Transforming Workplace Safety with Wearable Technology

 

By Lilian H. Hill

 

This illustration shows Mandy as she prepares for work. Before she enters her workplace, she must change into protective gear that incorporates wearable technology to monitor her personal vital signs, augment her physical abilities, scrutinize the atmosphere, and alert her to dangers.

 

Industries like construction, warehousing, and manufacturing consistently report high rates of workplace injuries and fatalities. Across these sectors, common causes of injuries include overexertion, contact with equipment, and falls. To prevent injuries and fatalities, workplaces have embraced wearable technology to promote safety and worker well-being. From smart helmets and vests to biometric trackers and augmented reality glasses, these devices provide real-time feedback, risk prevention, and data-driven safety interventions. To realize the full potential of workplace wearables and avoid unintended harms, employers and employees alike must be equipped with information literacy. This blog explores how wearables and information literacy together form a powerful alliance for building safer, ethical, and more effective workplaces.

 

The Rise of Wearable Safety Technologies

Wearable technologies are smart, body-worn devices embedded with sensors that collect and transmit data on health, behavior, and environmental exposure. In high-risk sectors such as construction, mining, logistics, and manufacturing, wearables are already being used to:

• Monitor physiological signs like heart rate, temperature, and hydration to prevent heat stress and overexertion (Cannady et al., 2024).
• Detect environmental hazards, including gas exposure, excessive noise, or harmful vibrations (Turney, 2025).
• Alert users to poor posture or dangerous lifting behavior, reducing long-term risk of musculoskeletal disorders (de Looze et al., 2016).
• Enable fall detection and emergency response, especially for lone workers or remote job sites (Chander et al., 2020).
• Augment workers’ physical abilities by reducing strain, enhancing strength, and improving endurance during repetitive or physically demanding tasks. These include exoskeletons and assistive devices (U.S. Government Accountability Office, 2024).
• Support social distancing or zone alerts, helping avoid collisions or entry into hazardous areas.

 

These tools shift safety from a reactive to a proactive model, enhancing situational awareness and reducing incident rates. Nevertheless, some challenges exist:

·      Organizations may incur significant initial expenses when purchasing and implementing wearable technologies across the workforce (U.S. Government Accountability Office, 2024).

·      Meta-analyses of electronic performance monitoring studies reveal that monitoring may negatively affect worker well-being, leading to increased work stress and decreased job satisfaction (Glavin et al., 2024).

·      Some employees perceive wearables as bulky, difficult to operate, or physically uncomfortable. For instance, research has noted that workers expressed concerns about the added weight and inconvenience associated with certain wearable devices (de Looze et al., 2016; U.S. Government Accountability Office, 2024).

·      The U.S. Equal Employment Opportunity Commission (EEOC) released a fact sheet on December 19, 2024 titled Wearables in the Workplace: Using Wearable Technologies Under Federal Employment Discrimination Laws. It divided risks from wearables into three categories: collecting information from wearables; using information from wearables; and reasonable accommodations for wearables (O’Brien, 2025). As of July 24, 2025, that fact sheet is no longer available on the EEOC website.

 

The Role of Information Literacy

The integration of wearable technology with information literacy creates a powerful synergy that enhances workplace safety while empowering workers to engage critically with the technologies that monitor them. Their effectiveness depends on the user’s ability to interpret data accurately and act on it appropriately. Information literacy equips workers and supervisors with the skills to assess the reliability, relevance, and implications of the data collected, reducing the likelihood of misinterpretation or misuse (Glavin et al., 2024).

 

When workers understand how wearable data is collected, stored, and used, they are more likely to participate in safety initiatives with trust and agency. This helps shift the narrative from surveillance and control to transparency and collaboration. Informed workers can question unethical practices, ensure consent, and advocate for data protection policies, helping employers balance innovation with responsibility (Glavin et al., 2024).

 

Together, wearable tech and information literacy reduce risk and promote a culture of ethical decision-making and shared responsibility in the workplace. Here’s how:

 

1. Understanding What the Data Means

Wearables generate real-time biometric and environmental data. Without the ability to interpret it correctly, workers may misread alerts or overlook risk signals. Information literacy helps workers contextualize data and understand its implications.

For example, a spike in heart rate might indicate brisk movement or overexertion. Recognizing the difference prevents unnecessary panic or misreporting.

 

2. Questioning the Source and Use of Data

Information-literate individuals ask:

• What data is being collected?
• Who has access to it?
• How will it be used?
• How is it secured?

This is crucial when wearable data can inform safety interventions and performance reviews, insurance claims, or disciplinary actions (Donovan et al., 2022).

 

3. Ensuring Ethical Consent and Privacy

With biometric and location tracking often built in, wearables pose risks to worker privacy. Informed consent, central to ethical technology use, requires information literacy including the ability to read privacy agreements, understand surveillance implications, and make informed choices about participation.

