As of October 2021, 44 countries were reported to have their own national AI strategic plans, showing their willingness to forge ahead in the global AI race. These include emerging economies like China and India, which are leading the way in building national AI plans within the developing world.
Oxford Insights, a consultancy firm that advises organisations and governments on matters relating to digital transformation, has ranked the preparedness of 160 countries across the world when it comes to using AI in public services. The US ranks first in their 2021 Government AI Readiness Index, followed by Singapore and the UK.
Notably, the lowest-scoring regions in this index include much of the developing world, such as sub-Saharan Africa, the Carribean and Latin America, as well as some central and south Asian countries.
The developed world has an inevitable edge in making rapid progress in the AI revolution. With greater economic capacity, these wealthier countries are naturally best positioned to make large investments in the research and development needed for creating modern AI models.
In contrast, developing countries often have more urgent priorities, such as education, sanitation, healthcare and feeding the population, which override any significant investment in digital transformation. In this climate, AI could widen the digital divide that already exists between developed and developing countries.
The hidden costs of modern AI
AI is traditionally defined as “the science and engineering of making intelligent machines”. To solve problems and perform tasks, AI models generally look at past information and learn rules for making predictions based on unique patterns in the data.
AI is a broad term, comprising two main areas – machine learning and deep learning. While machine learning tends to be suitable when learning from smaller, well-organised datasets, deep learning algorithms are more suited to complex, real-world problems – for example, predicting respiratory diseases using chest X-ray images.
Crucially, neural networks are data hungry, often requiring millions of examples to learn how to perform a new task well. This means they require a complex infrastructure of data storage and modern computing hardware, compared to simpler machine learning models. Such large-scale computing infrastructure is generally unaffordable for developing nations.
Beyond the hefty price tag, another issue that disproportionately affects developing countries is the growing toll this kind of AI takes on the environment. For example, a contemporary neural network costs upwards of US$150,000 to train, and will create around 650kg of carbon emissions during training (comparable to a trans-American flight). Training a more advanced model can lead to roughly five times the total carbon emissions generated by an average car during its entire lifetime.
Developed countries have historically been the leading contributors to rising carbon emissions, but the burden of such emissions unfortunately lands most heavily on developing nations. The global south generally suffers disproportionate environmental crises, such as extreme weather, droughts, floods and pollution, in part because of its limited capacity to invest in climate action.
Developing countries also benefit the least from the advances in AI and all the good it can bring – including building resilience against natural disasters.
Using AI for good
While the developed world is making rapid technological progress, the developing world seems to be underrepresented in the AI revolution. And beyond inequitable growth, the developing world is likely bearing the brunt of the environmental consequences that modern AI models, mostly deployed in the developed world, create.
But it’s not all bad news. According to a 2020 study, AI can help achieve 79% of the targets within the sustainable development goals. For example, AI could be used to measure and predict the presence of contamination in water supplies, thereby improving water quality monitoring processes. This in turn could increase access to clean water in developing countries.
The benefits of AI in the global south could be vast – from improving sanitation to helping with education, to providing better medical care. These incremental changes could have significant flow-on effects. For example, improved sanitation and health services in developing countries could help avert outbreaks of disease.
But if we want to achieve the true value of “good AI”, equitable participation in the development and use of the technology is essential. This means the developed world needs to provide greater financial and technological support to the developing world in the AI revolution. This support will need to be more than short term, but it will create significant and lasting benefits for all.
GreenBiz came up with these six tips for deploying data-driven energy management to drive meaningful emission reductions through reducing building operating emissions at scale with data analytics. So here is a much down to earth way to a certain decarbonisation strategy.
Reducing building operating emissions at scale with data analytics
Nearly 40 percent of global CO2 emissions come from the built environment — with 28 percent resulting from buildings in operation. Whether your organization owns, operates or occupies a building, data-driven energy management is key to reducing its GHG footprint and Scope 1 and 2 emissions.
In the past, organizations have struggled to scale building operational energy improvement efforts for a variety of reasons. The most-cited reasons include organizational structures that fracture ownership of energy performance across disparate stakeholders, a lack of goal alignment and collaboration between landlords and occupiers, and the preponderance of legacy systems that make interoperability and data consolidation challenging.
According to United Nations projections, carbon emissions from buildings are expected to double by 2050 if action at scale doesn’t occur. With more companies pledging to decarbonize their business, and investors increasingly scrutinizing ESG data, scalable energy management will be a critical step in the transition to a low-carbon economy.
Today, we share six tips for deploying data-driven energy management at scale to drive meaningful emission reductions from your business.
