Book chapter
10. ICT-related problems at the macro-level
Abstract
Energy consumption – Electronic services use a lot of energy. Google alone consumes more energy than the country Sri Lanka in total. The main factors of energy consumption of IT services are (1) the manufacturing of the hardware, (2) the use of the IT system, (3) the design of the IT system and (4) the disposal of a product. Consequences in all factors can be high, depending on the type of service. The main conflicts and trade-offs in energy consumption are that companies find it more important to earn money, than to make responsible decisions regarding the environment. Although it could be more, improvements are already made by companies. However, the trustworthiness of how green a company really is is not always very high. Solutions to consume less energy are (1) making the software more efficient, (2) fitting the software better to the hardware, (3) greening by IT, (4) greening the energy used for consuming and finally (5) the mindset of the society.
Abuse of ICT – As the information age progresses and globalization, networking and overall technological growth steadily increases, three generations of criminal behavior arose: The computer-assisted crimes; the computer-enabled crimes; and the computer-dependent crimes. Not only did the technological advancements help the criminal behavior in the type of how it could operate, also the scale of the malicious intentions vastly grew. They could more easily target individuals, organizations or even entire nations through various attacks such as DDoS attacks, various viruses and misinformation campaigns. Consequences of these attacks could therefore also vary from little to no damage, to millions of dollars in costs. Luckily, governments, organizations and individuals become more aware of their virtual environment, and more and better measures against malicious online behavior become available, so that ICT abusers have an increasingly harder time to operate their business.
Algorithmic bias – With the wide adoption of algorithms come some increasingly negative side effects. One of these side effects is algorithmic bias which can be defined as: the systematic and repeatable error in computational systems, that is responsible for unfair, wrongful results of data processing. The origin of this issue can be found within the problems that humans have to face too, biases. These biases find their way within algorithms in numerous ways. Mostly machine learning algorithms seem to be having significant issues, as bias can arise in both the implementation and the data sets that they use to train themselves. The usage of these algorithms bring forth striking ethical issues, such as whether or not data that doesn’t originate from you should be used to make predictions about your future. Especially within settings such as a courtroom, where ones personal freedom is at stake.
Privacy and data management – Privacy is an important aspect of human life. Especially online, this is often hard to guarantee. Almost everywhere we go on the internet our data gets collected in some form. There are, of course, laws in place that protect people’s personal identifiable information and that specify what is allowed to be stored and used, such as the European GDPR. However, not every country has such elaborate and strict laws regarding privacy. Furthermore, even in Europe, it is often hard to keep track of what information you’re sharing exactly, and even harder to find out what is done with this data. More and more people are feeling like they have no control over their data anymore. This phenomenon is called ’privacy fatigue’, which reflects a sense of weariness towards privacy issues. Another important aspect is the storage of data by companies. If this is not done properly, this can lead to data breaches, which occur when personally identifiable information is accidentally lost or stolen. There are numerous good examples of privacy and data management issues, some of which were discussed in this chapter. There are no easy solutions for these issues, but carefully evaluating privacy laws, and changing them over time with the emergence of new technologies is a step in the right direction.
