To what extent has a lack of diversity influenced the development of the internet? How does this lack of diversity harm societies and individuals?

 

ARIN 2610 Assignment 2

To what extent has a lack of diversity influenced the development of the internet? How does this lack of diversity harm societies and individuals?

The development of the internet has long had various factors contributing to its path of emergence ever since its onset in the early 80s. Chief among them were white male figures (Castells, 2001,pg. 107) who dominated its evolution from a small prototype to the global powerhouse it is today. This lack of diversity has become the target of popular discourse today, with much ill content finding its way into mainstream media discourse, particularly with growing concerns about certain groups of colour and the role of women lagging behind others concerning the ever-rapid growth of the internet. The deliberate exclusion of those mentioned above by these figureheads during the cusp of the internet’s development would have disadvantaged them as the absence of participation during the formation of the internet’s unique landscape (Nakamura, 2002, pg.124) would eventually lead to a crucial lack of diverse cultures, ideologies and identities today. These ramifications are based on the actions of these white tech elites whose domination during the dawn of the internet has led to the creation of a techno-meritocratic culture (Chang, 2019, pg.14). This has negatively affected highly discriminated groups like people of colour or women across the technological sector, excluding them from everyday decisions crucial for growth and progress in today’s society. 

A crucial element to the lack of diversity within the internet would be the development of racist and sexist algorithms by developers who actively believe and partake in such discrimination against women and people of colour (Noble, 2018, pg. 56). This willingness to propagate such distasteful ideas and attitudes in a neutrally designed platform demonstrates the lack of respect these developers have for these groups. Essentially, this establishes how each time a search algorithm is made, the results generated would be more inclined toward racist and sexist articles, images and information, potentially influencing the subject in question, who would go on to absorb said information and propagate it further—reinforcing this twisted cycle of sexism and racism that continues to plague our current society. With the evidence presented, companies today need to increasingly weed out their employees who actively engage in such far-right ideology. Separating their discriminatory practices from the company’s publicly sold products and decreasing the chances of further damaging society with said foul ideals.

Additionally, Google images, arguably the world’s leading search engine, has been exposed to operate with racist algorithms that often associate people of colour with images of animals and other harmful analogies. This detrimental form of representation has long plagued the World Wide Web, with current advancements in Artificial Intelligence allowing for more information from past digitised sources of information to be scanned and learned by these inanimate researchers who absorb the bias and racism threaded through these pieces of data. The data these AI rely on are often heavily influenced by human prejudice, with numerous police departments turning to these programs to predict where future crime areas might occur through the analyses of past arrest records, welfare distribution and other low-income areas(Buranyi, 2022). Conversely, the risk of learning from human bias increases exponentially with these AI potentially directing police forces to mainly over-police black or brown neighbourhoods, often areas of high crime rates, due to the data being fed to these machines, further augmenting the inequality of society today. To that extent, AI research today has to focus on simply not teaching the same racist and biased tendencies to these programs. Instead, they should be designed to erase such negativity in our society, improving it regardless of skin colour or gender

In a culture dominated by men, the role women played in the development of the internet has been harshly underplayed. As seen with arguably the most detailed book on the internet’s evolution, ‘Inventing the Internet’ by Janet Abbate, she describes the efforts of nearly sixty men who contributed to the growth of the internet today but neglects to mention or recognise any female character that also had a hand in the development process, besides the extensive use of female models for advertisements(Abbate, 2000, pg. 12). This oversight of the role of women from the very inception of the internet can be argued to sown the seeds of discrimination and sexism as undertones for the future portrayal of women in the digital world and the eventual prevalent discourse on the digital gender divide. This divide or exclusion of women in the tech industry has instead led to increased challenges that women need to beat in their pursuit of technological literacy. This often lowers their chances of obtaining higher-paid jobs that require better qualifications such as management and leadership skills or advanced arithmetic qualities, as such positions are filled by men who primarily have better accessibility and fewer hurdles to beat in earning those skills, as mentioned earlier. Additionally, this lack of diversity in the digital industry, as seen through the exclusion of women in vital roles such as in innovation teams or as entrepreneurs (Mariagrazia, 2018, pg. 10), removes critical perspectives and other inventive ideas offered by those shunned. Emphasising how the full potential of women during the innovative process has not been fulfilled as differing viewpoints and ideas are crucial to the generation of new technology. Thus, the removal of the devil’s advocate in these crucial decision-making positions negates the chances for potential gains in future economic growth, increased revenue streams and general standard of living, negatively harming society and the individuals present within it. 