Collect meter-level energy consumption data where possible
Identifying GHG reduction opportunities should be a data-driven, systematic process. Start by examining building-level energy meter profiles and understanding how usage patterns relate to changing occupancy and weather conditions. Meters, which typically generate one datapoint every 15 to 30 minutes, as opposed to one datapoint every month or quarter on a utility bill, provide rich data to better inform your organization’s decarbonization strategy.
Tip: Leverage meter data, which provides real-time transparency of when and where energy is being used, to identify unexpected usage patterns and unlock higher-resolution benchmarking and analysis opportunities.
Benchmark the energy intensity of your building portfolio
Building-level energy management is powerful, but it never pays to operate in a vacuum. Understanding how a building performs compared to others provides context and can help your organization identify where to focus first. The approach to benchmarking depends on the type of buildings in your portfolio.
For example, typical portfolios of small to medium buildings (buildings of 4,000 to 20,000 square feet or so) often include many buildings dispersed across a geography (such as convenience stores, bank branches and fast-food stores), while large shopping centers, hospitals and universities manage larger, but fewer, centralized complex buildings.
Portfolios with larger commercial buildings can leverage third-party frameworks, such as Leadership in Energy and Environmental Design, Energy Star and NABERS, which compare energy intensity against an industry benchmark.
For portfolios of small to medium buildings that are dispersed, external benchmarks are harder to find. In this case, Envizi recommends internal benchmarking using meter data to make meaningful performance comparisons. Advanced normalization techniques can be applied to identify the poorest performers in the portfolio, which helps to inform a highly targeted strategy for improving efficiency and reducing emissions.
Tip: Undertake energy benchmarking before making investment decisions — don’t make the mistake of focusing on areas where there are no material savings. Envizi’s software can combine meter data with other contextual data (floor area, weather, operating schedules, and production units) to enable performance comparisons on a normalized basis.
Tune operational and behavioral efficiency
Buildings can be complex, but not as complex as building operations: the interaction between a building, its operators and occupants, and flow-on effects to energy performance.
Building services such as heating, ventilation and air conditioning (HVAC), which often account for almost 30 percent of annual emissions, are subject to continuous change and are often responsible for considerable “energy drift” over time due to poor operational practices. For this reason, technology that proactively informs and educates building operators is necessary to support time-poor operations teams to maintain optimum performance.
Often, manual audits will not detect the inefficiencies, but Envizi’s software uses a combination of continuous equipment monitoring, building management systems data, equipment nameplate data, weather data and other metrics to provide transparency to HVAC system performance and uncover operational issues that are otherwise difficult to detect.
Consider plant and equipment upgrades
Investing in equipment to deliver emissions reductions is dependent on an organization’s scale, scope and asset type and may be relevant only to building owners.
The appetite for plant and equipment upgrades may depend on how long the asset owner intends to hold the asset, the age of the building and the age of the equipment. Envizi recommends that building owners and operators engage their engineering consultants and specialist contractors to determine the feasibility of plant and equipment upgrades.
Tip: Technology can assist in the pre- and post-analysis of reduction projects to measure effectiveness and return on investment (ROI). Envizi’s software uses the International Performance Measurement and Verification Protocol to ensure calculations will withstand audit and validation.
Consider on-site and off-site renewables
After implementing solutions for operational, behavioral and system efficiencies, many organizations seek renewable energy as a proactive solution to get ahead on the decarbonization journey. Decisions on whether to procure on-site or off-site renewables are complex, and Envizi recommends coordinating with your organization’s engineering consultant or specialist contractor to assess its options.
Tip: Software platforms such as the one offered by Envizi can assist with monitoring the performance of solar assets, comparing the actual performance to promised performance and integrating the accounting of the renewable energy certificates to facilitate the most traceable reporting and auditing process.
Energy management is rarely the remit of one team, but rather involves multiple stakeholders across an organization. The success of any emissions-reduction effort will be affected by the organization’s ability to effectively engage a cross-collaborative stakeholder group.
Typically, organizations with a strong culture of governance and executive ownership of the energy agenda can make the most impactful positive change. Often, inspirational leaders can make the difference with robust internal communication, empowerment through clear roles and responsibilities, and incentives for employees to take ownership of the energy reduction goals.
The transition to a low-carbon economy will require organizations to drastically increase the energy efficiency of buildings in operation. The following data-driven tactics can help your organization identify and achieve meaningful emission reductions:
Collect meter data where possible to understand granular energy consumption.
Benchmark the energy performance of the buildings by size/cohort in your organization’s portfolio to identify poor performers.
Use technology to monitor how HVAC systems are configured, to detect energy waste and optimization opportunities.
