Data Rights and Digital Hegemony

 

By Lilian H. Hill

The internet was once imagined as a democratic digital common; however, that notion has been rendered idealistic (Shurety, 2021). Today, mainstream internet use is predominantly governed by a handful of powerful corporations, signaling that cyberspace has also undergone significant privatization. Digital hegemony refers to dominance exercised by a small group of powerful technology companies and states over the digital infrastructure, norms, and data flows that shape global information ecosystems. This form of control extends beyond simple market power; it encompasses the ability to set standards, influence public discourse, and dictate the rules of engagement in cyberspace. Much like cultural or economic hegemony shapes societal values and resource distribution, digital hegemony influences how knowledge is produced, circulated, and monetized, often with limited transparency and accountability.

Digital hegemony intersects directly with data rights, meaning individuals’ and communities’ control over how their personal and collective data are collected, stored, used, and shared. Although AI tools may appear to generate content out of thin air, generative AI systems are built and trained on vast datasets, drawing from extensive collections of images, text, and audio. These systems rely on billions of parameters shaped by complex algorithms that analyze and learn from massive archives of digital information.

In a digitally hegemonic landscape, data are frequently extracted without meaningful consent and commodified by dominant actors, reinforcing asymmetries of power. Citizens often have little recourse or understanding of how their data shape algorithmic decisions, advertising profiles, or political targeting. As scholars like Shoshana Zuboff (2019) argue in The Age of Surveillance Capitalism, this unchecked exploitation of data amounts to a new form of dispossession. Advocating for data rights—including the right to access, delete, and control one's data—is therefore essential to challenging digital hegemony and restoring individuals’ democratic agency.

Monetizing Data

In the digital age, data have become a central asset. Personal information is collected, analyzed, and monetized by both corporations and governments. The commodification of personal data has given rise to growing concerns about privacy, surveillance, and individual autonomy. The concept of data rights has emerged as a response to these concerns, advocating for individuals’ control over their personal information. Verhulst (2022) emphasizes the need for digital self-determination, where individuals have the agency to decide how their data are used and shared. Likewise, Huang and Siddarth (2023) discuss the importance of protecting the digital commons, suggesting that generative AI models trained on public data should contribute back to the communities from which they draw.

The digital realm is also susceptible to more insidious forms of power consolidation. The term digital coup has been used to describe situations where digital platforms or technologies are leveraged to undermine democratic processes. A notable example is Meta's (formerly Facebook) response to Canada's Bill C-18, which aimed to ensure fair compensation for news content shared on digital platforms. In retaliation, Meta restricted access to news content for Canadian users, effectively using its platform's dominance to challenge governmental authority (MacArthur, 2023). Such actions highlight the immense power wielded by tech giants and the potential threats they pose to democratic institutions.

In more extreme cases, digital tools have been employed to facilitate governmental overthrows or suppress dissent. The 2021 military coup in Myanmar saw the junta implementing internet shutdowns, surveillance, and censorship to control the narrative and stifle opposition (Coppel & Chang, 2024). These tactics exemplify how digital technologies can be weaponized to consolidate power and suppress democratic movements. The international community must recognize and address these challenges to safeguard democratic values in the digital era.

Preserving Data Rights

Preserving data rights involves ensuring individuals have meaningful control over how their personal information is collected, used, and shared in digital environments. Legal frameworks play a foundational role in this effort. For example, the European Union’s General Data Protection Regulation (GDPR) provides comprehensive protection, including the rights to access, correct, delete, and restrict the processing of personal data (European Commission, 2016). Similarly, the California Consumer Privacy Act (CCPA) empowers consumers to know what personal information is being collected and to opt out of its sale (California Civil Code § 1798.100, 2018).

