially the same content that have already been made. If the discussion later uses assessment methods such as the argument plausibility evaluation, these basic ‘neutral’ credits are then modified by the group’s plausibility or importance assessment results – for example, by simply multiplying the basic credit point (e.g. ‘1’) with the group’s pl-assessment of that claim.
The immediate benefits of this are:
– Such rewards will represent an incentive for participation,
– for speedy assembly of needed information (since delayed entries of the same content will not get credit).
– They help eliminate repetitious comments that often overwhelm many discussions on social media: the same content will only be ‘counted and presented once;
– The prospect of later plausibility or quality assessment by the group – that can turn the credit for an ill-considered, false or insufficiently supported claim into a negative value (by being multiplied by a negative pl-value) – will also discourage contributions of lacking or dubious merit. ‘Troll’ entries will not only occur but once, but will then receive appropriate negative appraisal, and thus discouraged;
– Sincere participants will be encouraged to provide adequate support for their claims.
Together with the increased discipline introduced by the assessment exercises, his can help improve the overall quality of discourse.
Credit point accounts built up in this fashion are of little value if they are not ‘fungible’, that is, have value beyond the participation in the discourse. This may be remedied
a) within the process: by considering their uses to adjust the ‘weight’ of participant’s ‘votes’ or other factors in determining decisions;
b) beyond the process: By using contribution merit accounts as additional signs of qualification for employment or public office. An idea for using such currencies as a means of controlling power has been suggested, acknowledging both that there are public positions calling for ‘fast’ decisions that can’t wait for the outcome of lengthy discussions, and that people are seeking power (‘empowerment’) almost as a kind of human need, but like most other needs we are asked to pay for meeting (in one way or other), introducing a requirement that power decisions will be ‘paid for’ with credit points. (One of the several issues for discussion.)
In the discourse about collective plans, the process of evaluation – making judgments about whether a plan is ‘good enough’ or which of several plans is the better, — differences of opinions occur, which can be resolved by mutual explanation of the basis of evaluation judgments. The discussion here is focused on the role of ‘criterion functions’ in this process. These functions – showing how ones subjective ‘goodness’ judgments depend on ‘objectively’ measurable criteria – make it possible to explain one’s basis of judgment in much more specific detail than is usually done even in the most cooperative group processes. Some key insights of the discussion are the following:
While such detailed explanation is possible and conceptually not overly challenging, including this process in actual decision-making procedures would add cumbersome provisions to a planning discourse already calling for more structure than many participants are used to and feel comfortable with. The issues of ‘aggregation’ – of individuals’ partial judgments into overall judgments, and especially of individual judgments into ‘group’ evaluation measures are potential sources of controversy.
It becomes clear that any overall ‘measures’ or judgments that can meaningfully guide decisions cannot be derived in ‘top-down’ fashion from general ‘meta values’ and ‘common good’ concepts but must be constructed ‘bottom-up’ from individual participants’ concerns and understanding of specific situations and context.
Familiar claims of planning decision makers ‘to act on behalf of others (clients, users), with adequate knowledge of those others’ concerns and basis of judgment, but not having gone to the trouble of doing this, are unfounded and should be viewed with reserve.
Examination of criterion functions make it obvious that the quest for and claim of having found ‘optimal’ solutions is unrealistic: no plan will achieve the ‘best possible’ scores on all evaluation aspects even for individuals, and different people will have very different but legitimate criterion functions.
Considering plans or policies whose effects will occur – and change – over time, adds another level of complexity. System simulation models can track the performance of variables (criteria) over time, but do not show associated ‘goodness’ judgments (obviously, since this would either be just one person’s assessment, of some aggregated measure of judgments that have not been included in the system modeler’s data.
The examination of how evaluation judgments for different plans could be tracked over time (as a function of the simulated variable tracks) suggests a different decision guide: the (time-discounted) degree of improvement of a plan over the current or predicted problem situation under the ‘do nothing’ option.
The discussion takes place in the hypothetical ‘Fog Island Tavern’.
