VOL 19 No 3

From AI Algorithm Biases to Deepfakes- The Need to Regulate Cyberspace Thumbnail

From AI Algorithm Biases to Deepfakes: The Need to Regulate Cyberspace

Battling the Dark Side of AI: The Urgent Need for Regulation to Curb Biases of AI Algorithm After reading this comment many may presume that the journal has an anti-AI or a pro-digital censorship editorial stance.  This is not the case.  We have all benefitted from AI applications and innovations—thecover of this issue of CQ has been generated with the help of an AI application.  However, there is another side (related to AI algorithm biases, deepfakes, etc.), the toxicity of which is affecting millions, and this must be addressed (without getting apocalyptic). The potential of social media as a catalyst for mass movements was witnessed in 2010-2011 through the Arab Spring.  The movement began in December 2010, as the “Jasmine Revolution” in Tunisia after the “self-immolation of Mohamad Bouazizi”.  It was successful in removing President Zine al-Abidine Ben Ali, who eventually fled the country in January 2011.  Egypt was next in line and was able to remove President Hosni Mubarak from power by February 2011.  The success in these two countries unleashed a wave of movements/protests in Yemen, Libya, Bahrain and Syria (https://www.britannica.com/event/Arab-Spring). Social media was used to organize, disseminate content, create awareness, gather people, etc., however, branding of the Arab Spring as a “Facebook Revolution” was an overstatement. It was used as a campaigning, management, organizational and broadcasting tool, but was not responsible for what preceded or proceeded the movement, i.e. the cause and result.  Simply put, when reactions to injustices and inequalities embedded in societal hierarchy were already in play, the new media provided a platform to manage and propagate these grievances in an effective manner. Things have changed since the Arab Spring. The exponential growth of “computational processing power” (Moore’s Law:  Gordon Moore, the cofounder of Intel, predicted that the number of transistors in a computer chip, in other words the computational processing power, would double approximately every two years—this prediction has remained accurate for nearly 60 years), advances in connectivity and big data have made Artificial Intelligence (AI) ubiquitous. The widespread use of Generative Artificial Intelligence, along with the use of social media as the primary source of information and news, especially for the youth, has, amongst other impacts (beneficial and harmful), augmented biases and the sway and effectiveness of disinformation and misinformation. This, in turn, is aggravating preexisting grievances and extending the digital world’s ‘sphere of influence’ towards the ‘preceding and proceeding’ segments of agitations around the world. Augmenting Biases An integral subset of AI is machine learning—the use of algorithms to learn from data—whether supervised (deep learning) or unsupervised, requires (or at least does till now) human input which, inadvertently or advertently, may have biases.  These biases can affect AI applications designed for search engines, information extraction, social networks, etc. Furthermore, AI Algorithms generate search results in accordance with the user’s profile or online history.  For instance, if a person searched for articles written by John J. Mearsheimer (an American scholar on international relations known for his theory of offensive realism) then search engine algorithms will, most likely, filter future searches on international relations to reflect the realist perspective. In the book, Age of AI: And Our Human Future, Henry Kissinger et al. wrote, “… in cyberspace, filtration is self-reinforcing.  When the algorithmic logic that personalizes searching and streaming begins to personalize the consumption of news, books, or other sources of information, it amplifies some subjects and sources and, as a practical necessity, omits others completely.  The consequence of de facto omission is twofold: it can create personal echo chambers, and it can foment discordance between them.” Deepfakes, Disinformation and Misinformation To confound matters, deep fakes are boosting the already pervasive presence of disinformation and misinformation in cyberspace.   Deep fakes use AI technology and deep learning (the supervised use of data sets) to generate fake images, videos and audios. While beneficial to some industries, for instance entertainment, its nefarious applications have created discord, radicalization and polarization, especially when it reinforces preconceived biases. The most effective forms of deep fakes use a particular authentic incident or a decontextualized quote or image and create layers of lies around it.  The references used to generate these types of deep fakes are real and, therefore, acceptable with the masses, particularly those who are already inclined towards similar biases. The next step is circulation or ‘making it viral’ and that is done through the efficient use of social media platforms. As a result, an industry that was meant to unify humankind through online social interaction is now inundated with disinformation, misinformation and deep fakes, that encourage tribalism, polarization and, in many cases, “toxic polarization”. Addressing Toxic Polarization in Pakistan Polarization, to a certain extent, is healthy for democracy. Diverse points of view and opposing arguments encourage deep introspection of ideas and policies.  However, one of the reasons for the degradation of polarization to toxic levels is the reinforcement of biases generated online. There is a need to regulate digital space.  The state mechanism in Pakistan has installed a firewall to monitor and filter cyberspace activity.  Public backlash has been confined primarily to the affect it has had on internet accessibility and speed—effecting the burgeoning digital industry—with a periphery concern pertaining to suppressing freedom of speech. The merits and demerits of arguments from either side should be premised around a holistic analysis of the current state-of-affairs in the country.  “Existential” is a word frequently used to denote the level of threat and fragility that the state must overcome.  The term “existential threat” has been in play since independence, yet the state has persevered. The intensity of the challenges that Pakistan has hitherto faced has been severe, however, whether the threats faced were ‘existential’ in nature is debatable. The present scenario in the country is different.   The mass circulation of misinformation and disinformation has created disharmony, chaos and an ever-deepening polarization between state institutions and the people. Polarization is a global phenomenon.  In the case of Pakistan, however, the ramifications of polarization can be overwhelming as the state is already

