Gender Bias and Artificial Intelligence

Running head: GENDER BIAS AND ARTIFICIAL INTELLIGENCE
Gender Bias and Artificial Intelligence
Name of the student:
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Author Note

GENDER BIAS AND ARTIFICIAL INTELLIGENCE
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Systems thinking is critical in developing solutions to sustainability challenges
Here, by systems thinking gender bias and sustainability challenges, the issues with artificial
intelligence are considered. Having the quick development of artificial intelligence the biased
information can affect various predictions that are made by the machines. As one has the dataset of
different human decisions, this involves bias in it. It comprises of the hiring of decisions, medical
diagnosis, grading the exams for the student and approval of loans. Further, any aspect that is
demonstrated in the test, the vice and images needs the processing of information. It can be
influenced through the race, gender and cultural biases (Caliskan, Bryson and Narayanan 2017).
Here, the “wicked problem” is that though AI comprises of the potential for making decisions
ineffective and less biased way. This can never be actually a clean state. AI is just useful as the data
within it can power it. The quality relies on the way the creators can program that what, learn, decide
and think. Due to this reason, AI is able to inherit and amplify its creator’s biases. These developers
are commonly unaware of the biases created by them. Otherwise AI can use biased information.
Here, the outcomes of these technologies are life-altering (Buolamwini and Gebru 2018). The
already existing gas in workplaces has included the present gaps to promote and hire the females.
This can broaden as the biases get written unintentionally to the code of AI. Otherwise, the AI can
learn to make discrimination.
The various vital terms or ideas involving this area of concern is discussed hereafter.
Artificial Intelligence is found to disruptive in all the sectors of life. This consists of the well the
business can seek talent. Moreover, the organizations have been aware of Return Of Investment
coming from finding the proper person for a suitable task. Again, the women have been analyzed in
negative view from the other’s side. This happens as the behavioural differences granular in nature
present between the men and women. Again, colossal scale meta-analysis, on the other hand, has
shown that females have more enormous benefits as that coming to soft skills. This redisposes the

GENDER BIAS AND ARTIFICIAL INTELLIGENCE
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people in becoming more efficient leaders. They can adopt more efficient “leadership style” than
the males. Apart from this, as the leaders are chosen as per the self-awareness, coachability, integrity
and emotional intelligence. Besides, there most of the leaders who have been women instead of
being men.
The primary purpose of the following study is to evaluate the gender bias rising from the area
of artificial intelligence. The plan as per what the essay is organized is analyzed now. The study is
made around various sources that are negated to the discussion. Its analysis is presented critically
and two sides of the arguments are developed. Examples are to be provided where needed. Instead of
just making a reporting, the published work is summarized, assessed, explained and evaluated.
Ultimately, the study answers the primary concern, to what extent the statement that artificial
intelligence can five rises in gender bias or can to do away with gender bias is evaluated.
Discussion on gender bias and artificial intelligence:
To understand the scenario, the way AI can serve as the equalizer for the bias is to be
assessed. For this, the instances of artificial intelligence developing human processes are determined.
Next, the bad news regarding how the bias in AI is the barrier to the inclusion is confirmed. Then,
the instances of AI bias long with how the AI creators can be more diverse in nature is understood
from here. Further, the questions to consider are highlighted. Lastly, the AI consortiums, research
teams, along with the start-ups, are demonstrated (Osoba and Welser IV 2017).
The argument regarding AI serving as the equalizer:
AI can serve as the equalizer as it can decrease the decisions for people what has been
naturally subjected to their individual consciousness and make predictions with various algorithms
on the basis of the data. The algorithms can develop the process of decision-making ranging from
loan applications to gets hired for the job (Levendowski 2017).