The creators of technical infrastructure are under social and legal pressure to comply with expectations that can be difficult to translate into computational and business logics. The dissertation presented in this talk bridges this gap through three projects that focus on privacy engineering, information security, and data economics, respectively. These projects culminate in a new formal method for evaluating the strategic and tactical value of data. This method relies on a core theoretical contribution building on the work of Shannon, Dretske, Pearl, Koller, and Nissenbaum: a definition of information flow as a channel situated in a context of causal relations.
Defining privacy and related notions such as Personal Identifiable Information (PII) is a central notion in computer science and other fields. The theoretical, technological, and application aspects of PII require a framework that provides an overview and systematic structure for the discipline’s topics. This paper develops a foundation for representing information privacy. It introduces a coherent conceptualization of the privacy senses built upon diagrammatic representation. A new framework is presented based on a flow-based model that includes generic operations performed on PII.
Ontology engineering, along with semantic Web technologies, allow the semantic development and modeling of the operational flow required for blockchain design. The semantic Web, in accordance with W3C, "provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries" and can be seen as an integrator for various content, applications and information systems. The most widely used blockchain modelling system, by abstract representation, description and definition of structure, processes, information and resources, is the enterprises modelling. Enterprise modelling uses domain ontologies by model representation languages.
DOI: 10.13140/RG.2.2.19062.24642
Big Data can generate, through inferences, new knowledge and perspectives. The paradigm that results from using Big Data creates new opportunities. Big Data has great influence at the governmental level, positively affecting society. These systems can be made more efficient by applying transparency and open governance policies, such as Open Data. After developing predictive models for target audience behavior, Big Data can be used to generate early warnings for various situations. There is thus a positive feedback between research and practice, with rapid discoveries taken from practice.
DOI: 10.13140/RG.2.2.14677.17120
The LTCI* is a laboratory of Télécom ParisTech (Institut Mines-Télécom, IMT). Established in 1982, LTCI is characterized by its broad coverage of the field of information and communication science and technology (ICT). Its research activities range from the hardware layer (electronics, opto-electronics, system on chip, antennae, microwaves…) to the software layer (systems, algorithms, protocols…). They encompass studies on different kinds of data (audio, video, images, semi-structured data and web content) as well as works on network performance and services, or quantum cryptography issues.
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
Presentation given at the HEA Social Sciences learning and teaching summit 'Exploring the implications of ‘the era of big data’ for learning and teaching'.
A blog post outlining the issues discussed at the summit is available via: http://bit.ly/1lCBUIB
Defining privacy and related notions such as Personal Identifiable Information (PII) is a central notion in computer science and other fields. The theoretical, technological, and application aspects of PII require a framework that provides an overview and systematic structure for the discipline’s topics. This paper develops a foundation for representing information privacy. It introduces a coherent conceptualization of the privacy senses built upon diagrammatic representation. A new framework is presented based on a flow-based model that includes generic operations performed on PII.
Ontology engineering, along with semantic Web technologies, allow the semantic development and modeling of the operational flow required for blockchain design. The semantic Web, in accordance with W3C, "provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries" and can be seen as an integrator for various content, applications and information systems. The most widely used blockchain modelling system, by abstract representation, description and definition of structure, processes, information and resources, is the enterprises modelling. Enterprise modelling uses domain ontologies by model representation languages.
DOI: 10.13140/RG.2.2.19062.24642
Big Data can generate, through inferences, new knowledge and perspectives. The paradigm that results from using Big Data creates new opportunities. Big Data has great influence at the governmental level, positively affecting society. These systems can be made more efficient by applying transparency and open governance policies, such as Open Data. After developing predictive models for target audience behavior, Big Data can be used to generate early warnings for various situations. There is thus a positive feedback between research and practice, with rapid discoveries taken from practice.
DOI: 10.13140/RG.2.2.14677.17120
The LTCI* is a laboratory of Télécom ParisTech (Institut Mines-Télécom, IMT). Established in 1982, LTCI is characterized by its broad coverage of the field of information and communication science and technology (ICT). Its research activities range from the hardware layer (electronics, opto-electronics, system on chip, antennae, microwaves…) to the software layer (systems, algorithms, protocols…). They encompass studies on different kinds of data (audio, video, images, semi-structured data and web content) as well as works on network performance and services, or quantum cryptography issues.
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
Presentation given at the HEA Social Sciences learning and teaching summit 'Exploring the implications of ‘the era of big data’ for learning and teaching'.
A blog post outlining the issues discussed at the summit is available via: http://bit.ly/1lCBUIB
Knowledge Engineering and Intelligence GatheringNicolae Sfetcu
A process of intelligence gathering begins when a user enters a query into the system. Several objects can match the result of a query with different degrees of relevance. Most systems estimate a numeric value about how well each object matches the query and classifies objects according to this value. Many researches have focused on practices of intelligence gathering. In knowledge engineering, knowledge gathering consists in fiding it from structured and unstructured sources in a way that must represent knowledge in a way that facilitates inference.
DOI: 10.13140/RG.2.2.32191.15527
Dynamic IT Values and Relationships: A Sociomaterial PerspectiveLeon Dohmen
Management scholars are criticized for ignorance and the wrong approach when studying the impact of technology in organizational life. Impact of technology in this paper is interpreted as IT values created or achieved from equivalent and contingent interaction between human (people) and non-human agents (technology, organization). Researchers and theorists propose to include a sociomaterial perspective and to develop general and broader, empirical based patterns across different contexts. Based on a literature review containing publications of theoretical considerations and empirical research this paper introduces a first general and sociomaterial based overview and taxonomy of IT values and their relations. IT values have a techno-economic or socio-techno orientation, are dynamically entangled and competitive, and complementary or overlapping. IT values are related to time, sponsor and, hierarchy. The identified IT values are ordered into a framework which has to be treated as a starting point to discuss further the definition, dynamics and relations of IT values from a sociomaterial perspective.
Uma visão geral sobre Reality Mining e pesquisas que foram e estão sendo desenvolvidas neste contexto. O conteúdo dos slides foram extraídos dos estudos e experimentos do MIT Media Lab (http://hd.media.mit.edu/) dirigido pelo Prof. Alex Pentland
Social network, social profiling, predictive policing. Current issues and fut...Federico Costantini
BIG DATA: NEW CHALLENGES FOR LAW AND ETHICS - International scientific conference, 22 - 23 May 2017 - Faculty of Law, University of Ljubljana
22 may 2017, Big Data Policing, Session 4, Seminar room 5, 16:00 – 17:30
1.- Preliminary clarifications on “Predictive Policing”
2.- Predictive policing with Social Network Analysis
3.- What kind of «evidence» does «predictive policing» bring to us?
