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Amishi Agrawal‘s Article

Newest Student Article
Magnetoreception Based Navigation in Migratory Avian Species Using Quantum Entanglement
Amishi Agrawal

05 September 2022 | Download
Student's Published Works


Given that the first artificial navigation system was proposed less than a century ago (1956), the presence of a natural compass in species so old seems rather intriguing. The current quantum hypothesis to explain avian migration utilises a photosensitive pigment called cryptochrome which is responsive to very small changes in the geomagnetic field. This theory is based on the fluctuations of various entangled pairs as singlets and triplets, leading to some specific reactions which govern the bird’s flight trajectory. This natural compass is also unique in that it is not impaired by anomalous magnetic polarity readings due to artificial magnets. While ultimately there is an alternate perspective that suggests a more chemical based approach, the entanglement theory seems clearer at this point as analysed in this paper. In this research we explore the respective hypotheses presented by Henrik Morrison, and Schulten & Ritz. The Radical Spin model proposed by Schulten and Ritz forms the basis of the hypothesis as it suggests a correlation between the radical states and the production of certain proteins which might be the ultimate source of electrochemical signals that operate the bird during its flight time. Further, a corresponding idea of magnetovision is also proposed which highlights the possibility of explicit vision of the field to specific bird species.

Keywords: Quantum Entanglement, Avian Migration, Cryptochrome, Radical Spin Model, Magnetoreception, European Robin


Various theories have been developed to explain the phenomenon of magnetoreception in migratory avian species, particularly the European Robin (Paul Kerlinger, 2008). The quantum perspective however stands out because it suggests a possible link between teleportation, an idea that was once purely fictional, being integrated in the concepts of entanglement to explain the formation of singlet-triplet pairs (Kai et al., 2020). With the latest advancements in this theory, it has become apparent that by implementing the fundamentals of quantum mechanics in nature (in this case, the Robin), we might be able to develop simulations of various quantum based applications artificially too (Ryszard et al., 2009).

Materials and Methods

A recent experiment conducted by biologist Henrik Morrison (2018) used behavioural observations on a European Robin which was released in an artificial space with a manually controlled gravitational field and lined with a scratch sensitive paper. The Robin’s responses (in terms of the mean direction of motion) to specific changes in the field were recorded, after which, an opaque mask was used to cover one of her eyes. The same readings were then repeated with the mask. The entire process was then repeated after covering the other eye. Throughout the experiment, the robin’s behavior was only observed under different circumstances, not induced or manipulated. At any point of noticeable discomfort, all variables were returned to normals to ensure safety of the bird.

All Figures and tables used for explaining relevant concepts were developed by the author of this paper using information from relevant academic sources, which have been cited in the reference list.


When the Robin was set free under normal conditions, it was observed that she typically moved in the ideal direction of the migratory path with respect to the field’s set up. However, upon the introduction of visual obstruction, the antagonistic part of her brain shut down and showed signs of impairment in terms of magnetoreception.


In the recent studies conducted by biologist Henrik Morrison (2018), the behavioural changes in a European Robin were observed to identify any correlation between its visual senses and magnetoreception. It was seen that its sense of geomagnetic fields was impaired when either one of its eyes were covered with an opaque mask.

Initially, the idea of magnetoreception in migratory birds was supported by two distinct theories, one dealing with chemically triggered chain reactions among protein molecules while the other proposed a quantum perspective (Sönke et al., 2005). While both hypothesis involve a receptor called cryptochrome (Cry4), the biochemical perspective introduces another molecule, namely iodopsin (Haijia et al., 2020). However, the limitations posed by iodopsin’s lack of responsiveness to changes in light makes this hypothesis seem unclear at this point (Haijia et al., 2020). Thus, this paper will be analysing the theory based on quantum entanglement to express the magnetoreception-based navigation system in migratory birds.

