scef- 2003 international workshop 30 sep., 1 oct. 2003, rome socio-cognitive engineering...

SCEF- 2003 International Workshop 30 Sep., 1 Oct. 2003 , Rome http://erg4146.casaccia.enea.it/SCEF

Socio-Cognitive Engineering Foundations and Socio-Cognitive Engineering Foundations and Applications: Applications:

from Humans to Nationsfrom Humans to Nations (an introduction)

Adam Maria GadomskiAdam Maria Gadomski

High-Intelligence & Decision Research Group, CAMO, ENEA

& Sc. Board of ECONA, Italy

[email protected]

© 2003, A.M.Gadomski. All rights reserved. - Only for citation purposes.

This position paper will be available in the Proceedings of the SCEF-2003 Workshop

http:// erg4146.casaccia.enea.it/

SCEF-2003 International Workshop http://erg4146.casaccia.enea.it/SCEF/

© 2003 Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/

High-Intelligence & Decision Research GroupHID

1. Foundations, Paradigms, Context

2. SCE Domains, Activities and Strategy

3. Complexity & Objectives

4. Methodology: TOGA

5. Intelligent Organization, Roles & Decision-Making

6. Technology: Intelligent Decision Support Systems

7. Conclusions

Presentation outline

About “Foundations”


High-Intelligence & Decision Research Group

HID

Foundations is a basic theoretical framework of a research or engineering field.

It includes:

- initial assumptions/axioms/paradigms

- its conceptualization tools: methods, methodologies

- basic ontology of the domain of interest.

Its objective is to provide tools for computational models development.

Computational model : formal model which may be implemented on computer and enables computer simulations.

About “Paradigms”

HID

Paradigms are arbitrary chosen.

They are invariant rules/laws which are defined on a highest abstraction/generalization level.

They are either ontological assumptions or methods employed in the domain.

One of the key difficulties related to the acceptation of paradigms are their choice criteria (usually implicit).



About “Human Errors”

© Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/


HID

Human error:

Human action or inaction that can produce unintended results (*) or system failures (**).

(*) [ISO/ ITC Information Technology Vocabulary,96]

(**) [ NUREC-1624]

Machinefailures

Human errors

Reliability problems

Safetyproblems

Complex consequences interrelations[Gadomski, 2002 ]

Socio-Cognitive Engineering Context: 3rd Generation Research

SCE belongs to third research generation in the human culture.

These generations are distinguishable by the following specific techno-scientific development:

First Generation - specialization approach; incremental grown of subject oriented sciences and technologies. They are well isolated and self-limited by: their language (conceptualization systems), observation/measurement tools and engineering approaches.

Second Generation - interdysciplinary approach; autonomous cooperation between different branches of research caused by common interests and by the tentative of an unification of their objectives-oriented and interface terminology.

Third Generation - over-disciplinary approach; building new common perspectives, shared top conceptualization and ontology (redefinition of basic terms from a higher more abstract/universal perspective), in such way that they become valid for many, before separated research fields (something similar to the unification in physics).

At present

At a consequence, in 3rd generation of research, the integration of science and technology development should be seen as one parallel goal-driven incremental process.


About SCE Intervention Domain


High-Intelligence & Decision Research GroupHID

Domain of SCE are systems/networks of interacting humans and human like intelligent entities.

Intelligence-based systemsWe use an object-based framework for initial conceptualization of any

- individuals - organizations - associations - communities - society

- nations

- s/h technologies

Intelligent Web

H

HS

H

HSR

H human HS humans system R robot

communication link

can be substituted by

An Example of ABSTRACT VIEW OF INTERACTING NETWORKS

PHYSICAL

BIOLOGICAL

TECHNOLOGICAL

ORGANIZATIONAL[ From Sandro Bologna presentation,2003]

Complex systems

Made of many non-identical elements

connected by diverse interactions.