4.- What kind of «law» does «prediction» justify?
5.- What kind of penalty does «predictive policing» legitimate?
6.- Current issues and future perspectives (to take away)
Cloud computing is revolutionising the way software services are procured and used by Government organizations and SMEs. Quantitative risk assessment of Cloud services is complex and undermined by specific security concerns regarding data confidentiality, integrity and availability. This study explores how the gap between the quantitative risk assessment and the perception of the risk can produce a bias in the decision-making process about Cloud computing adoption.
The risk perception of experts in Cloud computing (N=37) and laypeople (N=81) about ten Cloud computing services was investigated using the psychometric paradigm. Results suggest that the risk
perception of Cloud services can be represented by two components, called “dread risk” and “unknown risk”, which may explain up to 46% of the variance. Other factors influencing the risk perception were “perceived benefits”, “trust in regulatory authorities” and “technology attitude”.
This study suggests some implications that could support Government and non-Government organizations
in their strategies for Cloud computing adoption.
The generation of digital content has undergone a great increase in recent years due to the
development of new technologies that allow the creation of content quickly and easily. A further step in this
evolution is the generation of contents by automatic systems without human intervention. Thus, for decadesit has
been developing models for the Natural Language Generation (NLG) that allow the transformation of content to
the form of narratives. At present, there are several systems that enable the generation in text format. In this
paper we present the Narrative system, which allows the generation of text narratives from different sources,
and which are indistinguishable for user from those made by a human being.
A Dynamic Intelligent Policies Analysis Mechanism for Personal Data Processin...Konstantinos Demertzis
The evolution of the Internet of Things is significantly a
ected by legal restrictions imposed for personal data handling, such as the European General Data Protection Regulation (GDPR).
The main purpose of this regulation is to provide people in the digital age greater control over their personal data, with their freely given, specific, informed and unambiguous consent to collect and process the data concerning them. ADVOCATE is an advanced framework that fully complies with the requirements of GDPR, which, with the extensive use of blockchain and artificial intelligence technologies, aims to provide an environment that will support users in maintaining control of their personal data in the IoT ecosystem. This paper proposes and presents the Intelligent Policies Analysis Mechanism (IPAM) of the ADVOCATE framework, which, in an intelligent and fully automated manner, can identify conflicting rules or consents of the user, which may lead to the collection of personal data that can be used for profiling. In order to clearly identify and implement IPAM, the problem of recording user data from smart entertainment devices using Fuzzy Cognitive Maps (FCMs) was simulated. FCMs are an intelligent decision-making system that simulates the processes of a complex system, modeling the correlation base, knowing the behavioral and balance specialists of the system. Respectively, identifying conflicting rules that can lead to a profile, training is done using Extreme Learning Machines (ELMs), which are highly ecient neural systems of small and flexible architecture that can work optimally in complex environments.
Ijeee 7-11-privacy preserving distributed data mining with anonymous id assig...Kumar Goud
Privacy Preserving Distributed Data Mining with Anonymous ID Assignment
Chikkudu Chandrakanth Bheemari Santhoshkumar Tejavath Charan Singh
M.Tech Scholar(CSE) M.Tech Scholar(CSE) Assistant Professor, Dept of CSE
Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech
Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India
Abstract: This paper builds an algorithm for sharing simple integer data on top of secure sum data mining operation using Newton’s identities and Sturm’s theorem. Algorithm for anonymous sharing of private data among parties is developed. This assignment is anonymous in that the identities received are unknown to the other members of the group. Resistance to collusion among other members is verified in an information theoretic sense when private communication channels are used. This assignment of serial numbers allows more complex data to be shared and has applications to other problems in privacy preserving data mining, collision avoidance in communications and distributed database access. The new algorithms are built on top of a secure sum data mining operation using Newton’s identities and Sturm’s theorem. An algorithm for distributed solution of certain polynomials over finite fields enhances the scalability of the algorithms.
Key words: Cloud, Website, information sharing, DBMS, ID, ODBC, ASP.NET
.
Social navigation can be considered as an effective approach for supporting information management issues particularly privacy and security concern that prevail in the management of information systems. Any of these management information system security issues are a matter of critical acknowledgement for knowledge management systems as well. This paper outlines multiple privacy and security risks that can be applied to information systems in general. Including examples from different sectors such as health care, public information, and e-commerce, these management information issues provide an outline of the present situation. It also observes the key concerns of information system executive in these areas, highlighting the identification and explanation of regional differences and similarities. Selecting on a current issue in management information system the paper provides a detailed amount of knowledge on the possible reasons for the issues such as factors of economic development, technological status, and political/legal environment. The paper concludes by providing a revised framework for the management information issues formulated with effective literature searches. This is going to be effective enough for the studies that will more likely support such reasoning in the future.
The Justification for an Analysis of Stakeholder Input in the National Inform...Jeremy Pesner
This was a presentation I gave of my research in progress for my Masters Thesis. In it, I discuss the background of the National Information Infrastructure policy debates and the reasons I was examining this event two decades years later.
This is the presentation of the Juan Cruz-Benito’s PhD “On data-driven systems analyzing, supporting and enhancing users’ interaction and experience” that was defended on September 3rd, 2018 in the Faculty of Sciences at University of Salamanca Spain. This PhD was graded with the maximum qualification “Sobresaliente Cum Laude”.
Gordana Dodig-Crnkovic: Participating and Anticipating. Actors and Agents Net...José Nafría
Lecture belonging to the thematic axis: "Cosmological Perspectives of the Possible Worlds"
International Workshop on Social Networks: from communicating to solidary netwoks (an interdisciplinary Approach), Sierra Pambley, León, Spain, Septiembre de 2013
http://primer.unileon.es/eventos/RS2013
Autonomic and cognitive architectures for the Internet of Things, Claudio Sav...Universita della Calabria,
Slides related to the conference paper Autonomic and cognitive architectures for the Internet of Things, Claudio Savaglio and Giancarlo Fortino, IDCS2015. Slide author: Claudio Savaglio
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a “realistic” network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition,countermeasures to cloud security breaches are presented.