– Hey Bog-Hubert – what kind of critters are you guys talking about? I couldn’t quite get it coming in, but it sounds like serious wildlife?
– Good morning Renfroe. Well, I guess you could call them critters, but not the kind you mean. Actually, we were talking about criterion functions. About how we can explain what we mean when we’re making judgments about, say, proposed plans. Calling them good, so-so, or bad, or anything in-between.
– Huh. Plans, as in what to do about saving the beaches where each storm washes away more of the sand?
– Yes, or about what to do about the climate change that makes the storms worse and the oceans rise.
– What, you guys can’t even come up with a plan for beach preservation on this little island, and now you want to talk about the oceans and global climate?
– Well, Renfroe, it looks like the problems of coming to some agreements about what to do are the same everywhere, just at a different scale.
– So where do your critters come in on that one?
– I guess we need to back track a little on that. It has to do with evaluation, say of different proposed plans, to decide which one is best, or whether any of them should be implemented. You could start by looking at them and then make an offhand judgment, say ‘good’; ‘not good’. If there are several proposals, you may want to use a more detailed scale, for example one with seven points ranging from ‘couldn’t be worse = – 3, to ‘couldn’t be better’: +3, with a midpoint of zero meaning ‘don’t know’ or ‘so-so’. In a group you’ll have to agree on some common scale. Now somebody asks you why you rate proposal X so high, and solution Y so low, since they came up with very different ratings from yours. So you may want to talk about the reasons, the basis of your judgments, maybe you each know something the other doesn’t know or see, that should be considered in making the decision. What do you do? How do you explain what makes a solution good or bad, in your view?
– Well, you could look at the various costs and benefits, and how well the plan will work for what it is meant to do?
– And how good it looks, if its’ a building or some thing we are looking at or living in?
– Yes, Sophie.
– And don’t we also have to worry about those ‘unexpected side-and-after-effects’ of plans, that people always talk about but keep forgetting?
– Good point. Next we list all those considerations or ‘aspects’ and make sure that we all mean the same thing when we name them. But we can only consider what people bring up in the discourse, so it’s important to make sure that is organized so as to let everybody put in their views. Now you can give each plan a ‘goodness’ judgment score – on the same scale — for each of those aspects. Let’s call those ‘partial’ judgments – all together they make up your ‘overall’, whole judgment for each plan. You’ll then have to explain how exactly all of those scores make up the overall judgment.
– And looking at the different aspects, you may want to reconsider the first overall, offhand judgment you made?
– Good point, Vodçek. Deliberating already. Learning. Excellent. But to get to the criterion functions: You realize how an explanation of a judgment the goodness score always consists of showing how the judgment relates to something else. That something else can be another judgment – look at how Sophie suggested that her overall ‘goodness’ judgment of, say, a building, should depend in part on the beauty of that building – which of course would be another judgment, and people may have different opinions about that. But the relationship would be that of some ‘degree of beauty’ about which she would have to make another ‘goodness’ judgment to explain how it contributes to the overall building goodness judgment.
– That’s not much on an explanation though, is it?
– Right. So you could ask her what, in her mind, makes a building beautiful. What would be you answer, Sophie?
– Well, if I got the sense that he just wants to annoy me with all these questions – because I can see how each answer will just lead to another one, and where will that end – I could just say that if he can’t see it he just doesn’t understand beauty and tell him to get lost. But if I think he really wants to learn what I see as beautiful, I might suggest that it has to do with, say, its proportions.
– Ah. Now we are getting closer to the criterion issue. Because proportions are really measurement relations: in a rectangle, the length of the short side to the length of the longer one. The relationship is now something we can ‘objectively’ measure. Quantitative. And many people are really adamant about making our decisions based on objective ‘facts’ and measures. So would it satisfy those folks to show them a graph that has the ‘objective’ measure on one axis – the horizontal one, say, and our judgment scale on the vertical one: If you are convinced that the most beautiful proportion is the ‘golden ratio’ – 1:1.618… the graph would touch the + 3 line at that 1.618… point, and go down from there in both directions. Like this, for example: Down to 1:1 (the proportion of the square) on one side, and down to -3 for infinitely long rectangles: 1:∞
Fig 1. A criterion function for proportion judgments
– Hey, didn’t we look at that proportion thing a while back? But then we looked at both sides on the 1:1 point – if the right side is for ‘vertical’ rectangles, the left one continues past the 1:1 point for horizontal ones.