NETWORK

H ZOOM

Fonte: Corriere della Sera 30.09.03

ELECTRICAL SYSTEM NETWORK

About Intervention Domain: Human Errors Socio-Cognitive Engineering application for

Multi-grid Large Complex Critical Systems/ Infrastructures (LCCI)

(such as electricity, telecommunication, gas networks)

© Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA, http://erg4146.casaccia.enea.it Author: Adam Maria Gadomski, 28/09/2003

Technological Grid

Human Errors

Organisation Network

Human component

Production/Transmission /Control componentof Physical &Technological Layers

Artificial Highly-Autonomous (Intelligent Agent) component for

Decision-support systems

Human Factors

Human Errors

Social Consequences

About Intervention ACTIVITIES

SCE contributes to the Vulnerability Analysis and to the Improvement of Robustness of Large Complex Critical Systems (Humans-Technology Systems).

Key Intervention Activities• Users/human Modelling and Simulation

• Organization Structures and Decision-Making Modelling and Simulation

• Assessment of Social Risk and Impacts

• Intrusions and Mismanagement

Development and Simulation of

Autonomous Artificial Intelligent Organizations embedded in Complex Human-Technology Systems.

© Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

About Strategy of Socio-Cognitive Engineering

Socio-Cognitive Engineering takes under consideration the interests and points of view of:

citizens, employers, managers, owners & politicians

SCE Integrated Strategy is human-centered and technology-based

Identification of the System of Interest and

its contexts

System Validation and Design of self-

regulation Management

Strategy

© Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.it Adam M. Gadomski,

27/09/2003

Design of System Modification

SOCIO-COGNITIVE ENGINEERING Integrated Approach

© Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

Organizational Barrier

Technology Barrier

Knowledge Barrier

Cognitive Barrier

Cultural Barrier

Technology is nothing without Competences

Competences are nothing without Motivation- Management

Management is inefficient under not adequate Organizational Constrains.

All above are nothing if Socio-Cultural Context are neglected.

Complexity Domains: Sustainable Development Strategic Factors (Application of the TOGA Methodology covers here computational

modelling task)

SCE: Problem of Real-word Complexity



Different Interrelations Different

Methods

Different Perspectives

Different Study Directions

Different Dependences

All in Human-Technology Systems is Complex



Domain Tools: Conceptualization,Methods, Methodologies Management

Complex Activites

Complex Context

Complex

Models of Socio-Cognitive Systems

DOMAIN

Complex

Complex

TOOLS

MANAGEMENT

About SCE Complexity



HID

Complexity in SCE is not only a physical complexity but it includes complexity of mental processes and actions of an intelligent entity.

SCE complexity includes new attributes, such as :

Vagueness, Uncertainty Conflicts, Incomplete knowledge, Variable access to information, Emotions, Irrationality, Ethical preferences, Organizational & Socio-cultural factors.

All of them influence Decisional Processes

SOCIO-COGNITIVE ENGINEERING: Objectives

© Copyuright: High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

Numerous improvements of real Socio-Cognitive Systems (SCS)

on the levels of efficacy of and interactions between their components ( defined before).

Examples of problems:

- Interaction between individuals and always more complex information and business society,

- Efficiency and “life cycle” of human organizations,

- Relation between decision-making and organization structures

- Diagnosis of pathologies of human organizations

- Individual Interest and Organization Interest impacts

- Strategies of the development: democratic, centralized

- Technological Support and Intelligent Artifacts

SOCIO-COGNITIVE ENGINEERING for LCCIs (Large Complex Critical Infrastructures)

Socio-Cognitive Engineering takes under consideration the interests and points of view of owners, operators and customers of LCCIs :

+ LCCIs customers need the reliability and continuous providing of the services as long as possible and at low cost as possible.

+ LCCIs operators wish to be well informed about the infrastructure state and require its efficient management to satisfy customers expectations + LCCIs owners are focused on the socio-economic aspects of LCCIs.