Correspondingly, while the exclusion and role of women in the digital world has been proven to be severely lacking and worrisome, women of colour as a community receive twice the amount of discrimination because of their skin colour and gender. Furthermore, the historical relationship between race and technology is rife with racist and gender biases that continue to terrorise women of colour in this modern age. As seen with Facebook’s constant removal of black women’s comments, which attempts to highlight the problems of sexism and racism present on their platform(Llansó & Lange, 2016). Such removals demonstrate Facebook’s stance on ignoring and disciplining these female users who demand justice for those frequently marginalised and discriminated against on the popular platform, damaging their ability to speak out about and campaign on problems that impact them, further reinforcing this repulsive cycle of bigotry based of race and gender impacting women of colour in the metaverse and real-world situations today. 

Conclusively, a lack of diversity did heavily influence the development of the internet, with white male tech-elites playing a predominant role in determining the future path the World Wide Web would take, sowing the subsequent seeds of racist and sexist undertones that continue to infect our society with their roots today, while simultaneously excluding women and their valuable contribution in nurturing the nascent internet to the force it is today. These pervasive roots not only extend to the discrimination of women and people of colour in the digital world but also has a firm hold on upcoming and innovative technology like Artificial Intelligence and search algorithms, which absorb copious amounts of data, rampant with bias and racist human prejudice that teaches them the means to potentially discriminate against future users based on their alleged race. To that extent, the evidence presented arguably demands drastic changes that are required for our society to be genuinely unified in mind and matter and free of any pre-existing human prejudice. Such changes would take place in education sectors, teaching the subsequent generation prejudice and bias-free lessons to break out of this omnipresent cycle of discrimination in our society. This would create opportunities for future technology to function absent of human prejudice and to achieve a fully diverse community, inclusive of all races and gender in humanity’s eternal pursuit of knowledge.

 

 

 

 

 

 

References

1. Abbate, J. (2000, pg. 12). Inventing the Internet. MIT Press
2. Buranyi, S. (2022). Rise of the racist robots – how AI is learning all our worst impulses. the Guardian. Retrieved 30 September 2022, from https://www.theguardian.com/inequality/2017/aug/08/rise-of-the-racist-robots-how-ai-is-learning-all-our-worst-impulses.
3. Castells, Manuel, ‘The Culture of the Internet’, The Internet Galaxy: Reflections on the Internet, Business, and Society, Clarendon Lectures in Management Studies (Oxford, 2002, pg. 107; online edn, Oxford Academic, 3 Oct. 2011), https://doi-org.ezproxy.library.sydney.edu.au/10.1093/acprof:oso/9780199255771.003.0003, accessed 26 Sept. 2022.
4. Chang, E. (2019, pg. 14). Brotopia: Breaking up the boys’ club of Silicon Valley. Penguin.
5. Grant, N. (2021). Google Quietly Tweaks Image Searches for Racially Diverse Results. Bloomberg.com. Retrieved 30 September 2022, from https://www.bloomberg.com/news/articles/2021-10-19/google-quietly-tweaks-image-search-for-racially-diverse-results?leadSource=uverify%20wall.
6. Llansó, E., & Lange, A. (2016). A Closer Look at the Legality of “Ethnic Affinity”. Center for Democracy and Technology. Retrieved 30 September 2022, from https://cdt.org/insights/a-closer-look-at-the-legality-of-ethnic-affinity/.
7. Metz, C. (2021). Who Is Making Sure the A.I. Machines Aren’t Racist? (Published 2021). Nytimes.com. Retrieved 30 September 2022, from https://www.nytimes.com/2021/03/15/technology/artificial-intelligence-google-bias.html.
8. Nakamura, L. (2002). Cybertypes: Race, ethnicity, and identity on the Internet(p. pg.13). Routledge.
9. Noble, Safiya U. (2018) A society, searching. In Algorithms of Oppression: How search engines reinforce racism. New York: New York University. pp. 56.
10. Squicciarini, Mariagrazia. (2018, pg. 10). Bridging the digital gender divide: Include, upskill innovate.