EDA About Gender Workforce Diversity in Tech Companies
Gender workforce diversity in a company is still the hottest topic when talking about the current social issue. As the development of society, gender workforce diversity is getting equal. But, the tech world is still a man’s world.
For any tech companies’ recruitment, skill sets should be one of the important measurements to decide who is qualified. In the group of the candidate for a tech company, it will have more male candidates than female candidates. The possibility to hire a female candidate might lower than to hire a male candidate. For the company’s benefit, hire committee people would favor someone who has closely match skilled than considering balancing gender diversity in the company. Thinking about the overall number of workers in the tech sector, there are more male workers than female workers which gives other people an impression that male is better to work in the tech sector.
From another point of view which is the same as my thought, tech companies should insist on diverse recruitment. If putting the priority on considering gender and race workforce diversity when hiring, there will be many benefits for a company after that. The company will be developed in more diverse ways since the company consists of diverse employees.
A diverse workforce can provide tangible benefits to a company besides just fulfilling legal compliance and good faith efforts. In fact, as markets expand globally being able to understand and reach out to the individual needs of people from other cultures and regions will be paramount. A multicultural, talented, and trained employee base gives companies that key advantage.
Biases I might have for this issue include motivated reasoning (seeking out information confirming what you already believe) and bias blind spot (seeing oneself as less biased than other people or to be able to identify more cognitive biases in others than in oneself.).
From the point of Shweder’s “Three Ethics” to view this social issue:
- Autonomy: “people have their own individual wants, needs, and preferences.” For a company, they want to hire more qualified men over women. For female candidates, they want to be treated fairly.
- Community: “The whole is greater than the sum of its part.” Nowadays, most of the people support and agree to gender equality especially in gender workforce diversity.
- Divinity: “life is a temporary gift to be cherished.” In the past, people think the male will handle tech-related work better than female due to their nature. As more and more women work in the tech sector, their skills are also the gift that needs to be cherished.
In order to bear on whether tech companies have a diverse gender workforce, I used a gender workforce diversity dataset in the major tech companies to do exploratory data analysis. Opponents will rely on the datasets showing male workers perform better than female workers to represent their good-faith argument. The major limitation of this dataset is timeliness. This dataset records the gender workforce diversity in key tech companies in 2016. The analysis strategy does not necessarily apply to current gender workforce diversity in these companies. The other limitation of this dataset is that it doesn’t include financial statistics of the tech companies. Since this dataset didn’t reflect a strong correlation between gender diversity and financial growth, for the analysis strategy, I cannot be 100% sure the growth in the companies’ profits is due to diversity recruitment.
The cognitive biases and backfire effects I anticipate triggering are all decision-making, belief, and behavioral biases:
- Continued influence effect — “The tendency to believe previously learned misinformation even after it has been corrected. Misinformation can still influence inferences one generates. Such as the backfire effect.” Even though, females are getting more favored over male now in the tech company. But the data still shows the percentage of male workers is higher than female workers in most of the tech companies.
- Bandwagon effect — “the tendency to do (or believe) things because many other people do (or believe) the same. Related to groupthink and herd behavior.” Most people, including my family member, still think a male would be more suited for tech job than female. Even I thought the same as these people that male might good at tech and be favored in the tech sector, I still choose to major and want to work in the tech sector. I have a tendency to believe things because many other people do the same but it doesn’t influence my action.
Due to these cognitive biases, I will view data analysis result as the one closed to the fact. I performed Exploratory Data analysis on Gender Workforce Diversity in key Tech Companies. I applied data cleaning steps to remove the blank columns and rows and replaced “-” value to “0” value to assist data analysis process.
In 2016, the percentage of male workers in major tech companies was still over female workers. The top three companies which had evenly gender distributed in 2016 were Secret, Etsy, and Pandora.
Compared to the gender workforce diversity data in 2015, the percentage of female workers on Facebook, Linkedin, Google, Apple, and eBay had increased.
Overall, the data shows that the number of male worker in tech companies is more than the number of female workers. But there was a trend that some of the tech companies hired more female.
Reference:
- List of cognitive biases -https://en.wikipedia.org/wiki/List_of_cognitive_biases
- Shweder’s “Three Ethics” — Haidt (2013). Chapter 5: Beyond WEIRD Morality, The Righteous Mind.