 

4. Collaborating in a Data-Driven Culture

As employers increasingly rely on predictive analytics and AI-generated safety dashboards, information literacy prepares workers to:

• Recognize algorithmic bias
• Participate in safety decision-making
• Demand transparency in digital monitoring systems

Without these skills, workers may be passive subjects of surveillance, rather than active participants in shaping safe and equitable working conditions.

 

Moving Forward: A Dual Investment

To maximize the benefits of workplace wearables, organizations must invest not only in technology, but also in human skills. This means:

• Training workers and supervisors in information literacy principles
• Establishing transparent data governance policies
• Fostering participatory safety cultures, where workers help shape how data is used

By aligning wearable innovation with information literacy, we can move toward ethical, empowering, and truly smart safety systems.

 

References

Argento, Z. M., Kelley, B. J., O’Brien, S. P. (2025, January 2). EEOC fact sheet on wearable technologies indicates growing concern over employee monitoring. Littler. https://www.littler.com/news-analysis/asap/eeoc-fact-sheet-wearable-technologies-indicates-growing-concern-over-employee

Cannady, R., Warner, C., Yoder, A. Miller, J., Crosby, K., Elswick, D., & Kintziger, K. W. (2024), The implications of real-time and wearable technology use for occupational heat stress: A scoping review. Safety Science, 177, 106600. https://doi.org/10.1016/j.ssci.2024.106600.

Chander, H., Burch, R. F., Talegaonkar, P., Saucier, D., Luczak, T., Ball, J. E., Turner, A., Kodithuwakku Arachchige, S. N. K., Carroll, W., Smith, B. K., Knight, A., & Prabhu, R. K. (2020). Wearable stretch sensors for human movement monitoring and fall detection in ergonomics. International Journal of Environmental Research and Public Health, 17(10), 3554. https://doi.org/10.3390/ijerph17103554

de Looze, M. P., Bosch, T., Krause, F., Stadler, K. S., & O'Sullivan, L. W. (2016). Exoskeletons for industrial application and their potential effects on physical work load. Ergonomics, 59(5), 671–681. https://doi.org/10.1080/00140139.2015.1081988

Glavin, P., Bierman, A., & Schieman, S. (2024). Private eyes, they see your every move: Workplace surveillance and worker well-being. Social Currents, 11(4), 327-345. https://doi.org/10.1177/23294965241228874

Turney, T. (2025, March 25). Wearable tech: Safer workplaces of the future. Industrial Hygiene in the Workplace. https://industrialhygienepub.com/wearables/wearable-tech-safer-workplaces-of-the-future/

 U.S. Government Accountability Office (2024, March 4). Wearable technologies in the workplace. GAO-24-107303. https://www.gao.gov/products/gao-24-107303

 

Healthcare Wearables and Information Literacy: Navigating Data for Better Health

 

 

By Lilian H. Hill

 

In today’s digital age, health is increasingly data-driven. Dehghani and Dangelico (2018) define healthcare wearables as portable, embedded computers designed to be worn on the body. McDowell (2025) comments that a “dizzying array of devices” is available to “track physical activity, heart rate, blood pressure, temperature, blood oxygen, glucose levels, stress, sleep patterns, and movement” (p. 28). These include smartwatches, smart rings, armbands, smart eyeglasses, ingestible devices, chest-strap monitors, and clothing embedded with sensors. Wearable health technology is not confined to specialized medical devices for patient care. Major tech companies, such as Apple, have developed wearables designed for health-conscious consumers (Kang & Exworthy, 2022). Nearly a third of adults wear a device to monitor their health and fitness. The global market for wearable healthcare devices is projected to reach nearly $70 billion by 2028, with annual growth expected to surpass 11% (Eastwood, 2024).

 

Wearable devices and artificial intelligence (AI) collaborate to enhance health and wellness monitoring by collecting real-time data, including heart rate, sleep patterns, and activity levels, and utilizing AI to analyze it for patterns and insights. AI enables wearables to provide personalized feedback, detect anomalies such as irregular heart rhythms, and support the management of chronic diseases. This combination also plays a key role in remote healthcare, allowing providers to monitor patients more effectively and reduce the need for in-person visits (Moore et al., 2021). Together, wearables and AI transform raw data into meaningful and actionable information.

 

Categories of Wearable Technology

Wearable devices can be categorized into two main types: consumer-grade and medical-grade wearables. The latter are approved by the U.S. Food and Drug Administration, or FDA, which requires that medical-grade wearables undergo clinical research and meet stringent standards. They require a doctor’s prescription, and many are equipped with an app or receiver to transmit information to the physician. Consumer-grade wearables include smartwatches, fitness trackers, and sleep monitors. These devices typically measure data such as heart rate, steps, calories burned, sleep quality, and sometimes blood oxygen or ECG readings. Unlike clinical or medical-grade devices, consumer wearables are not intended for diagnosis or treatment; however, they offer users real-time feedback and insights to support their wellness and lifestyle goals.

