Fields of View and IWI

In order to demonstrate the components and capabilities of the Inclusive Wealth Index (IWI), Fields of View is planning on using it in a game as a policy design exercise. This computer supported game will simulate different scenarios, and will enable physical interaction among the participants. The game looks at different aspects of the IWI: interconnectedness of parameters, relating qualitative and quantitative parameters, different indices, and possibilities of change for the future.

The target audience of the game are undergraduate students of economics and sustainability studies, in addition to policy-makers. It is assumed that the participants understand the mechanism of national budgets, and can perform basic mathematical operations.

This game has been designed to complement traditional teaching methods. The learning objectives of the game are as follows:

  • Understanding the components that are used to calculate the IWI, and how it compares other development indices such as GDP, HDI, etc
  • Learning how changes in national policies can alter different indices, and what advantages the IWI offers in understanding these changes
  • Encouraging players to develop a futures orientation, and apply the same to shape real-life sustainable economic policies

In this case, the players will be asked to prepare a national budget for a given country—using their judgment based on the national indices (IWI, GDP, etc.) they’re given. Based on these standard development indicators, the players will determine a fiscal budget plan and basic monetary policy.

The game is divided into a briefing, gameplay, and debrief session. In the briefing session, participants will be given a survey to determine their decision-making preferences—which will give them some information about the socio-political context of that country. As part of the gameplay session, the players set national targets (ex. levels of employment, sustainability, poverty levels), and use preferred strategies to achieve them. The game proceeds in multiple rounds, wherein each round simulates one year of operation. The country’s economic prosperity (after each round) will then be published to the participants, and will be calculated using indicators like GDP, HDI, and IWI. Finally, the debrief session looks at the advantages and disadvantages of using different development indicators, and examines the ability of the IWI to reflect upon a country’s economic health.

The system dynamic model of the game can also be used as an interactive way of engaging players with the IWI. For example, an online interactive visualization could be developed for policymakers and students to see the effects of different policies on the future economy. The inputs and interventions will be based on data from the Inclusive Wealth Reports, and from information generated by the game.

Eventually, the IWI could become a more appropriate and comprehensive indicator than GDP or HDI to measure the sustainable development of an economy. But we have realized that this requires serious involvement of different types of audience, such as students, policymakers, politicians, educators, economists, and other such groups.

To draw audiences from different backgrounds to understand the IWI and explore the implications of planning with IWI, we are in the process of building a game called Levers of Change. All the players will be responsible for a country’s well-being, and will plan for investing in different forms of capital, such as the human, natural, and produced capital. Players should be able to balance their economic growth with sustainable development to achieve sustainable goals. The game will challenge players to plan accordingly to ensure global sustainability.

The game design process relies on the functions and indicators in the IWR 2014 report. IWI accounts the wealth of all major socio-economic and environmental parameters and is represented as an index through incorporating several complex statistical models and mathematical formulas. We are triangulating data of quantity and price of produced crops, permanent cropland and pastureland from Food and Agriculture Organization of the United Nations (FAO) to calculate wealth of agricultural land. Similarly, we triangulated statistics on forest area, and stock of timber for all listed countries from FAO. We are also validating data on production, and reserves of oil, coal, and natural gas from US Energy Information administration to calculate the wealth of fossil fuels. We apply the similar procedure for the data on production, reserve, and price of all minerals from US Geological Survey to measure the wealth of minerals.

The most interesting part of the study is to calculate wealth of natural capital. Mathematical functions to calculate the wealth of different natural resources involve multiple numbers of independent variables, such as quantities or natural stock of resources, real prices, and rental prices. The major challenges in calculating natural capital are to identify all independent variables for the model and to validate units of all variables.

Conclusion of IWR 2014

This post was authored by Richa Gupta during an internship at Fields of View.

(Please read the previous blog ‘The Inclusive Wealth Report 2014’ on Inclusive Wealth Index)

These two reports have led to the development of several recommendations for the included countries. These include the incorporation of Inclusive Wealth into planning post-2015 Sustainable Development Goals (SDGs), and the evaluation of macroeconomic policies (such as monetary and fiscal policies) based on IWI rather than on GDP per capita—as this would ensure sustainable and long-term, rather than purely short-term, growth.