As the bird uses its eyes to see, the visual input recorded is replicated twice (Ortega, 2005). While one set is used for social aspects of her life (such as finding food, nourishing eggs, or finding mates), the other set is utilised for magnetoreception inside a complex quantum based mechanism (Ortega, 2005). According to this theory, the transduction pathway created between Cry4 and the entangled photons is constructed alongside 6 distinct genes GNAT2, LWS (iodopsin), GNG10, KCNV2, RBP and RGR (Qin et al., 2016).

As a consequence of these chain reactions Cry4-FADH is released and the concentration of Cry4-FAD in the retina’s photoreceptor cells is diluted resulting in the imbalance of the current equilibrium and creating a new one. This feedback loop drives a continuous stream of electrochemical signals which dominate the ongoing wing movement patterns and create a new one for the bird to turn (Qin et al., 2016).

However, if these reactions were to stay dependent on the geomagnetic fields only, then Morrison’s masked bird experiment would have to be a paradox. To understand the correlation between light and magnetoreception, we will refer to Schulten and Ritz’s Radical Pair Model (2000). This theory suggests that upon their interaction with light, the cryptochrome molecules exhibit an excited behaviour. This, along with the energy from the photons, induces the formation of a donor-receiver pair as a single electron is transferred between the paired molecules. These molecules are then considered to be an entangled pair. Such pairs can broadly exist in two forms: singlets and triplets (Ritz et al., 2000). Based on the concentrations of each of these pairs in the brain, corresponding molecules (Cry4-FAD and Cry4-FADH) are produced. Possibly, these molecules govern a certain state (active=1 or passive=0). If the state is active, it assures the bird that the opted path is correct, else it prompts her to change direction.

Figure 1: Sequence of events following the singlet-triplet pair entanglement in Cry4 and flight direction

Figure 1 depicts the key flow in the concentration changes of Cry4-FAD and Cry4-FADH as triggered by the ratio of singlet-triplet pairs in the quantum entangled photons.

Furthermore, it seems that the geomagnetic polarity does not influence the direction of motion of the Robin. Unlike a compass, the production or breakdown of Cry4-FADH and Cry4-FAD is sensitive only to the direction of the field lines (regardless of their respective polarities) as demonstrated in Table 1.


Direction of Field Lines

Orientation of path













Table 1: Effect of polarity and magnetic field line direction on the mean trajectory of migratory flight

Another attribute which must be considered is the threshold of the magnetic field for it to be recognised by the bird. The average strength of the geomagnetic field corresponds to with the overall range being (Ritz et al., 2000). When the Robin was exposed to fields beyond both extremes, its direction recognition was largely impaired. While this response to the lower values might be expected, the precise reasons for the Robin’s lack of responsiveness were initially counter-intuitive. Further experimentation showed that the Robin took about 17 hours to adapt to and about 1 hour to adapt to (as shown in Table 2). This also confirmed that the polarity of a specific direction did not influence the bird’s quantum navigation system and that the direction and strength of the geomagnetic field lines is solely what mattered.

Magnetic field strength     (uT)

Time taken for adaptation (s)

47 2.6
4 17.0
92 1.0

Table 2: Robin’s adaptation period for recalibrating its entanglement mechanism to the newly detected magnetic fields

Fig 2 highlights the effect of the magnetic field line directions on the path taken by the Robin. Note that represents the ‘normal’ state while represents the ‘inverted’ state.

Figure 2: Mean direction of the flight path of the Robin as per the changes in polarity and field line direction

Moreover, the arrows on the circumference of the circle represent the direction opted by every individual bird with the corresponding color-coded attributes ( and ). The mean direction is therefore calculated and is represented in the inner sectors as the longer arrows.

Additionally, for the quantum hypothesis to work, a bird’s general trajectory for migration must be defined in terms of the surrounding magnetic field line patterns (Qin et al., 2016). This theory projects two main ideas. The first proposal deals with a certain mathematical relationship between the defined path and the geomagnetic field (Ritz et al., 2000). Figure 3 addresses the first possibility through a simple example wherein the trajectory matches the field line patterns exactly.