Matching Uses and Protections for Government Data Releases: Presentation at t...Micah Altman
In the work included below, and presented at the Simons Institute, we describe work-in progress that aims to align emerging methods of data protections with research uses.
ABSTRACT : Computational social science (CSS) is an academic discipline that combines the traditional social sciences with computer science. While social scientists provide research questions, data sources, and acquisition methods, computer scientists contribute mathematical models and computational tools. CSS uses computationally methods and statistical tools to analyze and model social phenomena, social structures, and human social behavior. The purpose of this paper is to provide a brief introduction to computational social science.
Key Words: computational social science, social-computational systems, social simulation models, agent-based models
NG2S: A Study of Pro-Environmental Tipping Point via ABMsKan Yuenyong
A study of tipping point: much less is known about the most efficient ways to reach such transitions or how self-reinforcing systemic transformations might be instigated through policy. We employ an agent-based model to study the emergence of social tipping points through various feedback loops that have been previously identified to constitute an ecological approach to human behavior. Our model suggests that even a linear introduction of pro-environmental affordances (action opportunities) to a social system can have non-linear positive effects on the emergence of collective pro-environmental behavior patterns.
Knowledge Engineering and Intelligence GatheringNicolae Sfetcu
A process of intelligence gathering begins when a user enters a query into the system. Several objects can match the result of a query with different degrees of relevance. Most systems estimate a numeric value about how well each object matches the query and classifies objects according to this value. Many researches have focused on practices of intelligence gathering. In knowledge engineering, knowledge gathering consists in fiding it from structured and unstructured sources in a way that must represent knowledge in a way that facilitates inference.
DOI: 10.13140/RG.2.2.32191.15527
Dynamic IT Values and Relationships: A Sociomaterial PerspectiveLeon Dohmen
Management scholars are criticized for ignorance and the wrong approach when studying the impact of technology in organizational life. Impact of technology in this paper is interpreted as IT values created or achieved from equivalent and contingent interaction between human (people) and non-human agents (technology, organization). Researchers and theorists propose to include a sociomaterial perspective and to develop general and broader, empirical based patterns across different contexts. Based on a literature review containing publications of theoretical considerations and empirical research this paper introduces a first general and sociomaterial based overview and taxonomy of IT values and their relations. IT values have a techno-economic or socio-techno orientation, are dynamically entangled and competitive, and complementary or overlapping. IT values are related to time, sponsor and, hierarchy. The identified IT values are ordered into a framework which has to be treated as a starting point to discuss further the definition, dynamics and relations of IT values from a sociomaterial perspective.
Uma visão geral sobre Reality Mining e pesquisas que foram e estão sendo desenvolvidas neste contexto. O conteúdo dos slides foram extraídos dos estudos e experimentos do MIT Media Lab (http://hd.media.mit.edu/) dirigido pelo Prof. Alex Pentland
Social network, social profiling, predictive policing. Current issues and fut...Federico Costantini
BIG DATA: NEW CHALLENGES FOR LAW AND ETHICS - International scientific conference, 22 - 23 May 2017 - Faculty of Law, University of Ljubljana
22 may 2017, Big Data Policing, Session 4, Seminar room 5, 16:00 – 17:30
1.- Preliminary clarifications on “Predictive Policing”
2.- Predictive policing with Social Network Analysis
3.- What kind of «evidence» does «predictive policing» bring to us?
4.- What kind of «law» does «prediction» justify?
5.- What kind of penalty does «predictive policing» legitimate?
6.- Current issues and future perspectives (to take away)
Cloud computing is revolutionising the way software services are procured and used by Government organizations and SMEs. Quantitative risk assessment of Cloud services is complex and undermined by specific security concerns regarding data confidentiality, integrity and availability. This study explores how the gap between the quantitative risk assessment and the perception of the risk can produce a bias in the decision-making process about Cloud computing adoption.
The risk perception of experts in Cloud computing (N=37) and laypeople (N=81) about ten Cloud computing services was investigated using the psychometric paradigm. Results suggest that the risk
perception of Cloud services can be represented by two components, called “dread risk” and “unknown risk”, which may explain up to 46% of the variance. Other factors influencing the risk perception were “perceived benefits”, “trust in regulatory authorities” and “technology attitude”.
This study suggests some implications that could support Government and non-Government organizations
in their strategies for Cloud computing adoption.
The generation of digital content has undergone a great increase in recent years due to the
development of new technologies that allow the creation of content quickly and easily. A further step in this
evolution is the generation of contents by automatic systems without human intervention. Thus, for decadesit has
been developing models for the Natural Language Generation (NLG) that allow the transformation of content to
the form of narratives. At present, there are several systems that enable the generation in text format. In this
paper we present the Narrative system, which allows the generation of text narratives from different sources,
and which are indistinguishable for user from those made by a human being.
A Dynamic Intelligent Policies Analysis Mechanism for Personal Data Processin...Konstantinos Demertzis
The evolution of the Internet of Things is significantly a
ected by legal restrictions imposed for personal data handling, such as the European General Data Protection Regulation (GDPR).
The main purpose of this regulation is to provide people in the digital age greater control over their personal data, with their freely given, specific, informed and unambiguous consent to collect and process the data concerning them. ADVOCATE is an advanced framework that fully complies with the requirements of GDPR, which, with the extensive use of blockchain and artificial intelligence technologies, aims to provide an environment that will support users in maintaining control of their personal data in the IoT ecosystem. This paper proposes and presents the Intelligent Policies Analysis Mechanism (IPAM) of the ADVOCATE framework, which, in an intelligent and fully automated manner, can identify conflicting rules or consents of the user, which may lead to the collection of personal data that can be used for profiling. In order to clearly identify and implement IPAM, the problem of recording user data from smart entertainment devices using Fuzzy Cognitive Maps (FCMs) was simulated. FCMs are an intelligent decision-making system that simulates the processes of a complex system, modeling the correlation base, knowing the behavioral and balance specialists of the system. Respectively, identifying conflicting rules that can lead to a profile, training is done using Extreme Learning Machines (ELMs), which are highly ecient neural systems of small and flexible architecture that can work optimally in complex environments.