Beyond legislation, preserving data rights requires implementing technical and organizational strategies such as privacy by design, where data protection measures are integrated into the development of systems and technologies from the outset (Cavoukian, 2009; Solove, 2025). Another critical principle is data minimization, which means collecting only the data necessary for a specific purpose, thereby reducing the risks of misuse or unauthorized access. Additionally, increasing public awareness and digital literacy helps individuals make informed choices and assert their rights more effectively. Together, legal, technical, and educational approaches form a multi-layered strategy for upholding data rights in the digital age.

Counteracting Digital Hegemony

Counteracting digital hegemony involves resisting the concentrated power that dominant technology corporations and states hold over digital infrastructures, platforms, and user data. Digital hegemony allows a few powerful actors—often multinational tech companies like Google, Meta, and Amazon—to control the flow of information, shape public discourse, and exploit user data for economic and political gain (Couldry & Mejias, 2019). This monopolization raises concerns about surveillance, censorship, and the erosion of democratic processes. To counteract these trends, various strategies have emerged. These include promoting open-source technologies and decentralized networks that reduce dependency on corporate-owned platforms (Zuboff, 2019), enforcing antitrust regulations and data protection laws (Birhane, 2021), and enhancing digital literacy to empower users to navigate and critically engage with online systems (Hintz et al., 2018). Furthermore, advocating for digital sovereignty—where communities and nations assert control over their digital infrastructure and data—is a critical step toward reducing reliance on foreign or corporate technologies (Tomasello, 2023). Ultimately, counteracting digital hegemony involves redistributing digital power, protecting civil liberties, and promoting a more inclusive and equitable digital ecosystem.

 

References

Birhane, A. (2021). Algorithmic injustice: A relational ethics approach. Patterns, 2(2), 100205. https://doi.org/10.1016/j.patter.2021.100205

Brush, H. (2003). Electronic civil disobedience. In Encyclopedia of new media (pp. 167-168). SAGE Publications, Inc., https://doi.org/10.4135/9781412950657.n86

California Civil Code § 1798.100. (2018). California Consumer Privacy Act of 2018. https://codes.findlaw.com/ca/civil-code/civ-sect-1798-100/

Coppel, N., & Chang, L. Y. C. (2024). Coup #4: February 2021 and after. In Myanmar’s digital coup (pp. 23–45). Palgrave Macmillan. https://doi.org/10.1007/978-3-031-58645-3_2SpringerLink

Cavoukian, A. (2009). Privacy by Design: The 7 foundational principles. Information and Privacy Commissioner of Ontario. https://www.ipc.on.ca/sites/default/files/legacy/2018/01/pbd-1.pdf

Couldry, N., & Mejias, U. A. (2019). The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford University Press.

European Commission. (2016). General Data Protection Regulation (GDPR). https://eur-lex.europa.eu/eli/reg/2016/679/oj

Hintz, A., Dencik, L., & Wahl-Jorgensen, K. (2018). Digital citizenship in a datafied society. Polity Press.

Huang, S., & Siddarth, D. (2023). Generative AI and the Digital Commons. arXiv. https://arxiv.org/abs/2303.11074arXiv

MacArthur, J. R. (2023, October 1). A Digital Coup. Harper’s Magazine. https://harpers.org/2023/10/a-digital-coup/Harper's Magazine

Shurety, E. (2021, June 17). What happened to electronic civil disobedience? Hyperallergic. https://hyperallergic.com/654595/what-happened-to-electronic-civil-disobedience/

Solove, D. J. (2021). Understanding privacy. Harvard University Press.

Tomasello, F. Digital civics and algorithmic citizenship in a global scenario. Philos. Technol. 36, 39 (2023). https://doi.org/10.1007/s13347-023-00638-3

Verhulst, S. G. (2022). Operationalizing digital self determination. arXiv. https://arxiv.org/abs/2211.08539arXiv

Wikipedia contributors. (2025). Electronic civil disobedience. Wikipedia. https://en.wikipedia.org/wiki/Electronic_civil_disobedienceWikipedia

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

Artificial Empathy Using Robotics

 

Image of Pepper. Photo Credit: Alex Knight, Pexels

 