Additionally, nations experiencing diminishing returns (that is, the decrease in marginal output) of natural capital are encouraged to invest in reforestation, agricultural biodiversity, and renewable natural capital. Moreover, as said by Dr. Anantha Duraiappah, director of the UNESCO / Mahatma Gandhi Institute of Education for Peace and Sustainable Development, “The report is a tool for making macroeconomic decisions on what and where to invest”. And lastly, as written in the Inclusive Wealth Report 2014, “The inclusive wealth index is […] a complement to GDP, not its replacement. The shift to sustainability as a core development pillar demands an index that can quantify, measure, and track sustainability”.

However, although the IWI is a better indicator of economic growth and prosperity, it still has its own limitations. For example, it does not factor in happiness levels, suicide rates, life satisfaction, and the accessibility of housing. It also doesn’t take social capital of a country into account; social capital is a form of economic and cultural capital wherein goods and services are produced for a common good rather than for selfish interests, and transactions are characterised by trust, cooperation, and reciprocity.

In addition, natural capital is often difficult to accurately price. For example, the UN cannot include common access resources like clean air—since it is not directly owned by anyone, and is available for people to use without payment. Hence, when the Inclusive Wealth Index is computed, only natural capital with a market price can be included (such as petroleum, gas, metals, and timber). The Economist suggested another example: bees create honey, which can be sold on the market. But they also pollinate nearby apple trees, a useful service that is not purchased or priced. So, calculations of the Inclusive Wealth Index will invariably be rough, unless economists make a conscious effort to quantify the value of clean air, pollination, and the myriad of others.

But despite its limitations, the concept of Inclusive Wealth has been widely embraced, since it represents development based on concern for the environment and future generations. And it has been predicted by Professor Dasgupta that eventually, people will drop the adjective “inclusive”, and will only call it “wealth”—since, after all, economic wealth is not synonymous with solely income, but also with human capital, the environment, and sustainability.


The Inclusive Wealth Report 2014

This post was authored by Richa Gupta during an internship at Fields of View.

(Please read the previous blog ‘The Inclusive Wealth Report 2012’ on Inclusive Wealth Index)

The Inclusive Wealth Report of December 2014 covers information from 140 countries, and was released in New Delhi, India. It laid a special emphasis on human capital. The report concluded that 85 of the 140 countries were producing sustainably, in terms of inclusive wealth, while the consumption patterns of the 55 others were considered unsustainable.

The report also found the extent to which human capital and natural capital are huge indicators of wealth, as compared to only produced capital (which is accounted for by the Gross Domestic Product). For instance, while global GDP rose by 50% from 1992 to 2010, the IWI rose by a relatively paltry 6%. As said by Dr. Partha Dasgupta, chair of the 2014 Report’s science advisory group, “vast losses in natural capital (and small increases in human capital) largely explain the anaemic overall growth in Inclusive Wealth worldwide despite enormous gains in produced capital”.

Components of Global Inclusive Wealth, from 1990 – 2010

Type of Capital % of total Inclusive Wealth % change from 1990 to 2010
Produced Capital 20 + 50
Human Capital 57 + 8
Natural Capital 23 – 30

The following statistics also show the extent to which the Gross Domestic Product is an inadequate standard of a nation’s wealth and prosperity:

As can be extrapolated from the December 2014 report, in the US, India and China, wealth measured only by GDP (from 1990 to 2010) rose by 33%, 155% and 523% respectively.

However, when measures of the social values of natural, human and manufactured capital were considered, the USA’s Inclusive Wealth Index rose by 13%, India’s by 16%, and China’s by 47%—over the same span of time. These are gaping disparities, and provide an indication of the narrow scope of the Gross Domestic Product. The statistics of a few other countries have been tabulated below:

Country % change in GDP from 1990 to 2010 % change in Inclusive Wealth from 1990 to 2010
US +33 +13
India +155 +16
China +523 +47
Ecuador +37 –17
Guyana +97 –2
Qatar +85 –53
Tanzania +67 –37



The Inclusive Wealth Report 2012

This post was authored by Richa Gupta during an internship at Fields of View.

