Internet was based on the idea that there would be multiple independent networks of rather arbitrary design in the historical aspects (Kleinrock et al., 2009). The original envisions of the internet can be articulated as multidimensional, sharing, and could be easily approached by every user. The rapid development of the internet nowadays has satisfied most of the fine imaginaries, however, the controversy about diversity online is still intense. The lack of diversity on the internet constitutes serious problems in the history of the internet that continue to present in today’s world which including gender discrimination, stereotypes, racial discrimination and so on… This essay is aiming to demonstrate how lack of diversity influenced the development of the internet and how it harms societies and individuals.
Gender & Racial Discrimination
As white men continue to dominate at executive and non-executive levels across technology companies operating today (Chang, 2019), it relatively presents that women and people of color are placed at a weak stage as they have been excluded from making decisions in the technological system which are critical in contemporary society and economy. According to Pew Research Center, women or black and Hispanic workers remain underrepresented in the science, technology, engineering and math (STEM) workforce compared with their share of all workers, including in computing jobs (Richard Fry et al., n.d.). This situation leads to a third of women, compared with 19% of men, saying there is more gender discrimination against women in tech than in other industries, and similarly, four-in-ten blacks and 35% of Hispanics claimed that there is more discrimination against them in the tech industry than in other industries, compared with 11% of whites (Kim Parker & Cary Funk, n.d.). It is then deeply troubling under the white male-dominated enterprise because many of the tech companies and their managers have shaped an internal culture in which they ignore women’s requests and normalize the gender inequality. As the big techs play important roles online, those distorted concepts spread on the internet rapidly and abundantly. Real harm has resulted from the lack of diversity.
For example, as shown in the graph, individually, there are sizeable pay gaps between women and men in STEM jobs as well as across racial and ethnic groups. The pay gaps will eventually lead to negative stereotypes such as men do better in tech areas than women or women are subservient to men, the economic inequality also displays that STEM industries are lacking understanding of women employees, especially for Black or Hispanic women in the workplace. The huge imbalance in pay and power has created conditions for abuse and sexual harassment in the workplace. Furthermore, as the internet evolved, one of the major problems was how to propagate the changes to software (Kleinrock et al., 2009), the software will be closed-minded and masculism if no women members participate in the progress of developing the software. Say it with exaggerating, this phenomenon resembles the ‘Mad Men Era’ in which men are prior to women, our civilization will step backwards without listening to different races, kinds, and genders’ voices.
AI Bias and Fairness
Lack of diversity online takes a negative influence on the development of the internet can be shown in the algorithmic bias. Even though algorithms are just math and code, they are created by humans and use our data. Training data can reveal hidden biases in society, for instance, as the video (CrashCourse, 2019) states, if an AI was trained on recent news articles or books, the word ‘nurse’ is more likely to associate with a “female,” while the word “programmer” is more likely to refer to a ‘male.’. This is happening in Google image search as well, in which ‘programmer’ mostly resulted in ‘men’ while ‘nurse’ largely shows ‘women’. Those hidden biases in the data reinforce gender stereotypes and may be offensive to a male nurse or a female computer programmer. Another example is the unbalanced classes in training data, many facial recognition AI is trained on data that includes more examples of white peoples’ faces than other races. Some face detectors cannot even recognize one’s face just because of their dark skin, or eyes are not big enough. This is somehow unfair and frustrating for the groups who with color or have atypical features to spend more time on identity verification. Including different kinds of age, gender and race’s data online can help train the AI to be comparably fairer and more respectful to everyone.
Political Deliberation & Neglect
Political deliberation, that is conversation among diverse people that tackles problems and aims towards solutions, is essential to public opinion and democratic practice (Jennifer, 2003). However, lack of diversity is simply against the concept of political deliberation, which becomes unachievable if the society receives merely the homophily ideas. For instance, Weibo’s recent trendy topic is that sanitary pads are banned from selling in railway stations by the Chinese government, which a girl passenger shared her experience that she was not able to find sanitary products on the high-speed train but it generally sells everything from food to souvenirs (Li, 2022). She appealed to the government to sell period pads on the railway, adding that “many girls have had such embarrassing moments like I did.”, however after Weibo posted this new, many male netizens blame the women by claiming that period pads are private items, and she should be prepared. The rigid idea of menstruation by Chinese male netizens has inevitable connections because of the lack of diversity, female’s demands are being neglected and excluded online. In this situation, the lack of diversity made society become inhumanity and indifferent to women. Another example is the neglect of aged groups, while countless online applications have been published, the aged groups may be excluded and get confused by the complicated operations and short-cuts design. In this case, to make and promote the applications or software to be more inclusive, increasing diversity in internet governance and the tech industry is a necessary move, the views of the relatively small groups are indeed important as well. While all the voices have been heard, the software or applications will be optimized as more comprehensive and more convenient. In addition, it will then push and boosts the positive economic growth of the internet market.
In conclusion, lack of diversity in tech industries will cause serious problems of gender and racial discrimination in the workplace; lack of diversity online will trigger and bring negative influence on machine learning systems which then will reflect biased information; lastly, it violates the political deliberation and neglects feelings of those who are in the minority groups like the aged group, most service software, and applications only targeting the young market which lacks concerning the old. It is essential for both individuals and societies to absorb various advice from diverse internet participants and then there will be chances to improve. Cultural differences also need to be viewed and understood, the ultimate challenge for us all, is to build the internet which is capable to overcome the ‘fragmentation’ and ‘polarization’ that threaten the body of societies (Lusoli & Turner, 2020, p. 242).
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Chang, E. (2019, March 5). Brotopia: Breaking Up the Boys’ Club of Silicon Valley (Reprint). Portfolio.
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Kim Parker & Cary Funk. (n.d.). Women are more concerned than men about gender discrimination in tech industry. In Pew Research Center. https://www.pewresearch.org/fact-tank/2017/10/10/women-are-more-concerned-than-men-about-gender-discrimination-in-tech-industry/
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Li, X. (2022, September 19). China Railway Slammed for Not Selling Menstrual Products On Board. SixthTone. Retrieved October 4, 2022, from https://www.sixthtone.com/news/1011245/china-railway-slammed-for-not-selling-menstrual-products-on-board
Lusoli, A., & Turner, F. (2020, July 16). “It’s an Ongoing Bromance”: Counterculture and Cyberculture in Silicon Valley—An Interview with Fred Turner. Journal of Management Inquiry, 30(2), 235–242. https://doi.org/10.1177/1056492620941075
Richard Fry, Brian Kennedy, & Cary Funk. (n.d.). STEM Jobs See Uneven Progress in Increasing Gender, Racial and Ethnic Diversity. In Pew Research Center. https://www.pewresearch.org/science/2021/04/01/stem-jobs-see-uneven-progress-in-increasing-gender-racial-and-ethnic-diversity/
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