ENEA’s Competences

Modelling Metodology

TOGATOGA

User & Decision-Maker Models & Architecture

Intelligent Organisation Modelling & Simulation

© Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.it Adam M. Gadomski, 27/09/2003

About Methodology

Top-down Object-Based Goal-oriented Approach (TOGA)

TOGA is goal-oriented complex-knowledge ordering computational tool.

It assumes the top-down observation metaphor, to see complex problems from a bird eye’s view; this means to first identify a problem’s most general context constraints which remain always true and mandatory for every successive level of its specification (“fleshing out”).

It is based on formal step-by-step decomposition of the relation:

Intelligent Entity Environment

© Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

How is possible to cope with so complex domain and objectives?

SCE has to use new thinking methods TOGA METHODS

The methods are divided on:

1. New Methodology/method of Cooperation between a SCE project partners

2. New Methodology/method for Objectives Achieving,

where the Cooperation Method is focused only on the efficacy of the realization of Objectives Achieving Methodology.

They both, in different proportions, are based on parallel, top-down and goal-oriented application of main paradigms of physics, systemics, cognitive and social sciences related to a generic intelligence. The meta-theoretical approach TOGA is assumed as a initial methodological and ontological framework. [ see References].

Examples

The top methodology includes in parallel, top-down goal-oriented tools development and their subsequent applications.


SCE utility

Examples of human/organizational errors


• US Blackout 2003

“The initiating events appear to have happened under the lazy eyes of a mismanaged utility, but underlying conditions made a massive U.S. power failure almost inevitable”

[IEEE Spectrum, 23 Sep.2003, Special Report.]

• Italia Energetic Blackout 2003.

• Cernobyl Nuclear Disaster, Apr. 26, 1986.

•…

• ENEA commissioning, Italy, 2002

SOCIO-COGNITIVE ENGINEERING (SCE): Humans Modelling


Human ERRORs: Not proper or not sufficient Information

Lack or not proper Importance Scale (Preferences, risk ass.)

Not proper or not sufficient instructions, procedures (Knowledge)

Wrong Cognitive and Organizational Factors (Motivations).

Models are Knowledge

Problem Specifications are: Requested & Modified

Information

Motivations create proper Preferences which activate adequate Knowledge

Application of TOGA (Top-down Object-based Goal-

oriented Approach)

Modelling Frameworks

IPK Computational Model (Information, Preferences, Knowledge)

I

KP

Disaster Managers: simple model example

Real EmergencyDomain

Agent 1

Agent 2

Agent 3

Agent N

I2

PK

In

P C

I1

P

K

I3

P

K

Infrastructure Network

. . . .I – information system

P – preferences system

K – knowledge system

Agent Manager

I

P

K

Example

Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

Many places for human and organizational errors can be evidenced.

SCE perspective on a Large Research Center (LRC)

• Research Paradigms System

• Research Means

• Support Technological Means

• Research Results/Products

• Socio-Business Laws

• Socio-Cognitive Context

• Human components

• Technological components

• Informational components

• Economical components

• Political components

Example


Factors: Components:

Top-down Identification

it is necessary to see how a decision-maker sees his domain of activity.

In general, from socio-cognitive perspective:

SCE: Large Research Center (LRC) Example


Competences are LRC’s Knowledge

Project Specifications are: Requested & Produced

Information

Motivations create proper Preferences which activate adequate Competences

Application of LRC’s

Competences IPK Computational Model

LRC’s Competences are useful if and only if the motivations of human Intelligent Agents will be developed and properly managed.

Application of SCE Theorem to LRC (“light” version)

Human ERROR (on 1st metalevel): If motivation-management is not adequate then competences are not activated or corrupted.

SOCIO-COGNITIVE ENGINEERING: Intelligent Organization


TOGA theory framework

OrganizationMission/Fundation-Goal Products

Intelligent Organization is defined by reciprocally dependent roles of interacting/communicating intelligent subjects which should act in order to archive common goal ( usually defined in the organization statute ).

General Functional Frame

Organization is specified by the set of roles, its structure, decisional mechanisms and resources.

