Supporting public decision making in policy deliberations: An ontological approach

This is the post-print version of the Paper. The official published version can be accessed from the link below - Copyright @ 2011 SpringerSupporting public decision making in policy deliberations has been a key objective of eParticipation which is an emerging area of eGovernment. EParticipation aims to enhance citizen involvement in public governance activities through the use of information and communication technologies. An innovative approach towards this objective is exploiting the potentials of semantic web technologies centred on conceptual knowledge models in the form of ontologies. Ontologies are generally defined as explicit human and computer shared views on the world of particular domains. In this paper, the potentials and benefits of using ontologies for policy deliberation processes are discussed. Previous work is then extended and synthesised to develop a deliberation ontology. The ontology aims to define the necessary semantics in order to structure and interrelate the stages and various activities of deliberation processes with legal information, participant stakeholders and their associated arguments. The practical implications of the proposed framework are illustrated.This work is funded by the European Commission under the 2006/1 eParticipation call

TRANSFORMING GOVERNMENT AGENCIES’ APPROACH TO EPARTICIPATION THROUGH EFFICIENT EXPLOITATION OF SOCIAL MEDIA

Government agencies are making considerable investments for exploiting the capabilities offered by ICT, and especially the Internet, to increase citizens’ engagement in their decision and policy making processes. However, this first generation of e-participation has been characterised by limited usage of the ‘official’ e-consultation spaces of government agencies by the citizens. The emergence of Web 2.0 social media offers big opportunities for overcoming this problem, and proceeding to a second generation of broader, deeper and more advanced e-participation. This paper presents a methodology for the efficient exploitation of Web 2.0 social media by government agencies in order to broaden and enhance e-participation. It is based on a central platform which enables posting content and deploying micro web applications (‘Policy Gadgets’-Padgets) to multiple popular Web 2.0 social media, and also collecting users’ interactions with them (e.g. views, comments, ratings) in an efficient manner using their application programming interfaces (API). These interactions’ data undergo various levels of processing, such as calculation of useful analytics, opinion mining and simulation modelling, in order to provide effective support to public decision and policy makers. The proposed methodology allows government agencies to adopt advanced and highly effective ‘hybrid’ e-participation approaches

Reflective Artificial Intelligence

As Artificial Intelligence (AI) technology advances, we increasingly delegate mental tasks to machines. However, today's AI systems usually do these tasks with an unusual imbalance of insight and understanding: new, deeper insights are present, yet many important qualities that a human mind would have previously brought to the activity are utterly absent. Therefore, it is crucial to ask which features of minds have we replicated, which are missing, and if that matters. One core feature that humans bring to tasks, when dealing with the ambiguity, emergent knowledge, and social context presented by the world, is reflection. Yet this capability is completely missing from current mainstream AI. In this paper we ask what reflective AI might look like. Then, drawing on notions of reflection in complex systems, cognitive science, and agents, we sketch an architecture for reflective AI agents, and highlight ways forward

Linked democracy : foundations, tools, and applications

Chapter 1Introduction to Linked DataAbstractThis chapter presents Linked Data, a new form of distributed data on theweb which is especially suitable to be manipulated by machines and to shareknowledge. By adopting the linked data publication paradigm, anybody can publishdata on the web, relate it to data resources published by others and run artificialintelligence algorithms in a smooth manner. Open linked data resources maydemocratize the future access to knowledge by the mass of internet users, eitherdirectly or mediated through algorithms. Governments have enthusiasticallyadopted these ideas, which is in harmony with the broader open data movement

Towards a global participatory platform: Democratising open data, complexity science and collective intelligence

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac

The Future of eGovernment : An Exploration of ICT-driven Models of eGovernment for the EU in 2020

This report aims to describe how ICT can enable and shape future models of eGovernment. It summarizes the results of a research project, carried out by TNO and DTI on behalf of IPTS, based on desk research, expert interviews and a scenario-building exercise. It first identifies seven "hotspots" where ICT has a key impact on specific government tasks. It then analyzes these impacts under different possible future scenarios, in order to assess their robustness and the different implications for future models of eGovernment. It finally proposes a new measurement framework suitable for these future models, and outlines the key research challenges and policy options that emerge from this analysis.JRC.J.4-Information Societ

Linked Democracy

This open access book shows the factors linking information flow, social intelligence, rights management and modelling with epistemic democracy, offering licensed linked data along with information about the rights involved. This model of democracy for the web of data brings new challenges for the social organisation of knowledge, collective innovation, and the coordination of actions. Licensed linked data, licensed linguistic linked data, right expression languages, semantic web regulatory models, electronic institutions, artificial socio-cognitive systems are examples of regulatory and institutional design (regulations by design). The web has been massively populated with both data and services, and semantically structured data, the linked data cloud, facilitates and fosters human-machine interaction. Linked data aims to create ecosystems to make it possible to browse, discover, exploit and reuse data sets for applications. Rights Expression Languages semi-automatically regulate the use and reuse of content. ; Links information flow, social intelligence, rights management, and modelling with epistemic democracy Presents examples of regulatory and institutional desig

Computational Persuasion using Chatbots based on Crowdsourced Argument Graphs & Concerns

As computing becomes involved in every sphere of life, so too is persuasion a target for applying computer-based solutions. Conversational agents, also known as chatbots, are versatile tools that have the potential of being used as agents in dialogical argumentation systems where the chatbot acts as the persuader and the human agent as the persuadee and thereby offer a costeffective and scalable alternative to in-person consultations To allow the user to type his or her argument in free-text input (as opposed to selecting arguments from a menu) the chatbot needs to be able to (1) “understand” the user’s concern he or she is raising in their argument and (2) give an appropriate counterargument that addresses the user’s concern. In this thesis I describe how to (1) acquire arguments for the construction of the chatbot’s knowledge base with the help of crowdsourcing, (2) how to automatically identify the concerns that arguments address, and (3) how to construct the chatbot’s knowledge base in the form of an argument graph that can be used during persuasive dialogues with users. I evaluated my methods in four case studies that covered several domains (physical activity, meat consumption, UK University Fees and COVID-19 vaccination). In each case study I implemented a chatbot that engaged in argumentative dialogues with participants and measured the participants’ change of stance before and after engaging in a chat with the bot. In all four case studies the chatbot showed statistically significant success persuading people to either consider changing their behaviour or to change their stance