(Please read the previous blog ‘Measures of Wealth and Prosperity’ on Inclusive Wealth Index)

 Inclusive Wealth = (social value of manufactured capital) + (social value of human capital) + (social value of natural capital)

Natural capital encompasses the world’s stock of natural assets, such as fossil fuels (oil, coal, natural gas), minerals (bauxite, nickel, copper, iron, zinc, etc.), agricultural land (croplands, pasturelands), and forest resources (timber and non-timber forest resources). In the context of Inclusive Wealth, human capital comprises of education and health, and manufactured capital consists of equipment, roads, and machinery. Another variable used to compute IWI is its health capital, which includes health capital by age, and probability of dying by age.

So, rather than being ranked in terms of GDP, countries are ranked according to inclusive wealth. To take an example, USA’s inclusive wealth was almost $118 trillion in 2008 (with prices at those of the base year, 2000), whereas its GDP was only a fraction of that value. So, this observation implies that the USA is rich in either human capital or natural capital, or even both (in this case, it is human capital).


Country 2008 Inclusive Wealth ($ tr) 2008 Real GDP ($ tr)
United States 117.8 14.7
Japan 55.1 4.8
China 20.0 4.5
Germany 19.5 3.7
Britain 13.4 2.8
France 13.0 2.9
Canada 11.1 1.5
Brazil 7.4 1.7
India 6.2 1.2

Source: United Nations, World Bank

As written by the Inclusive Wealth Project, “The index measures an asset’s wider value to society, and not the price for which it could be bought or sold”. Professor Partha Dasgupta was one of the specialists who came up with the IWI; he criticised the GDP for neglecting the social value of natural ecosystems, and also observed that while the GDP and HDI indicators were rising for most of the third-world countries, their sustainable economic development (i.e., the approach that fosters economic growth while preserving environmental quality) was negative, except in the case of China. As said by Prof. Dasgupta, “Adam Smith did not write about the GDP of nations, nor the HDI of nations; he wrote about the ‘Wealth of nations’. […] Leading economics journals and textbooks take nature to be a fixed, indestructible factor of production. The problem with this assumption is that it is wrong: nature consists of degradable resources”.

The first Inclusive Wealth Report was released in 2012, and included statistical data from 20 countries. It is the first of a series of biennial reports, whose twenty included countries accounted for approximately 56% of the world’s global GDP, from 1990 to 2008. It was a core project by the UNU-IHDP (United Nations University’s International Human Dimensions Programme), in collaboration with the UNEP (United Nations Environment Programme). Before and after the 2012 report was published, the following statistics were noted:


Country % growth in economy from 1990 to 2008, based on GDP % growth in economy from 1990 to 2008, based on IWI
China +422 +45
USA +37 +13
Brazil +31 +18
South Africa +24 -1

This implies that these four countries substantially depleted their stocks of fossil fuels, fisheries, and forests—while simultaneously raising their Gross Domestic Product. Moreover, while India was ranked second in GDP per capita, according to the IWI report (with a 4.3% per year increase in GDP per capita), it ranked 6th in the Inclusive Wealth Index per capita, with a positive growth of 0.9 % per annum.

The following diagram, as published by the Inclusive Wealth Index website, depicts the per capita growth rate of IWI of the 20 countries (according to 2012 IWR). As can be seen, Colombia, Nigeria, South Africa, Saudi Arabia, Venezuela, and Russia experienced negative IWI growth rates—and were hence deemed unsustainable.

Furthermore, it was observed that although 5 countries (Colombia, Nigeria, Russia, Saudi Arabia, Venezuela) portrayed positive GDP per capita and HDI, they had negative IWI per capita growth rates. This depicts the deficiencies of not only the GDP, but also of the Human Development Index Hence, this graph also illustrates the importance of measuring economic health based on the IWI.

