Digital Divide and Crime - Cyber Criminology

Digital divide and crime examines how the unequal distribution of access to digital technology, the skills to use it effectively, and the capacity to benefit from digital participation shapes patterns of criminal victimization, criminal opportunity, criminal justice engagement, and the broader social conditions that criminological theory identifies as productive of crime. Within Cyber Criminology, the digital divide operates as a structural variable that simultaneously creates differential vulnerability to cybercrime (populations with less digital literacy may be more susceptible to certain fraud and exploitation schemes), differential criminal opportunity (populations with greater technical skill have access to more sophisticated forms of cybercrime), and differential access to the criminal justice protections and services that are increasingly mediated through digital channels (van Dijk, 2020; Hargittai, 2002). The concept has evolved from its original focus on binary access — having or lacking internet connectivity — to encompass a multi-dimensional framework incorporating quality of access, digital skills, and the capacity to translate digital engagement into social and economic benefit. This article examines the dimensions of the digital divide, their relationship to crime and victimization, the implications for criminal justice institutions, and the policy responses that address digital inequality as a criminological concern within the broader field of Criminology.

Introduction

The digital divide has been a persistent feature of American society since the internet’s transition from an academic research network to a mass communication infrastructure in the 1990s. The National Telecommunications and Information Administration’s (NTIA) 1999 report “Falling Through the Net” documented significant disparities in internet access across income, education, race, and geographic lines — disparities that, while narrowed substantially by the expansion of broadband and mobile connectivity over the subsequent two decades, have not been eliminated and have evolved in character as the nature of digital participation has changed (NTIA, 1999; Pew Research Center, 2021).

As of 2024, approximately 95 percent of American adults use the internet and 85 percent own a smartphone, suggesting that the original “access divide” has been substantially closed for most of the population (Pew Research Center, 2024). However, significant gaps persist in the quality of access (broadband versus mobile-only connectivity), the skills necessary to use digital technology effectively and safely, and the capacity to translate digital engagement into economic opportunity and social participation. These gaps are concentrated among populations that already face structural disadvantage — older adults, low-income households, rural residents, racial minorities, individuals with limited English proficiency, and persons with disabilities — creating compound vulnerabilities that affect susceptibility to digital crime, access to digital justice, and the broader social conditions that shape criminal behavior (van Dijk, 2020; Hargittai, 2002).

The criminological significance of the digital divide has received less systematic attention than its economic and educational dimensions, but the connections are substantial and multiply determined. Digital inequality structures who is victimized by cybercrime, who commits it, who reports it, who receives justice system services delivered through digital channels, and how the digitization of social and economic life creates or exacerbates the conditions that criminological theory associates with crime production. Understanding crime in the digital age requires attention to these structural inequalities alongside the analysis of specific offense categories.

Dimensions of the Digital Divide

Access, Skills, and Outcomes

Contemporary scholarship on the digital divide distinguishes multiple levels of inequality that have different criminological implications. The first-level digital divide — differences in physical access to internet connectivity and computing devices — has narrowed substantially in the United States but not disappeared. Approximately 7 percent of American adults do not use the internet, with non-use concentrated among adults over 65, those with less than a high school education, those with household incomes below $30,000, and rural residents (Pew Research Center, 2024). An additional population — estimated at 15 to 20 percent of households — relies exclusively on mobile devices for internet access, a form of connectivity that, while functional for many purposes, limits the capacity for activities that require larger screens, keyboards, and stable broadband connections (Perrin & Turner, 2019).

The second-level digital divide — differences in digital skills, literacy, and the capacity to use technology effectively — persists even among populations with comparable access. Hargittai (2002) first articulated the concept of the “second-level divide,” documenting that individuals with similar access differed substantially in their ability to search for information, evaluate online content, protect their privacy, and accomplish practical tasks online. Subsequent research has confirmed that digital skills vary significantly across age, education, income, and racial/ethnic groups, with older adults, less-educated individuals, and non-English speakers consistently demonstrating lower levels of digital literacy (van Deursen & van Dijk, 2014). These skill differences have direct criminological relevance because digital literacy affects the capacity to recognize and avoid online threats, to use protective technologies (password managers, multi-factor authentication, privacy settings), and to access the reporting and recovery processes that follow victimization.