Platform capitalism – Platform capitalism refers to a new phase of capitalist accumulation whereby large amounts of data is extracted from user’s activities and are mostly employed by data-dependent logistics companies. The value of knowledge creates an economic incentive for entities to accumulate and control the flow of this knowledge throughout the economy, in the form of information and data. This data is used to optimize production processes, give insights into consumer preferences, control workers, provide a foundation for new products and services, and sell to advertisers. There are, in total, five different types of platforms that can be distinguished within platform capitalism, namely: Advertising platform (e.g., Google); Product platform (e.g., Spotify); Industrial platform (e.g., Siemens); Lean platform (e.g., Uber); and Cloud platform (e.g., Salesforce)
Knowledge clip
| [1] | S. H. Schwartz et al., “Refining the theory of basic individual values”, Journal of personality and social psychology, vol 103, no 4, bl 663, 2012. |
| [2] | S. Murugesan, “Harnessing green IT: Principles and practices”, IT professional, vol 10, no 1, bll 24–33, 2008. |
| [3] | P. T. Krein, “Data center challenges and their power electronics”, CPSS Transactions on Power Electronics and Applications, vol 2, no 1, bll 39–46, 2017. |
| [4] | Ł. Iwasiński, “Social Implications of Algorithmic Bias”, 2020. |
| [5] | R. Baeza-Yates, “Data and algorithmic bias in the web”, in Proceedings of the 8th ACM Conference on Web Science, 2016, bll 1–1. |
| [6] | I. Brinkley, Defining the knowledge economy. The Work Foundation, London, 2006. |
| [7] | A. Acquier, T. Daudigeos, en J. Pinkse, “Promises and paradoxes of the sharing economy: An organizing framework”, Technological Forecasting and Social Change, vol 125, bll 1–10, 2017. |
| [8] | M. Şahin, İ. S. B. Oral, en A. Dhabi, “Translation and Interpreting Studies education in the midst of platform capitalism”. |
| [9] | D. W. Morgen, “Hoe het platformkapitalisme nieuwe monopolies en machtsconcentraties voorbrengt”. 2017. |
| [10] | Impakter, “Platform Capitalism: The Economy of the Future?” 2017. |
| [11] | Investopedia, “Sharing Economy”. 2020. |
| [12] | S. Mills, “# DeleteFacebook: From Popular Protest to a New Model of Platform Capitalism?”, New Political Economy, vol 26, no 5, bll 851–868, 2021. |
| [13] | N. K. Kougiannou en P. Mendonça, “Breaking the Managerial Silencing of Worker Voice in Platform Capitalism: The Rise of a Food Courier Network”, British Journal of Management, 2021. |
| [14] | S. Zuboff, The age of surveillance capitalism: The fight for a human future at the new frontier of power: Barack Obama’s books of 2019. Profile books, 2019. |
| [15] | A. Shapiro, “Between autonomy and control: Strategies of arbitrage in the ‘on-demand’ economy”, New Media & Society, vol 20, no 8, bll 2954–2971, 2018. |
| [16] | IPPR, “The challenges of platform capitalism: understanding the logic of a new business model”. 2017. |
| [17] | T. Ecologist, “The hidden environmental impacts of ‘platform capitalism’”. 2017. |
| [18] | L. Baruh, E. Secinti, en Z. Cemalcilar, “Online privacy concerns and privacy management: A meta-analytical review”, Journal of Communication, vol 67, no 1, bll 26–53, 2017. |
| [19] | Essence, “Airbnb works to clean up its reputation for racial discrimination in new 3-year report”. 2020. |
| [20] | G. Procaccianti, H. Fernández, en P. Lago, “Empirical Evaluation of Two Best Practices for Energy-Efficient Software Development”, Journal of Systems and Software, vol 117, no 1, bll 185–198, 2016. |
| [21] | T. Guardian, “‘I’m not a robot’: Amazon workers condemn unsafe, grueling conditions at warehouse”. 2020. |
| [22] | Wikipedia, “Criticism of Amazon”. 2021. |
| [23] | T. Guardian, “Google to shut down Google+ after failing to disclose user data leak”. 2018. |
| [24] | A. Acquisti, A. Friedman, en R. Telang, “Is there a cost to privacy breaches? An event study”, ICIS 2006 proceedings, bl 94, 2006. |
| [25] | C. Mundie, “Privacy pragmatism; focus on data use, not data collection”, Foreign Aff., vol 93, bl 28, 2014. |
| [26] | H. T. Tavani, “Informational privacy: Concepts, theories, and controversies”, The handbook of information and computer ethics, bll 131–164, 2008. |
| [27] | M. Goddard, “The EU General Data Protection Regulation (GDPR): European regulation that has a global impact”, International Journal of Market Research, vol 59, no 6, bll 703–705, 2017. |