Ijeee 7-11-privacy preserving distributed data mining with anonymous id assig...Kumar Goud
Privacy Preserving Distributed Data Mining with Anonymous ID Assignment
Chikkudu Chandrakanth Bheemari Santhoshkumar Tejavath Charan Singh
M.Tech Scholar(CSE) M.Tech Scholar(CSE) Assistant Professor, Dept of CSE
Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech
Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India
Abstract: This paper builds an algorithm for sharing simple integer data on top of secure sum data mining operation using Newton’s identities and Sturm’s theorem. Algorithm for anonymous sharing of private data among parties is developed. This assignment is anonymous in that the identities received are unknown to the other members of the group. Resistance to collusion among other members is verified in an information theoretic sense when private communication channels are used. This assignment of serial numbers allows more complex data to be shared and has applications to other problems in privacy preserving data mining, collision avoidance in communications and distributed database access. The new algorithms are built on top of a secure sum data mining operation using Newton’s identities and Sturm’s theorem. An algorithm for distributed solution of certain polynomials over finite fields enhances the scalability of the algorithms.
Key words: Cloud, Website, information sharing, DBMS, ID, ODBC, ASP.NET
.
Social navigation can be considered as an effective approach for supporting information management issues particularly privacy and security concern that prevail in the management of information systems. Any of these management information system security issues are a matter of critical acknowledgement for knowledge management systems as well. This paper outlines multiple privacy and security risks that can be applied to information systems in general. Including examples from different sectors such as health care, public information, and e-commerce, these management information issues provide an outline of the present situation. It also observes the key concerns of information system executive in these areas, highlighting the identification and explanation of regional differences and similarities. Selecting on a current issue in management information system the paper provides a detailed amount of knowledge on the possible reasons for the issues such as factors of economic development, technological status, and political/legal environment. The paper concludes by providing a revised framework for the management information issues formulated with effective literature searches. This is going to be effective enough for the studies that will more likely support such reasoning in the future.
The Justification for an Analysis of Stakeholder Input in the National Inform...Jeremy Pesner
This was a presentation I gave of my research in progress for my Masters Thesis. In it, I discuss the background of the National Information Infrastructure policy debates and the reasons I was examining this event two decades years later.
This is the presentation of the Juan Cruz-Benito’s PhD “On data-driven systems analyzing, supporting and enhancing users’ interaction and experience” that was defended on September 3rd, 2018 in the Faculty of Sciences at University of Salamanca Spain. This PhD was graded with the maximum qualification “Sobresaliente Cum Laude”.
Gordana Dodig-Crnkovic: Participating and Anticipating. Actors and Agents Net...José Nafría
Lecture belonging to the thematic axis: "Cosmological Perspectives of the Possible Worlds"
International Workshop on Social Networks: from communicating to solidary netwoks (an interdisciplinary Approach), Sierra Pambley, León, Spain, Septiembre de 2013
http://primer.unileon.es/eventos/RS2013
Autonomic and cognitive architectures for the Internet of Things, Claudio Sav...Universita della Calabria,
Slides related to the conference paper Autonomic and cognitive architectures for the Internet of Things, Claudio Savaglio and Giancarlo Fortino, IDCS2015. Slide author: Claudio Savaglio
Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a “realistic” network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition,countermeasures to cloud security breaches are presented.
Matching Uses and Protections for Government Data Releases: Presentation at t...Micah Altman
In the work included below, and presented at the Simons Institute, we describe work-in progress that aims to align emerging methods of data protections with research uses.
ABSTRACT : Computational social science (CSS) is an academic discipline that combines the traditional social sciences with computer science. While social scientists provide research questions, data sources, and acquisition methods, computer scientists contribute mathematical models and computational tools. CSS uses computationally methods and statistical tools to analyze and model social phenomena, social structures, and human social behavior. The purpose of this paper is to provide a brief introduction to computational social science.
Key Words: computational social science, social-computational systems, social simulation models, agent-based models
NG2S: A Study of Pro-Environmental Tipping Point via ABMsKan Yuenyong
A study of tipping point: much less is known about the most efficient ways to reach such transitions or how self-reinforcing systemic transformations might be instigated through policy. We employ an agent-based model to study the emergence of social tipping points through various feedback loops that have been previously identified to constitute an ecological approach to human behavior. Our model suggests that even a linear introduction of pro-environmental affordances (action opportunities) to a social system can have non-linear positive effects on the emergence of collective pro-environmental behavior patterns.
Final Paper Draft Outline – Week 7 For the second to last.docxcharlottej5
Final Paper Draft Outline – Week 7
For the second to last homework, you need to submit an outline of your final paper. What does
that mean? You need to read the article “Writing for College: What is an Academic Paper” and
conceptualize what the paper assignment for this course is about:
https://depts.washington.edu/owrc/Handouts/What%20is%20an%20Academic%20Paper.pdf
Next, you need to read the “Final Paper Minimum Requirements” to get a sense of how you shall
start creating the paper. Think of a topic that you are interest the most – it can be a critical paper,
project, applicative hacks – and then apply the instructions from the first two sources indicated.
The draft outline needs to answer:
• what is your topic,
• what are your main sections in the paper,
• what are the preliminary sources you will use,
• how you plan to write in each of these sections/use the sources.
The APA, IEEE, or MLA is required for this assignment. Why? You can just use the same
document to proceed with actually writing the paper, project report, or the white paper of the
hack. You can find the formatting guidelines in the “Paper Guidelines” module in D2L.
Once you have finalized your homework, please take a look at the document named “How to
Read an Academic Paper” that is also attached together in the same D2L module as the other
two. Make sure you read it – it is an excellent and critical tool that you will need in reading the
academic sources you plan to build upon in your paper.
Risking Security: Policies and Paradoxes
of Cyberspace Security
Ronald J. Deibert
University of Toronto
and
Rafal Rohozinski
University of Toronto
Conceptualizations of cyberspace security can be divided into two related
dimensions, articulated as ‘‘risks’’: risks to the physical realm of computer
and communication technologies (risks to cyberspace); and risks that arise
from cyberspace and are facilitated or generated by its technologies, but
do not directly target the infrastructures per se (risks through cyberspace).
There is robust international consensus, growing communities of practice,
and an emerging normative regime around risks to cyberspace. This is less
the case when it comes to risks through cyberspace. While states do collabo-
rate around some policy areas, cooperation declines as the object of risk
becomes politically contestable and where national interests vary widely.
These include the nature of political opposition and the right to dissent
or protest, minority rights and independence movements, religious belief,
cultural values, or historical claims. The contrast between the domains has
led to contradictory tendencies and paradoxical outcomes.
