10,244 research outputs found

    BEING PROFILED:COGITAS ERGO SUM

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    Profiling the European citizen: why today's democracy needs to look harder at the negative potential of new technology than at its positive potential

    Population Objects: Interpassive Subjects

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    While Foucault described population as the object of biopower he did not investigate the practices that make it possible to know population. Rather, he tended to naturalise it as an object on which power can act. However, population is not an object awaiting discovery, but is represented and enacted by specific devices such as censuses and what I call population metrics. The latter enact populations by assembling different categories and measurements of subjects (biographical, biometric and transactional) in myriad ways to identify and measure the performance of populations. I account for both the object and subject by thinking about how devices consist of agencements, that is, specific arrangements of humans and technologies whose mediations and interactions not only enact populations but also produce subjects. I suggest that population metrics render subjects interpassive whereby other beings or objects take up the role and act in place of the subject

    Problematising international placements as a site of intercultural learning

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    This paper theorises some of the learning outcomes of a three-year project concerning student learning in international social work placements in Malaysia. The problematic issue of promoting cultural and intercultural competence through such placements is examined, where overlapping hegemonies are discussed in terms of isomorphism of social work models, that of the nation state, together with those relating to professional values and knowledge, and the tyrannies of received ideas. A critical discussion of cultural competence as the rationale for international placements is discussed in terms of the development of the graduating social worker as a self-reflexive practitioner. The development of sustainable international partnerships able to support student placement and the issue of non-symmetrical reciprocation, typical of wide socio-economic differentials across global regions, is additionally discussed

    Legal Aspects of Artificial Intelligence on Automated Decision-Making in Indonesia

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    This paper analyzes the importance of Indonesia's comprehensive legal framework on automated decision-making empowered by Artificial Intelligence, comparing it to the European Union, the United States, and China. Specifically, this paper inquires about the status quo of the legal protection of automated decision-making In Indonesia. The analysis highlights profiling in an automated decision-making system with the following discussion about personal data protection. In this context, the European Union's member states set out the General Data Protection Regulation (GDPR) that prohibits automated decision-making to a certain extent. In the United States, the practice of automated decision-making is rather usual. Simultaneously, China takes an exceptional measure instead and develops this automation through a social credit system. The analysis concludes that Indonesia has weak legal protection towards personal data and profiling, which later becomes the basis in facilitating automated decision-making. The provision of automated decision-making and profiling is the absolute bare minimum to Indonesia's Personal Data Protection Bill due to insufficient legal certainty. In the end, it is paramount for lawmakers to consider a comprehensive regulation on automated decision-making by adopting the European Union's GDPR framework. KEYWORDS: Artificial Intelligence, Automated Decision-Making, Personal Data Protection

    Cookie Consents and Notices under the EU Data Protection Framework

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    Data protection has become a pivotal topic in modern democratic societies. Lawmakers have, however, faced challenges in protecting data in the face of rapid technological growth and development in the online environment. ‘Cookies’ are a prominent tool for website operators that enable the collection and processing of vast amounts of personal data of internet users. The use of cookies is based on user’s consent as required under Article 5(3) of Directive 2002/58/EC (ePrivacy Directive). It is, however, questionable whether cookie consent and notice practices are de facto effective in protecting internet users and providing them control over the use of their data obtained via cookies. The goal of this master’s thesis is to analyse whether the traditional model of consent and notice is the appropriate legal basis for the use of website cookies. The research question is divided into two parts. The first part concerns whether consent and notice are an effective tool in providing control and protection to individuals with respect to personal data processed through internet cookies. The second part concerns whether the EU’s data protection framework provides clear and harmonised rules on cookie consents and notices. It will focus especially on the General Data Protection Regulation 2016/679 (GDPR) and the ePrivacy Directive. This thesis uses mainly the legal doctrinal method and qualitative empirical evidence in answering its research question. After the introductory chapter, this thesis will in chapter 2 define cookies and its purposes, as well as outline the legal framework used in this research. Chapter 3 introduces the reader to the concept of consent and its different components, as well as the transparency principle and the accompanying information obligation. Consent consists of freely given, specific, informed and unambiguous elements. Chapter 4 will then discuss the first part of the research question. It will be seen that cookie consents and notices are burdened by many factors as evidenced through behavioural economics, cognitive and structural problems, as well as other factors. It is concluded, therefore, that cookie consents and notices in their traditional form are not an effective tool in providing control and data protection to internet users. Nevertheless, consent and notice are so enshrined in the EU’s data protection regime that they will not be easily abandoned. Chapter 5 discusses the second part of the research question by looking at practical examples in order to see how websites from the legal sector and different national data protection authorities have complied with cookie consent and notice obligations. It will be seen that cookie rules are interpreted inconsistently by even these websites, which has resulted in noncompliance in some instances. Hence, it is concluded that the GDPR and the ePrivacy Directive have failed to harmonise cookie consents and notices. Chapter 6 will look to the future and discuss briefly the proposed Regulation on Privacy and Electronic Communications (ePrivacy Regulation) in terms of i) ‘cookie walls’, which basically coerces website users to accept cookies or otherwise they will be denied access to the site or service, and ii) the legitimate interests ground, which has been introduced as an alternative legal basis to consent with respect to cookies in the latest revised draft of the ePrivacy Regulation adopted on 21 February 2020 by the Croatian Presidency. It will be concluded in chapter 7 that the traditional model of consent and notice might not always be the appropriate legal basis for cookies, hence legislators should look into other legal bases as well, such as, the legitimate interest ground. However, whether or not this ground will be able to provide better protection and control to internet users remains to be seen

    Profiling with Big Data: Identifying Privacy Implication for Individuals, Groups and Society

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    User profiling using big data raises critical issues regarding personal data and privacy. Until recently, privacy studies were focused on the control of personal data; due to big data analysis, however, new privacy issues have emerged with unidentified implications. This paper identifies and investigates privacy threats that stem from data-driven profiling using a multi-level approach: individual, group and society, to analyze the privacy implications stemming from the generation of new knowledge used for automated predictions and decisions. We also argue that mechanisms are required to protect the privacy interests of groups as entities, independently of the interests of their individual members. Finally, this paper discusses privacy threats resulting from the cumulative effect of big data profiling
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