Dynamic Role model (computational)

Definitions according TOGA

Role (competences, duties, privileges )

Competences: what he/she/it is able to do, possessed models of the domain (knowledge)

Duties: responsibility, tasks and requested preferences

Privileges: Access to the information. It produces conceptual images of the domain. Access to execution tools (information).

Every role is specified by its own IPK Bases Set:

Information Bases – how situation looks, continuously updated

Preferences Bases – importance scales/relations, ethics rules

Knowledge Bases – required models & know how


Universal Management Paradigm (UMP)



HID

Pattern-based Structure: Subjective, Incremental, Recursive

MANAGERMANAGER

INFORMER EXECUTOR

information tasks

ADVISOR

expertises COOPERATINGMANAGER

cooperation

SUPERVISOR

tasks information

H-INTERFACE

IN/EXH-INTERFACE

Knowledge Preferences

UMP includes 6 canonical roles and their interrelations

Pathologies of Organizations: Examples

Every human-agent is in 3 roles together :

1. Organizational role – requested/defined by the structure (fixed)

2. Informal role – applied, structure independent (variable)

3. Personal/real role – really realized (variable)



HID

Conflicts of Roles

Conflict of Interests/Motivations

Differ Risk-Benefits relation for

Compromise, inefficient, risky decisions

Dynamics of roles creates lack of congruence between them & conflict of interests

Social interest

Organization interest

Personal interest

Decision-Making


New Information

Knowledge Base

Preferences Base

Decision-Making

No action/response

Meta-action/Pseudo-action

Action adequate to D-M’er role and situation

Definitions [TOGA]

Decision-making: an individual or group reasoning activity/process implied by the request/necessity of a choice caused by received information or task, or by delivered conclusion about possibility of risks/benefits. It is started when either choice criteria are unknown or alternatives are unknown and finished when choice is performed.

Action-oriented decision-making: it is a decisional process when alternatives represent possible actions in pre-chosen physical domain.

Mental decision-making: when the final choice refers not to actions but to conceptual objects related to a preselected domain of activity of intelligent agent.

Group decision-making: when responsibility for decision is allocated to a group of intelligent agents and is based on shared decision-making process.

Decision-Making (computational models)


Controlability & updating of Ethics concept

reasoning pathcriticalnode

alternatives

d-mdata decision

??

??

decision

Types of Proper and Pathological Decisions

Main classes: - meta-D-M , - pseudo D-M, - proper D-M.

Pathologies are related to:

- response on source type ( “safety” filters );

- response on subject ( lack of competences, emotions, out of Interest).

- response according domain-preferences (organizational role): proper D-M.

If D-M autonomy increases then: Efficacy of Control decreases & Importance of Ethics and personal motivation increases. This rule indicate importance of Motivation Management.

SCE Ontological Tools -TOGA



HID

TOGA provides tools which could be used for Identification/Specification of real-world problems:

Complex domain: SPG Modelling framework

Complex interventions: WAG Modelling framework

Risky decisions: Risk-based Reasoning Model

Intelligent entity modelling with Human Factors, such as:

Emotions

Irrationalities

Motivations

Fractal-like Multi- and Meta- Modeling,

and Simulations tools are required.

Technology support: IDSS

SOCIO-COGNITIVE ENGINEERING (SCE) :

Intelligent Supports

Copy rights High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 8/10/2003

Reinforcement of the LCCI network by

Internal Artificial Intelligent Agents Organization

Higher Infrastructure Network Autonomy

Reinforcement of Human Organization by

Intelligent Decision Support Agents’ Grid

Better Human Control and Supervision

Infrastructure Dependencies

Selected Infrastructure

IDSS: Intelligent Decision Support Systems


What is it ? “Software program that integrates human intellectual and computer capacities

to improve decision making quality, in semi-structured problems situations” [Keen, Scott-Morton, 1996]

Provides active, partially autonomous Decisional Aid which involve human-like computational intelligence.