Globalization is generating new security challenges. Modern societies confront a
myriad of risks that threaten economic prosperity, undermine the safety and
security of citizens, and cause significant disruption to society and politics. These
risks range from empowered and mili.
LEGISLATIVE COORDINATION AND CONCILIATIONS SCIENCE AND TECHNOLOGY OPTIONS ASS...Karlos Svoboda
Pathways towards responsible ICT Innovation
Policy Brief Abstract ICT has an immediate and broad impact on the lives of most individuals. Ethical scrutiny is not well established. Existing ethics review mechanisms are not suited for many of the ethical issues that ICT is likely to cause in the future. Europe has the unique opportunity to show international leadership by pointing the way to how human rights, ethical values and moral norms can be explicitly considered in technology development. The ETICA project (Ethical Issues of Emerging ICT Applications, GA 230318) provides the basis for a new enlightened approach to the development, governance and use of emerging ICT. MAY 2011 PE 460.346 EN
Tfsc disc 2014 si proposal (30 june2014)Han Woo PARK
Technological Forecasting and Social Change Special Issue
http://www.journals.elsevier.com/technological-forecasting-and-social-change/
Special issue title
Open (Big) Data as Social Change: Triple Helix Innovation toward Government 3.0
Associated conference
The 2nd Annual Asian Hub Conference on Triple Helix and Network Sciences (DISC 2014) on Data as Social Culture: Networked Innovation and Government 3.0, to be held on December 11-13, 2014, in Daegu and Gyeongbuk (Gyeongju), Rep. of Korea.
Call for Papers: http://www.slideshare.net/hanpark/disc-2014-cfp-v3
The conference is organized by Asia Triple Helix Society (ATHS). Point of contact: Secretary to Prof. Dr. Han Woo Park (info.disc2014@gmail.com), Department of Media & Communication, YeungNam University, 214-1, Dae-dong, Gyeongsan-si, Gyeongsangbuk-do, South Korea, Zip Code 712-749.
Associate Editors: Managing Guest Editors (MGE)
Wayne Weiai Xu, Doctoral Candidate, SUNY-Buffalo, USA, weiaixu@buffalo.edu
Dr. In Ho Cho, YeungNam University, Rep. of Korea, haihabacho@gmail.com
Important Dates
DISC 2014: 11 to 13 December 2014
Full paper submission: 1 March 2015
Review & Revision period: 1 September 2015
Online Publication: 1 December 2015
* We are also open to non-conference submissions to the special issue. However, the priority will be given to papers presented at the DISC 2014 and its associated seminars.
This paper discusses the several research methodologies that can
be used in Computer Science (CS) and Information Systems
(IS). The research methods vary according to the science
domain and project field. However a little of research
methodologies can be reasonable for Computer Science and
Information System.
Similar to Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data Economics (20)
I explore ways to combine complex network science with the Rubin model of conference inference. In broad strokes, I discuss the difference between exogenous shocks and endogenous process, and how granularity in time can be used to tease causality out of a complex system.
In networked publics, power based on network positionality replaces media power. How can we design networked publics to improve parity? I present @TheTweetserve, a prototype solution.
A presentation of the underlying motivations and institutional context behind GeoNode, some of its major design decisions, and unresolved challenges for its sustainability.
I gave this talk at UC Berkeley School of Information's research seminar on Information and Communication Technology for Development (ICTD).
Much of the material comes from an older presentation I wrote with Rolando Peñate.
This presentation introduces the philosophical field of epistemology and the problem of skepticism. It then outlines Fred Dretske's response to the problem. Lastly, it argues that Dretske's use of information reduces to Shannon's 'mutual information'.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data Economics
1. Context, Causality, and Information Flow:
Implications for Privacy Engineering, Security,
and Data Economics
A presentation of doctoral dissertation research by
Sebastian Benthall
UC Berkeley School of Information
2. Outline
● Motivation
● Overview of Projects
● Project #1: Contextual Integrity through the Lens of Computer Science
● Disciplinary Bridge
● Project #2: Origin Privacy: Causality and Data Protection
● Project #3: Data Games and the Value of Information
● Concluding remarks
THIS IS A FUN INTERACTIVE TALK:
An image slide means it is time to ask a question.
I’ll answer one question per picture.
15. Social Norms
Market
Law
Technology
Project #1
“Contextual Integrity
through the Lens of
Computer Science”
CS, Statistics, EE
Law Social Philosophy
Contextual Integrity
Economics
...a typical I School dissertation...
Surveys the use of Contextual Integrity, a theory of privacy norms, in Computer Science.
Identifies theoretical gaps in CI and opportunities for innovation in privacy CS.
16. Social Norms
Market
Law
Technology
Project #2
“Origin Privacy:
Causality and Data
Protection”
CS, Statistics, EE
Law Social Philosophy
Economics
...a typical I School dissertation...
Identifies a information flow restrictions in law based both on semantics and origin.
Resolves this ambiguity through theoretical contribution: situated information flow.
Shows application of this contribution to information security in embedded systems.
17. Social Norms
Market
Law
Technology
Project #3
“Data Games and the
Value of Information”
CS, Statistics, EE
Law Social Philosophy
Economics
...a typical I School dissertation...
Invents data economics to fill gap in economic theory.
Theoretical contribution: data games, mechanism design for information flow.
Answers: what is the value of information? Demonstrates with several examples.
21. Contextual Integrity through the Lens of computer science
Sebastian Benthall
Seda Gürses
Helen Nissenbaum
A presentation of S. Benthall, S. Gürses and H. Nissenbaum. Contextual Integrity through the Lens of Computer
Science. Foundations and Trends in Privacy and Security, vol. 2, no. 1, pp. 1–69, 2017
Included as Chapter 2 of Sebastian Benthall’s doctoral dissertation titled.
“Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data
Economics”
22. Project Goals
● Characterize different ways various CS efforts have interpreted and applied
Contextual Integrity (CI);
● Identify gaps in both contextual integrity and its technical projection that this body
of work reveals;
● Distill insights from these applications in order to facilitate future applications of
contextual integrity in privacy research and design.
“Making CI more actionable for computer science and computer scientists.”
23. Background: What is Contextual Integrity?
A social philosophy of privacy developed by Helen Nissenbaum.
● Privacy is appropriate information flow.
● Appropriateness depends on social context;
social contexts have information norms.
● Norms are adapted to societal values, contextual purposes, and individual ends.
