RECONCILING TEMPUS AND HORA

Policy Knowledge in an Information Wired Environment

Sylvie Occelli

IRES - Istituto di Ricerche Economico Sociali del Piemonte, Via Nizza 18, 10125 Turin, Italy

Keywords: Policy knowledge, Modelling as a cognitive mediator, Social complexity, Information wired environment.

Abstract: Societal transformation and dramatic improvements in Information Communication Technologies, are

changing the context in which policy activity and the underlying knowledge process operate. There is a need

to develop a policy knowledge representation, capable of informing the co-evolution between policy process

and knowledge contents, while itself evolving in order to steer the process. This note is a contribution to this

endeavour. The functional roles of knowledge representation, in implementing a software tool for policy

design is discussed. As the technological potential is very promising, there is a need that the socio-cultural

context does not fall behind to get hold of it.

1 INTRODUCTION

In a seminal paper, Simon (1962) told a story about

two well-known watchmakers, Tempus and Hora,

who however enjoyed a contrasting destiny when

confronted with the event of increasing client

demand. Tempus used to construct watches

according to a design in which the many elementary

parts were assembled one by one. Being frequently

interrupted to meet the client calls, he could not

easily progress as he had often to start over again the

building process. Hora approached the task,

according to a design in which a number of

elementary parts were first assembled and then the

resulting components put together. When confronted

with the interruptions of the client calls, only a

limited number of the construction operations had to

be started again. Being able to achieve the

construction of the watches more timely than

Tempus did, therefore Hora prospered while Tempus

run out of business.

Notwithstanding a long time has elapsed since

the story was told, its metaphorical arguments help

us to elucidate a few main issues which are

becoming increasingly relevant in the today debate

concerning : a) the policy process (what in the above

metaphor relate to the watch construction and

market context), and b) the types of knowledge

which should back the policy components (what in

the metaphor stands for the design of the watch

construction process).

Actually, it is the very relationships between the

policy process and the types of knowledge – which

by the way is neglected in the story- that is at the

core of the debate.

Conventionally, the policy activity is understood

as a social process, which includes politics,

psychology and culture. It is usually visualized “as a

series of interdependent activities arrayed through

time—agenda setting, policy formulation, policy

adoption, policy implementation, policy assessment,

policy adaptation, policy succession, and policy

termination “ (Dunn, 2008, p. 45).

In addition, it is also acknowledged that in order

to support those interdependent activities a variety of

knowledge from different domains, such as

economics, geography, sociology, physics,

management, laws, computing, is required.

How the different knowledge contributions are

related to each other and how their resulting

outcome leveraged, depending on the specific issues

addressed and social context, are longstanding

questions. Recently however they are raising a

revival of interest as a result of current societal

transformations and the increasing difficulties to

deal with unexpected or unforeseen events (Lipshitz,

Popper and Friedman, 2002, Occelli, 2006a). (This

is particularly evident in innovation policy, where

the acknowledgement of ontological uncertainties

which accompany the attributions of new system

functionalities required by innovation has shaken the

conventional approaches at the roots, see Lane and

213

Occelli S..

RECONCILING TEMPUS AND HORA - Policy Knowledge in an Information Wired Environment.

DOI: 10.5220/0003071702130217

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2010), pages 213-217

ISBN: 978-989-8425-29-4

 2010 SCITEPRESS (Science and Technology Publications, Lda.)

Maxfield, 2005).

The aim of this note is to sharpen these questions

and to help elucidating how policy process and

knowledge contents might co-evolve, while

ultimately improve policy action courses. The fact

that governmental bodies should also strengthen

their own management capability to carry out this

activity, is an additional aspect worth mentioning

although it will not be dealt with in this note.

There is a need therefore to develop a policy

knowledge representation, capable of informing the

co-evolution between policy process and knowledge

contents, while itself evolving in order to steer the

process.

In the remainder, discussion proceeds as follows.

First, section 2 briefly recalls the main sources of

change in the policy context. These set the stage for

the issues addressed in section 3 concerning the

development of knowledge representation in policy

making.

In the concluding remarks it is argued that in

order to reconcile the Tempus and Hora approaches

in policy process, ICT tools and methods should be

better appropriated and leveraged. While the current

development stage of the ICT infrastructure is well

advanced, the human organization system is lagging

behind.

2 SOURCES OF CHANGE IN THE

POLICY CONTEXT

In the following, attention is turned to set the stages

of the discussion. Among the many changes

occurring in socioeconomic systems three main

sources are worth being recalled, concerning the

epistemological context, progress in information

technology and socio-cultural milieu (see Umpleby,

2007).

The main aspect of change in the epistemological

context is reflected in the evolution of the concept of

model. The main differences between the various

definitions lie in the emphasis given to the meaning

and role of the description derived from modelling.