Before implementing equipment retrofits, solar photovoltaics or energy projects, engage a specialist to understand your organization’s options, and use data to establish a baseline against which to measure improvements.
Nominate a senior executive to champion your organization’s emissions-reduction program. A single system of record for emissions and energy can help enable cross-functional collaboration.
If you’d like to learn more about using data and technology to streamline and accelerate decarbonization, read “Pathway to Low-Carbon Guide.”
Rich Miller writes in DATACENTERFrontier that Beyond Green Power: New Frontiers in Data Center Sustainability can easily be envisioned as these are increasingly populating planet earth.
Above picture is of Large pipes sporting Google’s logo colors move water throughout the cooling plant at the Google’ data center in Douglas County, Georgia. (Photo: Google)
February 3, 2021
Sustainable Construction Strategies
More data center projects will integrate sustainability into design and construction, with early collaboration between teams to minimize the environmental impact of the construction process and create a building with low operational carbon impact, enabling more effective and cost-efficient offset strategies. Design collaboration is essential in seeking to integrate cleaner technologies into the power chain and cooling systems.
Several data center providers are working with CarbonCure, which makes a low-carbon “greener” concrete material for the tile-up walls that frame data centers. Concrete’s durability and strength are ideal for industrial construction, but the production of cement requires the use of massive kilns, which require large amounts of energy, and the actual chemical process emits staggeringly high levels of CO2. CarbonCure takes CO2 produced by large emitters like refineries and chemically mineralizes it during the concrete manufacturing process to make greener and stronger concrete. The process reduces the volume of cement required in the mixing of concrete, while also permanently removing CO2 from the atmosphere.
Waste Stream Accountability and the ‘Circular Economy’
A key priority is tracking the environmental impact of construction components, including a “reverse logistics” process to track the waste stream and disposition of debris. Asset recovery and recycling specialists will become key partners, and the most successful projects will communicate goals and best practices across the contractors and trades participating in each project. The goal is a “circular economy” that reuses and repurposes materials.
Managing packaging for equipment that is shipped to a data center facility is an important and often underlooked facet of waste stream accountability. There are also opportunities in reuse of components and equipment that that can still be productive (although this must be closely managed in a mission-critical environment).
The ability to document a net-zero waste stream impact has the potential to emerge as an additional metric for data center service providers, as customers consider the entirety of their supplier’s sustainability programs.
As customers ask tougher questions about a providers’ environmental practices and corporate social responsibility policies, certifications may emerge as another avenue for service providers to differentiate themselves.
Several ISO certifications, including ISO 50001 and ISO 14001, which Iron Mountain is certified for across its global data center portfolio, focus on energy management and provide frameworks that can assure stakeholders that the provider is considering energy impact and environmental goals in audits, communications, labeling and equipment life cycle analysis.
Water Conservation and Management
Amid changing weather patterns, many areas of the world are facing drought conditions and water is becoming a scarcer and more valuable resource. Data center operators are stepping up their efforts to reduce their reliance on potable water supplies.
Sustainable water strategies include both sourcing and design. On the sourcing front, several Google facilities include water treatment plants that allow it to cool its servers using local bodies of water or waste water from municipal water systems. Data center districts in Ashburn (Va.), Quincy (Washington) and San Antonio offer “grey water” feeds that provide recycled waste water to industrial customers.
On the design front, more providers are choosing cooling systems with minimal need for water, while others are incorporating rainwater recovery strategies that capture rain from huge roofs or parking lots and store it on site, reducing potential burden on local water systems.
Matching Workloads to Renewable Energy
Google has been a leader in the use of artificial intelligence and sophisticated energy provisioning to match its operations to carbon-free energy sources. The company recently said it will power its entire global information empire entirely with carbon-free energy by 2030, matching every hour of its data center operations to carbon-free energy sources. This marks an ambitious step forward in using technology to create exceptional sustainability.
Google can currently account for all its operations with energy purchases. But the intermittent nature of renewable energy creates challenges in matching green power to IT operations around the clock. Solar power is only available during daylight hours. Wind energy can be used at night, but not when the wind dies down. Google created a “carbon-intelligent computing platform” that optimizes for green energy by rescheduling workloads that are not time-sensitive, matching workloads to solar power during the day, and wind energy in the evening, for example. The company also hopes to move workloads between data centers to boost its use of renewables, a strategy that offers even greater potential gains by shifting data center capacity to locations where green energy is more plentiful, routing around utilities that are slow to adopt renewables.
Google has pledged to share its advances with the broader data center industry, providing others with the tools to reduce carbon impact. Continued instrumentation of older data centers is a key step in this direction.
