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Programming programming languages, and analyzing Facebook's failure
Abstract
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Mark Guzdial considers an idea with significant educational implications, while Susan Landau looks into the Cambridge Analytica/Facebook scandal.
... The timing of our study coincided with emerging news headlines that Cambridge Analyticaa British data-mining firmhad collected personal data from an app advertised on Facebook in 2013 and targeted up to 87 million Facebook users with political and digital advertisements without consent from the user (Cuthbertson, 2018, April 6;Granville, 2018). The Cambridge Analytica affair received widespread media attention and highlighted to the public the fact that large companies and government bodies might be able to collect substantial amounts of information about people (Landau, 2018). Data collection also coincided with a major public health incident involving the deliberate use of a nerve agent in Salisbury, England, which attracted substantial media attention. ...
The use of mobile phone devices leaves digital traces which include personal data of the user’s location and can be used to produce aggregated and anonymised location data. There is widespread interest in utilising different types of mobile phone location data to optimise emergency health responses within a range of settings, however until now there has been no qualitative research exploring public opinions on sharing such data. A qualitative study with 40 millennials (born between 1981–2000) across six focus groups were conducted before and after widespread news reports about the leaking of personal data on social media and a major public health incident in the UK. Thematic analysis was used to identify themes in the data. Analysis identified four main themes and five subthemes suggesting the main concepts related to attitudes and concerns were ‘Control’, ‘Trust’, ‘Risks to sharing’ and ‘Pros and cons of data sharing’. Millennials were generally accepting of sharing different types of location data with ambulance services and a public health agency if they were able to give explicit consent and retain some personal control towards how their data would be used. The results suggest that policymakers who wish to use aggregated and anonymized mobile phone location data to improve healthcare services should focus on reassurance about how data will be used and promoting public trust.
... The rise of BDBMs underlines that BD and related technologies should no longer be seen as simple assets or resources, but rather as a set of strategic capabilities that can support organizational value creation and capture (Akter et al., 2016;Bharadwaj et al., 2016;Bhimani, 2015;Gupta and George, 2016). Yet, pursuing a BDBM can also entail severe consequences such as those recently experienced by Facebook when it faced public backlash over data privacy (Guzdial and Landau, 2018). Since users' privacy is "kryptonite" to Facebook's BDBM, the situation will not be remedied "unless they fundamentally change their business model" (King, 2018: 2). ...
The emergence of “big data” offers organizations unprecedented opportunities to gain and maintain competitive advantage. Trying to exploit the strategic business potential embedded in big data, many organizations have started to renovate their business models or develop new ones, giving rise to the phenomenon of big-data business models. Although big-data business model research is still in its infancy, a significant number of studies on the topic have been published since 2014. We thus suggest it is time to perform a critical review and assessment of the literature at the intersection of business models and big data (analytics), thereby responding to recent calls for further research on and sustained analysis of big-data business models. In particular, our review uses three major criteria (big-data business model types, dimensions, and deployment) to assess the state of the big-data business model literature and identify shortcomings in this literature. On this basis, we derive and discuss five central research perspectives (supply chain, stakeholder, ethics, national, and process), providing guidance for future research and theory development in the area. These perspectives also have practical implications on how to address the current big-data business model deployment gap.
... The rise of BDBMs underlines that BD and related technologies should no longer be seen as simple assets or resources, but rather as a set of strategic capabilities that can support organizational value creation and capture (Akter et al., 2016;Bharadwaj et al., 2016;Bhimani, 2015;Gupta and George, 2016). Yet, pursuing a BDBM can also entail severe consequences such as those recently experienced by Facebook when it faced public backlash over data privacy (Guzdial and Landau, 2018). Since users' privacy is "kryptonite" to Facebook's BDBM, the situation will not be remedied "unless they fundamentally change their business model" (King, 2018: 2). ...