– And if I remember correctly, didn’t somebody point out that there are many people who feel that the square, or the one based on the diagonal of the square, the √2 relationship, is the most beautiful proportion?
– You’re right. But that was in another book, a fat one, if I recall? So let’s not get too distracted by the details here. But perhaps we should just remember that there are many different forms of such functions: the one where ‘zero’ on the variable represents -3 on the judgment scale, which goes on to approach +3 at infinity, its opposite that starts with +3 at zero on the criterion scale and approaches -3 at infinity, the opposite of the golden ratio curve that goes from -3 at some value of our criterion and rises towards +3 on both sides.
– Can’t think of an example for that one though. Except perhaps weird ones like people’s appreciation for apartment levels going up towards the higher floors and +3 at the penthouse – but with a sudden drop to -3 at floor 13?
– Goes to show that people’s preferences can take strange contortions… But those are personal judgments. I guess they are entitled to hold those, privately. Now, what about collective decisions?
– Yes, Vodçek. That is the point where we left off when Renfroe came in. We can explain how our subjective goodness judgment relates to some objective measurement. And this is useful: I can ask somebody to make a decision on my behalf if I give him my criterion function to make a selection – even though I know that his criterion function likely has a different shape and the high +3 judgment score is in a different place. But the issue we started from was the idea that there should be measurements – expressing values – that everybody should agree on, so that collective decisions could be guided by those values and measurements. ‘Meta-values’?
– Yes, that notion seems to make perfect sense to many people – for example the feel that trying to stop climate change is so important for the survival of human civilization – that it is such a meta-value that everybody should agree on so that we can start taking more effective action. And that this is even an ethical, a moral duty. So they can’t understand why there are some people who don’t agree.
– Right. So we were trying to untangle the possible reasons why they don’t.
– Short of declaring them all just blindly indoctrinated by political or religious views or outright fraudulent misrepresentations, eh?
– Yes, let’s not go there. I guess there may have been some confusion because at first there was no distinction between the ‘meta-values – that were quite general and abstract – and the corresponding measures one would need to actually guide decisions: You can’t really argue against a concept like the Common Good as a guiding value – but when it comes to pin down just what that common good is, and how to get an ‘objective’ measure for it, history shows that there’s plenty of disagreement both about the ‘common’ part – my family, tribe, town, country, my religion, humanity, all life on the planet? And even more vicious: about the part what the ‘good’ might be.
– I agree; and the attempt to justify those different views have led to some pretty desperate contortions of moral guidelines for decisions to meet those good things: I remember the old ‘dulce et decorum est pro patria mori’ (‘sweet and decorous it is to die for one’s country’), or promising all kinds of heavenly rewards in the hereafter to those willing to fight and kill and die for religious ideas.
– Well, if your tribe or country or your faith is your ‘common’, and somebody is attacking it, what’s wrong with that?
– I guess it becomes questionable when these definitions lead to more of the good is ending up with some people – the fellows who are spouting these glorious quotes and values and then get to make the decisions ‘on behalf’ of everybody else, while many of the everybody else are doing the dying and sacrificing. If it becomes apparent that these value leaders and doers have actually been acting more on behalf of their own good, the trust in those values is eroded. No matter how they are justified: by philosophical theories, by divine revelations (mostly revealed only to some special prophets), by political theories, or scientific theories. Or systems thinking. Or holistic thinking and awareness.
– Even scientific and systemic investigations?
That’s the tragedy, right. You may argue that science and systems tools are our best available tools for guiding action, based on objective measurements and facts, and have all the evidence and replicable observations to support them: if they then are used by leaders, — governments or ‘movements’ — to postulate ‘meta values’ to guide actions ‘on behalf of’ others, they will run into the same trust issues as all the other attempts to do the same, — unless…
– Unless what?