Eliminating Diesel Generators
Microsoft recently announced plans to eliminate its reliance on diesel fuel by the year 2030, which has major implications for the company’s data centers, many of which use diesel-powered generators for emergency backup power. With its new deadline, Microsoft sets in motion a push to either replace its generators with cleaner technologies, or perhaps eliminate them altogether by managing resiliency through software.
Eliminating expensive generators and UPS systems has been a goal for some hyperscale providers. Facebook chose Lulea, Sweden for a data center because the robust local power grid allowed it to operate with fewer generators. In the U.S., providers have experimented with “data stations” that operate with no generators on highly-reliable locations on the power grid.
There are four primary options companies have pursued as alternatives to generators — fuel cells, lithium-ion batteries, shifting capacity to smaller edge data centers that can more easily run on batteries, and shifting to cloud-based resiliency.
Fuel Cells and On-Site Power
Microsoft has successfully tested the use of hydrogen fuel cells to power its data center servers. The company called the test “a worldwide first that could jump-start a long-forecast clean energy economy built around the most abundant element in the universe.”
Microsoft said it recently ran a row of 10 racks of Microsoft Azure cloud servers for 48 hours using a 250-kilowatt hydrogen-powered fuel cell system at a facility near Salt Lake City, Utah. Since most data center power outages last less than 48 hours, the test offered a strong case that fuel cells could be used in place of diesel generators to keep a data center operating through a utility outage.
Some companies, like Equinix and eBay, have deployed Bloom Energy fuel cells to improve reliability and cut energy costs, but have powered them with natural gas. The use of biofuels looms as another potential avenue to pair fuel cells with renewable sourcing.
Utility-scale energy storage has long been the missing link in the data center industry’s effort to power the cloud with renewable energy. Energy storage could overcome the intermittent generation patterns of leading renewable sources. Solar panels only generate power when the sun is shining, and wind turbines are idle in calm weather. Energy storage could address that gap, allowing renewable power to be stored for use overnight and on windless days.
A new project in Nevada will showcase a potential solution from Tesla, the electric car company led by tech visionary Elon Musk. Data center technology company Switch will use new large-scale energy storage technology from Tesla to boost its use of solar energy for its massive data center campuses in Las Vegas and Reno. It is a promising project in pioneering a holistic integration of renewable power, energy storage and Internet-scale data centers.
Talking Sustainability With Experts
Don’t miss the last installment of this series that features a conversation on the future of sustainable data centers. Data Center Frontier Editor Rich Miller discusses the topic with Kevin Hagen, Director, Corporate Responsibility at Iron Mountain, and Alex Sharp, Global Head of Design & Construction — Data Centers at Iron Mountain.
It’s a preview of the upcoming webinar where these experts will discuss sustainability strategies for greener data centers.
The spread of China’s “techno-authoritarianism,” its pursuit of the “innovation advantage,” and its incompatibility with the liberal democratic model is the focus of a new report. The underlying dynamics and tensions between markets, non-state actors and governments are compelling governments to pursue strategic alliances and partnerships, and the inherent ideological differences between the Chinese system and those of open market, liberal democracies will influence outcomes, argues analyst Alex Capri.
Beijing’s imposition of the national security law in Hong Kong, as well as its internment of ethnic Muslim minorities in China’s western Xinjiang autonomous region, were just several of the latest provocations causing European policymakers to rethink relations with China. Thus, for Beijing, it has become increasingly difficult to find sympathy in Europe regarding Washington’s campaign to crush Huawei….New partnerships, including the Global Partnership on Artificial Intelligence* (GPAI) and the G7 AI Initiative, that are designed to guide the liberal and transparent development of AI, stand in contrast to China’s export of techno-authoritarianism.
A question that has begun to circulate in trade policy circles is: could a coalition of willing nations form a new global trade institution with standards that require open market principles and democratic ideals? RTWT
In “Artificial Intelligence and Democratic Norms,” the fourth in the “Sharp Power and Democratic Resilience” series from the International Forum for Democratic Studies, Nicholas Wright explores how to establish democratically accountable rules and norms that harness the benefits of artificial intelligence-related technologies, without infringing on fundamental rights and creating technological affordances that could facilitate authoritarian concentration of power.
In Lebanon, around 350,000 Syrian refugees don’t have access to enough safe and nutritious food. To stem the crisis, the World Food Programme (WFP) of the United Nations introduced an electronic voucher system to distribute food aid. People are given debit cards loaded with “e-vouchers” that they can use in certain shops to buy food.
But we found that Syrian refugees living in rural Lebanon often have to make difficult choices when buying essential items at the expense of food. Their e-vouchers can only be used in exchange for food, not other essentials like nappies.