The third-level digital divide — differences in the outcomes that individuals derive from digital engagement — reflects the interaction of access and skills with broader social and economic circumstances. Individuals with equivalent access and skills may derive different benefits from digital technology depending on their education, social networks, economic resources, and institutional connections. Wei and Hindman (2011) documented that the internet amplified existing inequalities in political knowledge and participation, with better-educated and higher-income users benefiting disproportionately from online information resources. The extension of this finding to criminal justice — the possibility that digital tools for crime prevention, victim services, and justice system engagement similarly benefit those who are already advantaged — has implications for the equitable distribution of public safety in the digital age.

Geographic and Infrastructure Disparities

The geographic dimension of the digital divide — the disparity between urban areas with strong broadband infrastructure and rural areas with limited or no broadband availability — has particular implications for both crime patterns and criminal justice service delivery. The FCC’s Broadband Deployment Report has documented that approximately 14.5 million Americans lack access to broadband internet at speeds sufficient for modern digital participation, with the deficit concentrated in rural and tribal communities (Federal Communications Commission, 2023). The Infrastructure Investment and Jobs Act of 2021 allocated $65 billion for broadband expansion, but the deployment timeline ensures that connectivity gaps will persist for years.

Rural communities affected by the broadband divide face distinctive criminal justice challenges. Law enforcement agencies in rural areas may lack the connectivity necessary for real-time information sharing, digital evidence processing, and participation in regional intelligence networks. Courts serving rural populations may be unable to implement digital case management, electronic filing, and video conferencing capabilities that urban courts increasingly rely on. Victims of cybercrime in rural areas may have limited access to the online reporting platforms and digital victim services that agencies increasingly provide through web-based channels. And the digital evidence generated by criminal activity in rural areas may be more difficult to preserve and analyze when local agencies lack the bandwidth and infrastructure necessary for digital forensic operations (Rader & Wash, 2015).

Crime Victimization and the Digital Divide

Differential Vulnerability to Cybercrime

The relationship between digital literacy and cybercrime victimization is complex and varies by offense type. For some categories of cybercrime — particularly phishing, social engineering, and tech support scams — lower digital literacy is associated with higher victimization risk, as individuals who have difficulty distinguishing legitimate from fraudulent communications, who lack awareness of common fraud tactics, and who do not employ protective technologies are more susceptible to deception. The FBI’s IC3 data documenting high loss concentrations among older adults for tech support fraud and romance scams are consistent with this pattern, as older adults on average score lower on digital literacy assessments than younger cohorts (Federal Bureau of Investigation, 2024; Holt & Bossler, 2016).

However, the relationship is not uniformly protective: for some cybercrime categories, greater digital engagement — which correlates with higher digital literacy — is associated with higher victimization risk. Individuals who conduct more transactions online, maintain more digital accounts, and share more personal information through digital channels have larger “attack surfaces” that create more opportunities for credential theft, account compromise, and identity fraud. The Bureau of Justice Statistics’ Identity Theft Supplement documented higher identity theft victimization rates among higher-income and higher-education respondents — a pattern that reflects greater digital exposure rather than lesser digital competence (Harrell, 2023). The implication is that the digital divide affects the distribution of cybercrime victimization across offense types rather than creating a simple linear relationship between digital disadvantage and victimization risk.

The intersection of the digital divide with other forms of social inequality compounds victimization disparities. Immigrants with limited English proficiency may be targeted by scams that exploit language barriers and unfamiliarity with American institutions. Elderly individuals with limited digital experience may be vulnerable to schemes that exploit their trust in authority figures and their difficulty evaluating the legitimacy of digital communications. Low-income individuals who lack the resources to absorb financial losses may suffer disproportionate harm from fraud that higher-income victims experience as minor inconvenience. These intersecting vulnerabilities — where digital disadvantage compounds existing social disadvantage — create populations whose victimization risk reflects the accumulation of multiple forms of inequality rather than any single dimension of the digital divide (Bossler & Holt, 2010; Pratt, Holtfreter, & Reisig, 2010).