By Lilian H. Hill

One example of artificial empathy is Japan's use of robots for elder care. The aging population and a declining birth rate have led to a growing demand for elder care. The national government has invested hundreds of millions of dollars in funding research and development for such care devices using artificial intelligence to display simulations of empathy (Wright, 2023). They are designed to assist in caregiving tasks, provide companionship, and improve the quality of life for the elderly. In addition to robots used for assistive care and safety monitoring, examples of robots endowed with artificial empathy include:

·      Paro: A therapeutic robot designed to look like a baby seal, Paro responds to touch and sound, providing comfort and emotional support to the elderly, particularly those with dementia. The robot is programmed to cry for attention and respond to its name. It includes an off switch.

·      Pepper: Created by Aldebaran Robotics and acquired by SoftBank Robotics in 2015, Pepper is a humanoid robot that can recognize human emotions and engage in basic conversations. It is used in elder care facilities to provide companionship, entertainment, and even lead group activities. Pepper is also used in retail settings for customer service. It talks, gesticulates, and seems determined to make everyone smile.

·      Nao: Originally created by Aldebaran Robotics, acquired by SoftBank Robotics in 2015. Nao is a small humanoid robot designed to interact with people. It is packed with sensors. It can walk, dance, speak, and recognize faces and objects. Now in its sixth generation, it is used in research, education, and healthcare all over the world.

These examples are only a small selection of humanoid robots. For more information, refer to ROBOTS: Your Guide to the World of Robotics (robotsguide.com)

It may strike you as strange, or possibly even creepy, to interact with a robot in intimate ways; however, robots are rapidly being integrated into daily life. The idea of robots was once limited to the world of science fiction, where they were depicted as humanoid machines carrying out tasks with human-like precision and intelligence. Think of R2-D2 and C-3P0 of Stars Fame or Rosey the Robot from the Jetson’s TV Shows. You could also picture Terminator as a more frightening version of movie robotics. Although humanoid robots are still a focus of research and development, robots today come in many different shapes and serve a wide range of functions in our daily lives. Robotics are used in automated vacuum cleaners, Smart home devices, home security systems, and personal assistants like Alexa and Siri (Galiniostech, 2023).

Artificial empathy aims to make interactions with AI systems feel more human-like, fostering trust and comfort in users. However, it also raises ethical considerations about the authenticity of machine-generated empathy and the potential for manipulation.

Wright (2023) notes that there needs to be more connection between promoting robotic care assistants and their actual use. His research in Japan indicates that robotic devices require setup, maintenance, and time to manage and store, reducing caregivers' time with residents. He comments that “existing social and communication-oriented tasks tended to be displaced by new tasks that involved more interaction with the robots than with the residents. Instead of saving time for staff to do more of the human labor of social and emotional care, the robots actually reduced the scope for such work” (para. 13). He concludes by saying the robotic devices may be an expensive distraction from the difficult choices we face regarding how we value people and allocate resources in our societies, leading policymakers to postpone tough decisions in the hope that future technologies will "rescue" society from the challenges of an aging population.

 

References

Galiniostech (2023, November 6). Robots in everyday life: A glimpse into the future. Medium. https://medium.com/@galiniostech/robots-in-everyday-life-a-glimpse-into-the-future-c966640a783d

Wright, J. (2023, January 9). Inside Japan’s long experiment in automating elder care: The country wanted robots to help care for the elderly. What happened? MIT Technology Review. https://www.technologyreview.com/2023/01/09/1065135/japan-automating-eldercare-robots/

 

Artificial Empathy: Creepy or Beneficial?

Photo Credit: Pavel Danilyuk, Pexels

 

By Lilian H. Hill

 

Artificial empathy refers to the simulation of human empathy by artificial intelligence systems, allowing them to recognize, understand, and respond to human emotions in a way that appears empathetic. Empathy encompasses various cognitive and emotional abilities that allow us to understand the internal states of others. Consequently, developing artificial empathy represents both a symbolic goal and a significant challenge for artificial systems, especially robots, as they work towards creating a potentially symbiotic society (Asada, 2018).

