SCEF International Workshop 30 Sep., 1 Oct. 2003, Rome Socio-Cognitive Engineering Foundations and Applications: from Humans to Nations from Humans to Nations ( an introduction ) Adam Maria Gadomski High-Intelligence & Decision Research Group, CAMO, ENEA & Sc. Board of ECONA, Italy © 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 erg4146.casaccia.enea.it/

SCEF-2003 International Workshop © 2003 Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID 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” © 2003 Adam Maria Gadomski, erg4146.casaccia.enea.it/ 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). © 2003 Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group

About “Human Errors” © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID Human error : Human action or inaction that can produce unintended results (*) or system failures (**). (*) [ISO/ ITC Information Technology Vocabulary,96] (**) [ NUREC-1624] Machine failures Human errors Reliability problems Safety problems Complex consequences interrelations [Gadomski, 2002 ]

Socio-Cognitive Engineering Context: 3 rd 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 3 rd generation of research, the integration of science and technology development should be seen as one parallel goal-driven incremental process. © Adam Maria Gadomski, erg4146.casaccia.enea.it/

About SCE Intervention Domain © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID Domain of SCE are systems/networks of interacting humans and human like intelligent entities. Intelligence-based systems We use an object-based framework for initial conceptualization of any - individuals - organizations - associations - communities - society - nations - s/h technologies Intelligent Web H HS H R 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 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, Author: Adam Maria Gadomski, 28/09/2003http://erg4146.casaccia.enea.it Technological Grid Human Errors Organisation Network Human component Production/Transmission /Control component of 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, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it

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, Adam M. Gadomski, 27/09/2003http://erg4146.casaccia.enea.it Design of System Modification

SOCIO-COGNITIVE ENGINEERING Integrated Approach © Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group Different Interrelations Different Methods Different Perspectives Different Study Directions Different Dependences

All in Human-Technology Systems is Complex © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group Domain Tools: Conceptualization,Methods, Methodologies ManagementComplex Activites Complex Context Complex Models of Socio- Cognitive Systems DOMAIN Complex TOOLS MANAGEMENT

About SCE Complexity © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group 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, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 MetodologyTOGA User & Decision-Maker Models & Architecture Intelligent Organisation Modelling & Simulation © Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, Adam M. Gadomski, 27/09/2003http://erg4146.casaccia.enea.it

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

SCE utility Examples of human/organizational errors © Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 Cernobyl Nuclear Disaster, Apr. 26, … ENEA commissioning, Italy, 2002

SOCIO-COGNITIVE ENGINEERING (SCE): Humans Modelling © Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 K P

Disaster Managers: simple model example Real Emergency Domain Agent 1 Agent 2 Agent 3 Agent N I2I2 P K InIn P C I1I1 P K I3I3 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, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it TOGA theory framework Organization Mission/Fundation-GoalProducts 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 Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it

Universal Management Paradigm (UMP) © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID Pattern-based Structure: Subjective, Incremental, Recursive MANAGER INFORMER EXECUTOR information tasks ADVISOR expertises COOPERATING MANAGER cooperation SUPERVISOR tasks information H-INTERFACE IN/EX H -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) © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group 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 © Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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) © Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it Controlability & updating of Ethics concept reasoning path critical node alternatives d-m datadecision ? ? 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 © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group 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, Adam M. Gadomski, 8/10/2003http://erg4146.casaccia.enea.it 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 Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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 IDSS DSS 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:

INTELLIGENT DECISION SUPPORT FOR RESEARCH MANAGEMENT © Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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,... INTELLIGENT DECISION SUPPORT SYSTEM Strategic Periodical monitoring Continuous monitoring Financial & Decisional requests Research Activities Actions Administrative Activities EXAMPLE

Conclusions © Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group 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 3 rd 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, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID Futurology: extrapolations Extrapolation of the current trends in three basic macro-engineering domains. [US Sources, DARPA, Web, 2000] Future Grow in Arbitrary Units Current name is Socio- Cognitive Engineering

References Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID 1A.M. Gadomski, Lectures on Safety and Reliability of Human-Machine Systems. Materials of SA-EUNET EU Project, 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), Gen., Rome, 1993, Publisher ENEA, Feb 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, 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, 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, A.M.Gadomski, Socio-Cognitive Scenarios for Business Intelligence Reinforcement: TOGA Approach, The paper preliminary accepted for publicatiin in "International Quarterly of Cognitive Science“, For more information see :