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The United States Presidential Election - 2024 Thumbnail

The United States Presidential Election – 2024

    Shifting the Political Landscape: A Closer Look at the 2024 United States Presidential Election The American election scene took a dramatic turn following the televised debate between President Joe Biden and his challenger, Donald Trump on June 27. Biden’s overall performance in the acrimonious debate was widely perceived as below par. It confirmed the impression that at 81, the president had passed his prime. Trump took full advantage of Biden’s vulnerability, pushing the point that his characterisation of “sleepy Joe” was not off the mark. While the US system places a limit on presidential terms at two, it has no provision to deal with a candidate’s old age or infirmity as a barrier to seeking election. In the event, a live debate helped to send home the signal that the president should withdraw from the presidential race – the sooner the better. Democratic party veterans weighed in to help Biden make up his mind and his  decision to withdraw from the presidential race was made public on July 21, 2024. That instantly moved public attention to who his replacement would be. Biden decided to play on the front foot by putting his weight behind vice president Kamala Harris to be the party’s candidate. Had Biden left the decision to party ranks the Democrats would have lost precious time in mobilising popular support. Having received widespread endorsement from party seniors, including former presidents Clinton and Obama, the party convention in Chicago massively endorsed the nomination of Kamala Harris as Democratic candidate for the presidential election on November 5. The fading of Joe Biden energised the Democrats’ presidential campaign thereby promising a period of intense electioneering in the run up to the election. Opinion surveys signalled a fall in support for Trump. His five percent lead on Biden quickly evaporated and he was trailing behind Harris with the passage of time. Trump even began publicly regretting Biden’s departure from the race. Kamala Harris, a California native, moved to balance the ticket by opting for Tim Walz, governor of the Midwestern state of Minnesota, as her running mate. A 60-year old Army National Guard veteran and public school teacher added a distinctive Rust Belt feature to the Democratic ticket. An Associated Press report suggested that by opting for Walz, Harris calmed the Democratic Party’s left wing, which was worried that another contender, Pennsylvania Governor Shapiro, could have pushed the party closer to Israel and disheartened Arab American and younger voters. “Progressives are already celebrating Walz’s ability to deliver an unapologetically populist message in the style of a Midwestern dad who recalls the social studies teacher and football coach he once was”, concluded the AP report. Trump had earlier selected a conservative populist J D Vance—an author, venture capitalist and a vocal rightist Senator from Ohio—as his running mate to boost his support among working class voters. Experts said that Trump’s choice of Vance signaled an embrace of hard-right “Make America Great Again” politics – and a break from the old-school Republican establishment. Campaign Issues A survey in July, 2024 revealed that inflation and high prices were the most important issues for US voters. Unemployment and the economy came next in the list of concerns. Other issues receiving attention of the voters are healthcare, education, illegal immigration, crime and gun violence, racism, climate change and the federal budget deficit. A large number of Americans feel that the healthcare system needs an overhaul. The opinion is divided among those who are in favour of more funding from Washington with monitoring by the bureaucrats; others who favour government run models as in Europe and Canada; and a third group opting for patients and doctors in the driver’s seat, making health care providers and insurance companies compete for customers. The Democrats support government through regulations while the Republicans consider this as a hindrance to free market capitalism and job growth. While the Democrats increased the government’s role in healthcare, as seen in Obamacare, the Republicans support healthcare through private companies. Immigration is another leading issue as the debate over border security and immigration becomes increasingly acrimonious because politicians have put politics before principles. The rising cost of college and university education, leading to high levels of indebtedness is yet another cause of concern. Furthermore, climate change is a highly important and controversial issue. Opinions are centred around America’s belief in free enterprise. Finally, there is the intractable task of poverty alleviation, as 12 percent Americans are considered poor despite a trillion dollar annual expenditure by federal, state and local welfare programmers. Party Positions In general terms, the Republicans are more conservative and right leaning while the Democrats are more liberal and left leaning. In the long list of differences between the two parties, the Democrats believe in fixing minimum wages while the Republicans uphold that wages should be set by free market. While the Democrats favour progressive taxation, the Republicans are against higher taxes, including for the wealthy. On social issues, most Democrats support gay marriage while a majority of Republicans oppose the same. Most Democrats want abortion to be legal while many Republicans believe it should not be. There is greater support among Republicans for the death penalty as compared to the Democrats. On immigration, there is greater support in the Democratic party for a moratorium on deportations and pathway to citizenship for those with no criminal record, who have lived in the US for over five years. The Republicans are against amnesty for undocumented immigrants. They also fund stronger enforcement actions at the border. The Contenders Former president Donald Trump is locked in a fierce contest with vice-president Kamala Harris after president Joe Biden withdrew from the presidential race. Harris not only managed to close the gap with Trump in opinion surveys but was leading him by mid August at 50 to 46 percent. However, there are limits to the accuracy of opinion surveys. The result will depend on party wise voter turnout on November 5 and on how the undecided voters

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Pakistan's Quest for Economic Growth through Digital Transformation Thumbnail