Artificial empathy has significant implications for the development of social robots, customer service bots, and other AI applications that interact with humans on a personal level. Below are some key aspects, applications, benefits and drawbacks of artificial empathy.

Key Aspects of Artificial Empathy

Emotion Recognition: AI systems use sensors and algorithms to detect human emotions through facial expressions, voice tones, and body language. These data are processed to identify specific emotional states.

Sentiment Analysis: By analyzing text data from conversations, social media, force and speed of keystrokes, or other sources, AI can gauge the sentiment behind the words and understand the emotional context.

Context Awareness: AI systems are designed to understand the context of interactions, considering factors like the user's environment, past interactions, and specific situations to respond appropriately.

Personalization: Artificial empathy involves tailoring responses based on the user's emotional state and preferences, creating a more personalized interaction.

Behavioral Mimicry: AI can be programmed to exhibit empathy behaviors, such as offering comforting words, showing understanding, or providing appropriate responses in emotional situations.

Applications of Artificial Empathy

Healthcare: AI systems with artificial empathy can support patients by providing emotional comfort, recognizing signs of distress, and improving the overall patient experience.

Customer Service: Chatbots and virtual assistants can use artificial empathy to handle customer inquiries more effectively by responding to the customer's emotional state.

Education: AI tutors can provide personalized support, recognizing when a student is frustrated or confused and adjusting their teaching methods accordingly.

Companionship: Social robots with artificial empathy can provide companionship to individuals, particularly the elderly or those with special needs, by engaging in empathetic interactions.

Benefits and Drawbacks

Artificial empathy can significantly enhance interactions between humans and AI systems but also presents challenges and ethical concerns.

Benefits

AI systems that recognize and respond to emotions create more natural and satisfying interactions, improving user satisfaction and engagement. Empathetic AI in customer service can handle queries more effectively, reducing frustration and increasing loyalty by providing more personalized and considerate responses. AI with artificial empathy can offer support in mental health contexts, providing immediate emotional recognition and support and assisting professionals by monitoring patient well-being. For elderly or isolated individuals, empathetic robots and virtual assistants can provide companionship, reducing feelings of loneliness and improving quality of life.  AI with empathy can be used in educational tools and training programs, providing supportive and encouraging feedback to learners and enhancing their motivation and learning outcomes.

Drawbacks

There is a risk that users may feel deceived if they discover that a machine simulated the empathy they experienced, potentially damaging trust in AI systems.  Emotion recognition often requires sensitive data, such as facial expressions and tone. This raises concerns about data privacy and security and the potential misuse of personal information. AI with artificial empathy could manipulate emotions for commercial or political purposes, exploiting users' emotional states to influence their decisions or behaviors. Over-reliance on empathetic AI for emotional support might reduce human-to-human interactions, potentially impacting social skills and relationships. The development and use of artificial empathy raise ethical questions about the boundaries of human-AI interaction, the role of AI in emotional contexts, and the potential for AI to replace human empathy in critical situations. Current AI systems might misinterpret emotions or provide inappropriate responses, leading to frustration or harm rather than support.

Balancing these benefits and drawbacks is crucial for developing and deploying artificial empathy in AI systems.

 

References

Asada, M. (2018). Artificial empathy. In K. Shigemasu, S. Kuwano, T. Sato, & T. Matsuzawa (Eds.), Diversity in Harmony – Insights from Psychology. Wiley. https://doi.org/10.1002/9781119362081.ch2

Galiniostech (2023, November 6). Robots in everyday life: A glimpse into the future. Medium. https://medium.com/@galiniostech/robots-in-everyday-life-a-glimpse-into-the-future-c966640a783d

Wright, J. (2023, January 9). Inside Japan’s long experiment in automating elder care: The country wanted robots to help care for the elderly. What happened? MIT Technology Review. https://www.technologyreview.com/2023/01/09/1065135/japan-automating-eldercare-robots/

Navigating the Complexities and Dynamics of the Information Ecosystem

 

 

By Lilian H. Hill

 

The information ecosystem refers to the complex network of processes, technologies, individuals, and institutions involved in the creation, distribution, consumption, and regulation of information. It encompasses various elements that interact and influence each other, shaping how information is produced, shared, and used in society. The use of the term ecosystem as a metaphor suggests key properties of environments in which information technology is used. An information ecosystem is a complex system of parts and relationships. It exhibits diversity and experiences continual evolution. Various parts of an ecology coevolve, changing together according to the relationships in the system (Nardi & O’Day, 1999).