Measures of Wealth and Prosperity

This post was authored by Richa Gupta during an internship with Fields of View.


The Gross Domestic Product (GDP) has long been used to measure the prosperity and health of an economy. The GDP is defined as the market value of all final goods and services produced in a country’s economy, over a given time period (usually a year) [1]. It includes the four components of spending—spending by consumers, firms/businesses, the government, and foreigners (on exports).


According to the expenditure approach, GDP = Consumption + Gross Investment + Government Spending + (Exports – Imports)


There are other variations of GDP that are also in use, such as the NDP (Net Domestic Product), GNP (Gross National Product), and NNP (Net National Product). That said, all of them still factor in variables related to a country’s manufactured/produced output.



It is essentially the annual measure of a country’s output, but adjusted to account for depreciation (depreciation refers to reduction in the value of an asset, such as a car or house, over time).


  • Gross National Product = GDP + (net income inflow from abroad) – (net income outflow to foreign countries)


The GNP is the total value of a country’s output (final goods and services) produced by a country’s residents (domestically produced goods and services).



The NNP is the monetary value of domestically produced goods and services, minus depreciation.


Despite its variations, the Gross Domestic Product is largely used as a metric of a country’s prosperity and economic health. Nominal GDP (i.e. GDP evaluated at current market prices) is used to determine the economic performance of a country and to make international comparisons.


However, widely used as the GDP is, it has still come under criticism for not accounting for a range of factors; for example, it cannot accurately measure standards of living, such as levels of education, health, life expectancy, and quality of life. Furthermore, it does not look at negative environmental externalities caused by production, such as compromised air quality, water pollution, and land degradation. It also fails to look at the sustainability of capital stock used; capital stock is the total amount of a firm’s capital, represented by the value of its issued stock. All in all, the GDP of a country cannot give policy-makers an indication about the economy’s future; it’s all about the present. In fact, as said by Danish politician and former environmental minister, Ida Auken, “we need to move beyond GDP as soon as possible”.


Since GDP on its own cannot account for negative environmental externalities, a modification of the Gross Domestic Product was duly proposed, called the Green GDP. Green GDP is an index of economic growth that factors in environmental quality to the conventional GDP. It monetises the loss of biodiversity, and takes into consideration external costs caused by climate change. For example, if there is an oil spill in a country’s ocean, the money used to clean up the spill and to treat subsequent illnesses will invariably be included in the country’s GDP—thereby making it appear better off than it was before the spill. China was one of the first countries to measure its performance based on Green GDP; the first green GDP report for 2004 was consequently published in September 2006.


Green GDP = GDP – (value of environmental degradation) – (price of fixing environmental damage) [2]


However, Green GDP does not look at human capital. Moreover, as remarked by renowned economists Joseph Stiglitz, Jean-Paul Fitoussi, and Amartya Sen, “[Green GDP does not] characterize sustainability per se. Green GDP just charges GDP for the depletion of or damage to environmental resources”.


Another index was also decided upon—the Human Development Index, or HDI. The HDI not only takes a country’s value of output into consideration, but also looks at four important criteria: life expectancy at birth, mean years of schooling, expected years of schooling, and gross national income per capita.  So, the HDI is a much more comprehensive measure of a country’s development, since it includes a social aspect as well.


However, GDP, Green GDP, and HDI are insufficient when it comes to gauging environmental sustainability This observation has led to the inception of the Inclusive Wealth Index (IWI), which computes a country’s wealth by also taking the environmental and sustainability dimensions into account. It was launched by the United Nations at Rio+20 (a conference on sustainable development), in an attempt to develop a divergent way of gauging prosperity. A country’s Inclusive Wealth Index includes natural capital, in addition to produced/manufactured capital and human capital. Measuring sustainability of a country is critically important, since, as stated by the Sustainable Housing Foundation, “our global future depends on it”.

[1] Tragakes, E. (2012) Economics for the IB diploma [With CDROM]. 2nd edn. Cambridge: Cambridge University Press.


