(DOC) SYSTEMS THINKING IS CRITICAL IN DEVELOPING SOLUTIONS TO SUSTAINABILITY CHALLENGES

Running head: SYSTEMS THINKING IS CRITICAL IN DEVELOPING SOLUTIONS TO
SUSTAINABILITY CHALLENGES
SYSTEMS THINKING IS CRITICAL IN DEVELOPING SOLUTIONS TO
SUSTAINABILITY CHALLENGES
Name of the Student
Name of the University
Author Note

SYSTEMS THINKING IS CRITICAL IN DEVELOPING SOLUTIONS TO
SUSTAINABILITY CHALLENGES
1
Table of Contents
Introduction................................................................................................................................2
Discussion..................................................................................................................................2
Conclusion..................................................................................................................................7
References..................................................................................................................................8

SYSTEMS THINKING IS CRITICAL IN DEVELOPING SOLUTIONS TO
SUSTAINABILITY CHALLENGES
2
Introduction
The research essay focuses on gender bias and artificial intelligence within the context
of system thinking a critical approach in focusing to succeed in finding solutions for
sustainability challenges. System thinking and traditional thinking are different in various
aspects. System thinking focuses on the inter relationship between various components in the
organisation (Blewitt 2013). The research essay discusses about the significance of using
system thinking for solving sustainability challenges in addressing gender bias and artificial
intelligence. A system is a set of approaches that is used to achieve a common goal.
Discussion
System thinking deals with the problems related to sustainability challenges because
this research essay paper surveys each things much closer. System thinking was founded by
Professor Jay Forrester in the year 1956. He stated that there is an observed difference in
system thinking approach and tradition approach. He described that traditional analysis
approach is an analysis where it checks what is being studied (Buolamwini 2018). System
thinking approach is an interrelationship between various constituents of the system. It cannot
be ignored which the world is adopting for transforming towards industrialisation and
towards effective outcome through globalisation. In the world of globalization, the world is
facing many complexities, this dealt by system thinking (Courtland 2015). System test in
system thinking helps to solve such problems. There are three elements in process of system
test, they are; purpose, element, and functions. Their purpose is to practice system thinking is
stated. The second part is element which work on various elements such as technology,
environmental impacts and human behaviour of system thinking (Caliskan 2017). Last part is
the function, this checks for the relationship between the different elements. These
sustainability challenges need to be addressed in different ways.

SYSTEMS THINKING IS CRITICAL IN DEVELOPING SOLUTIONS TO
SUSTAINABILITY CHALLENGES
3
The nature of system thinking makes it possible to solve such complex problems
faced by the society. In the society, women are now treated equally and they are not
considered as under- represented in the economic life. But technology makes it worse. It is
observed that Women have only 19% in the board directorship in Europe and US. This has
led to gender gap in the board room. It is also true that women have obtained higher
education qualification compared to male aspirants. This scenario is observed from two
decades in various OECD countries because of social biasness in the society (Du 2013). This
can be addressed by artificial intelligence where current data is to train the machines for
learning which is often biased many times. It is observed that with the introduction in
deployment of artificial intelligence, the biased data will then influence to predict which
machines makes. It is also observed that whenever there is a dataset of decisions taken by
human mainly includes biases (Arroyo 2013). This bias data can include loan approvals,
decisions for hiring, medical diagnosis and grading students in exam. The artificial
intelligence states that whatever is presented in text, or in voice or in image needs for
information processing which are influencing by gender, cultural and race bias.
Artificial intelligence in every action can be described as the way machines learn.
There is a subfield of Artificial Intelligence which feeds in the computer with effective sets of
data. It may be in various forms of text, or voice or images by adding to it a classifier can
describe these data. The work of artificial intelligence can be described by an example such
as if the input is in the form of image where a women working in an office, then the computer
outputs the data of that image as woman office worker (Figueiró 2105). The computer have
recognised several images as similar images and have successfully associated with the images
to the women who works in the office. In the future, with regard to new algorithms, the
computer will be then able to predict many things are issuing insurances, job candidate
screening this means replacing the human being with screen CVs and doing loan approvals.