Figure 3: Possible reaction in the Robin’s behavior at different points on the Globe

Figure 3 aims to illustrate a possible response of a migratory bird using Cry4 and quantum entanglement for magnetoreception. In this, the star represents the bird while the arrows determine the proposed path of migration. The poles are represented by <<mS>> (magnetic south) and <<mN>> (magnetic north) and represents the force of gravity.

The second proposal appears more bizarre as it suggests the visual appearance of the geomagnetic fields for the birds (Al-Khalili, 2018). However, due to the complexities involved in the recognition of the nature of entangled pairs, the quantum aspect of navigation is yet to be thoroughly understood and remains a big challenge.


While avian magnetoreception is typically analysed from two different perspectives (chemical and quantum), it seems that given all observations so far, including the effect of light, polarity and field line directions, the quantum model seems more apt. Further, the correlation between the concentrations of Cry4-FAD, Cry4-FADH and singlet-triplet pairs was also analysed to understand the relationship between entanglement patterns and chemical production in the brain and how the fluctuations in the quantum states affect the electrochemical signals sent to the bird.

This concept of quantum based magnetoreception contributes a great deal in our understanding of how biological molecules have evolved and adapted to magneto-sensitivity. It also proposes a new approach to magnetovision supported by the fundamental idea of singlet and triplet pair fluctuations. However, as the experiment conducted in the European Robin specifically tests the relation of Cryptochrome in that species, it is still unclear if the relation between Cry4 and quantum magnetoreception can be generalised to all avian migratory species.

Regardless, it is certain that the emergence of biology with quantum physics can certainly explain some of the most bizarre phenomena in this field.


Kerlinger, Paul. How birds migrate. Stackpole Books, 2008.

Bairlein, Franz. "The study of bird migrations–some future perspectives." Bird study 50.3 (2003): 243-253.

Wu, H., Scholten, A., Einwich, A. et al. Protein-protein interaction of the putative magnetoreceptor cryptochrome 4 expressed in the avian retina. Sci Rep 10, 7364 (2020).

 Högl, B., Stefani, A. & Videnovic, A. Idiopathic REM sleep behaviour disorder and neurodegeneration — an update. Nat Rev Neurol 14, 40–55 (2018).

Wiltschko, Roswitha, and Wolfgang Wiltschko. "Sensing magnetic directions in birds: radical pair processes involving cryptochrome." Biosensors 4.3 (2014): 221-242.

Wiltschko R, Wiltschko W. Sensing Magnetic Directions in Birds: Radical Pair Processes Involving Cryptochrome. Biosensors (2014).

Qin, S., Yin, H., Yang, C. et al. A magnetic protein biocompass. Nature Mater 15, 217–226 (2016).

Sun K, Wang Y, Liu ZH, Xu XY, Xu JS, Li CF, Guo GC, Castellini A, Nosrati F, Compagno G, Lo Franco R. (2020) Experimental quantum entanglement and teleportation by tuning remote spatial indistinguishability of independent photons. Opt Lett; 45(23):6410-6413. doi: 10.1364/OL.401735. PMID: 33258824.

Wu, H., Scholten, A., Einwich, A. et al. Protein-protein interaction of the putative magnetoreceptor cryptochrome 4 expressed in the avian retina. Sci Rep 10, 7364 (2020).

Ortega, L. J., (2005) “Avian visual perception: Interocular and intraocular transfer and head-bobbing behaviour in birds”, International Graduate School of Neuroscience (IGSN) of the RUHR-UNIVERSITY BOCHUM.

Thorsten Ritz, Salih Adem, Klaus Schulten (2000) “A Model for Photoreceptor-Based Magnetoreception in Birds”, Volume 78, Issue 2.