[2] Tragakes, E. (2012) Economics for the IB diploma [With CDROM]. 2nd edn. Cambridge: Cambridge University Press.


₹ubbish! at Goobe’s

In the year and a half that we have been playing ₹ubbish!, our game on Bangalore’s waste management, a lot of our sessions have been with researchers, field experts, students of sustainability studies, etc. We have had community engagement sessions as well, playing with a varied audience in the Hebbal ward, the Citizen Consumer and Civic Action Group in Chennai, amongst others. We are keen to have more sessions on the ground, sessions that reach out to neighbourhoods, communities and the general audiences.

On 23rd July, we played ₹ubbish! At Goobe’s, one of Bangalore’s favourite indie bookstores. If you’ve been there, you’d be familiar with the stairs leading you down to the basement space, the corridor walls lined with bookshelves, and the display of compost pots from Daily Dump. Ravi Menezes, the owner of the store, agreed to host the game session in a heartbeat.


The game was set up in a cosy corner and we had nine players, some in teams of two. We began with a briefing session, like we always do, where we spoke about the Mavallipura protests, Bangalore’s decentralised waste system, and the idea of a scientific landfill (where the ground water is protected with a layer of concrete and the waste is compressed in layers), source segregation and Dry Waste Collection Centres.

We then started playing, with everyone enthusiastically picking their wards and colours. The players started with buying only part of their waste, but once they saw the landfill filling up with blocks for their wards, they conscientiously started buying all the waste they could.  What ensued was whispers of certain strategies, ebbing and flowing depending on how full the landfill box was.

Photo Credit – Goobe’s Book Republic

By the seventh round, there was  a consistent pattern of most of them buying all the waste their wards generated, irrespective of how much money they were making. However, the landfill was brimming by the eighth round, and we wound up the game by the ninth or tenth.

Photo Credit – Goobe’s Book Republic

There was a lot of interesting feedback and insights about the game. We discussed ideas of including the pourakarmikas or waste experts again, adding a personal, human touch to the game. One of the players even spoke of playing the game in housing colonies and apartments, in a championship-style tournament! There was a palpable energy in the air, with all these exciting ideas and there seemed to be a reinforced resolve to segregate waste at the source.

We hope to conduct many more sessions to reach out to Bangalore’s citizens, neighbourhoods and communities. If you’re interested in hosting a session, please contact us by writing to


₹ubbish! goes to Hebbal

So far we have played ₹ubbish! board game with participants from Hasirudala, ELCITA, city planners and researchers. This time we wanted to take this game and play at a ward level, which could give us some valuable feedback.

We chose to play our first game at Hebbal ward, I invited a few students to play this game. Two students from NMIT, two students from M.S.Ramiah, and 1 from Florence High School. The idea was to have a mixed audience from same locality.

As you can see in the picture, the game started with people going after well known wards like Koramangala and Malleshwaram thinking it would generate more waste, but in reality areas like Chikpet, Yeshwanthpur generate more waste. Amount of waste generated is based on real data, which was collected by ₹ubbish! game designers at FoV. The game went on till 14 rounds, the players could only manage to build in 9 out of 18 wards. The game went on for about 40 mins.


Interestingly, the two final semester mechanical students from NMIT, who had opted for solid waste management as their elective were aware of the present situation in Bangalore. In the first 4 rounds they spent most of the money on expensive wards thus making it hard for them to generate money.

At round 8, the landfill started to rise and the game dynamics changed. Players tried their best to adapt to the situation as quickly as possible, but it was too late.

Participants enjoyed the game and it was an exciting end to our first game session at ward level. Some of the participants were not aware about most of the garbage problems and also said it was good to know about landfills and about other garbage related issues.

We look forward to playing the game in more wards, to see what the feedback we get.

A human centric look at electricity consumption and design towards a “Smart Campus”

It was almost a year ago when we concluded a project named “The Smart Campus Simulation Tool”. We are looking to release the simulation tool to open source. In this post, we wanted to explore the problem context which informed our design.