 

Consumer-Grade Wearables

Information literacy is now essential to digital health. While they have become popular tools in personal wellness routines, using consumer-grade wearables effectively requires more than just strapping on a device. It requires the ability to critically assess, evaluate, and use data to make informed decisions. It enables individuals to navigate the complex flow of personal health data generated by wearables. For example, a fitness tracker may tell you that your heart rate variability is lower than average or that your sleep quality declined last night. McDowell (2025) notes that wearable devices may not be suitable for everyone. Although fluctuations in heart rate or blood pressure are normal, continuous monitoring can provoke anxiety in some individuals. When users lack the information literacy skills needed to interpret data patterns or assess the reliability of the information, these readings may cause confusion or stress (Piwek et al., 2016).

 

Consumer-grade wearables are improving in accuracy, but their performance may vary across different types and brands (McDowell, 2025). Algorithms can oversimplify complex health conditions, and not all devices meet clinical accuracy standards. Individuals need to understand the difference between consumer-grade tools and medical diagnostics and know when to question or supplement data with professional input. Information-literate users recognize that data alone is not knowledge. They contextualize numbers, look for patterns over time, and consider additional sources of information, including conversations with healthcare providers, to make informed judgments about their well-being (Lupton, 2014).

 

Medical-Grade Wearables

Medical-grade wearable devices support the management of chronic conditions such as diabetes, cardiovascular disease, and sleep disorders by delivering real-time data to individuals and their healthcare providers. Technological advances have made these devices more compact and less intrusive than they were before. They enhance patient engagement by providing tools and information that enable individuals to track their health and make informed decisions. Through remote monitoring and early detection of issues, wearables also have the potential to lower hospital readmission rates and reduce overall healthcare expenses.

 

Healthcare professionals increasingly rely on patients' wearable data for remote monitoring. This makes it even more important that individuals know how to read and report their data accurately. Patients who can summarize trends, ask informed questions, and detect irregularities are better equipped to collaborate with their providers and take an active role in managing their health (Kvedar et al., 2016). Advances in telemedicine have improved access to medical care for patients in rural or remote areas. Wearable technology also contributes significantly by supporting virtual care environments such as telemedicine and helping to ease the demand on hospitals and clinics (LaBoone & Marques, 2024). Information literacy, in this context, becomes a bridge between raw data and effective care. A growing body of research indicates that wearable devices can empower individuals by supporting diagnosis, promoting behavior change, and enabling self-monitoring (Kang & Exworthy, 2022).

 

Data Collected by Wearable Devices

Wearables collect vast amounts of data through sensors that track metrics such as steps, sleep stages, oxygen saturation, and heart rhythm. While these devices make health data more accessible, they also raise important questions:

·      What exactly is being measured?

·      How accurate is the data?

·      What external factors might affect these readings?

·      Who has access to and control of the data?

 

These questions point to broader concerns about data privacy and individual autonomy in the age of digital health (Marr, 2020). As wearables continuously collect and transmit sensitive physiological data, users often have limited knowledge of how their information is stored, shared, or used by third parties such as app developers, insurers, or employers. The lack of transparency in data governance raises ethical issues about consent and control. Without explicit regulatory protections, individuals risk losing ownership of their biometric information, which can be monetized or used in ways that impact their access to services or employment opportunities. Therefore, discussions around wearables must extend beyond functionality and convenience to include advocacy for stronger privacy policies, clearer user rights, and mechanisms for individuals to manage their health data meaningfully.

 

Adult Health Learning

Wearables enhance healthcare education by making learning timely, relevant, and integrated into everyday health practices. They enable real-time, personalized education focused on health management and wellness. For example, adults using fitness trackers, glucose monitors, or heart rate sensors receive immediate feedback that helps them understand how lifestyle choices impact their health, promoting self-directed learning aligned with adult learning principles. In chronic disease management, wearables support ongoing education by providing data that encourages patients to adjust behaviors and adhere to treatment plans. Users often find themselves researching the meaning of new metrics or using apps that recommend changes to diet, exercise, or sleep hygiene. The more informed the user, the more likely they are to seek out trustworthy sources, compare conflicting claims, and avoid misinformation. In this way, wearable technology can promote lifelong learning about health and wellness.

 

Conclusions

As wearable technology continues to evolve, it will play an even more prominent role in preventive medicine and personal health. Devices are becoming increasingly sophisticated, featuring AI-driven recommendations, real-time alerts, and seamless integration with electronic health records. However, the real value of this technology lies in the user’s ability to understand and act on the information it provides. Healthcare wearables represent a promising frontier in personal health management, but only when paired with strong information literacy. To benefit from information generated by wearables, individuals must develop the skills to interpret data critically, seek reliable sources, evaluate the credibility of health claims, and make informed decisions. Ultimately, health is not just about collecting data; it is about making sense of it.