Anuva Ghosalkar's Paper

Newest Student Article
Tracking the Trends of the Most Popular Programming Languages Over the Past Decade Using Github's API
Anuva Ghosalkar

09 November 2022 | Download
Student's Published Works


The following research was designed to use experimental data to propose what the most popular programming languages are, as well as offer insight and discussion into the rise and fall of these languages. While programming is a relatively new field, the number of options for languages to code in has grown exponentially over the decades to account for new needs in various fields. However, some programming languages’ versatility helps popularize them internationally, and as their usability becomes more established, their learner and user counts grow.

To compute the most used programming language, the Github API was used in conjunction with Powershell. Together these were able to return two types of data for the 200,000+ files found: the last updated date and the file type. With this data, the amount of files that were found for a language were quantified per year, and growth along those languages was tracked. These trends indicated when the language was the most popular, and also whether its growth or decline is oncoming.

Results show that while new, quickly growing languages were hypothesized to be the most popular, in actuality, older languages that remain versatile today have far more users than that of new languages. An example of this is the difference between Ruby, which came out in 1995, and that of a more recent language, such as Swift, which was released in 2014. Ruby was the first rated language in popularity, with 4,501 uses found in the last decade, while Swift does not even make these charts. This implies that whole programming languages can quickly be picked up and used for various kinds of development, the most populous languages are those which have long been established. Even though learning new programming languages generally becomes easier with skill, languages still need time to establish themselves on a global, industrialized sphere.

Keywords: Computer science, Programming Languages, Github, Popularity, Ruby


As programming languages rapidly fall in and out of favor, choosing to work with the most versatile language that suits your project’s needs is an essential part of every programmer’s journey. However, every programming language has different strengths, but based on the popularity of the language, assumptions can be made about its functionality.

In this paper, the popularity trends of the top programming languages, according to data taken from Github are summarized and graphed, and inferences are drawn based on these findings. I hypothesize that languages such as Java, Javascript, and Python will be at the top of the list; However, according to Columbia Engineering[1], lesser known languages like Swift, Pascal, and Kotlin may not have a large user base, but could be on the rise in current programming spheres.

Materials and Method

To draw my conclusions, I used the Github API, or Application Programming Interface, to collect information about these files from certain repositories. Additionally, a Powershell script was needed to go through repositories and find file information that would then have to be post-processed. Microsoft Excel later processed this data, as well as to create the final charts and graphs.


By using a Powershell script and the Github API, I was able to get the last updated date and extension type for 234,502 different files from various repositories and users. From there, I analyzed 2 variables - (i) the programming language(s) in the repository and (ii) the last date that the files were edited. The number of files of each type was quantified by totaling all of the files that had a specific file extension, indicating the language that the file was originally written in. After post processing these files, which primarily consisted of formatting all of the data as a CSV (Comma Separated Values) file, I then opened it in Microsoft Excel and saved it as an .xlsx file to reduce storage space on my harddrive. All of the files were individual rows in a table that was later converted to a Pivot Table that summed up the number of files found. From there, results were filtered so that only languages with over 800 uses from 2012 - 2022 were shown to eliminate data that had very few appearances in this decade. This is mainly meant to take care of the large number of languages that had between 1 and 10 uses; 800 was chosen as the cutoff because of a break in the data that formed a natural separation. Languages that were not programming languages (ex: markup languages) were also filtered out (see Figure 3). The number of files of each language remaining was quantified based on the year, and the results were plotted in a clustered column chart using Microsoft Excel. By performing this experiment, the most widely used programming language was established, and its growth was able to be tracked and assessed.

These statistics provide an area for analysis. The most used programming language was Ruby[4] (.rb), which was first released in 1995. However, data verifies that the popularity of this language has increased significantly, and that this is still a popular choice to code in. Other languages also follow a similar, yet less pronounced pattern, such as Go, C#, C, and Javascript. Languages that have not been as popular for as long, or have a smaller range of uses, display much less stable growth (e.g., Python).