● Norms are structured with five parameters:
○ (1) Sender, (2) Receiver, (3) Subject, (4) Attribute, (5) Transmission Principle
Example: In the health care context, there is a norm that when (1) a patient gives
information about (3) their (4) health to (2) a doctor, that information is treated
confidentially.
24. Background: Context in computing and policy
● Contextual Integrity:
○ Privacy as appropriate information flow according to contextual norms. First paper: 2004..
○ Uptake in computer science since 2006.
● Context in ubiquitous computing
○ An earlier computer science research tradition, pioneered by e.g. Dey in 2001 is also concerned
with privacy
○ “Context” refers to a situation: facts about the user, computer, environment. Location, identity,
state…
○ Dourish (2004) publishes a critique, arguing for interactional (not representational) context in
UbiComp.
● Context in policy
○ Excitement about privacy (FTC, White House, WEF) as respect for context motivates computer
science interest in Contextual Integrity...
○ … but within CS, multiple traditions are blended together.
25.
26. Study: research method
● Developed analytic template based on research questions.
● Searched for CS papers that claim to be using CI. (We found 20)
● Applied analytic template systematically to each paper.
● Used results to derive answers to each research question.
A systematic review of computer science literature using Contextual Integrity.
27. Study: research questions
● RQ1. For what kind of problems and solutions do computer scientists use CI?
○ Particular subfields of CS.
● RQ2. How have the authors dealt with the conceptual aspects of CI?
○ Social contexts, norms with specific parameters…
● RQ3. How have the authors dealt with the normative aspects of CI?
○ Norms are derived from social contexts, which are adaptations of a differentiated society.
● RQ4. Do the researchers expand on CI?
○ Where do CS researchers need to fill gaps or add to CI to make concrete systems work?
28. Results: RQ1 Architecture
CS researchers used CI across a few classes of technical architecture.
● User interfaces and experiences. These focus on an individual user’s activity
and preferences, rather than social norms.
● Infrastructure. Catering to a large set of users and diverse applications.
○ Social platforms. Technology that spans multiple social contexts.
○ Technical platforms. Technology that mediates many different other technologies. What about
the operators of these platforms?
○ Formal models. Frameworks to be used in design, but without implementation details.
● Decentralization. Decentralized architectures mirror complexity of society
itself. An interesting area for future research.
29. Findings: RQ1 Architecture
Theoretical Gaps:
- “Modular Contextual Integrity”,
faceting CI and giving guidelines
for design and research at specific
levels of the technical stack
- Specific guidance for
infrastructure design
Calls to Action:
- Be explicit about how system is
situated among other actors
(operators, moderators, etc.)
- Develop formal models that
connect user preferences with
contextual norms
30. Results: RQ2 What did they mean by context?
CS researchers had varying understandings of ‘context’’; e.g. sphere vs. situation.
Substantiality Abstract: Hospitals in general. Concrete: Mount Sinai Beth Israel hospital.
Domain Social: A classroom with a teacher and
students is a social context.
Technical: A language education mobile app.
Valence Normative: A conference Code of Conduct
is an account of norms inherent in a context.
Descriptive: A list of attendees, keynote
speakers, and program committee members
is a description of the context.
Stability
(Dourish, ‘04)
Representational: The Oval Office in the
White House is an easily represented
context..
Interactional: A flash mob is an interactional
context.
31. Findings: RQ2 Contexts
Theoretical Gaps:
- CI needs an account of how social
spheres connect to sociotechnical
situations
- What about interactional
contexts?
Calls to Action:
- Specifically address how ‘context’
is used, and when technology
bridges two or more meanings of
the term
- Detail flows of information to
third parties; what context is
that?
32. Results: RQ3 Source of Normativity
CI is specific about where norms come from: social adaptation to ends, purposes,
and values within differentiated spheres of society.
CS papers have not adopted this source of normativity entirely. Instead, they use:
● Compliance and Policy. System is designed to comply with existing laws and
policies.
● Threats. System is designed with a Threat Model, typical of security research.
● User preferences and expectations. Individual user preferences and/or
expectations solicited.
● Engagement. Users interact with system to determine norms dynamically.
33. Findings: RQ3 Normativity
Theoretical Gaps:
- Connect CI’s metaethical theory
with concrete sources of
normativity familiar to CS
- Spheres to threats?
- Spheres to user expectations?
- Spheres to the law?
Calls to Action:
- Measuring norms, not
expectations
- Supporting user engagement
around identifying norms
- Technical solutions for handling
conflicts over norms
34. Results: RQ4 Expanding CI
● Technological adaptation to changing social conditions.
● Technology operating in multiple contexts at once, or addressing context clash,
where activity in different contexts interact.
● Addressing the temporality and duration of information, and its effect on
privacy
● User decision making with respect to privacy and information flow controls.
35. Findings: RQ4 Expanding CI
Theoretical Gaps:
- Develop account of normative
change and adaptation
- Address the questions around
multiple interacting contexts
- Address time: duration of
information, forgetting, etc.
- What about user choice?
Calls to Action:
- More modeling CI from
information theory, information
flow security
- CI and differential privacy?
38. Bridge: Themes from Project #1
Contextual Integrity needs to be expanded...
● ...to account for social and technological platforms that span multiple social
spheres, perhaps by introducing an “operator” context.
● ...to account for more of the meanings of “context” that range from abstract
social spheres to concrete sociotechnical situations.
● ...for clarity on how social norms form to reflect ends, purposes, and values in
society, and the relationship between these norms and the law.
● ...to address the challenging cases where multiple social contexts collide or
clash.
39. What we get…
… life and technology make things
complicated.
Bridge: Dealing with context collisions
What society wants from privacy...
Professional Personal
Med Edu Fin
Professional Personal
Med
Edu
Fin
40. The problem with information semantics
Contextual Integrity says there are five parameters of an information norm:
Sender, Receiver, Subject, attribute, and Transmission Principle.
[Patient, Doctor, Patient, Health, Confidentiality]
But... information topics are indeterminate. E.g.:
41. What does information mean?
● In CI, information gets its meaning from its context: how actors in roles
normatively communicate with each other.
○ The meaning of information and the contextual practices are mutually constitutive.
● When information flows in a new way (between situations), that information
gets new meanings.
○ E.g. When your relatives see a Facebook post intended for friends, it gives them the opportunity
to make judgments about you that were not the intended meaning.