| [28] | H. Berghel, “Malice domestic: The Cambridge analytica dystopia”, Computer, vol 51, no 5, bll 84–89, 2018. |
| [29] | J. Isaak en M. J. Hanna, “User data privacy: Facebook, Cambridge Analytica, and privacy protection”, Computer, vol 51, no 8, bll 56–59, 2018. |
| [30] | S. Zuboff, “Surveillance capitalism and the challenge of collective action”, in New labor forum, 2019, vol 28, bll 10–29. |
| [31] | E. Nasaescu, I. Marin-Lopez, V. J. Llorent, R. Ortega-Ruiz, en I. Zych, “Abuse of technology in adolescence and its relation to social and emotional competencies, emotions in online communication, and bullying”, Computers in Human Behavior, vol 88, bll 114–120, 2018. |
| [32] | R. Dhamija, J. D. Tygar, en M. Hearst, “Why phishing works”, in Proceedings of the SIGCHI conference on Human Factors in computing systems, 2006, bll 581–590. |
| [33] | M. Del Vicario et al., “The spreading of misinformation online”, Proceedings of the National Academy of Sciences, vol 113, no 3, bll 554–559, 2016. |
| [34] | A. Hutchings en P. Jorna, “Misuse of information and communications technology within the public sector”, Trends and issues in crime and criminal justice, no 470, bll 1–9, 2015. |
| [35] | K.-K. R. Choo, “The cyber threat landscape: Challenges and future research directions”, Computers & security, vol 30, no 8, bll 719–731, 2011. |
| [36] | W. V. Alain Strowel, “Digital Platforms: To regulate or not to regulate? Message to regulators: Fix the economics first, then focus on the right regulation”. 2017. |
| [37] | C. Douligeris en A. Mitrokotsa, “DDoS attacks and defense mechanisms: classification and state-of-the-art”, Computer networks, vol 44, no 5, bll 643–666, 2004. |
| [38] | P. Olson, We are anonymous. Random House, 2013. |
| [39] | R. Hischier, V. C. Coroama, D. Schien, en M. A. Achachlouei, “Grey energy and environmental impacts of ICT hardware”, in ICT Innovations for Sustainability, Springer, 2015, bll 171–189. |
| [40] | D. Wall, Cybercrime: The transformation of crime in the information age, vol 4. Polity, 2007. |
| [41] | R. Frischknecht, F. Wyss, S. B. Knöpfel, T. Lützkendorf, en M. Balouktsi, “Cumulative energy demand in LCA: the energy harvested approach”, The International Journal of Life Cycle Assessment, vol 20, no 7, bll 957–969, 2015. |
| [42] | “Flaw leads to Google+ shutting down”, Network Security, vol 2018, no 10, bl 3, 2018. |
| [43] | M. Couto, P. Borba, J. Cunha, J. P. Fernandes, R. Pereira, en J. Saraiva, “Products go green: Worst-case energy consumption in software product lines”, in Proceedings of the 21st International Systems and Software Product Line Conference-Volume A, 2017, bll 84–93. |
| [44] | D. S. Wall, “The Internet as a conduit for criminal activity”, Information technology and the criminal justice system, Pattavina, A. , ed, bll 77–98, 2015. |
| [45] | T. S. of S. Project, “The story of stuff”. 2009. |
| [46] | N. Wirth, “A plea for lean software”, Computer, vol 28, no 2, bll 64–68, 1995. |
| [47] | Wikipedia contributors, “Pandora Papers”. 2021. |
| [48] | R. Bryce, “How Google Powers Its ‘Monopoly’ With Enough Electricity For Entire Countries”. 2020. |
| [49] | U. S. E. I. Administration, “Use of electricity”. 2021. |
| [50] | B. C. K. Choi en A. W. P. Pak, “Bias, overview”, Wiley StatsRef: Statistics Reference Online, 2014. |
| [51] | D. Danks en A. J. London, “Algorithmic Bias in Autonomous Systems”, in IJCAI, 2017, vol 17, bll 4691–4697. |
| [52] | S. Silva en M. Kenney, “Algorithms, platforms, and ethnic bias”, Communications of the ACM, vol 62, no 11, bll 37–39, 2019. |
| [53] | T. T. Nguyen, P.-M. Hui, F. M. Harper, L. Terveen, en J. A. Konstan, “Exploring the filter bubble: the effect of using recommender systems on content diversity”, in Proceedings of the 23rd international conference on World wide web, 2014, bll 677–686. |
| [54] | L. Hook en D. Lee, “Tech has gone big on green energy — and it could take the world with it”. 2021. |
| [55] | K. Arora, K. Kumar, en M. Sachdeva, “Impact analysis of recent DDoS attacks”, International Journal on Computer Science and Engineering, vol 3, no 2, bll 877–883, 2011. |
| [56] | T. Pimonenko, Y. Bilan, J. Horák, L. Starchenko, en W. Gajda, “Green brand of companies and greenwashing under sustainable development goals”, Sustainability, vol 12, no 4, bl 1679, 2020. |