Digital Exclusion and Indirect Crime Effects

The digital divide affects crime not only through direct victimization pathways but through the indirect effects of digital exclusion on the social and economic conditions that criminological theory associates with crime production. Strain theory, in both its classic (Merton, 1938) and general (Agnew, 1992) formulations, proposes that crime is produced when individuals experience gaps between their goals and the legitimate means available to achieve them. The digital divide creates such gaps by limiting access to the economic opportunities — online education, remote employment, e-commerce, digital financial services — that digital participation increasingly provides. Individuals and communities excluded from these opportunities experience relative deprivation that may contribute to criminal motivation through the mechanisms that strain theory describes (Holt & Bossler, 2016; Kshetri, 2010).

The digital divide also affects the social bonds and institutional attachments that social control theory identifies as protective against crime. As social interaction, civic participation, and institutional engagement increasingly occur through digital channels, individuals who lack digital access or skills face diminished opportunities for the social connection and institutional attachment that Hirschi’s (1969) bonding theory identifies as constraints on criminal behavior. Schools that deliver instruction through digital platforms, employers that recruit and manage through online systems, government agencies that provide services through web portals, and community organizations that coordinate through social media all create conditions in which digital exclusion translates into social exclusion — and in which the weakened bonds and reduced stakes that result may diminish the informal social control that inhibits criminal behavior.

Criminal Justice Implications

Access to Justice in a Digital System

The digitization of criminal justice services — online court systems, electronic filing, virtual hearings, digital victim services, web-based complaint portals — creates access-to-justice concerns for populations on the wrong side of the digital divide. The COVID-19 pandemic accelerated the adoption of digital justice delivery mechanisms, with courts conducting virtual hearings, probation offices implementing digital check-in systems, and victim service providers offering online counseling and support. While these innovations improved access for populations with adequate digital resources, they created barriers for those without — including defendants who could not participate effectively in virtual hearings, probationers who lacked the connectivity for digital supervision check-ins, and victims who could not access online support services (Bannon, 2021; National Center for State Courts, 2021).

The pretrial process illustrates the access-to-justice dimension of the digital divide with particular clarity. Electronic monitoring as an alternative to pretrial detention requires the monitored individual to maintain a charged smartphone or dedicated monitoring device — a requirement that may be difficult for indigent defendants to meet. Court notification systems that rely on text messages, email, or smartphone applications to remind defendants of hearing dates reduce failures to appear for defendants with reliable digital access but may increase them for defendants who lack such access. Online bail payment systems, electronic court document access, and web-based communication with public defenders all create efficiencies for digitally connected defendants while potentially disadvantaging those who must rely on in-person transactions, paper documents, and telephone communication (Bannon, 2021).

The expansion of digital services in corrections and reentry raises additional equity concerns. Incarcerated individuals who lack digital literacy — many of whom were digitally disadvantaged before incarceration and whose skills have atrophied during confinement — face additional barriers to the reentry services, employment applications, housing searches, and social service access that increasingly require digital competence. Reentry programs that incorporate digital literacy training address this gap directly, but such programs are not universally available and may not adequately prepare individuals for the digital demands of contemporary social and economic participation (Western, 2018).

Law Enforcement and Investigation Disparities

The digital divide affects law enforcement capacity as well as civilian access to justice. The disparity in digital investigation capability between federal agencies (which have invested heavily in cybercrime investigation infrastructure) and state and local agencies (many of which lack specialized digital forensic capacity) creates a two-tier system in which cybercrime cases that attract federal attention receive sophisticated investigation while those that remain at the local level may receive minimal attention. This enforcement disparity is not randomly distributed: rural communities, small municipalities, and resource-constrained jurisdictions are least likely to have the digital investigation capacity that cybercrime demands, meaning that cybercrime victims in these communities are least likely to receive effective law enforcement response (Goodison, Davis, & Jackson, 2015; National White Collar Crime Center, 2023).