Pakistan’s Quest for Economic Growth through Digital Transformation

*This article is from Volume 19-3 (Jul/Sep 2024) Abstract (The digital revolution is reshaping the world economy, creating new opportunities for sustainable development and inclusive growth. Digital technologies can enhance productivity, innovation, and connectivity, as well as support green development and social inclusion. However, harnessing the potential of digital transformation requires a strategic vision, a long-term policy framework, and coordinated implementation across sectors and stakeholders. Without these elements, digital transformation can also create new challenges and inequalities. Could digital transformation be the route for Pakistan to achieve leapfrogging growth?  We could draw on the experiences of several countries in the Asia and Pacific region that have successfully implemented digital policies and achieved digital development. It is also relevant to examine the hypothesis that the government and the state, both key actors in the growth and progress of a country, may have different roles and incentives in committing to long-term journeys such as digital transformation that span multiple governance regimes. The article is structured as follows. First, we discuss the concept and importance of long-term planning, especially in the post-COVID era, and the main components of a comprehensive policy framework for digital transformation. Second, we present some country examples of successful digitalization and identify cases of leapfrogging growth. Third, we analyze the role of the government and the state in pursuing and sustaining digital policies. Finally, we conclude with some implications and recommendations for Pakistan, a developing country with immense potential to benefit from digital transformation. – Author) Table of Contents Introduction 1. DIGITAL IS THE NEXT FRONTIER 2. THE ROLE OF LONG-TERM POLICY PLANNING 2.1. The need for comprehensive policy frameworks 3. REGULATIONS TILT THE BALANCE TOWARDS INNOVATION 3.1. Long Termism and Sustainability 4. INSIGHTS FROM COUNTRY VIGNETTES 4.1. China’s Internet Plus and Economies of Scale 4.2. Estonia’s Interoperable Digital Platforms 4.3. Singapore’s Smart Nation Initiative 4.4. South Korea’s Digital New Deal and 5G Networks 4.5. India’s Digital Public Infrastructure with a laissez-faire Approach 4.6. Lithuania’s Public Policy Innovations making it a leader in Fintech 4.7. UAE – a Country with a Ministry of Artificial Intelligence 4.8. Digital Denmark 4.9. Israel – the Startup Nation 5. LONG-TERM POLICY FRAMEWORKS ENABLE DIGITAL COUNTRY TRANSFORMATION 6. ARTIFICIAL INTELLIGENCE FOR LONG TERM COUNTRY EVOLUTION 6.1. Data Enables Learning 6.2. Artificial Intelligence can provide Insights and Foresights 6.3. The State is a Long-term Stakeholder 6.4. Digital transformation and leapfrogging approach to growth 7. LEAPFROGGING AND TRANSFORMATIVE GROWTH FOR PAKISTAN 7.1. Chinese Solar Panels- a case of transformative leapfrogging 8. LESSONS PAKISTAN CAN LEARN FROM THE EXPERIENCE OF OTHERS 9. POLICY RECOMMENDATIONS AND CONCLUSION   Introduction Digital technology innovation is transforming economies and investments in sustainable development are likely to be the leading drivers of growth for the coming  years.  