Systems Thinking and Gender Equality in Sustainable Business Planning & Strategy

This research report explores the role of systems thinking in addressing gender equality issues in sustainable business planning and strategy. It discusses the importance of systems thinking over traditional thinking, the challenges of sustainable development, and the impact of artificial intelligence on gender equality. The report also provides suggestions and recommendations for creating sustainable solutions to gender biases.

SUSTAINABLE
BUSINESS PLANNING
& STRATEGY

Table of Contents
Introduction........................................................................................................................1
Key Definitions...................................................................................................................1
Problem Statement............................................................................................................2
Literature Review...............................................................................................................2
Importance of Systems Thinking over Traditional Thinking...........................................3
Systems Thinking and Sustainable Challenges.............................................................3
Systems thinking and Gender Equality..........................................................................3
Gender equality and Artificial intelligence......................................................................4
Findings.............................................................................................................................5
Suggestions and Recommendations.................................................................................5
Conclusion.........................................................................................................................6
References.........................................................................................................................7

Introduction
Systems approach has been the new method of thinking. This technique has out-landed
the traditional methods. More than a necessity, the system’s approach came up with
time, as a revolution in the thought design patterns. Systems thinking is a pattern of
thought process by linking and connecting smaller parts and pieces of the problem to
attain a solution. The major advantage the system’s process provides is the opportunity
to develop solutions with a sustainable approach. The systems thinking is a very fruitful
tool for attaining solutions to certain wicked and alarming concerns in the everyday
scenarios (Andersen, 2014). One such concern of gender biases is under review in this
research report, where the artificial intelligence systems can act as a solution provider
to the globally existing gender discrimination problem.
Key Definitions
Systems thinking is a process of analysis of the holistic picture by fragmenting the parts
of the feature under review and understanding the interrelationship between them. A
vast majority of subjects undergo research with the approach, namely, medicinal,
educational, environmental, political, social, economic and human resourcing (Änelmen,
2010). Systems thinking consists of two elements that are analyzed under the overall
process. One is reinforcement process and the other is balancing process.
Reinforcement alters the stability of the system by some componential enlargement
behavior, whereas balancing process outruns the change by making appropriate
changes. Therefore, an equilibrium is maintained.
Today’s society deals with a large number of issues that have been existent from a very
long course of time and its effects and impacts are still existing in the overall society.
Such long-term issues fall under the wicked category, which hampers the society at
large (Bashir, et al., 2013). Many approaches have been identified to reduce and
eliminate the behavioral impact of the problems but only few sustainable solutions exist
that actually helps in removal of the concerns. One such existent issue comes from the
gender discrimination behavior in the society. This behavior restricts the development
Page 1 of 12
Sustainable Business Planning & Strategy

and downgrades the process of evolution by its wicked attributes of inequality towards
people, directed by the gender.
Problem Statement
Systems thinking is a process of analysis of the holistic picture by fragmenting the parts
of the feature under review and understanding the interrelationship between them. A
vast majority of subjects undergo research with the approach, namely, medicinal,
educational, environmental, political, social, economic and human resourcing (Änelmen,
2010). Systems thinking consists of two elements that are analyzed under the overall
process. One is the reinforcement process and the other is balancing process.
Reinforcement alters the stability of the system by some componential enlargement
behavior, whereas balancing process outruns the change by making appropriate
changes. Therefore, an equilibrium is maintained.
Today’s society deals with a large number of issues that have been existent from a very
long course of time and its effects and impacts are still existing in the overall society.
Such long-term issues fall under the wicked category, which hampers the society at
large (Bashir, et al., 2013). Many approaches have been identified to reduce and
eliminate the behavioral impact of the problems but only a few sustainable solutions
exist that helps in the removal of the concerns. One such existent issue comes from the
gender discrimination behavior in the society. This behavior restricts the development
and downgrades the process of evolution by its wicked attributes of inequality towards
people, directed by the gender.
Literature Review
Literature review is an insight into the studies and researches conducted earlier on the
topics relative to the current research. These helps in viewing the necessary
background information that a research must be aware of. Not only dies a researcher
gains knowledge about previous efforts, but also gets a view of the earlier methods,
process, suggested solutions and recommendations, that have been presented to deal
with the concerns.
Page 2 of 12
Sustainable Business Planning & Strategy