Well: unless they can also offer guarantees that those leaders are not just acting on their own behalf. Even if Congress were full of scientists and systems thinkers: if they make laws to deprive people of health insurance while themselves enjoying the best insurance and health care, no matter what justification they offer for their actions, they would run into trust problems. So that would be one condition.
– One condition, Vodçek? Are there others?
– In theory, yes. Its’ actually part of the job of the legislature: isn’t it in the constitution, even, that they should make laws on behalf of their constituents. And the representative notion is, of course, that representatives should be part of the communities they represent and communicate with then so that they know what the community wants? And then go and vote for laws that realize those preferences.
– Which they should do even if they don’t agree with them? Even if they know better? Doesn’t the constitution also state that they should vote according to their own conscience?
– Right: there seems to be some contradiction there. And it’s leading to that constant tug-of-war between the principle of electing representatives whose judgment we trust — to vote in view of the common good – even if we don’t agree, — because we don’t have all the information? Or because we are suffering from doctrinaire blindness or stupidity, or ethical or moral depravity? And to the alternative of passing laws by referendum, regardless of what the representatives are saying.
– Well, there’s the practical issue: we can’t possibly make all laws by referendum, can we? And if we are too ignorant to give our representatives proper guidance about how to vote so they have to vote by their own better knowledge and information and conscience, should we be allowed to vote on laws?
– But we are allowed to vote for the representatives? Isn’t there an expectation that the representatives should provide enough information to their constituents to know and understand the best available basis of judgment for the needed actions and also be confident that the representatives’ basis of judgment is sound enough to let them vote according to their own judgment conscience if and when necessary?
– Right. Theory, perhaps; current practice of governance looks a bit different. But that’s where our question about the criterion functions come in, again: They are part of the process of not only making up our minds about what actions to take or to support, but also of explaining our basis of judgment to each other. In the extreme, so that we can trust somebody else to make judgments and take action on our behalf – because we have conveyed our mutual basis of judgment well enough, as well as made sure it does give adequate consideration to all available information and concerns.
– So what we are trying to clear up for ourselves is this question: Are there general or universal ‘meta-values’ that can give us adequate criteria to guide effective action — not only let leaders invoke those values without an way of checking whether they actually are served by the proposed actions? And how would those criteria / measures come to be identified and agreed upon?
– Even more specifically, whether those measures should be determined by objective measurement, and then used by some people who are able or entitled to initiate ‘effective action’ to not only do so, — on behalf of everybody else – but to claim that this is ethically and morally defensible and necessary.
– And to declare everybody who disagrees to be ethically misguided – really: to be ‘bad’ or ‘evil’ people.
– Do they come right out and say so?
– I think both sides are, in so many words, unfortunately. So the question of whether there are ‘meta-values’ with related performance measures that everybody should adopt and thus support the resulting actions, is an important one. The sticking part being, to support collective actions taken on our behalf, and perhaps compelling us to take certain everyday actions ourselves, in pursuit of those meta-values. Didn’t we say, a little while ago, that somebody can take action on my behalf if I have given him my criterion functions? – But now it looks like the suggestion is the other way around: that there are criterion functions people tell us we should adopt, to comply with the ethical demands of the Meta Values. So we are trying to understand what that really means.
– Okay: so, let us assume that we have persuaded the participants in the climate change debate to explain their basis of judgment to each other, as much as possible by use of criterion functions. Diagrams that explain how or subjective ‘goodness’ judgments g about proposed plans relate to some ‘objective’, measurable properties of climate change aspects. Take the example of the ‘evil’ CO2 that we are adding to the atmosphere. Assuming that there is some agreement about how much that matters – a different scientific question that also needs sorting out in many people’s minds. And assuming there’s some meaningful agreement about how and where those levels of CO2 will be measured.
– What do you mean – are agreements about CO2 needed? Isn’t that just a simple scientific fact?