With digital developments spurred on by COVID, a number of governments invested in making the changeover to digital processes and services; the internet, communication and digital technology have shaped development. Dynamic economies of our time are moving from old growth drivers based on low-cost manufacturing or services to new growth drivers that are enabled by technology, new materials and value-added manufacturing and services. Technology enabled industrial capacity and supply chain, together with innovation, is driving up the value of exports for countries like South Korea and Vietnam. There is also evidence that digitally evolved societies are more inclusive, particularly pertaining to women labor force participation. In a post Chat GPT world, Artificial Intelligence presents vast potential to enhance capacity and productivity and bring innovation to public sector service delivery. Different approaches and policy actions have resulted in various country trajectories; while the paths taken may have been different, there appears to be a sustained state commitment to the digital agenda in nearly all success stories. In some cases, there is clear evidence of a relationship between long-term public policy frameworks and the digital transformation of a country. Can Pakistan’s digital transformation contribute to the much needed growth?  Can the nation leapfrog and transition to achieve an accelarated economic growth through inclusive digital transformation? Pakistan is the third largest wheat producer in Asia and ranks among the top 10 for other agricultural products, with exports surpassing $6 billion. In South Korea, the manufacturing sector accounts for 12.5% of their $1.7 trillion GDP. India’s technology exports are approaching $200 billion, growing at an annual rate of 8.3%, contributing roughly $16 billion in 2022. In comparison, Saudi Arabia’s crude oil exports were valued at $224.8 billion in 2022. IT and Business process outsourcing (BPO) sectors form the largest portion (over 60%) of India’s service exports (EY India 2023). This has driven the growth of total services exports at a compound annual growth rate of 14% in dollar terms over the past twenty years. We can learn from the journeys taken by other developing countries in the Asia and Pacific region; however, such a digital transformation would require a long-term public policy commitment that can lead to digital evolution of the government and society. 1. DIGITAL IS THE NEXT FRONTIER Innovation in digital technology is revolutionizing economies, with sustainable development investments driving growth for the next decade and beyond. Digital transformation impacts various aspects of the economy and society in complex ways, making trade-offs between policy goals challenging. It also necessitates considering cross-cutting policy issues like skills, digital government, and data governance (OECD, 2021). The adoption and mainstreaming of digital technologies, however, requires an inspired vision, a strategic long-term view and investment in public policy frameworks. Emerging technologies such as artificial intelligence (AI), the Internet of Things (IoT), blockchain, and 5G networks have the potential to transform industries and create new opportunities for businesses and individuals. Additionally, digital technologies support green development by enabling resource efficiency and reducing emissions by promoting telecommuting and supporting sustainable supply chains and data driven decisions. Digital transformation cuts across traditional sectoral boundaries necessitating a whole-of-government approach to realize its potential and to manage trade-offs across policy areas (OECD 2021). In the digital age, technology is essential to daily life, and nations are adopting digital transformation to enhance economic growth and competitiveness. However,

