The development of the Internet has actively promoted the visualization of global information, promoted the popularization of information sharing, and reduced the cost of information transmission. While the Internet allows for free speech and campaigns against injustice, the current culture is plagued by “online racism, hate speech, harassment, and fake news.” (Flew, 2019) There is no denying that the Internet is widening gaps and inequalities in gender, race, and social class.
- Structural biases of the early Internet
According to United Nations, Economic and Social Commission for Western Asia (UNESCWA)，structural inequality is defined as a condition where one category of people has attributed an unequal status with other categories of people. Some of the structural biases from the early Internet continue to influence modern digital culture. Before the advent of the Internet, racism and sexism existed and formed stereotypes in the public mind. As technology advances and it becomes easier to publish and receive information, the Internet becomes the catalyst. Cultures that remain primarily white, male, and middle-class – not alert to structural inequalities. Social discrimination against women and race, the algorithmic bias of artificial intelligence, and ‘Bro-culture’ unsympathetic to minorities, e.g. inequalities within Silicon Valley, all bring a set of prejudices that still haunt us today. (Lusoli et al., 2021)
- Gender inequality
Society still holds a variety of sexist ideas about women，and the Internet has exacerbated gender inequality. People living as minority groups under the influence of a majority culture, such as people of color and sexual minorities in the United States，are often whims by majorities and other commercial influences. (Noble, 2018) Due to information, search preferences are determined by clicks and the commercial value of paid advertising. The technology and social render the pornification of Black women a top search result, naturalizing them as sexual objects so effortlessly. When Safiya Noble did a Google search using these keywords, the first page of results was always associated with pornography. Noble (2018) indicated that not only the black girls’ ，Asian girls, Asian Indian girls, Latina girls, White girls, and so, are all not faring well in google search. But conversely, Google searches for “professional” almost invariably turn up white men in suits and ties, and Google’s dominant narrative bluntly reflects the hegemonic frameworks and perceptions that women and people of color often reject. According to the research, even though women comprise more than half of Internet users, their voices and perspectives are not as loud and do not have as much impact online as men. The Internet gives the male gaze privileges and marginalizes women as objects. Levels of racism and sexist hierarchies’ discrimination through the pornification of women, structural inequalities of society are being reproduced on the Internet. Black women have been locked out of Silicon Valley venture capital and broader participation. (Noble, 2018) Those marginalized people do not have the economic, political, and social capital to withstand the misrepresentation consequences.
- The Chief culprit—Algorithms
Cathy O’Neil points out that ‘The math-powered applications powering the data economy were based on choices made by fallible human beings.’ An algorithm doesn’t exist in a vacuum, to be judged solely on its mathematical properties and nothing else – it’s intended to be used for actual real human purposes, and therefore should be designed and judged in that context. Yet many of these models encode human biases, misconceptions, and biases into software systems that increasingly govern our lives. The Algorithms are opaque judged by mathematicians and computer scientists, even if wrong or harmful, is indisputable or appealable. They tend to punish the poor and oppressed while making the rich richer. In ‘Algorithms of Oppression,’ Safiya Noble finds old stereotypes persist in new media. To take systematic racism as an example, Google Black People and the prompts that follow are probably mostly negative, Such as crime, anger, poverty, etc. (Noble, 2018)
The search results show systematic prejudice because the racial discrimination that black people encounter in the American context not only comes from individual ideological prejudice but is scattered in all aspects. “Potential exists for artificial intelligence to detect and embed discriminatory bias in human behavior.” Such a view was made by Hanrahan also. (Hanrahan, 2020) Information monopolies like Google have the ability to prioritize web search results on different topics for their business interests. In the face of Silicon Valley’s rampant denial of the impact of its technology on racialized people, it is difficult to develop an understanding of their practices and appropriate interventions. The group identity triggered by keyword search reveals the profound power differences reflected in contemporary American social, political and economic life. Algorithms created by people unsubtle shapes inequality and intensifies the impact of structural inequalities.
- Digital divided inequality
Digital division refers to the gap between those who have access to new forms of information technology and those who do not. Traditionally disadvantaged citizens are similarly disadvantaged on the Internet, for example, limited access to technology, restricted use opportunities, and lacking important digital skills. (Lutz, 2019) Vulnerable groups and those who are marginalized have difficulties in accessing, which exacerbates development inequalities. Make the gap more pronounced.
The use of ICTs has grown with the development of the Internet and WEB 2.0. The vast majority of citizens in industrialized countries use it to access information; the digital geography divide has developed in developing countries where most households have access to high-speed Internet. (Kerras et al., 2020) This has further widened the social divide and the gap between rich and poor countries. The UN reveals that 80% of the population of developed countries uses technologies, compared to only 50% in developing countries and 20% in the least developed countries. (Kerras et al., 2020) It is a serious matter for those who are currently behind in internet access, for they cannot enjoy the many benefits of being wired and barriers to participating fully in society’s economy. Nevertheless, all evidence suggests a significant gender gap in access to and use of ICT. Globally, men are about 12 percent more likely than women to use the Internet in developing countries. (Souter, 2018) This is the result of deep-rooted ideas about the social-economic role of women in society. ICTs are empowering technology. If we are not careful, it could exacerbate inequalities in other areas of society. Increasing the gap in information and resources, health and education, rather than closing it. (Souter, 2018)
- Action and Vision
There are still some areas that help correct gender inequality, such as online activism like the #MeToo movement
Ai-Jen Poo, executive director of the National Domestic Workers Alliance, said, “#MeToo is a movement of survivors and their supporters, powered by courage, determined to end sexual violence and harassment.” (North, 2019) It has been aimed at raising awareness about the prevalence and harmful effects of sexual violence. More and more vulnerable groups stand up to speak for themselves, safeguard their rights and interests, and narrow structural inequality through the Internet. The existence of unequal rights and opportunities among individuals creates a split in status, which constitutes the concept of structural inequality. Internet users from around the world have intensified the discussion about these structural inequalities. It shows that these problems of discrimination on the Internet can be improved. Therefore, the Internet can be called a double-edged sword. The Internet still has major challenges to overcome. Reducing these inequalities will go a long way and require more policy or regulatory support.
Reference
Flew, T. (2019). Guarding the gatekeepers: Trust, truth and digital platforms. Griffith Review, 64, 94-103.
Hanrahan, C. (2020, December 2). Job recruitment algorithms can amplify unconscious bias favouring men, new research finds. ABC News. Retrieved from https://www.abc.net.au/news/2020-12-02/job-recruitment-algorithms-can-have-bias-against-women/12938870
Kerras, H., Sánchez-Navarro, J. L., López-Becerra, E. I., & de-Miguel Gómez, M. D. (2020). The impact of the gender digital divide on sustainable development: Comparative analysis between the european union and the maghreb. Sustainability (Basel, Switzerland), 12(8), 3347–. https://doi.org/10.3390/SU12083347
Lutz, C. Digital inequalities in the age of artificial intelligence and big data. Hum Behav & Emerg Tech. 2019; 1: 141– 148. https://doi.org/10.1002/hbe2.140
Noble, S. U. (2018). Algorithms of oppression : How search engines reinforce racism. ProQuest Ebook Central https://ebookcentral-proquest-com.ezproxy.library.sydney.edu.au
Souter, D. (2018). Inside the Information Society: ICTs, the Internet and structural inequality. Association for Progressive Communications. https://www.apc.org/en/blog/inside-information-society-icts-internet-and-structural-inequality
Does the Internet improve or expand structural inequality? by Shi Mengyao is licensed under a Creative Commons Attribution 4.0 International License.