Importance of Systems Thinking over Traditional Thinking
Research and analysis indicate that the systems approach breaks down the concern
into constituent parts and then collectively forms a solution to the holistic picture. These
solutions consider a variety of factors correlated to the problem. The consideration of
macro factors itself makes the system approach more useful and reliable, as many
variables are put under the microscope for leading to a conclusion. On the other hand,
the traditional approach is more theoretical and remains closely associated with only the
problem at the core, thereby making only the micro variables under analysis (Richmond,
1993). This restricts the view of research and presents a less practical scenario. Also, it
has been observed that solutions generated from the systems thinking process have
proximity to becoming solutions to sustainability challenges and succeed in attaining the
intended goal. Previous efforts based on traditional techniques have failed to achieve
the desired goal, says Kim (2017).
Systems Thinking and Sustainable Challenges
Sustainable challenges are a bit complex than the regular challenges. Thee are also
termed as adaptive challenges, as there are no fixed or set procedure to deal with eth
concern. Moreover, the suitability challenges are not restricted to a region, but rather
have a global expanse (Kirkpatrick, 2016). Global challenges like these require a more
focused and multi-directional approach that is driven by evolving and self-analyzing
techniques that can improve from its failures. The diversification due to a global platform
and the variety available in the content is a primary reason that justifies the systems
approach to handle and perform on the sustainable challenges.
Systems thinking and Gender Equality
Gender equality is a measure of the fairness in gender, without any biases in any
activity that might be considered. A system thinking is a necessary factor in the process,
as only a broad scope attempt can help maintain and regulates the various processes
that witness the gender biases (Devine, 1989). To measure the gender equality, there
are three measuring indices, that highlight the existing gender balance. These indices
are the United Nation’s Human Development Index, the inequality-adjusted Human
Development Index and the United Nations Gender Inequality Index. These indices
Page 3 of 12
Sustainable Business Planning & Strategy

present a global picture of discrimination and its relative effects for all the countries in
the world (Sielbeck-Bowen, et al., 2002). Below is a pictorial representation of the
measurement procedure of the United Nations with Gender Inequality Index
measurement.
Fig1: Gender Inequality Index by UN
Source: http://hdr.undp.org/en/content/gender-inequality-index-gii
Gender equality and Artificial intelligence
Computers and technology have been laying down the new foundation of growth and
evolution for mankind. The use of high-end devices, automated mechanisms are the
rapid expansion factors. Computational and mechanical thinking has not changed its
shape to more complex, and real-time data. The analysis is now catered with data sets
of vast demographics and variety, along with a giant set of associated meta-data is also
used (Onat, et al., 2017). Computers interpret the data at unimaginable speeds and are
now even capable of suggesting alternatives. These intelligent systems have entered in
everyday life. But it is also necessary to teach these systems the right information or
share with the right learnings on which the intelligent machine works. If the data or
learning shared with the system is inaccurate and filled with discriminatory notes either
in learning or through any other way, the recommendations would flow from the same
set (Kranzberg, 1986). Also, as these complex systems are self-evolving and learns
from its previous inferences, the learning of cases from discrimination and the pattern
can be retained in their memory for a long time. Therefore, with artificial intelligence
Page 4 of 12
Sustainable Business Planning & Strategy

systems in place, it is very crucial to deliver work and results that are discrimination-
free, gender-equal and fair in every aspect.
The involvement of Natural Language Processing and Machine Learning has grown in
the recent time. NLPs are the voice intelligent systems that take instructions over voice
and performs a certain action, like Siri and Cortana. The natural language processing
includes, but is not restricted to, modeling, training data, resourcing and others (Rush &
Collins, 2012). Complex systems can extrapolate information and can sometimes
amplify the prediction generated from the biased information entered in the language
processing systems. Therefore, the role of artificial intelligence is very crucial in creating
a solution to the long-term sustainable challenge solution to the problem of gender
biases.
Findings
A recent report from the World’s Economic Forum for Global Gender Gap, indicated that
only 22% of the professionals working in the technology of artificial intelligence are
women. Further a step into technology, the Ernst and Young company indicates the rise
of artificial intelligence into customer relationship management to have an exponential
growth. A magnified 95% of all customer interactions are depicted to be with the use of
AI by 2025 (Teigland, 2019). The upcoming time would also see over 30% companies
harnessing the power given by AI. Very soon, the chatbots will start responding to all
possible questions based on the learnings from the AI and self-evolving algorithms. If
these revolutionary advancements are fed with biased and discriminatory data, the
same content will be amplified and extrapolated, increasing the gender instability curve
in the global professions (Befani, et al., 2015).
A researcher, Gartner (2016) predicted that by the year 2022, over 85% of the world’s
automated machines would produce incorrect outcomes, based on the biased and
unfair data fed into the machine learning process.
Page 5 of 12
Sustainable Business Planning & Strategy

