The advent of Artificial Intelligence (AI), automation, algorithms, and datafication has transformed various aspects of society, including internet cultures and governance. These technologies have changed the way we live, work, and communicate. At the same time, they have raised concerns about their impact on privacy, security, and democratic processes. Their value to society is then not void of demerits that may need to be contained before fully enjoying their merits. The following is then an exploration of the implications of AI, automation, algorithms, and datafication on internet cultures and governance, plus an analysis of the key issues in their governance, and an illustration of these concepts through relevant case studies.
Key Issues in the Governance of AI, Automation, Algorithms, and Datafication
AI, automation, algorithms, and datafication have fundamentally changed the internet culture. Stieglitz & Dang-Xuan (2013) highlight the increased tendency of social media platforms, search engines, and other online services to collect vast amounts of data about users which is then used to target advertisements and personalize content. AI algorithms are used to process this data and make decisions about what content users see, what products they buy, and even what job offers they receive (Stieglitz & Dang-Xuan, 2013). The result is the emergence of a data-driven culture, where personal data is a valuable resource to be exploited for commercial gain. The free access in exchange for personal data is then an idea that is widely emulated within the AI, automation, and datafication scene with regard to social media and other online platforms. These issues then negate proper governance of AI, automation, algorithms, and datafication in this digital age. nevertheless, there is still a lack of transparency and accountability in the use of these technologies. Another significant issue is the impact of these technologies on privacy and security. The collection and use of personal data by online platforms raise concerns about the right to privacy and how personal information is used (Stieglitz & Dang-Xuan, 2013). With the increased number of people working, communicating, shopping, and trading online, there is a risk that such associated data could be exploited for malicious purposes, such as identity theft or cyber-attacks. Furthermore, the use of AI algorithms to process personal data and make decisions tend to raise concerns about the fairness and accuracy of these decisions, particularly in areas such as employment and financial decisions. Governance of Ai, Automation, algorithms, and datafication is then crucial within this digital age.
Regulation of Platforms
One key issue in the governance of these technologies is the need for effective regulation. Flew (2021) argues that effective regulation of online platforms is necessary to ensure that they are held accountable for their actions and that they are transparent about how they use personal data. There is a need for regulatory frameworks to govern the power of online platforms, which have become dominant players in the digital economy such as Facebook, Google, and Amazon. These platforms have become powerful gatekeepers that can control access to information and content resulting in concerns about their impact on democracy, privacy, and competition. Such regulation, however, raises concern over censorship and overregulation. There is a need for a balance between government intervention and self-regulation. While governments have a responsibility to protect citizens from harmful content and ensure fair competition, they must also avoid overregulation that may stifle innovation and limit free speech. Self-regulation, on the other hand, can be ineffective if platforms prioritize profits over the public interest. An example case study is Facebook’s handling of the Cambridge Analytica scandal, where the company failed to protect user data from misuse by a third party.
Cambridge Analytica was a political consulting firm that was charged with the harvesting of personal data from millions of Facebook users without their consent (Lee, 2020). This data was then used to influence the outcome of the 2016 presidential elections in the United States (Lee, 2020). This case demonstrated the power of technology to manipulate public opinion through the exploitation of personal data. The scandal was a wake-up call for internet users, lawmakers, and tech companies to reconsider the ethical implications of AI, automation, algorithms, and datafication. It showed how digital platforms can be used as tools for political propaganda and undermined democracy by manipulating public opinion. The case also raised concerns about the use of personal data and the role of tech companies in safeguarding user privacy (Lee, 2020). It highlighted the need for stronger regulation and transparency to prevent abuses of personal data by third-party firms. As a result, data privacy regulations, such as the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) in the United States, have been introduced with the primary objective of safeguarding user data and promoting transparency regarding data collection and usage (Lee, 2020). These regulations have been established to ensure that individuals have greater control over their personal information, including the right to access and correct their data, as well as the ability to request its deletion (Lee, 2020). Additionally, these regulations impose strict requirements on organizations that collect, store, and use personal data, including the need to obtain explicit consent from individuals before collecting their information and implementing appropriate security measures to protect it (Lee, 2020).
The Cambridge Analytica scandal also exposed the vulnerabilities of social media platforms and the need for greater accountability for tech companies. Social media and other online platforms operate behind closed doors and often make decisions that impact millions of users without consulting them. This case then demonstrated the potential impact of AI and data analytics on democracy, and the importance of transparency and oversight in the use of these tools. It serves as a cautionary tale for the future of technology and the potential dangers of unchecked data collection and manipulation. As such it depicted the need to hold more social media platforms accountable for their actions, particularly when they engage in anticompetitive behavior or fail to protect user privacy.