 

References

Dehghani M, Kim K, Dangelico R. (2018). Will smartwatches last? Factors contributing to intention to keep using smart wearable technology. Telematics Informatics, 35(2), 480–90. doi: 10.1016/j.tele.2018.01.007. doi: 10.1016/j.tele.2018.01.007.

Eastwood, B. (2024, June 21). The latest trends in wearable technology for healthcare. CDO Times. https://cdotimes.com/2024/06/21/the-latest-trends-in-wearable-technology-for-healthcare-healthtech-magazine/

Kang, H. S., & Exworthy, M. (2022). Wearing the future-wearables to empower users to take greater responsibility for their health and care: Scoping review. JMIR Mhealth Uhealth, 10(7), e35684. https://doi.org/10.2196/35684

Kvedar, J., Fogel, A. L., & Elenko, E. (2016). Digital medicine's march on chronic disease. Nature Biotechnology, 34(3), 239–246. https://doi.org/10.1038/nbt.3495

LaBoone, P. A., & Marques, O. (2024). Overview of the future impact of wearables and artificial intelligence in healthcare workflows and technology. International Journal of Information Management Data Insights, 4(2), 100294. https://doi.org/10.1016/j.jjimei.2024

Lupton, D. (2014). Health promotion in the digital era: A critical commentary. Health Promotion International, 30(1), 174–183. https://doi.org/10.1093/heapro/dau091

Marr, B. (2020). The future of wearable technology in healthcare. Forbes. https://www.forbes.com/sites/bernardmarr/2020/01/13/the-future-of-wearable-technology-in-healthcare/

McDowell, J. D. (2025. July/August). Wear your health on your sleeve. AARP Bulletin.

Moore K, O'Shea E, Kenny L, Barton J, Tedesco S, Sica M, Crowe C, Alamäki A, Condell J, Nordström A, Timmons S, (2021). Older adults’ experiences with using wearable devices: Qualitative systematic review and meta-synthesis.
JMIR Mhealth Uhealth, 9(6):e23832 https://doi,org/10.2196/23832

 Piwek, L., Ellis, D. A., Andrews, S., & Joinson, A. (2016). The rise of consumer health wearables: Promises and barriers. PLOS Medicine, 13(2), e1001953. https://doi.org/10.1371/journal.pmed.1001953

Historical Literacy and Civic Responsibility

 

By Lilian H. Hill

"Those who cannot remember the past are condemned to repeat it."
— George Santayana, The Life of Reason: The Phases of Human Progress (1905)

This quote is often paraphrased as, “Those who do not learn history are doomed to repeat it.” It emphasizes the idea that historical understanding is essential to learn from past errors to prevent their recurrence, a central argument for promoting historical literacy in civic education. Historical literacy is more than memorizing names, dates, and events. It involves understanding how knowledge about the past is constructed, how evidence is used to support interpretations, and how history influences the present and future. This form of literacy is essential for developing critical, informed, and empathetic citizens in a democratic society.

 

Core Components of Historical Literacy

Historical literacy encompasses a range of skills that enable individuals to think critically about the past. Chronological thinking involves understanding historical time, sequencing events, and recognizing patterns of change and continuity over time (National Center for History in the Schools [NCHS], 1996). Historical comprehension refers to the ability to interpret primary and secondary sources, distinguish between fact and interpretation, and identify the perspective and context of each source (Wineburg, 2001). Historical analysis and interpretation include comparing different historical narratives, analyzing cause and effect, and considering multiple perspectives and contingencies (Seixas & Morton, 2013). Historical empathy involves understanding the beliefs, values, and motivations of people in the past while avoiding presentism, the tendency to interpret past events through the lens of contemporary norms and values (Endacott & Brooks, 2013).

 

The use of historical evidence requires evaluating sources for credibility, reliability, bias, and corroboration to construct informed interpretations (Wineburg, 1991). Historical significance refers to judging which events, people, or developments are important and understanding the reasons why they matter within broader historical contexts (Seixas, 1994). Lastly, historical revisionism entails the reinterpretation of past events, often to incorporate new evidence or perspectives and develop more nuanced understandings of the past. While this process is a legitimate part of historical scholarship, the term is sometimes misused to describe intentional distortions or denial of historical facts (Evans, 1997).

 

Historical Literacy as a Civic Tool

Historical literacy empowers individuals to navigate contemporary issues by drawing on historical precedents and insights. For example, understanding the history of voting rights and immigration policy in the United States provides a critical lens through which to evaluate current debates on these topics. Scholars such as Sam Wineburg (2001) emphasize that historical literacy is crucial for countering simplistic or nationalistic narratives. He argues that to be historically literate means learning to question and critically examine the past, rather than simply accepting it at face value. This interrogative stance is foundational for civic engagement, especially in pluralistic societies where multiple, sometimes conflicting, histories coexist.