Refugees have to engage in “grey-area transactions” that work around the e-voucher system, by asking shop owners to sell them the nappies and instead record on the system that they bought food. This places refugees in a vulnerable position – shop owners often charge higher prices for scanning non-food items as food, but refugees have no choice but to depend on shop owners to cooperate.
Collective purchasing allows refugees to pool their cash and e-vouchers so that one person can buy non-food items for another and be repaid with food. This allows people a degree of autonomy – they don’t have to rely on shop owners to allow them to buy non-food items using their vouchers. Instead, the community can manage their resources and needs among themselves.
Unfortunately, the e-voucher system prevents refugees from buying goods in bulk. Shop owners are advised by the WFP that purchases by refugees should be typical of buying food for a family. If refugees want to buy enough rice for their community and benefit from a wholesale discount, then the shop owner can refuse the transaction. This makes collective purchasing – something refugees often prefer to do when they have cash available – more difficult.
The WFP is currently piloting blockchain technology to replace this e-voucher system in Jordan and Pakistan. This is an exciting opportunity to alleviate these problems and help to empower both refugees and the shop owners, but only if the refugees themselves are involved.
Food aid designed by refugees
Rather than using a debit card, under this new system refugees would have a digital wallet that is similar to a bank account that you can access online. And instead of it being hosted by a bank, it’s part of the blockchain.
A blockchain is a shared log of transactions, with each user being able to track how much money and goods have been exchanged. This is constantly updated as transactions of food aid and money transfers are agreed between the customer and the shop owner. Each transaction forms a block of new information. The digital ledger is an expanding chain of interconnected blocks of information – hence the name, blockchain.
The WFP is using blockchain technology to cut costs on currency exchange and bank transfers. But the blockchain still allows transactions between refugees and shop owners in the same manner as the e-voucher system. If this new and innovative technology mimics the model that came before, the restrictions on what refugees can do will continue and blockchain will mimic paternalistic aid models that focus on efficiently distributing aid, rather than empowering refugees to leverage their own ways of coping with food insecurity. But if aid is designed with input from refugee communities, the technology could give Syrian people in Lebanon more agency when buying the essentials they need to live.
Blockchain can write smart contracts, which would allow people to buy items together. These are agreements whose terms are automatically enforced by an algorithm. Smart contracts act like a lock box with two keys that can be used to open it, one key is given for each party involved in the contract.
When the smart contract is created, both parties set the conditions that need to be met for them to be able to use the keys to open the lock box. Both keys need to be used for the lock box to open and for the money to transfer to complete the transaction. Before this can happen, both parties must agree that the conditions of the contract have been met. With this, refugee communities can negotiate collective purchases with shop owners and hold them accountable to the agreements they make.
Negotiating the terms of the smart contract means that refugees have more of a say over what they consider to be a fair deal. Once the smart contract is in place, the agreed sum of money for the purchase will be placed in a digital wallet – the lock box – that is bound by the terms of the smart contract. The value of items purchased by refugees is deducted once they’ve verified their identity with a retina scan, but the money will only be released to the shop owner if the refugees verify that they received the items.
We saw how these smart contracts could rebalance the power disparity between refugees and shop owners. Including refugees in the design process of humanitarian technologies and aid models can ensure they incorporate the values and practices of the people they’re supposed to help. Future innovations must be rooted in the daily lives of refugee communities. These technologies can empower people and make a real difference to their lives, but only if they’re allowed to design how they work.
Originally posted on The Present Perfect: Day one of my spring break trip and I am already being reminded that traveling is not all sunshine and rainbows. Over the last two years of not traveling, I had almost forgotten about the unpleasant side of traveling just wanting to be magically transported to the colorful scenes…
Originally posted on Journal of Pharmacy & Pharmacognosy Research: The Blog: Image: Flickr Article published in the Journal of Pharmacy & Pharmacognosy Research 10(2): 279-302, 2022. Ouafae Benkhnigue1,2*, Noureddine Chaachouay3, Hamid Khamar1,2, Fatiha El Azzouzi2, Allal Douira2, Lahcen Zidane2 1Department of Botany and Plant Ecology, Scientific Institute, University Mohammed V, B. P. 703, Rabat 10106, Morocco. 2Plant,…
Originally posted on International Relations Today: Radia Mernissi is an International Relations student, her Moroccan background make her particularly interested in North African politics and neo-imperialism. She is also passionate about International Law and its application to conflict and security. On the 24th of August 2021, Algeria officially declared it would cut diplomatic ties with…
This site uses functional cookies and external scripts to improve your experience.
Privacy & Cookies Policy
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.