| [57] | M. Kay, C. Matuszek, en S. A. Munson, “Unequal representation and gender stereotypes in image search results for occupations”, in Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 2015, bll 3819–3828. |
| [58] | R. Torelli, F. Balluchi, en A. Lazzini, “Greenwashing and environmental communication: Effects on stakeholders’ perceptions”, Business strategy and the Environment, vol 29, no 2, bll 407–421, 2020. |
| [59] | A. Datta, M. C. Tschantz, en A. Datta, “Automated experiments on ad privacy settings: A tale of opacity, choice, and discrimination”, arXiv preprint arXiv:1408. 6491, 2014. |
| [60] | M. Garcia, “Racist in the machine: The disturbing implications of algorithmic bias”, World Policy Journal, vol 33, no 4, bll 111–117, 2016. |
| [61] | C. O’neil, Weapons of math destruction: How big data increases inequality and threatens democracy. Crown, 2016. |
| [62] | L. Eckhouse, K. Lum, C. Conti-Cook, en J. Ciccolini, “Layers of bias: A unified approach for understanding problems with risk assessment”, Criminal Justice and Behavior, vol 46, no 2, bll 185–209, 2019. |
| [63] | R. Balebako, J. Jung, W. Lu, L. F. Cranor, en C. Nguyen, “‘ Little brothers watching you’ raising awareness of data leaks on smartphones”, in Proceedings of the Ninth Symposium on Usable Privacy and Security, 2013, bll 1–11. |
| [64] | S. Romanosky, R. Telang, en A. Acquisti, “Do data breach disclosure laws reduce identity theft?”, Journal of Policy Analysis and Management, vol 30, no 2, bll 256–286, 2011. |
| [65] | S. Romanosky, D. Hoffman, en A. Acquisti, “Empirical analysis of data breach litigation”, Journal of Empirical Legal Studies, vol 11, no 1, bll 74–104, 2014. |
| [66] | L. Cheng, F. Liu, en D. Yao, “Enterprise data breach: causes, challenges, prevention, and future directions”, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol 7, no 5, bl e1211, 2017. |
| [67] | M. J. Wolf, K. W. Miller, en F. S. Grodzinsky, “Why we should have seen that coming: comments on microsoft’s tay ‘experiment,’ and wider implications”, The ORBIT Journal, vol 1, no 2, bll 1–12, 2017. |
| [68] | O. W. in Data, “Global primary energy: how has the mix changed over centuries?” 2021. |
| [69] | P. J. Denning, Computer viruses. Research Institute for Advanced Computer Science, 1988. |
| [70] | M. Del Vicario et al., “The spreading of misinformation online”, Proceedings of the National Academy of Sciences, vol 113, no 3, bll 554–559, 2016. |
| [71] | A. Shehabi, S. J. Smith, E. Masanet, en J. Koomey, “Data center growth in the United States: decoupling the demand for services from electricity use”, Environmental Research Letters, vol 13, no 12, bl 124030, 2018. |
| [72] | A. Mian en S. Khan, “Coronavirus: the spread of misinformation”, BMC medicine, vol 18, no 1, bll 1–2, 2020. |
| [73] | G. Coleman, “Anonymous in context: The politics and power behind the mask”, 2013. |
| [74] | E. Goldberg, “Demand Surges for Deworming Drug for Covid, Despite Scant Evidence It Works”. 2021. |
| [75] | M. van Rijmenam, “Algorithmic Management: What is It (And What’s Next)?” 2020. |
| [76] | Wikipedia, “Platform economy”. 2021. |
| [77] | S. Kalia, “The Great Social Cost of Facebook Prioritizing Profit Over Minimum Public Good”. 2021. |
| [78] | F. Pasquale, “Two narratives of platform capitalism”, Yale L. & Pol’y Rev., vol 35, bl 309, 2016. |
| [79] | C. L. Dezsö en D. G. Ross, “Does female representation in top management improve firm performance? A panel data investigation”, Strategic management journal, vol 33, no 9, bll 1072–1089, 2012. |
| [80] | T. Scholz, “Platform cooperativism”, Challenging the corporate sharing economy. New York, NY: Rosa Luxemburg Foundation, 2016. |
| [81] | E. Papadimitropoulos, “Platform Capitalism, Platform Cooperativism, and the Commons”, Rethinking Marxism, vol 33, no 2, bll 246–262, 2021. |
| [82] | E. Commission, “Data protection in the EU”. Jun-2021. |
| [83] | H. Choi, J. Park, en Y. Jung, “The role of privacy fatigue in online privacy behavior”, Computers in Human Behavior, vol 81, bll 42–51, 2018. |
| [84] | S. Schjølberg, The History of Cybercrime (1976-2016). 2017. |
| [85] | L. Mathews, “Nearly 600 Arrested In Massive Cybercrime Bust”. 2021. |
| [86] | R. Whitwam, “Cyberpunk Developer Hit with Ransomware Attack”. 2021. |
| [87] | U. K. Government, “Managed Cyber Security Operations Centre (CSOC)”. . |