 

In the 21st century, digital technology has transformed the way historical information is accessed and disseminated. While this democratizes access, it also creates challenges, such as the proliferation of disinformation, historical revisionism, and algorithm-driven echo chambers. Historian and media literacy scholars alike emphasize the importance of lateral reading, a practice that involves verifying sources by consulting multiple credible references across various platforms (Wineburg & McGrew, 2017). Thus, historical literacy now includes digital historical literacy, the ability to critically evaluate online historical content, including images, videos, and interactive platforms, which may be edited or decontextualized to promote specific agendas.

 

Implications for Education and Society

Historical literacy is not about revering the past, but rather about understanding it with nuance, critical thinking, and empathy (Wineburg, 2001). It equips individuals to think independently, recognize how the past informs the present, and act with greater awareness in the public sphere. A historically literate public is essential for a functioning democracy. Historical literacy fosters acceptance and understanding by exposing individuals to diverse narratives and cultural histories, encouraging empathy and respect across differences (Barton & Levstik, 2004; Seixas & Morton, 2013). Historical literacy builds resistance to propaganda by teaching people how historical narratives can be manipulated to serve political agendas (Wineburg, 2001).

 

Historical literacy is deeply connected to civic literacy, as understanding the past enables individuals to engage more thoughtfully in democratic processes, recognize patterns of injustice, and make informed decisions about civic life. Social responsibility is promoted by helping individuals connect past injustices to contemporary inequities (VanSledright, 2008). Promoting historical literacy involves encouraging inquiry-based learning, facilitating debates over primary source documents, and fostering critical engagement with public history as represented in museums, monuments, and media portrayals (Levstik & Barton, 2011; Epstein, 2009). Through these practices, students and citizens develop the tools to question dominant narratives and actively participate in democratic life. In a world saturated with conflicting narratives and contested memories, historical literacy is more than an academic skill; it is a civic imperative (Seixas, 2000; Noddings, 2013).

 

References

Barton, K. C., & Levstik, L. S. (2004). Teaching history for the common good. Lawrence Erlbaum Associates.

Endacott, J. L., & Brooks, S. (2013). An updated theoretical and practical model for promoting historical empathy. Social Studies Research and Practice, 8(1), 41–58. https://doi.org/10.1108/SSRP-01-2013-B0004

Epstein, T. L. (2009). Interpreting national history: Race, identity, and pedagogy in classrooms and communities. Routledge.

Evans, R. J. (1997). In defense of history. W. W. Norton & Company.

Levstik, L. S., & Barton, K. C. (2011). Doing history: Investigating with children in elementary and middle schools (4th ed.). Routledge.

National Center for History in the Schools. (1996). National standards for history: Basic edition. University of California, Los Angeles.

Noddings, N. (2013). Education and democracy in the 21st century. Teachers College Press.

Santayana, G. (1905, 2018). The life of reason: The phases of human progress. Pantianos Classics.

Seixas, P. (1994). Students’ understanding of historical significance. Theory and Research in Social Education, 22(3), 281–304. https://doi.org/10.1080/00933104.1994.10505746

Seixas, P. (2000). Schweigen! die Kinder! Or, does postmodern history have a place in the schools? In P. N. Stearns, P. Seixas, & S. Wineburg (Eds.), Knowing, teaching, and learning history: National and international perspectives (pp. 19–37). New York University Press.

Seixas, P., & Morton, T. (2013). The big six: Historical thinking concepts. Nelson Education.

Wineburg, S. (1991). Historical problem solving: A study of the cognitive processes used in the evaluation of documentary and pictorial evidence. Journal of Educational Psychology, 83(1), 73–87. https://doi.org/10.1037/0022-0663.83.1.73

Wineburg, S. (2001). Historical thinking and other unnatural acts: Charting the future of teaching the past. Temple University Press.

Wineburg, S., & McGrew, S. (2017). Lateral reading and the nature of expertise: Reading less and learning more when evaluating digital information. Teachers College Record, 119(13), 1–40.

 

Information Warfare, Virtual Politics, and Narrative Dominance

 

By Lilian H. Hill

As the Internet becomes more advanced, it is giving rise to new challenges for democracy. Social media platforms sort users into like-minded groups, forming echo chambers that reinforce existing beliefs. Pariser (2011) states that in a world shaped by personalization, we are shown news that aligns with our preferences and reinforces our existing beliefs. Because these filters operate invisibly, we may remain unaware of what information is excluded. This dynamic contributes to the growing disconnect between individuals with differing political views, making mutual understanding more difficult. It also enables extremist groups to harness these platforms for harmful purposes. While diverse opinions are inherent to politics, social media has created a fast-paced, ever-evolving space where political discord is continuously generated (De’Alba, 2024).