Provides passive Informational Aid and Toolkits

IDSSIDSS

DSSDSS

When IDSS is important?

• amount of information necessary for the management is so large, or its time density is so high, that the probability of human errors under time constrains is not negligible.

• coping with unexpected situation requires remembering, mental elaboration and immediate application of complex professional knowledge, which if not properly used, causes fault decisions.

More information: http://erg4146.casaccia.enea.it

INTELLIGENT DECISION SUPPORT FOR RESEARCH MANAGEMENT


link to computer networks

MIND

Tasks

Strategic Activities

Information

Situation Assessment & Decision Making is based on:Information: DOMAIN status, Knowledge: rules, procedures, instructions,Preferences: role criteria, risk criteria, resources criteria,...

INTELLIGENTDECISIONSUPPORTSYSTEM

Strategic

Periodicalmonitoring

Continuousmonitoring

Financial &Decisionalrequests

Research Activities

Actions

Administrative Activities

EXAMPLE

Conclusions



HID

Nowadays SCE is a response on dramatically grown risk of negative consequences of Human Errors, it is inevitable tool of XXI Century.

- Complexity of problems requires new 3rd Generation Approaches, such as TOGA multi-factor problem representation and parallel modelling, and IDSS development.

- Key problems refer to the understanding and transparency of decision-making processes for their intelligent actors-contributors.

- Socio-Cognitive Engineering requires new specialists on organization, national and international levels.

- EU promotes assessment of possible socio-cognitive impacts, innovation governance and new updated roles for policymakers.

- EC coordinates cross-integrations of national initiatives with objective of parallel harmonic and sustainable development of science, technology and society.

The above mentioned tasks have to be supported by theoretical foundations and in consequence, by conscious, wise and socio-ethical responsible decision-making.

Conclusions

Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/


HID

Futurology: extrapolations

Extrapolation of the current trends in three basic macro-engineering domains. [US Sources, DARPA, Web, 2000]

0

100

200

300

400

500

19

00

19

25

19

50

19

75

20

00

20

25

20

50

Physics & Energy

Chemistry & Bioengin.

Social & KnowledgeEngin.

Future Grow in Arbitrary Units

Current name is Socio-Cognitive Engineering

References

Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/


HID

1 A.M. Gadomski , Lectures on Safety and Reliability of Human-Machine Systems. Materials of SA-EUNET EU Project, 1998.

2 A.M. Gadomski , SOPHOCLES Project – Cyber Virtual Enterprise for Complex Systems Engineering: Cognitive Intelligent Interactions Manager for Advanced e-Design, Transparent-sheets, 28/08/2001, ENEA. ITEA.

4 A.M.Gadomski. TOGA: A Methodological and Conceptual Pattern for modeling of Abstract Intelligent Agent.Proceedings of the "First International Round-Table on Abstract Intelligent Agent". A.M. Gadomski (editor), 25-27 Gen., Rome, 1993, Publisher ENEA, Feb.1994.

6. A.M.Gadomski, "The Nature of Intelligent Decision Support Systems". The key paper of the Workshop on "Intelligent Decision Support Systems for Emergency Management ", Halden, 20th-21st October, 1997.

7. A.M.Gadomski, S. Bologna, G.Di Costanzo, A.Perini, M. Schaerf. Towards Intelligent Decision Support Systems for Emergency Managers: The IDA Approach. International Journal of Risk Assessment and Management, 2001.

8. A.M.Gadomski, A.Straszak. Socio-Cognitive Engineering Paradigms for Business Intelligence Modelling: the TOGA conceptualization. Proceedings of the 5th Business

Information System International Conference– BIS 2002, Poznan, Poland, April 24-25, 2002.9. A.M.Gadomski, Socio-Cognitive Scenarios for Business Intelligence Reinforcement:

TOGA Approach, The paper preliminary accepted for publicatiin in "International Quarterly of Cognitive Science“, 2003.

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