 

While the term Information Ecosystem has been in use in academic circles for more than 20 years, it has penetrated today’s media. The dynamic and often unpredictable information ecosystem we inhabit necessitates renewed focus on the fundamental concepts of that ecosystem (Kuehn, 2022). The relationship between information literacy and the information ecosystem is symbiotic and integral. Information literacy refers to the set of skills and knowledge that allows individuals to effectively find, evaluate, use, and communicate information. It encompasses critical thinking and problem-solving abilities in relation to information handling. The term information ecosystem describes the complex environment in which information is produced, distributed, consumed, and preserved. This includes libraries, databases, media, social networks, and other channels and platforms where information flows.

 

Burgeoning and rapidly evolving information technologies influence information production and access. While the emphasis should be on the human activities served by information technologies, the truth is that technology is radically changing ways that information is produced, accessed, understood, and applied.

 

Components of the Information Ecosystem

Multiple constituents work together to produce, distribute, interpret, consume, and regulate information.

 

Information Producers

·      Journalists and Media Organizations: Traditional news outlets, digital news platforms, and independent journalists who gather, verify, and disseminate news.

·      Academic and Research Institutions: Universities, research centers, and scholars who produce scholarly articles, studies, and data.

·      Government Agencies: Institutions that generate reports, statistics, and public records.

·      Businesses and Corporations: Companies that create content for marketing, public relations, and corporate communications.

·      Individuals: Citizens who produce content through blogs, social media, and other personal platforms.

 

Information Distributors

·      Social Media Platforms: Facebook, Twitter, Instagram, LinkedIn, and others that facilitate the rapid spread of information.

·      Search Engines: Google, Bing, and others that organize and provide access to information.

·      Traditional Media: Newspapers, television, radio, and magazines distributing news and entertainment content.

·      Online Platforms: Websites, forums, and blogs that host and share various forms of content.

 

Information Consumers

·      General Public: Individuals who consume news, entertainment, educational content, and other forms of information.

·      Professionals: Individuals in specific fields who create and rely on specialized information.

·      Organizations: Businesses, nonprofits, and governmental bodies that use information for decision-making and strategy.

 

Regulatory Bodies

·      Government Regulators: Agencies that enforce laws and regulations related to media, information privacy, and intellectual property.

·      Industry Groups: Organizations that set standards and guidelines for information dissemination and ethical practices.

 

Dynamics of the Information Ecosystem

Engaging within the information ecosystem requires participating in interrelated activities. Information is generated through research, reporting, personal expression, and other methods. Verification processes, such as fact-checking and peer review, are crucial to ensure accuracy and credibility. Information is distributed through various channels, from traditional media to digital platforms. Access to information is influenced by factors such as digital divide, censorship, and platform algorithms. Individuals consume information based on personal preferences, biases, and social influences. Interpretation of information can vary widely, affecting public opinion and behavior. Consumers provide feedback through comments, shares, likes, and other forms of engagement. This interaction can influence future content production and distribution strategies. Finally, regulatory bodies and ethical standards shape the practices of information producers and distributors. Unfortunately, technological innovations occur more rapidly than regulation and ethical standards. Issues such as misinformation, data privacy, and intellectual property rights are key considerations.