The results were not as expected, but definitely worth some insight. Ruby being at the top of this list established that despite its age, it has managed to keep up with current demand for programming features. This brings up interesting discussion points as to what makes Ruby so popular. Proposed answers may be its established popularity throughout time, as well as its power and ease.

However, other proposed languages to top this list, such as Java, appear far below Ruby despite their popularity. Additionally, quickly rising languages such as Python have shown some growth, but not enough to be comparable with that of Ruby and Go. This could imply that while programming languages rapidly fall in and out of favor, they still need time to grow to considerable heights before they gain widespread popularity. It also raises discussion of the speed that programming languages popularize at. Despite the ease of learning new programming languages in the digital age, languages still need time to acquire a following that lets them be recognized for the functionality they offer.

Languages such as Javascript, C#, C, Go, and PHP, however, are commonly held as some of the most popular languages, and the results of this study corroborate with these findings. Northeastern University Graduate Programs[2] lists all five of these in their web page when listing some of the most popular programming languages, and Berkeley Extensions[5] also makes reference to a few of these in their own version of a similar article. While the presence of Ruby is surprising using such sources, the languages that reappear also have similarities, if not in their individual languages, then in their applications, usability, and versatility. This may imply that for a programming language to be popular (which is necessarily “useful” or ‘good” in all situations), certain factors that these languages possess must be addressed. Not all languages that work like these ones will succeed, but a starting point for the requirements of a “good” programming language can be found in all of these.

Then comes the importance of analyzing trends. For instance, even though Ruby is far ahead of any other language, its usage has been steadily declining over the 5 years. However, languages like Go and, C#, and Javascript, have shown a general increase, or at least less of a drastic decrease. The obvious outliers to this statement are 2020, which could be accounted for by stating the impacts of the COVID-19 pandemic, and 2022, which at this time has not yet completed, and statistics for these languages may increase in the coming months. Additional research would be required to confirm the above statement. Regardless of these outliers, the success of these languages increases in their popularity, and also explains why even today, there is such an emphasis to achieve mastery in them among computer scientists.

While these results also may be by fluke of the random repositories selected, the number of files indicates a margin of error of only 0.2%. Another factor that could have impacted these results was that all of a user’s repositories and files were analyzed before the program moved to the next repository and/or user, which meant that multiple large repositories containing only one file type because of the user’s preference would have heavily skewed the data. Thus, being able to access all files on Github, which is likely the most accessible source for programing metadata, would provide much more sound findings. Github, however, also only has a fraction of the international programming community; learners and hobbyists may not have been represented in this data because Github is used industrially as one option for a Version Control System. To process more files in an attempt to produce more accurate results, substantial time and power will be needed that I did not have access to, as the file we ran had limited calls even with authentication, and the computer the program was executed on did not have the power to go through all users’ files.


In order to find the most widely used programming language and track its popularity over the past decade, I used the Github API to iterate through repositories on Github and record all of the file extensions and updated dates present in a CSV. This data was later processed in Microsoft Excel, where only languages which had over 800 total uses were analyzed, limiting the number of languages that would be processed after this point. Next, languages that were not programming languages were filtered out as to not deter from the goal of the experiment, and this determined the top 14 languages which were later graphed. While it could have been a result of the repositories used, older languages such as Ruby and C# were seen as far more popular than newer languages, implying the time languages need to gain popularity is significantly higher than the time it takes for them to be learned by any number of users. Even in a rapidly expanding field such as Computer Science, time will tell which languages are suited for success based on their versatility and usability. 


I thank Harvard’s Learn with Leaders for the guidance they provided throughout the course of this publication.

Figure 1: Processed data of the top programming languages and their use over time

Figure 2: Data from Figure 1 in a Clustered Bar Chart

Figure 3: A list of programming languages that were taken out. These file types include those that were erroneously entered, languages are not for programming (ex: .png, .jpg), files for markup (.xml, .html), languages that are continuations of other, more well-known programming languages (.h), etc.