To us a Smart Campus represented a socio-technical system that would be “malleable” enough for us to achieve our objectives. We approached it to be a socio-technical system, the technology (the adaptive sensor based control system) has to work with the social context of an academic institute. At the end of the day, people have to accept and be willing to make changes to their lifestyles.

We wanted to look at the issue of electricity consumption for the IIIT-Bangalore. The institute had invested in a fair amount of energy saving equipment such as solar panels and more efficient water heating systems. But, they were not clear about the eventual savings in energy, the electricity consumption patterns or if there was a strategy to reduce the overall consumption in the campus.

An overview of campus simulation model.
An overview of campus simulation model.

Consumption of electricity is a difficult notion to comprehend and convey. For example, when a switch is thrown, does one wonder where the electricity is generated from? It may so happen that a forest is being cleared in Chattisgarh so that you may be able to spend an extra hour on Xbox. Furthermore, we have an inherent expectation (if you grow up with some privilege,) that electricity “has” to flow if a switch is turned on. People who have no access to electricity are vulnerable in many ways to the extent that their social mobility may suffer due to lack of electricity. People who have intermittent access or pay huge bills are also cautions about consumption. Nevertheless, we seldom question the source of generation. 

Causal relationships like the one above between your consumption and environmental degradation are common and are uncomfortable (but true). Such examples try to guilt you into changing your consumption behaviour. However, it is not an easy to make lifestyle changes nor is it easy to ponder on the utility before doing everyday mundane tasks. Responsible use of electricity requires changes to behavioural and cultural practices as well as upgrades to the technical systems around us. Looking at both social and technological aspects was the cornerstone of our approach. 

We tried to look at the campus as a location which enables different people to achieve their academic goals. People in the campus perform various activities that allow them to achieve this goal. We looked at activities that consumed electricity. We then developed a simulation tool that assumed the use of sensor -based control and behavioural modification to try and check if a technology-assisted behavioural change was possible. The results of the simulation would be the base to design a serious game. The game in conjunction with sensor-based control systems would address both social and technological aspects of the issue.

Our simulation mainly consists of:

  1. a model for generating activities (explanation for what this activity means below) for various actors present on the campus,
  2. an agent based model for minimising electricity usage while keeping the comfort level of individuals at an acceptable level.

We define an activity as any action that an individual takes during the course of one’s day in the campus. A good way to model an activity is to collect detailed information using “energy dairies”. As a small academic institute, the campus had limited types of actors. We therefore chose to use a survey-based approach to collect information on daily routines. We conducted a survey to understand various daily routines for all the individuals on the campus. We also conducted interviews with some of the administrative and housekeeping staff.  We used this information to create a model for the generation of activities for various actors on the campus.

The smart campus simulation setup.
The smart campus simulation setup.

To model the “smart” systems of the campus, we created a control mechanism based on autonomous agents trying to collectively bring down the electricity consumption of the campus while keeping track of inhabitant’s comfort levels. We modelled the rooms and work areas as the autonomous agents. Each such agent was responsible for the operation of various devices that would consume electricity. It was then tasked with the objectives of minimising usage of certain devices by:

  1. negotiating the electricity consumption with other rooms (agents).
  2. Directing uses to use more common areas.
  3. Restricting when possible, the use of high power consumption devices such as air-conditioners and elevators.

In all of the above cases the it is assumed that the individual can override the agents, thus, keeping the human at the centre of the system.  (This also allows us to collect information on what sort of activities will not be compromised in the name of energy savings. ) However, a denial from the system to allow the operation of devices resulted in a decrease in the satisfaction of the inhabitants. The agents were asked to minimise the use of electricity with as little discomfort as possible for the inhabitants.