– No, Sophie: It makes a difference whether you measure CO2 content in the atmosphere, and at what height, or in the oceans. All those things must be sorted out. Then: is the ‘amount’ or ‘percentage’ of CO2 a good choice of criterion for explaining our judgments about the quality of a plan to improve things?
+ Sure: Haven’t scientists found out, in may serious studies, that the amount of CO2, at the time when we began so see substantial human-based climate change, was some value ‘c*’? Whether you wish to use the actual measure of the amount of CO2 in the atmosphere or its percentage, does not really matter, at least for the sake of this question. Now, say a plan or policy P1 has been proposed to try to get things back in line, whatever that means. So a person tries to explain how her judgment score on some scale +U, to –U, say +3 to -3 depends on how close a proposed plan comes to that ‘goal’ of c*. Would you say that to get a ‘goodness score of +3 (meaning ‘couldn’t possibly get any better’, on a ‘goodness scale of +3 ‘couldn’t possibly get any better, to -3 meaning ‘couldn’t possibly get any worse’ with a midpoint of zero ‘’so-so’, do don’t know’), the plan would have to achieve a return to that value ‘c*’? So you’d draw up a criterion function with the top of the curve touching the +3 line at c*. But another person B thinks that a slightly higher level of CO2 would be OK given some measures in the plan to mitigate it faster. It looks like this:
Figure 3: Criterion functions of two persons, for a plan to return the CO2 value to a desirable CO2 level
It shows their different judgment basis regarding what that level c* should be, showing the CO2-measure on the x-axis and the judgment score on the y-axis. Any lower or higher than that would get a lower score.
– Okay; I see. And you are saying that in principle, every participant in the evaluation would be entitled to his or her own curve? Even one that doesn’t have the highest score at ‘c*’?
– Now why would you – or anybody – put the highest score anywhere else?
– Well, aren’t you guys saying that having spewed so much CO2 into the atmosphere since it was at that benign level ‘c*’ has done a lot of damage already? So to repair that damage – to get the glaciers to grow back, for example, or to cool down the oceans, – it would be necessary to reduce the CO2 to a lower level than ‘c*’ – at least for a while? If you could calculate that level, that’s where a person B might put the +3 score. And give that score to another plan P2 that would achieve that level. Does that make sense?
– Wait a minute: wouldn’t it be better to look at the effectiveness of a plan to reduce the amount of CO2 – at least, as you say, for a while, until the effects of increased CO2 level have been ‘repaired’?
– Good question, at least for showing that even the choice of criterion is a controversial issue. You could say that it might be even better to look at how close to the ideal CO2 level a plan can get with its reduction effectiveness, and show how that relates to what would happen if nothing is done? Which is always an alternative ‘plan’?
– Good. But the question is really about whether the criterion of ‘c*’ or ‘c•’ is an appropriate one to base you judgment upon: Both plans are claiming to reach those values – claims that should be assessed for their plausibility, don’t forget – but at different points in time. So which one is ‘better’?
– I guess we should say: the plan that gets there ‘sooner’ – all other aspects being equal, for the sake of the argument.
– Yes, but doesn’t that mean you really have a different criterion? Specifically: the criterion of ‘time for the plan to get to c* — or c•? Which really is a different criterion, so which one are you going to use?
– Does it matter whether we use different levels of desirable c’s as long as we all come up with a goodness judgment g, and we each have explained what that judgment depends upon?
– If the outcome is that your judgment will support P1 while –‘s score will prefer P2 as the better plan – all else being equal, as you say: the problem isn’t really solved yet, is it?
– Hey guys, aren’t you missing something essential here? Well, you did sort of stumble on it, – with your remark ‘at least for a while’.
– Huh? Explain, Vodçek. What’s missing?
– Time, of course. In your criterion functions so far, you seem to make an assumption that your plans P1 and P2 will somehow ‘achieve’ some level of CO2 one they got implemented, and that things would then stay that way? But come on, that’s not how things work, is it? Even a plan for this kind of issue would have to involve activities, policies, processes, all continuing over time. It can’t be a sudden magic spell to change things overnight. And then it would take time for the actual CO2 level to change back to whatever level you’d have in mind — if the plan works. But how long is that going to take? And is it going to stay at that level? Shouldn’t that be part of your systemic ‘due consideration’?