Figure 4: KellyAnn Fitzpatrick’s 2021 data taken from Redmonk. This correlates with my findings in regards of high popularity programming languages


Columbia Engineering. (2021, December 3). 11 new programming languages to learn in 2022. Columbia Engineering Boot Camps. Retrieved August 13, 2022, from https://bootcamp.cvn.columbia.edu/blog/new-programming-languages/

Eastwood, B. (2022, January 5). The 10 most popular programming languages to learn in 2021. Northeastern University Graduate Programs. Retrieved August 13, 2022, from https://www.northeastern.edu/graduate/blog/most-popular-programming-languages/

Fitzpatrick, K. A. (2021, March 9). Redmonk Top 20 languages over time: January 2021. RedMonk. Retrieved August 13, 2022, from https://redmonk.com/kfitzpatrick/2021/03/02/redmonk-top-20-languages-over-time-january-2021/

Ruby. Ruby Programming Language. (n.d.). Retrieved August 13, 2022, from https://www.ruby-lang.org/en/

Trilogy Education Services. (2021, December 22). 11 most in-demand programming languages in 2022. Berkeley Boot Camps. Retrieved August 13, 2022, from https://bootcamp.berkeley.edu/blog/most-in-demand-programming-languages/#:~:text=According%20to%20Stack%20Overflow's%202020,(PDF%2C%202.4%20MB).

Niharika Roy

Newest Student Article
How Emerging Companies Have Added to Sustainability Models: The UN SDGs Fuelling Corporate Social Responsibility
Niharika Roy

09 November 2022 | Download
Student's Published Works


Businesses may use the Sustainable Development Goals (SDGs) as a strong foundation to engage in corporate social responsibility. Essentially, the SDGs were created about the same time as India's CSR policy was introduced under Section 135 of the Companies Act (2013). To meet the different development issues, the CSR policy was formed. Together, CSR and SDGs have immense potential to create a linked paradigm for sustainable growth. There is tremendous potential for corporate involvement in the SDGs. More so, thematic areas of development for the SDGs and CSR have a lot in common. Through the investigation of synergies between many stakeholders for cumulative synchronized growth, this research paper aims to bring private participants from all sectors together to realize the shared goal of sustainable development. For instance, when a company decides that improving livelihoods through skill development training for women and youth is its CSR focus area, it is helping to achieve a number of SDGs, such as finding a way to end poverty, end hunger, provide high-quality education, promote gender equality, and promote economic growth. The smooth achievement of the sustainable development goals depends on the integration of corporate resources with the knowledge and experience of civil society organizations. Corporates are already aware of the benefits that may come from advancing the SDGs, and many of them have already begun to move cautiously in this direction. Some corporations however, are involved in a phenomenon known as ‘Greenwashing’ (making insincere CSR efforts that serve only to mask underlying ethical issues) which goes against the long-term benefits of SDGs. SDGs serve as a mechanism to handle rising scrutiny from many stakeholder groups over diverse social, environmental, and labor concerns in addition to providing strategic commercial advantages. Even though corporations are making great strides, much needs to be done to meet the SDGs in a way that aids in creating strategies to control the social and environmental performance of businesses. This will lead to the creation of smart businesses that seize opportunities and develop cutting-edge goods and services in order to meet the highest sustainability standards.

Keywords: Sustainable Development Goals, Corporate Social Responsibility, Stakeholders, Environment, Development, Synchronization; Greenwashing


CSR stands for Corporate Social Responsibility. In essence, it is a company’s/organization’s responsibility to overlook the following effects of its conduct:

  1. Social
  2. Economic
  3. Environmental

Based on the above parameters given by the UN SDGs, the main objective of CSRs is to hold and attend to the above-mentioned objectives, in addition to maximizing profits. It gives rise to moral accountability towards companies itself, its stakeholders, and its community.