Once the models were ready we created a simulation tool and calibrated it based on the data collected by the campus for over a year on a daily basis. We could then play out scenarios such as:

  • What happens when we want to aggressively minimise consumption
  • or, what happens when the comfort for the inhabitant is paramount and
  • finally, what happens when we set a electricity consumption target for ourselves?
Calibration of the simulation, Real Data: Red, Simulated Data: Blue
Calibration of the simulation, Real Data: Red, Simulated Data: Blue


Results from using a aggressive savings scenario.
Results from using an aggressive savings scenario


Results from allowing a maximum savings scenario.
Results from allowing a maximum savings scenario
Results from using a popular choice for devices, scenario.
Results from using a popular choice for devices, scenario

It was very interesting for us to see the results and present it to the inhabitants of the campus. We are now trying to work with students to create and deploy the sensor systems at the campus. We see a potential for extending this tool to include larger spatial/network levels such as a neighbourhood or a set of neighbourhoods as opposed to a campus. We are also looking at including multiple sources of electricity, given that decentralised power and micro-grids can become popular. Furthermore, we are also exploring the possibility to include other resources such as water consumption and sewage as well into the analysis. For a more detailed description to the tool and to some other people doing similar work please refer to our paper “Krishna, Harsha, Onkar Hoysala, Krishna G. Murali, Bharath M. Palavalli, and Eswaran Subrahmanian. “Modelling technology, policy and behaviour to manage electricity consumption.” In Humanitarian Technology Conference (R10-HTC), 2014 IEEE Region 10, pp. 40-45. IEEE, 2014.”. We hope to produce and publish more results soon. In the meantime please free to check our tool at:The Smart Campus Simulation Tool

Indian Energy Game session at IIIT-B

Does the length of your laptop cord matter for how you experience a game? It was one of the many questions that cropped up as I watched the most recent session of the Indian Energy Game we played with students of the Digital Society course at IIIT-B on 29 July, 2015.

The Indian Energy Game is designed to help you learn about how decisions in energy policy are made in India. The participants were divided into two teams – Team 1 and 2. Each team had three groups who represented three Ministries: Ministry of Power; Ministry of New and Renewable Energy; and Department of Atomic Energy. The Ministries have to design the energy mixture for the 12th and the 13th Five-Year plans.

On your left, is Team 1 and on the right is Team 2. The one standing is Onkar from FoV who is facilitating the game. Photo Credit: FoV

The first part of the game went on for around 30 minutes. As participants began planning, there were messages handed around signifying certain public announcements or policy changes.

The Indian Energy game is a computer-assisted game – as you see in the photograph, each Ministry is peering into their respective laptops.


As the game play unfolded, slowly the ordered sitting arrangements broke up. “Tumhara budget khatam ho gaya kya?” And other such comments floated around.

Discussions underway.


As people started discussing and conversing, minor things such as the length of the laptop cord too seem to matter – how far can I slide across the table without switching power sources. All of it, as trivial as it seems now, when the clock was ticking down seemed to influence the participants and the choices they made.

The materiality of the setting matters to the game play, as much as the game mechanics and the participants. A game session is by nature ephemeral, and that ephemerality or transience poses challenges to evolve theories around it.



Eventually, Team 2 won.

During the debrief the participants shared what they experienced during the game. Describing how excited he was during the game, one of the participants said, that the game “teaches you a lot of things,” and you can “change something and see its repercussions.” He added,”I have never spent lakhs and crores of rupees!”

We had a short discussion after that talking about the use of games and simulations in public policy planning.

If you are interested in playing the Indian Energy Game, please mail us at A paper on the game can be found here.

Fields of View at Anthill Hacks 2015

Anthill Hacks was one of the first open events I attended where we were free to propose and conduct sessions to a diverse set of audiences, with very few rules. The location of the event was extremely inviting too. We were going to play our games and hack on the picturesque and peaceful hills of Devarayanadurga. (This was also the first time I was going to drive on a highway – the fancy Bangalore – Tumkur connector.)

Kshiraja and I managed to reach the location by 10:30 in the morning while driving through peaceful state forests. It was a sunny but cool morning and the conference hall of the event overlooked the hills.

Anthill Hacks Event Location
Anthill Hacks Event Location
Conference room overlooking the hills
Conference room overlooking the hills

Dinesh (from Servelots) was our host and was there to greet us. He explained the events planned for the day and the overall objectives for the events.