In this respect, two interpretations have been

provided (Occelli, 2002, 2006b).

According to the first, which has been referred to

as structuralist, modelling is an activity through

which to understand the structure and organisation

of an artificial or human system. Modelling, allows

the identification of the relevant components and

relationships of the system, and makes it possible to

grasp significant features of its behaviour. Through

it a ‘representation’, although simplified and partial,

of the system internal dynamics and its reactions to

the impact of external events can be obtained;

According to the second interpretation, which we

call cognitivist, modelling activity is primarily a way

of testing the modeller’s knowledge about certain

phenomena.

These interpretations reflect the two souls of

system modelling and are intrinsically linked.

Whereas the structuralist approach was dominant in

the earlier generation of models, the cognitivist one

has progressively acquired importance as computing

power increased and become distributed web based.

The acknowledgement of the limits of rationality

and the need to adopt a new philosophy for social

action has fostered a growing interest in the

cognitivist interpretation. There exists a number of

analytic tools that can act as cognitive mediators,

between a so called internal loop, i.e. that related to

the conventional steps underlying a process of

abstraction, and a so-called external loop, i.e. that

representing the general context of a modelling

activity, see Fig.1 (Occelli, 2006b).

Action domain

Social

issues

Knowledge

systems

Theories

Mental

models

Knowledge

levels

Models of the

obervable

External loop

Modeling domain

Internal loop

Modeling process

Computer

models

Indicators

Maps

cognitive mediators as

components of knowledge

kernels

Figure 1: Modelling as a cognitive mediator.

In cognitive mediator tools, in fact , several links

exist and can be leveraged between the internal and

external loops of a modelling process.

A second source of change is the progress

Information Communication Technology, as

produced by the increasing power of computing and

diffusion of Internet use. This greatly improves the

linking of activity system models with other spatial

analysis methodologies, i.e. connections between

spatial data, indicators and graphical representations

(visual images). It also broadens the scope of model

applications: increasingly, in fact, models are tools

for sharing knowledge experiences, and learning

A final source of change relates to the

transformations in the social and cultural milieu.

Since the cultural and information levels of society

as a whole are rising, the socio-cultural context is

becoming more demanding and selective in the

KEOD 2010 - International Conference on Knowledge Engineering and Ontology Development

214

knowledge requirements (Snowden and Stanbridge,

2004). The increasing diversification of social and

economic phenomena is also acknowledged on

phenomenological grounds. Sustainability,

decentralisation of government, globalisation of

economy and impact of new information

technologies, are all recognised as important factors

in affecting novel policy issues.

Together, they concoct a radically different

policy background, also popularized as e-

government and e-governance transformations (see

Centeno, Revel and Burgleman, 2005, van Dijk and

Winters-van Beek, 2009). In particular, the

transformations associated with the responsibility

enhancement, are of outmost relevance. They in fact

urge public administration to strengthen, also by

means of Information Communication Technologies

(ICT), a twofold capacity: a) accounting, monitoring

and evaluating its own actions and b) designing,

managing and implementing policy actions in

innovative ways (see Kuhlmann, 1999, Swederberg

and Douglas, 2003).

3 REPRESENTATION OF (FOR)

POLICY KNOWLEDGE

3.1 The Roles of Knowledge

Representation

Eventually, the above discussion emphasizes a need

to address the issues of how to represent, build and

leverage knowledge for policy in a changing

context.

Loosely speaking a knowledge representation is

a posture of mind adopted for reasoning about a

problem. In so far as policy situations are perceived

as complex, they require to adopt a complexity

approach, that is a modelling endeavour capable of

making those situations intelligible (Morin and Le

Moigne, 1999, Lerbet-Sereni ed. 2004). But this

modelling endeavour is not meant to provide a

simplified account of that situation. This, in fact, is

associated with a system as an entity of interrelated

elements (activities, individuals) organized for some

purpose in an environment. Systems, however, do

not exist in nature but through an observer’s eyes.

In an attempt to go to the basics of the notion,

knowledge representation some researchers (Davis,

Shrobe and Szolovits, 1993) contended that this can

be understood considering the roles entailed,

whenever it is applied in a certain task. In this

respect, they identified the roles summarized in

Tab.1 and underlined the fact that all of them are

important in defining the properties of a

representation.

Table 1: The roles of Knowledge Representation (based on

Davis, Shrobe and Szolovits, 1993).

Roles Contents Implications and

questions raised

A surrogate it is a stand-in for the

things that exist in

the world

intended identity

and fidelity

A set of

ontological

commitments

a view in order to

focus on the things in

the world we are

interested in

definition of the

sets of concepts

offered as a way of

thinking about the

world

A fragmentary

theory of

intelligent

reasoning

identification of the

fundamental concepts

of intelligent

reasoning

all representations

are imperfect, and

any imperfection

can be a source of

error

A medium for

efficient

computation

representation should

be computable

representations

offer a set of ideas

about how to

organize

information in

ways that facilitate

recommended

inferences

A medium

of human

expression

the means by which

we express things

about the world and

communicate for our

use

how well does the

representation

function?