● Technical context collapse is challenging not because it violates norms, but
because it is beyond our social understanding but creates information flows
with new social meaning that may be disruptive to social life.
43. What does “information” mean?
According to Dretske (1981) (epistemology, philosopher of mind)
building on Shannon (1948), information is a naturalistic and causal
property:
Information that P is the message/signal needed for a suitably equipped
observer to learn P, due to the nomic associations of the signal with P.
Nomic means “law-like”, as in scientific law.
The red light carries the information that the train is coming because
(lawfully, regularly) the red is light if and only if the train is coming.
44. In the following projects we will update Dretske’s theory.
Using insights from statistics and computer science, we
will arrive at a specific formal concept of
situated information flow
for cross-disciplinary use.
45. Bayesian Networks
Bayesian Networks (BN) are a formalism for
representing the relationship between random events.
A BN has:
● A directed, acyclic graph of nodes, representing random variables, connected
by edges
● A conditional probability distribution (CPD) for each node, which is the
probability distribution of its random variables, conditional on its parent.
Together. these define a joint probability distribution over all the random variables,
with some important independence relations qualitatively inferable from the graph.
A
C
D
B E
46. What is information flow, really?
Pearl’s (2000) system for understanding causality is widely
acknowledged and applied in statistics, philosophy, machine learning,
cognitive psychology, social science research methods, …
Events are part of a causal
structure represented as a
directed acyclic graph.
This structure determines the
conditional dependency
of events on each other.
Recession Earthquake
Burglary
Alarm
47. What is information flow, really?
The alarm carries information about earthquakes, burglaries, and
recessions. (Topics are indeterminate).
In this model, the recession
and earthquakes are
conditionally independent.
I(Recession, Earthquake) = 0
(Carry no information
about each other;
have no mutual information.)
Recession Earthquake
Burglary
Alarm
48. What is information flow, really?
The alarm carries information about earthquakes, burglaries, and
recessions. (Topics are indeterminate).
In this model, the recession and earthquakes
are conditionally dependent
if we know the alarm has gone off. Recession Earthquake
Burglary
Alarm
49. Information flow: a unified model
1. Privacy is appropriate information flow.
(Nissenbaum)
2. Information flow is a message or signal from which
something can be learned because of nomic association.
(Dretske)
3. The nomic associations are the conditional
dependencies derived from causal structure. (Pearl)
The meaning of data is a function of the processes that
generated it, and their context.
51. Causality
What makes these causal models is Pearl’s do-calculus: an intervention on an event
severs the links from its parent nodes.
An intervention can made by anything exogenous to the model.
Recession Earthquake
Burglary
Alarm
do
52. Causality
“But this isn’t causality!
What about Rubin, treatment effects, randomized controlled experiments, ….”
- an economist in the audience
Pearlian causation fits how we experience and reason about causality (e.g., Sloman).
Interventionist causation has support from philosophers (e.g., Woodward).
It is compatible with other methods of causal inference and model fitting (e.g.,
Gelman).
It is used widely in social sciences like demography and sociology (e.g., Elwert).
It is the consensus view. We should use it!
56. Origin Privacy: Causality and Data Protection
Sebastian Benthall
Anupam Datta
Michael Tschantz
A technical report.
Included as Chapter 4 of Sebastian Benthall’s doctoral dissertation titled.
“Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data
Economics”
57. Origin Privacy: Highlights
● Policy motivations:
○ Origin and topic information flow restrictions in the law
○ Bounded information processing systems
● Use the theory of situated information flow
● Model a system embedded in its environment
● This uncovers an interesting class of security threats due to a confusion
between caused and embedded inputs.
(There’s a lot more in the chapter…)
58. Origin Privacy: Policy requirements: HIPAA
The HIPAA Privacy Rule defines psychotherapy notes as
notes recorded by a health care provider who is a mental health professional
documenting or analyzing the contents of … [a] counseling session
Psychotherapy notes are more protected than other protected health information,
intended only for use by the therapist.
These restrictions are tied to the provenance of the information: the counseling
session.
59. Origin Privacy: Policy requirements: GLBA
The Privacy Rule protects a consumer's "nonpublic personal information" (NPI).
● any information an individual gives you to get a financial product or service (e.g.,
name, address, income)
● any information you get about an individual from a transaction involving your
financial product(s) or service(s) (for example, the fact that an individual is your
consumer or customer),
● any information you get about an individual in connection with providing a financial
product or service (for example, information from court records or from a consumer
report).
There are origin requirements, but also more general subject requirements.
(from FTC.gov)
60. Claim: policies use origin and meaning based information flow restrictions in an
ambiguous way because:
(1) real information flow is situated
(2) the causal context determines:
- The origin
- The nomic associations (meaning)
Policy ambiguity problem solved!
Pregnancy
Purchases
Advertisements
61. Policy requirements: PCI DSS
“The PCI DSS security requirements apply to all system components included in or
connected to the cardholder data environment. The cardholder data environment
(CDE) is comprised of people, processes and technologies that store, process, or
transmit cardholder data or sensitive authentication data.”
PCI DSS determines the domain in which it applies in terms of the physical
connections between components.
Could PCI DSS be enforced or complied with if it applied to system components
unconnected from the CDE?
70. The point
● Probabilistic modeling of situated information flows can express both an
information processing system and its environment.
● Different security properties can be mapped onto this model and onto different
model conditions (interventions, observations)
● This gives us a fine-grained way to do compliance engineering.
73. The story so far...
● Social expectations of privacy may be expressed as norms of information flow
indexed to social spheres (Contextual Integrity)...
● … but our situation today is messy; our contexts collide because of our technical
infrastructure.
● Our complex situation means that we have lost control over what our
information means. Topics (part of the structure of norms) are indeterminate.
● Moving forward, we should scaffold our theory of privacy with situated
information flow, and build up to normative theory.
74. Data Games and the Value of Information
Goals (narrow version):
● Address the problem raised by Chapter 1 about how to model and design for
cross-context information flows in infrastructure…
● ...using the insights about situated information flow…
● ...to understand the economic impact of data protection laws.
76. U.S. Data Protection Laws
● Intellectual property laws
○ Since Feist v. Rural (1991), data (facts) are not protected by copyright.
○ Samuelson (2000) argues intellectual property won’t work for privacy because property is
alienable, but privacy rights aren’t.
● Confidentiality and sectoral privacy laws. HIPAA, GLBA, FERPA,
attorney-client privilege.