CSRs are mostly voluntary. These cover all aspects affecting, or being affected by, the above 3 factors. CSRs are completely a public matter. Thus, it has effects ranging from establishing a stable and well-rounded reputation to media and community criticism involving the same. 

Established Relation

For some, CSR is only a chance for PR, as a company attempts to look good through different socially or ecologically responsible efforts without adopting structural changes that would have long-term beneficial impacts (Reckmann, 2022). Greenwashing is the practice of making insincere CSR efforts that serve only to mask underlying ethical issues (particularly when it comes to the environment) and acting solely for the sake of public relations (Seele & Gatti, 2017; Wilson et al., 2010). It is important to go beyond the words on a company's website or in its advertising to comprehend a company's approach to the environment in its entirety.

Most customers would stop doing business with a brand if they knew about careless or dishonest business practices. Therefore, it should not be surprising that businesses are turning their attention to socioeconomic and environmental challenges. In addition to the advantages for society, CSR activities give them a chance to increase profits while also enhancing their favorable reputation in the market (Reckmann, 2022). The difficulty, however, is in explaining such CSR activities. This paper thus attempts to explore and articulate the intricate link between corporate social responsibility and public relations.

It can be deduced that the relation between a company’s visibility or presence is found to be directly proportionate with its Corporate Social Responsibility. The higher its online presence and transparency is, the more questions its own community has. Thus, it holds higher responsibility and a duty towards its audience.

Figure 1: Relationship between CSRs and Customer Support Source: Submittable (2022)

Case study 1: Starbucks

Starbucks Corporation is an American multinational chain of coffeehouses and roastery reserves headquartered in Seattle, Washington. Starbucks has a very indigenous method of practicing sustainability. It is a leading global chain, and is a prime example of how there is a network of value-based objectives that the company needs to adhere to besides being profitable:

  1. the coffee is ethically sourced
  2. aim at creating a global network of farmers
  3. developing green stores
  4. generating a lot of community service hours
  5. launching collegiate programs for their employees
  6. prioritizing health amidst the COVID pandemic (UN Global Compact, 2017; Britannica, 2022)

The above shows that a company can go beyond the restrictive and conventional social responsibilities and benefit the society in innumerable ways. This is where the SDGs (Sustainable Development Goals) come in.

The 17 SDGs set by the United Nations aim to lay a very clear, helpful, and all-encompassing route for companies to decide and implement their CSRs.

Case Study 2: Education and Sports for All Initiative

The Education and Sports for All initiative was launched in 2010. Its objectives were to:

  1. provide access to quality education
  2. support various initiatives working towards underprivileged children
  3. promote girl-child education
  4. teach life skills to the differently abled (Reliance Industries, 2010)

It would be fair to assume that the aforementioned initiatives significantly contributed to achieving the SDG goals mentioned in Figure 2, owing to the following statistical figures. Reliance Foundation has positively impacted the lives of 2 lakh+ underprivileged children (CSR Box & CSR Journal India, 2021). This initiative also cooperated with, and helped 15+ NGOs like Aarambh, One Billion Literates Foundation, Saakhi for Girls Education, etc. This initiative also provides a life-time experience to around 18 thousand children who get to watch a match in the Wankhede Stadium every year (Indian Express, 2014). Reliance Industries recognized the fact that improving the quality of life of these children goes beyond education and opportunities, and provides these children with food, goodies, and merchandise every year.

Figure 2: Deduced CSRs associated with the ESA initiative

Case Study 3: Earthian

Earthian is an initiative of the WIPRO conglomerate (one of the world’s largest IT companies), designed to bridge the gap between sustainable action & academic education in India (Wipro Foundation, 2019). It was launched in 2011 at the pan-India level, which successfully completed 10 years in 2021. Under this initiative, WIPRO Earthian members and contributing organizations engage with students at school and higher education levels in chosen institutes to foster sustainable thinking and actions (Indian Express, 2019).