The disparity extends to the data infrastructure that supports crime analysis and resource allocation. Departments with advanced data analytics capabilities — real-time crime centers, predictive policing platforms, integrated records management systems — can direct resources more precisely and respond to crime trends more rapidly than departments that rely on paper records and manual analysis. The resulting analytical divide mirrors the broader digital divide, concentrating advanced crime analysis capability in large, well-resourced agencies while leaving smaller agencies with analytical tools that have not evolved significantly in decades. Federal grant programs (including those administered by the Bureau of Justice Assistance and the Community Oriented Policing Services office) have attempted to address this disparity, but the scope of the need exceeds available funding (Hollywood, Boon, Silberglitt, Chow, & Jackson, 2015).

Theoretical Perspectives

Digital Inequality as a Criminological Variable

The integration of digital inequality into criminological theory requires treating the digital divide not as an external condition that contexts crime but as a structural variable that operates through the same mechanisms — strain, social control, routine activities, rational choice — that explain crime in non-digital contexts. The routine activities framework, adapted for digital environments by Holt and Bossler (2008), identifies digital exposure as a dimension of lifestyle that shapes victimization risk; the digital divide structures this exposure, determining who encounters what types of online risks and who possesses the digital guardianship resources to mitigate those risks. Strain theory, as applied to the digital divide, identifies digital exclusion as a source of the goal-means disjunction that produces criminal motivation. Social control theory identifies digital exclusion as a mechanism that weakens the institutional bonds — educational, economic, civic — that constrain offending.

Kshetri (2010) proposed a framework for understanding how digital inequality drives cybercrime at both individual and national levels. At the individual level, the combination of technical skill and limited legitimate opportunity that characterizes some populations — software engineers in developing economies, IT workers in regions with depressed technology sectors — creates conditions conducive to economically motivated cybercrime. At the national level, countries with high technical education rates but limited legitimate technology employment serve as cybercrime production centers, exporting criminal activity to wealthier nations through the internet’s borderless infrastructure. Lusthaus’s (2018) empirical research on Eastern European cybercrime documented precisely this dynamic, showing how structural economic conditions — not individual moral failings — drove technically skilled individuals into criminal enterprise.

The policy implication of treating digital inequality as a criminological variable is that cybercrime prevention must address the structural conditions that produce both criminal motivation and criminal vulnerability — not merely the immediate technical dimensions of digital security. Programs that expand digital access, develop digital literacy, create legitimate economic opportunity for technically skilled populations, and ensure equitable access to criminal justice services all function as crime prevention measures when understood through the lens of digital inequality as a structural driver of crime.

Intersectionality and Compound Disadvantage

The digital divide does not operate in isolation from other forms of social inequality but intersects with racial, economic, geographic, age-based, and disability-related disadvantages in ways that create compound vulnerability. An elderly, low-income, rural resident with limited English proficiency faces a qualitatively different digital risk profile than a young, affluent, urban professional — not because of any single dimension of disadvantage but because the accumulation of multiple disadvantages produces vulnerability that exceeds the sum of its parts. Intersectional analysis of the digital divide — examining how multiple dimensions of inequality interact to produce specific patterns of digital risk and digital exclusion — provides a more accurate picture of the criminological implications of digital inequality than single-variable analysis permits (Crenshaw, 1989; van Dijk, 2020).

The application of intersectional analysis to cybercrime victimization research is in its early stages but has produced initial findings consistent with the compound disadvantage hypothesis. Studies documenting the concentration of tech support fraud losses among older adults, the disproportionate targeting of immigrant communities by government impersonation scams, and the elevated cyberbullying victimization rates among LGBTQ+ youth all illustrate how multiple dimensions of social position interact to create specific victimization profiles that single-dimension analysis would miss. The development of prevention programs, victim services, and policy interventions that address these intersecting vulnerabilities requires the kind of granular, population-specific analysis that intersectional frameworks provide (Holt & Bossler, 2016; Pew Research Center, 2021).