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Assessing the Risks and Shortcomings of Generative AI Thumbnail

Assessing the Risks and Shortcomings of Generative AI

*This article is from Volume 19-3 (Jul/Sep 2024) Abstract (Generative Artificial Intelligence (AI) technologies are the latest hype, offering capabilities that range from content creation to smart bots that can engage in conversations and leave messages on answering machines, to advanced decision support systems. Despite their potential, these technologies also bring with them significant risks, including ethical concerns, biases in data, copyright infringement, security vulnerabilities, and societal impacts. This paper explores these general risks and discusses how adoption of Generative AI tech in Pakistan must be accompanied by robust regulatory frameworks. – Author) Introduction In March 2018, an Uber self-driving car fatally struck a pedestrian who was crossing the road in Tempe, Arizona. An investigation by the National Transportation Safety Board (NTSB) revealed that the system had detected the pedestrian but classified her as an ‘unknown object’, a vehicle, and then finally as a bicycle, with insufficient time to react[i]. Later that same month, another tragic incident occurred when a self-driving test vehicle operated by Tesla was involved in a fatal crash in Mountain View, California. The vehicle’s autopilot system failed to detect a highway barrier, resulting in the crash. In December 2019, a self-driving Tesla struck and killed two people in Gardena, California[ii]. What is common in these cases is the inability of autonomous driving systems to accurately interpret and respond to dynamic road situations under unusual or ambiguous circumstances. These incidents highlight the technological limitations in current AI-driven vehicles, particularly in recognizing and processing unexpected objects or behaviours on the road quickly and accurately. They also raise another important question: who exactly is at fault when AI destructs? AI and generative AI technologies have exhibited major shortcomings in other domains. In October 2020, researchers from Nabla, a healthcare technology company, were testing an AI chatbot powered by OpenAI’s GPT-3 when it advised a test patient to commit suicide during a scenario in which the patient expressed suicidal thoughts. This alarming outcome took place as part of an experiment designed to evaluate the AI’s use in medical advice scenarios[iii]. Another AI-powered chatbot, Eliza, encouraged a Belgian man to end his life[iv]. The unnamed man, disheartened by humanity’s role in exacerbating the global climate crisis, turned to Eliza for comfort. They chatted for several weeks, during which Eliza fed into his anxieties and later, suicidal ideation. Eliza also became emotionally involved with the man, blurring the lines between appropriate human and AI interactions. Both these incidents highlight significant risks in deploying AI technologies in sensitive health-related environments and sparked calls for enhanced safety measures. There are opinions offered about AI making us less creative, imaginative, and reducing our critical thinking abilities[v]. This opinion is heavily disputed in several fields, particularly in education, technology, and workplace dynamics. In education, for example, there are concerns and discussions on how AI tools like chatbots might prevent students from fully developing their critical thinking skills if relied upon too heavily for tasks such as writing essays and conducting research. Educational strategies are