How precise and

adequate?

How each role is instantiated in a representation,

and the rationale for that, reveals what the

representation would command about how to view

the world. Eventually, providing insights into these

roles turns out to be useful mostly because they can

inform a conscious choice of the properties of the

knowledge representations required in a certain task.

3.2 Knowledge Representation in

Policy Making

A claim is made that addressing the above roles can

steer the formulation of knowledge representation in

(for) policy process. To provide some evidence

reference is made to a case study (see, Boero and

Occelli, 2009), in which the discussion of those roles

provided grounds for developing a software learning

tool, using a case base reasoning approach, aimed at

collecting regional broadband and ICT projects, and

extracting the knowledge which was acquired in

RECONCILING TEMPUS AND HORA - Policy Knowledge in an Information Wired Environment

215

their implementation.

In particular, the study pointed out that in a field

such as policy, where the theoretical domain is

weak, compared to mathematics or the natural

science, the possibility by means of an ICT based

tool to reinforce the role of surrogate is an

extraordinary challenge in policy design and

process.

As for the ontological commitments, the study

focussed on the relationships between the results of

a policy practice and the practice itself, this being

viewed as a set of actions accomplished by some

actors to achieve some objectives. It recognizes as

an important source of knowledge that stemming

from the situated actions, such as those produced by:

a) a variety of human competences and decision-

making involved, interacting in non trivial ways; b)

the existence of a certain organizational and

institutional context which may hamper or favour

the lawfulness of certain courses of action.

Actually the reasoning approach builds upon

findings from organizational and complexity studies

advocating that knowing cannot be assumed, only

achieved (Swederberg and Douglas, 2003).

What the approach recommended is that in order

to provide an understanding of those situations a

modelling endeavour is required (Nahapiet and,

Ghoshal, 1998, Nonaka, 1994, Orlikowski, 2002).

Two main hypotheses play an important role in

guiding this activity, and namely that: a) in most

policy situations, the decision-making activity is a

design process (i.e. it entails a problem solving

activity oriented at some socially valued objectives);

and b) the identification of the problems to be

addressed leverages a reasoning process. What this

approach sanctions is the certainty of our actions. As

Minsky put it “we can never be sure our

assumptions are right, and must expect eventually to

make mistakes and entertain inconsistencies. To

keep from being paralyzed, we have to take some

risks. But we can reduce the chances of accidents by

accumulating two complementary types of

knowledge: a) we search for islands of consistency

within which commonsense reasoning seems safe; b)

we also work to find and mark the unsafe boundaries

of those islands” (Minsky, 1994).

A main aspect clearly shown by the study, was

that the development of the software tool was itself a

challenge. In fact, it compelled the analysts to

categorize the policy questions and design a

convenient template to collect the relevant

information. It thus required to carry out reasoning

activities which in fact belong to those undertaken in

the encoding phase of a modelling process (see

Fig.1).

As for the decoding phase, no definitive evidence

so far exists. What is apparent by now, however, is

that the tool will require to maintain an actor

network on a permanent basis. Actually, the

implementation of this function endorses a

knowledge representation (a cognitive mediator) of a

novel role. This turns out to be an important feature

for meeting the requirements of informing and

supporting the co-evolution between policy process

and knowledge contents.

4 CONCLUDING REMARKS

The reconciliation of Tempus and Hora approaches

in policy process requires additional insights into the

knowledge representation processes, conventionally

used.

So far attention has been paid to the cognitive

mediation role of models from the point-of-view of

the internal loop of the modelling activity. The

progress in ICT and the web endorses the knowledge

representation tools (models) of unprecedented

potentials

(Angehrn and Nabeth, 2606, Thorne,

2003, Occelli, 2008).

There is a need to improve model building

process activities. This is not only a matter of having

an accessible user friendly device, through which

operating the methodology transfer. Rather a socio-

cultural context prone to engage itself in innovative

thinking is necessary to take advantage of

modelling and of its different knowledge leverages,

i.e. recognition, guidance and capability (Occelli,

2007).

Apart from argumentative rhetoric about

Information Society, we are going through an

extraordinary periods of change in which modelling,

and namely computer supported modelling, is

opening unprecedented ways of yielding the

knowledge constitutive components of human

organization systems.

As progress in modelling is advancing at speedy

space, there is an urgent need that the socio-cultural

environment does not fall behind in appreciating its

potentials. Engaging into experimenting model

applications, i.e. involving the various collaborative

competencies in an inter-disciplinary perspective can

help avoiding that risk.

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