– You are right. So let me see – looks like we have to draw up a kind of three-dimensional criterion function, is that what you are implying?
– Right. If you are serious about this idea of ‘explaining how your subjective judgment relates to objective criteria’. Not everybody does…
– Okay, I see your point. So we draw the diagram like this: Time on the horizontal right-left axis, CO2 – level on the horizontal up-down axis y, and your judgment on the vertical axis z.
– And before you ask, I think Dexter would say simulation models to predict the track of the CO2 levels for each plan over time can and have been developed, given reliable data…
– But now, what’s your score for those plans? If the CO2 levels and judgments change all the time? By the way, wouldn’t you have to also include a simulated track for the ‘current’ state of affairs and its future track if nothing is done?
+ Right. So we have the time CO2 simulation with three tracks – like this?
– Okay, what about instead looking at the difference between the desired targets and what the plans are actually achieving, over time? It would require looking at the total measure of those differences over time, and I agree that it would also require an agreement about the time frame we are willing to look at. People keep talking about the world we are going to leave for our grandchildren, from a more systemic and holistic perspective – but don’t offer any specifics about how we might distinguish one plan from another, or even from just doing nothing?
– I like your point about looking at the difference, the degree of improvement we can expect from a plan. What would that look like in your diagram?
– Well, the measure would have to be one like the area of the judgment ‘surface’ between two alternatives? Because we agree that in order to reach some kind of meaningful overall measure, it will have to be made up of judgment’ measures, right? But I’m sure that at least for individual judgment systems, ways can be found to calculate that, just as there are equations that describe the simple line functions in the previous examples. But for the time assessment, it will have to include some feature of ‘discounting’ the judgments over time – like calculating the ‘present’ value of a series of income or cost payments over time. Work to do, eh? Because you can see in the diagram that if a plan ‘works’, the improvement judgment area will get wider and wider over time – but after since the probabilities / plausibility judgments will also get more and more uncertain for long future time periods, they will become less and less important factors in the final overall judgment.
– I see what you mean. Not because we don’t care about future generations, mind you – but simply because we just can’t be certain about our predictions about the future.
– Right. Meanwhile, the discourse may become more productive if we threw more of these kinds of diagrams into the fray? Like this one about the judgment surfaces – I agree it needs discussion?
– So you may have to look at the actual results that those changes in CO2 will bring about, over time? Like: levels of ocean rise expected until the remedy sets in – will it actually recede if the plans are any good? I haven’t heard anybody even mention that yet… And provisions for what to do about sea level change until it stops rising?
– Coming to think of that – have there been any plans put out there with that kind of details?
– I admit, I haven’t been following all the reports on that controversy – but I am not aware of any.
– Hey, here’s a test for promoters of a plan: ask them whether they are willing to put up down payments for new ocean front real estate that will emerge if their plan works as intended?
– Renfroe… Ah well, maybe you’ve got something there. Get Al to put down money for property on the beach in front of Mar-a-Lago?
– You guys are giving me a headache. How are we ever going to get moving on the problem if you keep analyzing things to death and wasting time with stupid pranks?
– Well, who was claiming and boasting about taking a more systemic and holistic look at these problems, and of making decisions based on objective facts? It may be useful to turn that big talk down a notch, and focus on the painful nitty-gritty aspects of how to make these decisions. So that people can agree on something specific instead of calling each other names, and resisting plans because of distrust – deserved or not – about what the promoters for plan P1 or P2 are really after? Like power? The next election? More profit for one industry rather than another? That lack of trust may be the real reason why people keep resisting plans to do something about problems. But can’t talk about them because those suspected motives or their lack of them aren’t being part of the discourse?
– Ah: the discourse. Yes. How to talk about all that without starting to call each other names or throwing rocks at each other and storefronts… What does that take? Where’s Abbé Boulah?