As part of its corporate social responsibility (CSR), WIPRO had spent around $1 billion in the education sector in the financial year 2020-21 (Wipro Foundation, 2021). Like many other programs, WIPRO's ‘Earthian’ initiative is playing a crucial and pathbreaking role in achieving sustainable thinking & actions which are important in the current predicament of the climate crisis. These are a focus of SDG 4: Quality Education and SDG 13: Climate Action.

Climate change is the single biggest problem of our times (Amnesty International, 2019). A sustainable way of living is the only option that can save us from imminent disaster. However, the Indian education system lacks imparting values along with academic rigor in students. WIPRO recognized this problem, and aimed to solve it.

The Earthian Initiative aims to fill this lacuna in the Indian education system by fostering sustainable thinking and actions amongst youths. It is helping India in achieving SDG goal 4 i.e Quality education, more particularly, its target 4.7 that mentions ensuring all learners acquire skills, knowledge, values, and spirit to promote sustainable development in various aspects by 2030 (Wipro Foundation, 2019).

The Earthian initiative has overarching features which can be divided into two parts: at school level and at higher education level. It organizes a continuous engagement program with different schools across India, providing multiple perspectives to students, teachers, and the community around them. Moreover, every year a national level competition is organized for school students to take part in sustainable thinking for water, biodiversity, and waste (Wipro Foundation, 2019). These are activity-based programs that help students to identify and analyze the problems and to find sustainable solutions.

Similarly, Earthian initiative at higher education level targets college students by inculcating sustainable thinking in various aspects (Economic Times, 2019). There are continuous engagement programs where experts interact, ideate, and contemplate with students and teachers in chosen colleges across India about sustainable approaches. An all-India national level competition is organized where college students compete for the best sustainable ideas in the spectrum of waste, agriculture, and water (Wipro Foundation, 2019). Moreover, as part of the initiative, a sustainability quiz has been organized since 2015 providing an opportunity to college students to participate and win prizes up to 2 lakhs.

But why is it important for WIPRO? Why is it spending almost $1 billion with the help of various agencies to promote vocational, sustainable, and equal education? There are two mutual interests behind it. WIPRO pledged to be a Net-Zero producer company by 2040 and to reduce almost 55% of its carbon emission by 2030 (Economic Times, 2021). The company has the principle of sustainability at its core and it is trying to create and promote its products that are sustainable (Indian Express, 2019). Projecting itself as an innovative and eco-friendly conglomerate, WIPRO’s different divisions such as FMCG (Fast-moving consumer goods), AI-related division, Cloud computing, and so on want to have a team that provides sustainable and innovative ideas that balance ecology with its economy. Hence, it looks like the company needs those employees that have a sustainable and ecologically sensitive mindset who can carry on the company’s fundamental values and spirit.

Therefore, Earthian initiative not only helps WIPRO to complete its CSR yearly targets but also to create and develop sustainable thinking and spirit in students that may become WIPRO employees in the future and carry on the company’s values and goals. Referring to the numbers and the feedback for the program, it can be ascertained that Earthian has been a successful initiative that has engaged with over 55,000 schools and colleges, 130,000 students, and 13,000 teachers from across India since 2011.


Good business leaders are aware that a firm foundation is necessary for a company to grow and expand its commitment to sustainability and corporate social responsibility (CSR) across the board. Companies that genuinely want to integrate CSR into their long-term strategy begin by asking for feedback from a broad range of stakeholders, which is followed by a clear implementation, commitment, and enforcement process. Corporate social responsibility is a mindset that captures the idea of setting down deep roots, not simply another policy. In addition, CSR shows that a business is ready to invest the money and people needed to make it more than simply a talking point. The difficulty, though, is in complying to these CSR activities in a way not to attract customers and increase brand value, but rather to instill a sense of long-term sustainability and social ethics for the globe.

The problem with CSRs is that they are very subjective in nature. A few laws and policies need to be established in order to ensure moral compliance of companies with their CSRs.


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