Policy Responses

Digital Inclusion as Crime Prevention

The recognition that digital inequality functions as a structural driver of both criminal victimization and criminal opportunity supports the framing of digital inclusion initiatives — broadband expansion, digital literacy programs, device provision, accessible design — as crime prevention measures alongside their more commonly recognized educational and economic functions. The FCC’s Affordable Connectivity Program (which subsidized broadband access for low-income households before its expiration in 2024), state and local digital literacy programs, library-based technology access programs, and nonprofit digital inclusion initiatives all reduce the digital divide in ways that have crime-relevant consequences — reducing vulnerability to cybercrime, expanding access to legitimate economic opportunity, strengthening institutional connections, and improving access to criminal justice services (James, 2008; Ragnedda & Muschert, 2013).

The integration of digital literacy into cybercrime prevention strategy is supported by the situational crime prevention framework, which identifies increasing target resistance as a primary mechanism for crime reduction. Digital literacy programs that teach participants to recognize phishing attempts, employ strong authentication practices, protect personal information, and use online environments safely increase the “digital guardianship” that routine activities theory identifies as protective against victimization. The cost-effectiveness of digital literacy relative to other crime prevention investments has not been systematically evaluated, but the dual-benefit character of digital literacy programs — serving economic, educational, and crime prevention functions simultaneously — suggests favorable returns on investment when all benefits are considered (Clarke, 1997; Holt & Bossler, 2008).

Ensuring Equitable Criminal Justice Access

The equity implications of criminal justice digitization demand proactive measures to ensure that digital transformation does not create or exacerbate access-to-justice disparities. Courts that implement digital services should maintain non-digital alternatives for individuals who cannot access or effectively use digital systems. Law enforcement agencies that provide online reporting should ensure that telephone and in-person reporting options remain available and adequately staffed. Victim service providers that offer digital counseling and support should maintain capacity for in-person and telephone services. And corrections systems that implement digital supervision and reentry services should provide the training and equipment necessary for supervised individuals to participate effectively (Bannon, 2021; National Center for State Courts, 2021).

The design of digital criminal justice systems should incorporate accessibility standards that address the needs of populations affected by the digital divide — including multilingual interfaces, screen-reader compatibility for visually impaired users, plain-language content for users with limited literacy, and mobile-optimized design for users who access services exclusively through smartphones. The application of universal design principles to criminal justice technology — designing systems that are usable by the widest possible range of users without requiring adaptation — can reduce the access barriers that digital transformation creates while preserving the efficiency and convenience benefits that motivate digitization.

Conclusion

The digital divide and crime exist in a relationship that is mediated through multiple criminological mechanisms — differential victimization vulnerability, differential criminal opportunity, differential access to justice, and the structural conditions that digital inequality creates or exacerbates. Populations on the wrong side of the digital divide face compound disadvantages: greater vulnerability to certain types of cybercrime, reduced access to protective resources and criminal justice services, and the strain and weakened social bonds that digital exclusion produces in a society where digital participation is increasingly prerequisite to economic and social inclusion. The policy response to these dynamics requires treating digital inclusion as a component of crime prevention strategy, ensuring that criminal justice digitization does not create access-to-justice disparities, and developing prevention and victim service programs that address the specific needs of digitally disadvantaged populations.

The digital divide is not a static condition but an evolving feature of social structure that changes as technology, economy, and policy change. The closing of the first-level access gap has been accompanied by the emergence of second- and third-level divides that are more difficult to address through infrastructure investment alone. The continued integration of digital technology into every dimension of social, economic, and institutional life ensures that the criminological implications of digital inequality will grow in significance — making the digital divide not a peripheral concern for criminology but an increasingly central variable in the understanding of crime in contemporary society.