○ All tied to specific sectors or spheres.
○ They do reduce information flow outside of the situations where they apply.
○ But they do not regulate “the gaps”
● FTC notice-and-consent self-regulatory standard
○ Paradox: the more technically and legally detailed the notices, the more ignorant the consent!
○ Nobody thinks this is working.
77. E.U. General Data Protection Regulation
● It’s based on privacy rights. (Compare with IP)
○ Sort of like a property right, but different.
● Omnibus. It covers all the cases. (Compare with sectoral laws)
● New obligations protect the rights:
○ Data minimization says don’t keep or process data for no agreed upon reason.
○ Also some general exceptions to data protection, which may erode the protections...
● Consent is given to particular purposes of use.
○ A purpose is less complicated than legalease or technical data flow, so better notices?
Purpose-binding in the GDPR is reminiscent of Contextual Integrity, but is based on
rights not norms.
78. Law and economics for data?
● There is an important legal tradition of law and economics, using economic
theory to inform legal judgments.
● Do we have one for the data economy?
● To better design data protection policy (and antitrust? etc.), we need economic
theory that captures the economic impact on everyone involved (data
processors, data subjects, and others)...
79. Data Games and the Value of Information
Goals (real agenda):
● Using the insights about situated information flow…
● … develop a new tool, data games, for understanding the value of information ...
● … to start a new field of inquiry, data economics, that can better understand the
foundational principles of the information economy!
“Surely, that has been done before,” you say.
80. Contextualism in privacy economics
● “The Economics of Privacy,” by Acquisti, Taylor, and Wagman (2016) surveys
the existing privacy literature.
● They judge that economics can only ever deal with privacy in a contextually
specific way.
● While this sounds nice, it runs into the same problem as CI! Namely, …
● We know the most important practice in the data economy is date reuse, i.e., use
of data collected in one context for another!
81. Something new!
● We need a new data economics! Really!
● We need a way to model the outcomes of creating and destroying information
flows between strategic actors.
● The difference in outcome for each actor is the value of information.
82. We need a new tool to measure the value of information..
We will start with situated information flow
and add features for game theory
and mechanism design.
We can call this new tool a
data game
83. Multi-Agent Influence Diagrams (MAIDs)
MAIDs: Bayesian Networks + game theory. (Daphne Koller & Brian Milch, ‘03)
They have a set of agents and a directed acyclic graph with three kinds of nodes:
Chance variables. Random variables with a CPD conditioning on their
Parents in the graph.
Decision variables. The have an associated player. They
do not have a CPD (this is chosen by the player later).
Utility variables. These have a CPD and an associated player. They
may not have any descendants.
X
Y
Z
84. Multi-Agent Influence Diagrams (MAIDs)
To “play” a MAID:
1) Each player simultaneously chooses a CPD for
every decision node they control. This is their
strategy profile, σ.
2) The strategies induce the MAID into a Bayesian
Network, which is sampled.
3) The sum of the sampled values of each player’s
utility variables are awarded as payoffs.
W
X1
Z1
X2
Z2
Y
86. Data Games: Optional Edge
An optional edge (dotted arrow) implies the
diagram represents two different games, an open
and a closed case.
Note that the edge is an information flow.
We can now reason systematically about
consequences of allowing an information flow.
(This is mechanism design).
W
X1
Z1
X2
Z2
Y
87. Let’s look at two data games
for economic contexts that are well-understood
88. Example: Principal/Agent
V B
Up
Ua
Earliest privacy economics argument (?) by Richard Posner (1981):
Employers depend on information about potential hires (V) to make efficient
decisions (B).
More privacy means less information means less efficiency.
89. Example: Principal/Agent
E(U) Open Closed
Principal (E(X | X > w) - w) P[X > w] (x - w)[E(X) > w]
Agent w P[X > w] w[E(X) > w]
Agent, x > w w w[E(X) > w]
Agent, x < w 0 w[E(X) > w]
V B
Up
Ua
90. Example: Price discrimination
V R B
Uf
Uc
An important economic use of personal information is price differentiation (Shapiro
and Varian, 1998).
The firm chooses its price (R) with or without knowledge of the consumer’s demand
(V). The consumer chooses whether or not to buy (B) after getting the price.
91. Example: Price discrimination
E(U) Open Closed
Firm x - ϵ z* P[X > z]
Consumer ϵ (x - z*)P[X > z]
Consumer, x > z* ϵ x - z*
Consumer, x < z* ϵ 0
z* = argmaxz
E[z P(z < x)]
V R B
Uf
Uc
92.
93. Let’s look at two data games
for economic situations that have not yet been studied
94. Example: Expert Services
V
C
R
A
Uf
Uc
W The expert knows some specialized facts
about the world (W) (i.e., medicine, law, the
web).
The client’s personal character traits (C),
determine the value of each of m actions.
The expert, who may or may not know the
character traits, provides a recommendation
(R). The consumer takes an action (A).
The incentives of the expert and the client
are aligned (no conflicts of interest).
95. Example: Expert Services
V
C
R!
A
Uf
Uc
W First observation:
If the domain of R allows for enough bits (in
the Shannon sense) for the expert to encode
all the information in W, then personalization
is irrelevant.
This demonstrates a fundamental link
between Shannon information theory and
data economics: information bottlenecks
matter.
96. Example: Expert Services
V
C R
A
Uf
Uc
W First observation:
If the domain of R is narrow compared to the
expert knowledge W, then personalization
(an open edge C -> R) does improve outcomes
for the expert and client.
The value of a personalized service is
efficient dissemination of information
through a small channel.
99. Cross-context flows: the point
Data is valuable not as a good, but as a strategic resource.
It’s not consumed; it is part of the structure of the game of social and economic
relations itself.
Market externalities are the rule, not the exception.
Traditional theories of market equilibrium, industrial organization,
etc. are not going to cut it. We need to start the field of data
economics.
100. Tactical vs. Strategic Flows
● When considering an optional information flow, we can compare the
equilibrium outcomes of the open and closed cases. Call this the strategic
consequences of the information flow.
● We can also consider the outcome of opening the flow, while keeping the
closed equilibrium strategy for all players except the recipient of the
information. Call this the tactical consequences of the flow.
We can use this to make sensitive distinctions about, e.g. the effects of a data breach
vs. the chilling effects of ongoing surveillance. A data economics for cybersecurity?