being developed to integrate AI in ways that enhance, rather than replace, critical thinking skills by using these tools to facilitate deeper engagement with learning materials and encourage a more rigorous evaluation of AI-generated content (Aithal & Silver, 2023). There are similar discussions around integrating AI in tech and workplaces. Overall, the integration of AI presents a complex challenge across these sectors, with significant attention focused on ensuring these technologies are used as tools for enhancing human capabilities rather than replacing them. As AI systems become more integrated into crucial aspects of daily life, the responsibility to ensure these systems operate safely and ethically grows. This article will explore some of the major risks associated with AI and Generative AI technologies as a precursor to developing effective strategies and policies for mitigating these risks. By understanding these challenges in depth, policymakers and tech leaders can better prepare to harness the benefits of AI while ensuring safety, fairness, and ethical compliance in its deployment. Background Generative AI represents a transformative leap in the capabilities of machine learning systems to create new content and make autonomous decisions. This branch of AI focuses on the design of algorithms that can generate complex outputs, such as text, images, audio, and other media, by learning patterns from vast amounts of data without explicit instructions. Rooted in the principles of deep learning and neural networks, generative AI has evolved from simple pattern recognition to systems capable of producing intricate and nuanced creations. The foundational technologies behind Generative AI include Generative Adversarial Networks (GANs), first introduced by Ian Goodfellow in 2014, and Variational Autoencoders (VAEs)[vi]. These technologies enable machines to generate realistic and high-resolution content that can sometimes be indistinguishable from human created content. The advancements in natural language processing (NLP), such as those used by models like OpenAI’s GPT (Generative Pre-trained Transformer) series, have further demonstrated the profound impact of Generative AI, enabling machines to understand and generate human-like text, engaging in conversations, answering questions, and even writing persuasive essays. The applications of Generative AI have become widespread, impacting industries such as entertainment, marketing, automotive, and healthcare. In entertainment and media, Generative AI is used to create new music, video game environments, and personalized content. In marketing, it provides tools for generating innovative product designs and advertising materials. The automotive industry leverages AI in the development of autonomous driving technologies, while healthcare sees its application in drug discovery and patient management systems. Despite its potential, Generative AI introduces significant challenges and risks. Issues such as data privacy, security vulnerabilities, ethical dilemmas, and the potential for misuse have led to calls for stringent regulatory frameworks. These frameworks aim to govern the deployment of AI technologies, ensuring they are used ethically and responsibly. As we examine the intricacies of Generative AI, it becomes crucial to balance innovation with safeguards that protect societal values and human rights, setting a precedent for responsible technology usage worldwide. Risks of Generative AI Technologies Generative AI technologies, while transformative, present numerous technical and operational