Suggestions and Recommendations
In order to create a solution for a sustainability challenge, that can be viable and
responsive, as well as successful in bringing the desired change, artificial intelligence
can play an important role. The first and foremost is, that the artificial intelligence
systems can be relied on and trusted with the fact that they can bring in the change the
world needs to see. Creating awareness to stop feeding the learning systems with
unintentional or intentional biased data can be the primary step in enabling the change.
Skill enhancement and literacy for the existing anomalies in the overall system can be
brought to light and reminded regularly (Review, 2017). In many areas, what is
observed is that the gender biases is self-inflicted and not pushed, because it is never
brought o light that the cation can be unfair or discriminatory. And the last suggestion
would be to actually fairly treat and respect women in all aspects whether professionally
or personally.
Conclusion
The wicked problem of gender biases is a vastly existing and unfortunate principles that
are being followed. Intentionally or unintentionally, these principles set the stage for a
continuous follow-up without bringing any change in the existing societal structure. The
concern of finding a solution to this sustainable challenge is more than a necessity now.
A systems approach by considering the holistic picture is a remedial plan of elimination
of discrimination from society (Anderson & Anderson, 2007). The research report
presented here highlights the key definitions used along with focus on the existing
problem. The report also looks into research done in the past as a literature review, for
reference and understanding purposes. Findings based on secondary information and
suggestions derived in the same indicate artificial intelligence and its importance in
changing the society for women's empowerment and equal opportunity.
Page 6 of 12
Sustainable Business Planning & Strategy

References
Andersen, O. W., 2014. Some thoughts on development evaluation processes.. IDS
Bulletin, 46(6), pp. 77-84.
Anderson, M. & Anderson, S., 2007. ‘Machine ethics: creating an ethical intelligent
agent’. AI Magazine, 28(4), pp. 15-58.
Änelmen, E., 2010. Implementing system thinking in the design of a learning
enviornment. Innovation and Creativity in Education, 2(2), pp. 501-506.
Bashir, N. Y. et al., 2013. The ironic impact of activists: Negative stereotypes reduce
social change influence. Eur. J. Soc. Psychol., Volume 43, p. 614–626.
Befani, B., Ramalingam, B. & Stern, E., 2015. Introduction – towards systemic
approaches to evaluation and impact. IDS Bulletin, 46(1), pp. 1-6.
Devine, P. G., 1989. ‘Stereotypes and prejudice: Their automatic and IMPLICIT
ASSOCIATION TEST 1479 controlled components’. Journal of Personality and Social
Psychology, Volume 56, p. 5–18.
Easterbrook, S., 2017. From Computational Thinking to Systems Thinking: A
conceptual toolkit for sustainability computing.. [Online]
Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.641.2473
[Accessed 31 August 2019].
Garcia, M., 2016. ‘Racist in the machine: The disturbing implications of algorithmic bias’.
World Policy Journal, 33(4), pp. 111-117.
Gartner, R. & Sterzing, P., 2016. Gender microaggressions as a gateway to sexual
harassment and sexual assault: Expanding the conceptualization of youth sexual
violence. Affilia, 31(4), pp. 491-503.
kim, s., 2017. Can Systems Thinking Actually Solve Sustainability Challenges? Part 1,
The Diagnosis.. [Online]
Page 7 of 12
Sustainable Business Planning & Strategy

Available at: https://erb.umich.edu/2012/06/04/systems-thinking-part-1/
[Accessed 31 August 2019].
Kirkpatrick, K., 2016. ‘Battling algorithmic bias’. Communications of the ACM, 59(10), p.
16–17.
Kranzberg, M., 1986. ‘Technology and History: “Kranzberg’s Laws’. Technology and
Culture, 27(3), p. 544–560.
Onat, N., Kucukvar, M., Halog, A. & Cloutier, S., 2017. Systems Thinking for Life Cycle
Sustainability Assessment: A Review of Recent Developments, Applications, and Future
Perspectives. Sustainability, 9(5), p. 706.
Pennington, J., Socher, R. & Manning, C. D., 2014. ‘Glove: Global vectors for word
representation’. EMNLP, Volume 14, p. 1532–1543.
Review, H. L., 2017. State v. Loomis.. [Online]
Available at: https://harvardlawreview.org/2017/03/state-v-loomis/
[Accessed 31 August 2019].
Richmond, B., 1993. Systems thinking: Critical thinking skills for the 1990s and beyond.
System Dynamics Review, 9(2), pp. 113-133.
Rush, A. M. & Collins, M., 2012. A Tutorial on Dual Decomposition and Lagrangian
Relaxation for Inference in Natural Language Processing.. Journal of Artificial
Intelligence Research, Volume 45, pp. 305-362.
Sielbeck-Bowen, K. A. et al., 2002. Exploring feminist evaluation: the ground from which
we rise. New Directions for Evaluation, 2002(96), pp. 3-8.
Teigland, J. L., 2019. Why we need to solve the issue of gender bias before AI makes it
worse. [Online]
Available at: https://www.ey.com/en_gl/wef/why-we-need-to-solve-the-issue-of-gender-
bias-before-ai-makes-it
[Accessed 31 August 2019].
Page 8 of 12
Sustainable Business Planning & Strategy

Page 9 of 12
Sustainable Business Planning & Strategy