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What can we learn from the Facebook-Cambridge Analytica scandal?

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As the data‐based political consulting firm shuts its doors, we get the statisticians’ perspective on the story and its impact What can we learn from the Facebook–Cambridge Analytica scandal?; Commerce Secretary orders citizenship question for 2020 Census; Pollsters told: “Get your house in order”.

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... This is typically sufficient for a city but inadequate when wishing to investigate usage at a country level. Further complicating this approach was a tightening of the geosearch API during the course of this study due to the Cambridge Analytica scandal [36]. To overcome these limitations, we implemented a simple yet novel method for extracting the images for an entire country using Instagram location ids. ...
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... We should not neglect the other possibility of information leakage, namely from the social media itself. Similar to the case of Facebook-Cambridge Analytica when leaked data related birth dates, residence, current location, personal messages, etc. of millions of users leaked [14]. ...
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... The internet does not merely accumulate its users' location, financial confidentiality, health data statistics; personal social networks, interests and activities, but also stores them in Cloud storage which can be accessed by others. In 2018, Facebook and Cambridge Analytica, an election consultancy, gained massive public attention (Isaak & Hanna, 2018;Tarran, 2018) when the former was accused of selling its users' details to the latter. Another international scandal is the ongoing Huawei security scandal (Gibney, 2019), sparked when the United Stated charged Huawei with online security threats. ...
... The use of personal data, especially with the use of technology and smart systems, is an important factor that needs to be considered to enhance democratic processes that need to be just that, democratic (Common, 2018;Edwards, 2018). In the work of Tarran (2018), the author mentions that, according to Christopher Wylie, Cambridge Analytica "exploited Facebook to harvest millions of peoples' profiles and used that data to target voters with personalized political adverts" (The Guardian, 2018a). ...
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... It is impossible to make any system which ensures hundred percent security against leaks but we can make the data itself useless for the potential attackers. Recently in the Cambridge Analytica scandal [1], users gave away their personal information for academic purposes. However, it was sold off for targeted advertisements. ...
Chapter
Security of personal information is affirmation of the right to privacy. With increasing data requirements of consumers and the bulk of archival information thereby created needs storage space and here cloud storage comes to the rescue, which however is prone to cyber attacks and needs better data security protocols as time changes. In this paper, we propose a novel symmetric-key image encryption scheme by shuffling the pixels which renders the information unintelligible. We show how our technique provides an additional layer of security on top of the regular encryption techniques. We analyze our algorithm by performing statistical and difference attack tests. We also discuss the brute force attack and its viability. The results validate effectiveness of our encryption scheme.
... The changing nature of social media sites and their privacy and security control settings has meant that some previously identified barriers to participation when social media emerged, such as risk and safety concerns, need re-examination. It is important to note that privacy breaches, such as the recent Cambridge Analytica privacy breaches at Facebook [47] are not due to technical lapses from the Facebook application itself, but a breach of user trust in a broader sociotechnical sense. This complicates the issue of privacy and trust. ...
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... It is impossible to make any system which ensures hundred percent security against leaks but we can make the data itself useless for the potential attackers. Recently in the Cambridge Analytica scandal [1], users gave away their per- sonal information for academic purposes. However, it was sold off for targeted advertisements. ...
Conference Paper
Security of personal information is affirmation of the right to privacy. With increasing data requirements of consumers and the bulk of archival information thereby created needs storage space and here cloud storage comes to the rescue, which however is prone to cyber attacks and needs better data security protocols as time changes. In this paper, we propose a novel symmetric-key image encryption scheme by shuffling the pixels which renders the information unintelligible. We show how our technique provides an additional layer of security on top of the regular encryption techniques. We analyze our algorithm by performing statistical and difference attack tests. We also discuss the brute force attack and its viability. The results validate effectiveness of our encryption scheme.
... With significant progress, also comes great responsibility for Artificial Intelligence (AI) and machine learning (ML) community. Moreover, human behavior on the Internet is often overlooked and is sometimes neglected by the corporate giants as they work in the best interest of their stockholders, not in the best interest of the ordinary people [4,7]. As we are in an era of AI and ML we need to think carefully what type of platforms and system should we develop not for ourselves but the future generation? ...
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Since 1990's the Internet has played the dominant role in the advancement of the modern world. With significant progress, also comes great responsibility for Artificial Intelligence (AI) and machine learning (ML) community. Moreover, human behavior on the Internet is often overlooked and is sometimes neglected by the corporate giants as they work in the best interest of their stockholders, not in the best interest of the ordinary people. As we are in an era of AI and ML we need to think carefully what type of platforms and system should we develop not for ourselves but the future generation? There is the enormous problem at stake academically: how can we optimize and strengthen the ML and data-driven platform for the social web that understands human emotions and feelings?
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Previous research into children's political knowledge and attitudes has been scarce. To address this gap, a total of 150 British children in Year 2 (58% male, 43% female, Mage = 6.6 years, n = 50), Year 4 (46% male, 54% female, Mage = 8.4 years, n = 50) and Year 6 (56% male, 44% female, Mage = 10.4 years, n = 50) reported their factual knowledge and attitudes towards different political characters, their motivation and aspiration to become prime minister, and what gender stereotypical characteristics a prime minister should have. Results showed children in Year 6 to have more political knowledge and more negative attitudes than those in Year 4 and Year 2. Overall, children indicated a prime minister should have more stereotypical female characteristics. In addition, there were no significant gender differences. Practical implications of the findings are discussed in line with previous research on political socialisation.
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While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between doing ethical things and doing things ethically , to understand and to make pedagogical choices that are ethical, and to account for the ever-present possibility of unintended consequences. However, addressing these and related questions is far from trivial. As a first step towards addressing this critical gap, we invited 60 of the AIED community’s leading researchers to respond to a survey of questions about ethics and the application of AI in educational contexts. In this paper, we first introduce issues around the ethics of AI in education. Next, we summarise the contributions of the 17 respondents, and discuss the complex issues that they raised. Specific outcomes include the recognition that most AIED researchers are not trained to tackle the emerging ethical questions. A well-designed framework for engaging with ethics of AIED that combined a multidisciplinary approach and a set of robust guidelines seems vital in this context.
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