Information warfare is the strategic use of information to influence, disrupt, or manipulate public opinion, decision-making, or infrastructure, often in service of political, military, or economic goals. Instead of physical force, information warfare targets the cognitive and informational environments of adversaries. Pai (2024) comments that information warfare has become central to international politics in the Information Age in which society is shaped by the creation, use, and impact of information. According to Rid (2020), information warfare aims to undermine trust between individuals and institutions. It includes tactics like propaganda, disinformation, cyberattacks, and psychological operations. In today’s digital era, state and non-state actors use social media, news platforms, and digital technologies to conduct disinformation campaigns, often blurring the lines between truth and manipulation (Pomerantsev, 2019).

Virtual politics refers to the strategic use of digital technologies, including social media, artificial intelligence, and data analytics, to manipulate political perceptions, simulate democratic engagement, and manipulate public opinion. Originally coined in the post-Soviet context, the term captured how political elites created fake parties, opposition figures, and civil society groups to manufacture the illusion of pluralism and democratic process (Krastev, 2006). Contemporary virtual politics functions through multiple mechanisms. One tactic is the creation of simulated political actors and events, where governments or interest groups establish fake NGOs, social movements, or social media accounts to fragment opposition or feign civic engagement. These simulations create an illusion of public discourse while neutralizing dissent (Krastev, 2006). A contemporary example is Russia’s promotion of fake social media accounts and organizations during the 2016 U.S. presidential election. Russian operatives created false personas, Facebook pages, Twitter accounts, and even staged events that appeared to be organized by grassroots American groups (Mueller, 2019).

Another core feature is the widespread use of disinformation and memetic warfare. Ascott (2020) notes that while internet memes may appear harmless, memetic warfare involves the deliberate circulation of false or misleading content to polarize populations or erode trust in institutions (Marwick & Lewis, 2017). A popular meme, Pepe the Frog is a green anthropomorphic frog usually portrayed with a humanoid body wearing a blue T-shirt. Originally apolitical, it expressed simple emotions like sadness and joy. The symbol was appropriated by the alt-right (alternate-right), a far-right white nationalist movement. During the 2016 U.S. presidential election, some alt-right and white nationalist groups co-opted Pepe for propaganda, using edited versions to spread hateful or extremist messages. Another common meme, the NPC Wojak is an expressionless, grey-headed figure with a blank stare, a triangular nose, and a neutral mouth. NPC is an acronym for non-player characters, a term derived from video games. The NPC Wojak meme first appeared in 2018 to mock groups seen as conformist. The NPC meme gained traction before the 2018 U.S. midterm elections amid right-wing outrage over alleged social media censorship. Conservatives used it to portray liberals as unthinking “bots,” meaning individuals who lack internal monologue, unquestioningly accept authority, engage in groupthink, or adopt positions that reflect conformity and obedience.

The most insidious aspect of virtual politics lies in data-driven psychological manipulation. Social media and other platforms collect vast amounts of personal data that is used for targeted marketing and psychological persuasion. This shift from persuasion to manipulation erodes the foundation of informed democratic decision-making. Moreover, the performative nature of online political engagement often reduces participation to reactive, emotionally charged interactions, such as likes, shares, and outrage, instead of reasoned deliberation or civic dialogue (Sunstein, 2017).

 

Narrative Dominance and Virtual Politics

Narrative dominance refers to the phenomenon in which a particular storyline, interpretation, or framework becomes the prevailing lens through which events and realities are understood and perceived. It reflects the power to shape meaning, frame discourse, and control the perceived legitimacy of knowledge or truth. A contemporary example of narrative dominance is China’s global media campaign to reshape global perception of its handling of the COVID-19 pandemic, deflect blame, criticize Western failures, spread alternative origin theories, and suppress dissenting domestic narratives (Zhou & Zhang, 2021).

 

In media, politics, and culture, dominant narratives can marginalize alternative viewpoints and solidify ideological control. In the digital age, virtual politics is a key arena in which narrative dominance is exercised and contested. Virtual politics involves the creation and circulation of curated realities that prioritize perception over policy or truth and thrive on controlling emotional responses and engagement.

 

Virtual Politics and Democracy

The consequences of information warfare, virtual politics, and narrative dominance for democracy are profound. Together, they result in diminished trust in public institutions and blur distinctions between reality and fiction. As digital platforms become the dominant venue for political communication, traditional forms of accountability —such as investigative journalism, public debate, and civic literacy —are weakened. In authoritarian regimes, virtual politics serve as a tool for controlling dissent while projecting a false image of openness. Even in democratic societies, the same tools sway elections, fragment publics, and distort political will (Bennett & Livingston, 2018). The challenge for democratic societies, then, is to develop regulatory, technological, and civic strategies to counteract the manipulative aspects of virtual politics without undermining legitimate political speech.