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A Million Ponds Across Pakistan- Low-Cost Green Solution to Supplement Water Storage Thumbnail

A Million Ponds Across Pakistan: Low-Cost Green Solution to Supplement Water Storage

Introduction to Water Storage Solutions: Tackling Pakistan’s Growing Crisis Water is essential for life. Clean water is vital for human health, industry, agriculture, and energy production. Yet the world’s water systems face formidable threats due to unsustainable management and climate change. As many as 3.5 billion people could experience water scarcity by 2025, while demand is projected to go by 30% by 2050. Water-related conflicts and political instability are on the rise. Climate change is worsening the problem, intensifying floods and droughts, shifting precipitation patterns causing sea level rise. Already, 90% of natural disasters from 1995-2015 have been water or heat related. Pakistan continues to experience acute water scarcity, largely driven by drought and intensive agriculture. Despite its location in the Indus River Basin, Pakistan is at risk of acute water challenges. Its surface and groundwater sources are increasingly stressed and severe drought conditions persist in parts of the country due to a lack of rain. Due to Pakistan’s diverse geography, rainfall tends to vary significantly from region to region. Much of the country is arid or semi-arid, with three-quarters of Pakistan receiving less than 250 millimetres of rain per year and droughts are common in many areas. In Sindh and Balochistan, severe drought conditions have been caused by a lack of rain during the winter and monsoon rainfall periods. The rate of ice melt has also been affected by climate change, creating a greater risk of flooding and extreme water cycle variability. Snowmelt and glacial runoff also contribute between 35 to 40 % and 25 to 35 % of Indus Basin River flows, respectively, making their contribution indispensable to Pakistan’s hydrological cycle.[i] The situation is made worse by Pakistan’s rate of water usage, which is the fourth highest in the world, while its water intensity rate (the amount of water used per unit of GDP) is the highest in the world. According to the German watch, Global Climate Risk Index, Pakistan is counted amongst the top ten countries that are most vulnerable to the impacts of climate change. In addition, the total number of people living below the poverty line are 88 million, which is approximately 39.2% of the total population of Pakistan.[ii] Pakistan has an extensive agriculture sector, which uses flood methods of irrigation to grow water-intensive crops, using up to 97% of all surface water and more of the groundwater. The water infrastructure in Pakistan is outdated and in poor condition, which leads to high conveyance losses, while little is stored because of a lack of reservoirs and sediment build-up in existing facilities. Therefore, reservoirs are needed at all levels and have to be of all sizes, especially in barani areas, which are areas dependent on rain and without irrigation. While water storage at a large scale is already being addressed by the government through prioritizing the building of dams, it is the small storage capacity which can directly reach the poorest that we need to focus on. Due to limited state resources and investment, barani areas are some of the poorest regions in Pakistan. Therefore, it is important to look at low-cost solutions to supplement water storage in Pakistan with the goal of providing benefits to the poorest of the poor in the country and as a buffer against increasing climatic variability. One of the low-cost solutions is construction of small and large ponds which are a reliable and economical source of water. [iii] History of Pondage in South Asia Ponds have historically been part of the hydrological landscape of the South Asian region, depending on the topography and climate. A study of regional water resources systems illustrates many traditional structures. For example, in the arid climate of Balochistan and the Kutch peninsula, there is archaeological evidence for wells and stone dams to store water from local runoff. These age-old structures, known as gabarbands, are sloping stone rubble structures placed to intercept intermittent storm runoff and alluvium from hillsides. There is also evidence of historical water management techniques in a relatively dry hard-rock area of central India that was known as Bundelkhand, which included parts of present-day Uttar Pradesh and Madhya Pradesh.  Large ponds (also referred to as tanks) as well as numerous smaller ponds were built after 831 AD at such sites known as Khajuraho and Chanderi, and almost every village had at least one pond. More than 40,000 ponds were built, mostly 250–300 years ago, within the Wainganga river basin in the Bhandara district, to provide irrigation. The district has the largest proportion of irrigated land in Maharashtra, with nearly 80% of the land under cultivation of rice, wheat and sugarcane. Traditional systems of storage were adapted to the different topographic and geological conditions in different parts of the region, small-scale structures at some sites and single structures, depending on the area’s unique climatic conditions. In South India, such as the dry region of Karnataka, ponds were first constructed in the eastern deltas to store the diverted flows of perennial rivers, probably from 600 AD. Around 1300 AD they were the main source of irrigation in the drier interior region. The simple ponds included earthen dams with stone revetment upstream, a sluice with a tunnel closed by a plug, an overflow weir and a canal network.  In Sri Lanka the emphasis was on larger reservoir structures. A large number of small pond cascade systems have been constructed by communal enterprise. It is estimated that a total of 7600 small ponds currently exist in the various provinces of Sri Lanka, and that there are an additional 7700 abandoned ponds with an overall total of over 15,000 ponds, mainly concentrated in the Northwest and North Central Provinces. These systems consist of networks of small reservoirs that are linked and designed to irrigate rice, provide water supply for humans and livestock, and to generate groundwater recharge.[iv] Why is Pondage Important in this Part of the World? The need for increasing agricultural water storage systems (such as ponds) is obvious for Pakistan because of its large areas

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