 

Challenges in the Information Ecosystem

With technological advances, numerous challenges exist, including the rapid spread of mis-and dis-information, information overload, echo chambers, inequities, and increased privacy concerns. The spread of false or misleading information can have significant societal impacts, from influencing elections to public health crises. The vast amount of information can overwhelm consumers, making it difficult to discern credible sources.  Algorithms and personalized content can create echo chambers where individuals are exposed only to information that reinforces their existing beliefs. Inequities in access to technology and information resources can exacerbate social and economic disparities. The collection and use of personal data by information platforms raises significant privacy issues.

 

Artificial Intelligence and the Information Ecosystem

AI systems are reshaping the information ecosystem. Information systems play a crucial role in everyday life by influencing and reorganizing people’s thoughts, actions, social interactions, and identities. Hirvonen et al. (2023) argued that the “affordances of AI systems integrated into search engines, social media platforms, streaming services, and media generation, shape such practices in ways that may, paradoxically, result both in the increase and reduction of diversity of and access to information” (p. 1).

 

Fleming (2023) indicated that AI tools can create distorted histories and fake profiles, presenting them persuasively as facts. The stakes are escalating daily as rapid advancements in generative AI pose the risk of escalating online hate speech and misinformation to unprecedented levels. These voices are not new, but the global reach of social media allows lies and conspiracy theories to spread instantly worldwide, affecting millions, undermining trust in science, and fostering hatred potent enough to incite violence. Pernice (2019) indicates that the questions of how to (1) effectively safeguard the deliberative process of building political will and (2) preserve the legitimacy of the democratic process against various IT-driven manipulation attempts remains unresolved. 

 

Importance of a Healthy Information Ecosystem

Peterson-Salahuddin (2023) commented that concerns within information ecosystems include (1) ways information production, particularly in mainstream journalism, can lead to information inequity in its representations and (2) the dissemination and retrieval of this journalistic information via algorithmically mediated online systems, such as social media and search platforms, can replicate and reinforce information inequity within the broader information ecosystem. A healthy information ecosystem is essential for informed citizenship, effective governance, and social cohesion. It promotes:

 

1.    Informed Decision-Making: Accurate and reliable information enables individuals and organizations to make informed decisions.

 

2.    Democratic Participation: Access to diverse and credible information supports democratic processes and civic engagement.

 

3.    Social Trust: A trustworthy information ecosystem fosters social trust and cooperation.

 

4.    Innovation and Progress: Access to knowledge and information drives innovation, education, and cultural development.

 

In a prophetic comment, Nardi and O’Day (1999) indicated that the ecological metaphor conveys a “sense of urgency about the need to take control of our information ecologies, to inject our own values and needs into them so that we are not overwhelmed by some of our technological tools” (p. 49). Maintaining a healthy information ecosystem requires efforts from all stakeholders, including information producers, distributors, consumers, and regulators, to uphold standards of accuracy, fairness, and transparency.

 

References

Fleming, M. (2023, June 13). Healing Our Troubled Information Ecosystem. Medium. https://melissa-fleming.medium.com/healing-our-troubled-information-ecosystem-cf2e9e8a4bed

Hirvonen, N., Jylhä, V., Lao, Y., & Larsson, S. (2023). Artificial intelligence in the information ecosystem: Affordances for everyday information seeking. Journal of the Association of Information Science Technology, 74(12), 1–14.

Kuehn, E. F. (2022). The information ecosystem concept in information literacy: A theoretical approach and definition. Journal of the Association of Information Science Technology, 74(4), 434-443. https://doi.org/10.1002/asi.24733

Nardi, B. A., & O’Day, V. L. (1999). Information ecologies: Using technology with heart. MIT Press.

Pernice, I. (2019, March 5). Protecting the global digital information ecosystem:  A practical initiative. Internet Policy Review. https://policyreview.info/articles/news/protecting-global-digital-information-ecosystem-practical-initiative/1386

Peterson-Salahuddin, C. (2024). From information access to production: New perspectives on addressing information inequity in our digital information ecosystem. Journal of the Association for Information Science & Technology, 1. https://doi-org /10.1002/asi.24879