The emergence of ‘big data’ offers organizations unprecedented opportunities to gain and maintain competitive advantage. Trying to exploit the strategic business potential embedded in big data, many organizations have started to renovate their business models or develop new ones, giving rise to the phenomenon of big-data business models (BDBMs). Although BDBM research is still in its infancy, a significant number of studies on the topic have been published since 2014. We thus suggest it is time to perform a critical review and assessment of the literature at the intersection of business models and big data (analytics), thereby responding to recent calls for further research on and sustained analysis of BDBMs. In particular, our review uses three major criteria (BDBM types, dimensions, and deployment) to assess the state of the BDBM literature and identify shortcomings in this literature. On this basis, we derive and discuss five central research perspectives (supply chain, stakeholder, ethics, national, and process), providing guidance for future research and theory development in the area. These perspectives also have practical implications on how to address the current BDBM deployment gap.
... W11 -Special issues in designing and implementing social software elements: User privacy regulations in general and in special contexts; Supporting IT decision makers on criteria to consider when making social element choices for their future systems; Providing policy guidelines in addition to decision making tools; Contextual elements to consider when adding social software elements to systems; and Cultural issues in the design of social software elements. Readings: [12,20,23]. Due: Quiz 2 (20%) during first half of class for topics from W06 to W10. ...
The goal of this paper is to initiate a conversation on the undergraduate teaching of social software analysis and design in applications which are non-social-media specific. This course covers the topics required to strategically "socialify" organizational applications to engage users in the most productive way for the organization. To capture this effort, we suggest the term "socialification" which means the use of social software design features in non-social-media applications. We provide some background and course goals and learning objectives as well as a course structure. We then discuss issues to consider when implementing a course in social software elements development. We also cover the theoretical grounding related to the interdisciplinary process and explain how it contributes to the design of the course.
... 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? ...
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?
Media pay considerable attention to episodes that involve children and adolescents and the internet. Usually, the excessive time spent on social networking sites is highlighted as the principal source of risk for cyberbullying as well as for the various types of cyber addictions that can develop. Anonymity is reported to be one of the principal factors that favor cyberbullying, whilst sexting and homophobia are indicated as being among the principal circumstances that bring victims to commit suicide. In this chapter, some relevant aspects of the use of social networking sites will be illustrated and some notions regarding how the internet works will be introduced. Other questions, such as the spread of cyber hate and online incivility will be discussed, and a case of the incautious use of Facebook by a higher public education institution will be reported. Many concepts highlighted here will be useful in the following chapters in which strategies for the prevention of cyberbullying will be considered.
We challenge the idea that a course intended to convey principles of languages should be structured according to those principles, and present an alternate approach to teaching a programming language course. The approach involves teaching emerging programming languages. This approach results in a variety of course desiderata including scope for instructor customization; alignment with current trends in language evolution, practice, and research; and congruence with industrial needs. We discuss the rationale for, the course mechanics supporting, and the consequences of this approach.
Media pay considerable attention to episodes that involve children and adolescents and the internet. Usually, the excessive time spent on social networking sites is highlighted as the principal source of risk for cyberbullying as well as for the various types of cyber addictions that can develop. Anonymity is reported to be one of the principal factors that favor cyberbullying, whilst sexting and homophobia are indicated as being among the principal circumstances that bring victims to commit suicide. In this chapter, some relevant aspects of the use of social networking sites will be illustrated and some notions regarding how the internet works will be introduced. Other questions, such as the spread of cyber hate and online incivility will be discussed, and a case of the incautious use of Facebook by a higher public education institution will be reported. Many concepts highlighted here will be useful in the following chapters in which strategies for the prevention of cyberbullying will be considered.
Digital technology allows an individual to simultaneously interact with a multitude of people and with smart objects, namely intelligent devices and electronic programs. As a consequence, new modalities for involving citizens in participatory processes can be applied.Applications can be created with the goal of collecting data as well as ideas, suggestions, and opinions from the multitude of citizens at large, but citizens need to be motivated to participate and be able to trust that their privacy will be respected. In this article, we propose a mobile platform, called Citybook, that aims to provide citizens with a personal smart diary that includes itineraries, automatic generated searches, repositories for images and videos, and functions for sharing personal feelings, opinions, and suggestions with other users and with public services.We present the functional structure of this platform, which has been conceived in a perspective of smart and connected communities. It should also be able to integrate crowd sensing with existing data repositories via an OpenData approach.
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