The ethical governance of AI, automation, algorithms, and datafication is a crucial consideration in today’s technological landscape. As these technologies continue to advance, they have the potential to significantly impact society and individuals’ lives, which highlights the need for ethical oversight and regulation. Crawford (2021) notes that regulation should address the broader social implications of these technologies, such as their impact on labor markets, the environment, and democratic processes. Crawford argues that AI is not neutral and that it reflects the values and biases of those who create it (Crawford, 2021). As such, there is a need for greater awareness of the societal impacts of AI and greater regulation to ensure that it is developed and deployed ethically. With the recent development of chatGPT which can give instant answers to almost everything including college essays and develop well-polished marketing campaigns and content, there is increased discussion over its ethical use and integration into such sectors as education and training. At the same time, its use raises questions over ethical usage to limit the adverse impact on the labor market as it puts many content writers out of the market. There is also increased fear over potential misuse and the opaque nature in which the data fed into this AI is processed. Similarly, most of the other AI systems tend to be complex and opaque, making it difficult for users to understand how they work or why they make certain decisions. This lack of transparency can lead to distrust and suspicion, particularly when AI is used to make decisions that have a significant impact on people’s lives, such as in hiring or lending decisions (Crawford, 2021).
Challenges in Governance
The regulation of these technologies is challenging, as they are often global in scope and operate across multiple jurisdictions. Just & Latzer (2019) argue that governance by algorithms creates new forms of power relations and poses significant challenges to democratic decision-making. The duo argues that algorithms shape the information we see and the decisions we make and that this can have significant impacts on our perceptions of the world (Just & Latzer, 2019). As such, there is a need for greater awareness of the ways in which algorithms shape our online experiences and greater regulation to ensure that algorithms are developed and deployed in a way that is fair and equitable. Bottom of Form
Pasquale (2015) argues that the use of algorithms in financial markets and credit scoring systems raise concerns about the fairness and accuracy of these decisions. This has significant implications for individuals’ access to credit and financial services.
Although AI, automation, algorithms, and datafication have fundamentally transformed internet cultures and governance, they also have the potential to exacerbate existing social and economic inequalities as they reinforce biases and discrimination. For example, if an AI algorithm is trained on biased data, it may produce discriminatory results when making decisions related to hiring, loan approvals, and other important areas of life. Noble (2018) highlights the implications of algorithms for social justice, arguing that search engines reinforce racism and perpetuate discriminatory practices. Noble argues that search engines are not neutral and that they reflect the values and biases of those who create them. As such, there is a need for greater awareness of the societal impacts of search engines and greater regulation to ensure that they are developed and deployed ethically. When they are trained on the right set of data and the AI automation or datafication is done right then the output on such a search engine would be less discriminatory but provide well-rounded responses to search queries. Quite often the training process and the operations of search engines and other online platforms tend to be opaque, with the inner workings of the algorithms and the data used to train them being kept secret by developers and managers. This lack of transparency can make it difficult to hold these entities accountable for their actions and decisions, further exacerbating existing power imbalances.
The governance of AI, automation, algorithms, and datafication poses significant challenges that require a comprehensive approach to resolve. One possible solution is the development of more transparent and accountable AI algorithms, with greater participation from diverse stakeholders in the design and implementation of these technologies. By doing so, it is possible to address issues related to bias and discrimination, which can lead to more accurate and fair algorithmic decision-making. Consequently, it is integral to have greater regulation and oversight of online platforms and algorithms to protect the users’ rights to privacy and freedom of expression. This may involve the creation of new laws and regulations, as well as better enforcement of existing regulations like the GDPR in the European Union.
Moving forward, it is also essential to promote the ethical development and deployment of AI, automation, algorithms, and datafication. This can be achieved through the establishment of ethical standards and guidelines, including the development of codes of conduct and ethical principles. This would help to ensure that these technologies are developed and deployed in a way that is fair, transparent, and equitable.
Lastly, there is a need for greater collaboration between governments, civil society, and the private sector to address the challenges in the governance of these technologies. Such collaboration would involve the sharing of best practices and knowledge, as well as the establishment of multi-stakeholder working groups to ensure that diverse perspectives are considered in the development and deployment of these technologies. The result would be an ethical development and deployment.
In summary, AI, automation, algorithms, and datafication are transforming our societies in profound ways, with both positive and negative consequences. While these technologies have the potential to improve efficiency and productivity, they also raise important issues related to privacy, bias, and discrimination, as well as employment and economic displacement. As such, there is a need for greater regulation and oversight, as well as the development of more transparent and accountable AI algorithms. By addressing these issues, the power of these technologies can be harnessed for the benefit of all mankind.
Flew, T. (2021). Regulating Platforms. Cambridge: Polity.
Crawford, K. (2021). The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven, CT: Yale University Press.
Andrejevic, M. (2019). Automated Culture. In Automated Media (pp. 44-72). London: Routledge.
Pasquale, F. (2015). The Need to Know. In The Black Box Society: the secret algorithms that control money and information (pp.1-18). Cambridge: Harvard University Press.
Just, N., & Latzer, M. (2019). Governance by algorithms: reality construction by algorithmic selection on the Internet. Media, Culture & Society, 39(2), 238-258.
Noble, S. U. (2018). A society, searching. In Algorithms of Oppression: How search engines reinforce racism (pp. 15-63). New York: New York University.
Stieglitz, S., & Dang-Xuan, L. (2013). Social media and political communication: a social media analytics framework. Social network analysis and mining, 3, 1277-1291.
Lee, C. (2020). The aftermath of Cambridge Analytica: A primer on online consumer data privacy. AIPLA QJ, 48, 529.