 

Narrative dominance in virtual politics involves creating an environment in which alternative realities are delegitimized or neglected. Narrative dominance reflects a shift from a politics of substance to a politics of spectacle and emotional resonance. Understanding this dynamic is essential for analyzing contemporary media landscapes, political behavior, and the challenges of democratic resilience in the digital era. Virtual politics is not merely about politics taking place online; it represents a fundamental transformation in how political reality is constructed, experienced, and contested. Because public life is mediated by screens, algorithms, and data, understanding the mechanics of virtual politics is critical to preserving democratic integrity and fostering genuine political engagement.

 

References

Ascott, T. (2020, February 16). How memes are becoming the new frontier of information warfare. The Strategist. https://www.aspistrategist.org.au/how-memes-are-becoming-the-new-frontier-of-information-warfare/

Bennett, W. L., & Livingston, S. (2018). The disinformation order: Disruptive communication and the decline of democratic institutions. European Journal of Communication, 33(2), 122–139. https://doi.org/10.1177/0267323118760317

De’Alba, L. M. (2024, April 15). The virtual realities of politics: Entrenched narratives and political entertainment in the age of social media. Uttryck Magazine. https://www.uttryckmagazine.com/2024/04/15/the-virtual-realities-of-politics-entrenched-narratives-and-political-entertainment-in-the-age-of-social-media/

Gerbaudo, P. (2018). The digital party: Political organisation and online democracy. Pluto Press.

Isaak, J., & Hanna, M. J. (2018). User data privacy: Facebook, Cambridge Analytica, and privacy protection. Computer, 51(8), 56–59. https://doi.org/10.1109/MC.2018.3191268

Krastev, I. (2006). Virtual politics: Faking democracy in the post-Soviet world. In Post-Soviet Affairs, 22(1), 63–67.

Marwick, A., & Lewis, R. (2017). Media manipulation and disinformation online. Data & Society Research Institute. https://datasociety.net/library/media-manipulation-and-disinfo-online/

Mueller, R. S. (2019). Report on the investigation into Russian interference in the 2016 presidential election. U.S. Department of Justice.

Pariser, E. (2011). The filter bubble: What the internet is hiding from you. Penguin.

Pomerantsev, P. (2019). This is not propaganda: Adventures in the war against reality. PublicAffairs.

Rid, T. (2020). Active measures: The secret history of disinformation and political warfare. Farrar, Straus and Giroux.

Sunstein, C. R. (2017). #Republic: Divided democracy in the age of social media. Princeton University Press.

Zhou, L., & Zhang, Y. (2021). China’s global propaganda push: COVID-19 and the strategic use of narrative. Journal of Contemporary China, 30(130), 611–628.

 

 

Data Literacy and Data Justice

 

 

By Lilian H. Hill

Data literacy is a fundamental skill set that entails the ability to read, write, understand, and communicate data in context effectively. It empowers individuals and organizations to derive meaning from data, make informed decisions, and solve problems. Data literacy is an interdisciplinary competency that integrates elements of mathematics, science, and information technology. Data literacy requires understanding data sources and constructs, analytical methods, and AI techniques (Stobierski, 2021). Data literacy is not about being a data scientist; it's about having a general understanding of data concepts and how to apply them effectively. 

The rapid expansion of digital information in today’s world has triggered a significant shift in how knowledge and skills are valued, making the ability to understand, interpret, and extract meaningful insights from data a vital competency. Schenck and Duschl (2024) comment that data increasingly drive decisions across all sectors of society, and promoting data literacy has become essential to preparing individuals to participate actively and thoughtfully in the digital age. In education, this changing environment calls for a reimagined approach that goes beyond conventional literacies, positioning data literacy as a core skill necessary for future success.

Skills of Data Literacy

Building data literacy skills is an essential process in today’s data-driven world. It begins with learning the fundamentals of data, including understanding different types such as quantitative versus qualitative data, and recognizing basic statistical concepts like mean, median, standard deviation, and correlation. Familiarity with common data formats (e.g., CSV, JSON, Excel files) lays the groundwork for deeper analytical work (Mandinach & Gummer, 2016). Introductory courses from platforms like Coursera or edX, as well as open-access tutorials and videos, offer accessible entry points for building this foundational knowledge.

To apply data literacy practically, individuals should become familiar with commonly used tools. Beginners might start with spreadsheets like Microsoft Excel or Google Sheets to learn basic data manipulation and chart creation. As comfort grows, they can explore more advanced platforms such as Tableau or Power BI for data visualization or learn coding languages like Python (using libraries such as Pandas) and SQL for deeper analysis. Practicing with real-world data available from open sources like government portals or World Bank Open Data helps bridge theory and application.