References

Agnew, R. (1992). Foundation for a general strain theory of crime and delinquency. Criminology, 30(1), 47–88. https://doi.org/10.1111/j.1745-9125.1992.tb01093.x
Bannon, A. (2021). Courts and COVID-19. Brennan Center for Justice.
Bossler, A. M., & Holt, T. J. (2010). The effect of self-control on victimization in the cyberworld. Journal of Criminal Justice, 38(3), 227–236. https://doi.org/10.1016/j.jcrimjus.2010.03.001
Clarke, R. V. (1997). Situational crime prevention: Successful case studies (2nd ed.). Harrow and Heston.
Crenshaw, K. (1989). Demarginalizing the intersection of race and sex. University of Chicago Legal Forum, 1989(1), 139–167.
Federal Bureau of Investigation. (2024). Internet Crime Complaint Center 2023 annual report. U.S. Department of Justice.
Federal Communications Commission. (2023). 2023 Broadband Deployment Report. https://www.fcc.gov/reports-research/reports/broadband-progress-reports
Goodison, S. E., Davis, R. C., & Jackson, B. A. (2015). Digital evidence and the U.S. criminal justice system. RAND Corporation.
Hargittai, E. (2002). Second-level digital divide: Differences in people’s online skills. First Monday, 7(4). https://doi.org/10.5210/fm.v7i4.942
Harrell, E. (2023). Victims of identity theft, 2021. Bureau of Justice Statistics, U.S. Department of Justice.
Hirschi, T. (1969). Causes of delinquency. University of California Press.
Hollywood, J. S., Boon, J. E., Silberglitt, R., Chow, B. G., & Jackson, B. A. (2015). Real-time crime centers in the field. RAND Corporation.
Holt, T. J., & Bossler, A. M. (2008). Examining the applicability of lifestyle-routine activities theory for cybercrime victimization. Deviant Behavior, 30(1), 1–25. https://doi.org/10.1080/01639620701876577
Holt, T. J., & Bossler, A. M. (2016). Cybercrime in progress. Routledge.
James, J. (2008). Digital divide complacency: Misconceptions and dangers. The Information Society, 24(1), 54–61. https://doi.org/10.1080/01972240701774816
Kshetri, N. (2010). The global cybercrime industry. Springer.
Lusthaus, J. (2018). Industry of anonymity: Inside the business of cybercrime. Harvard University Press.
Merton, R. K. (1938). Social structure and anomie. American Sociological Review, 3(5), 672–682.
National Center for State Courts. (2021). Principles for judicial administration in a digital age. https://www.ncsc.org/
National Telecommunications and Information Administration. (1999). Falling through the Net: Defining the digital divide. U.S. Department of Commerce.
National White Collar Crime Center. (2023). Annual report 2023. https://www.nw3c.org/
Perrin, A., & Turner, E. (2019). Smartphones help Blacks, Hispanics bridge some — but not all — digital gaps. Pew Research Center.
Pew Research Center. (2021). Internet/broadband fact sheet. https://www.pewresearch.org/internet/fact-sheet/internet-broadband/
Pew Research Center. (2024). Internet and technology data. https://www.pewresearch.org/internet/
Pratt, T. C., Holtfreter, K., & Reisig, M. D. (2010). Routine online activity and internet fraud targeting. Journal of Research in Crime and Delinquency, 47(3), 267–296. https://doi.org/10.1177/0022427810365903
Rader, E., & Wash, R. (2015). Identifying patterns in informal sources of security information. Journal of Cybersecurity, 1(1), 121–144. https://doi.org/10.1093/cybsec/tyv008
Ragnedda, M., & Muschert, G. W. (Eds.). (2013). The digital divide: The Internet and social inequality in international perspective. Routledge.
Van Deursen, A. J. A. M., & van Dijk, J. A. G. M. (2014). The digital divide shifts to differences in usage. New Media & Society, 16(3), 507–526. https://doi.org/10.1177/1461444813487959
Van Dijk, J. A. G. M. (2020). The network society (4th ed.). SAGE Publications.
Wei, L., & Hindman, D. B. (2011). Does the digital divide matter more? Comparing the effects of new media and old media use on the education-based knowledge gap. Mass Communication and Society, 14(2), 216–235. https://doi.org/10.1080/15205431003642707
Western, B. (2018). Homeward: Life in the year after prison. Russell Sage Foundation.

Related Articles