The village we were at, and the surrounding villages are in a fairly remote location with very little digital communication to the outside world except for an occasional signal from a BSNL tower. Dinesh and his team have been studying methods and history of community content generation and dissemination as part of their research, including oral transfer of information, folk art and music, etc. He stated that these art forms and traditions served a similar purpose as the Internet in spreading information and local community and cultural development.

At the event Dinesh explained next to an exhibit of a colourful print from West Bengal, the tradition employed for content delivery in the form of prints and folk songs. He explained that it was common in small communities in West Bengal for local artists and folk singers to be employed to create prints and come up with songs to best convey everyday events, news and information to individual families. These songs would differ depending on information and intended audience and was ideal for the differently literate audience. Not everyone could read and write. We then discussed at what point we arrive at a definition of “literate” in a country where we had traditions for oral transfer of knowledge from one generation to another.

Dinesh’s team is involved in leveraging technology for mass communication and community development while promoting the use of open-source and freely accessible communication. His team is building a mesh network in the location to connect the remote village at the foot of the hill with other villages in the area and to the Internet itself using a gateway. Due to the remoteness of the villages and a small customer base, not all telecom companies provide coverage in the area.  It is interesting that Dinesh and his team are promoting open-source decentralised methods for connecting the last mile when there is a bitter argument going on nationally about Net-Neutrality in India.

Apart from the mesh network, he explained the use of community radio. He said that the challenge for community radio operators was the ability to respond to the overwhelming amount of participation. One of the tasks for the team is to develop possible apps to handle this process and open up community radio at the location.

Community Radio Setup
Dinesh explains the community radio setup

What is further interesting is how he intends to use all of this art and technology to demonstrate community action. He led us to a location where he had laid out various maps of the region on the floor. The current Open Street Map (OSM) of the area shows very little information except for the major roads. He contrasted that with an extremely old map of the area that was prepared to map the sources of tax collection. He now intends to use a group of a hundred school children, scheduled to arrive very soon, to map out the surroundings to make the area visible on an open platform.

Local Maps
Local Maps
Old Tax Map
Old Tax Map

On to our game sessions. Kshiraja and I proceeded to have some locally prepared poha and managed to get an audience to play a session of our “Rubbish! Kaasu Kasa” game based on the garbage situation in Bangalore. The audience included a mix of artists, open technology hackers, engineers, musicians, sculptors and researchers from around India. We had an interesting session of the game where the participants were involved in heated strategic discussions to do something about Bangalore’s garbage problem.

After the game session we were able to spend some time with Renu Mukunda, a veteran researcher in the area of Urban Poverty. We compared notes and discussed at length about each others’ research and notes.  We had a quick, simple and a delicious lunch of palav (not pulav!), before it was time to play again.

Kshiraja and I managed to rally another group of players to play a session of our City Game. This was definitely one of the most interesting sessions we have had. First and foremost we were playing a game session on the face of a gentle slope of a hill, under an open sky, overlooking all the hills and villages in the area. Second, we had an interesting mix of audience from researchers, artists to kids. And finally this was one of the first sessions that I had to do the briefing and de-briefing sessions in three languages, English, Kannada and Hindi. (Although I wish I could speak Bangla and Tamil in order to have communicated better with the audience).

City Game on a hill
City Game on a hill
City Game on a hill 2
City Game on a hill

It was an interesting city with fish markers, art institutes, schools and low income housing. It was agreed that it is somewhat a small city to live in. Dinesh was enthusiastically building garbage dumps, breweries and canteens all over the city.

We managed to complete the game just before the evening showers hit. It was time to get back to my thesis and Monday Morning Meeting in Bangalore. We thanked Dinesh and promised that we would return to the beautiful venue again very soon.

And finally, the frustration of Bangalore traffic hit us as it took more time for us to get home from the border of Bangalore than it took for us to travel to Bangalore from a different city! But at least we got to get away from the city and play at a beautiful session at the event.