A crucial next step is learning to interpret data visualizations. Charts, graphs, and dashboards are the primary means of communicating data, and understanding how to read them critically is crucial for avoiding misinterpretation. Tools such as Gapminder or data stories from Our World in Data provide engaging ways to practice understanding patterns and trends visually (Knaflic, 2015).

Equally important is the development of critical thinking skills about data itself. This means asking questions such as: Where did the data come from? Is the sample size sufficient? Is there potential for bias or missing information? Cultivating skepticism and inquiry when reviewing data sources helps prevent the spread and influence of misinformation (Bhargava et al., 2021).

Communication is another fundamental part of data literacy. It’s not enough to understand data. The ability to clearly and ethically explain insights is equally important. This involves selecting appropriate visuals, simplifying complex ideas, and telling compelling data-driven stories (Knaflic, 2015). Platforms like Flourish or Datawrapper can help users experiment with design and narrative techniques that enhance data communication.

Ultimately, data literacy must be maintained and continually updated through ongoing learning. Schenk and Duschl (2024) call for a transformative change in educational practices, recommending a move away from formal, theory-first instruction toward contextual, inquiry-based learning. This change is viewed as crucial for equipping students with the practical skills necessary to apply data literacy effectively in real-world situations. Data literacy is not only a technical skill but also a civic and ethical one, enabling people to make informed decisions and engage in democratic processes.

Data Literacy and Social Justice

One of the core connections between big data analytics and data literacy lies in the ability to manage and critically evaluate the quality and relevance of data. Big data involves massive, unstructured datasets sourced from sensors, social media, transactional records, and more. This can introduce biases, inconsistencies, and privacy risks. Data-literate individuals are better equipped to ask critical questions: Where does the data come from? Is it representative? What algorithms are being applied? Who might be harmed by this analysis? These questions are especially important in fields like healthcare, criminal justice, education, and marketing, where big data can amplify existing societal inequities if not interpreted responsibly (boyd & Crawford, 2012).

Data justice aims to ensure that data practices do not perpetuate or exacerbate structural inequities and social injustices, but instead promote human rights, dignity, and democratic participation (Dencik & Sanchez-Monedero, 2022). The increasing dependence on data-driven technologies in all aspects of social life is a driving force behind major shifts in science, government, business, and civil society. While these changes are frequently promoted for their potential to improve efficiency and decision-making, they also introduce profound societal challenges. Data justice refers to the fair and equitable treatment of individuals and communities in the collection, analysis, use, and governance of data. It emphasizes that data are not neutral. How data are gathered, interpreted, and applied often reflect existing power structures, biases, and inequalities. Data justice has emerged as a critical framework for addressing these challenges through a lens centered on social justice. For example, if a predictive policing algorithm unfairly targets neighborhoods based on biased crime data, it may lead to over-policing in communities of color. A data justice approach would question the assumptions behind the data, advocate for community oversight, and explore alternative models that prioritize community safety without reinforcing systemic bias.

Finally, data literacy supports democratic participation in a big data society. As governments and corporations increasingly rely on data to guide decisions, including pandemic response, urban planning, and surveillance, citizens need the skills to engage with data-related policies, challenge unfair uses, and advocate for transparency and accountability. Without broad-based data literacy, power becomes concentrated in the hands of a few data-literate experts and institutions, potentially reinforcing social and economic inequalities (D’Ignazio & Klein, 2020).

References

Bhargava, R., Kadouaki, R., Bhargava, E., Castro, G., & D’Ignazio, C. (2021). Data murals: Using the arts to build data literacy. The Journal of Community Informatics, 17(1), 1–15. https://doi.org/10.15353/joci.v17i1.4602

boyd, d., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878

Dencik, L., & Sanchez-Monedero, J. (2022). Data justice. Internet Policy Review, 11(1). https://doi.org/10.14763/2022.1.1615

D’Ignazio, C., & Klein, L. F. (2020). Data feminism. MIT Press.

Jones, B. (2025). Data literacy fundamentals: Understanding the power and value of data (2^nd ed.). Data Literacy Press.

Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. Wiley.

Mandinach, E. B., & Gummer, E. S. (2016). Data literacy for educators: Making it count in teacher preparation and practice. Teachers College Press.

Schenck, K. E., & Duschl, R. A. (2024). Context, language, and technology in data literacy. Routledge Open Research, 3(19).

            (https://doi.org/10.12688/routledgeopenres.18160.1)

Stobierski, T. (2021). Data literacy: An introduction for business. Harvard Business Review Online. https://online.hbs.edu/blog/post/data-literacy

Taylor, L. (2017). What is data justice? The case for connecting digital rights and freedoms globally. Big Data & Society, 4(2). https://doi.org/10.1177/2053951717736335