Lack of data is certainly not one of the issues at the table when discussing energy production and carbon emissions. Well-known sources for the former include the UN Statistics Division, the International Energy Agency (IEA), the U.S. Energy Information Administration (EIA), and British Petroleum (BP). The latter publishes an annual report while IEA data is behind a paywall. EIA offers open data access to a vast number of resources, including international carbon emissions. The main source for the latter is the Global Cabon Project created in 2001 and operating as an international partnership. The World Bank has carbon emissions data starting in 1960, but updates seemed to have stopped in 2014. The Global Carbon Atlas, initially funded by the BNP Paribas Foundation, is a good secondary source
Trade is one of the main trademarks of the globalization process. Nowadays, most countries in the world exchange products and services on a regular basis and use local comparative advantages to specialize in specific trade sectors and/or commodities. Food and agricultural products are important components of this process. Within countries, rapid urbanization has increased the demand for food. At the same time, the number of people working in the agricultural sector and living in rural areas has decreased substantially. While some food staples are imported, others are still produced locally but must travel from rural areas to urban centers and big cities to meet the demand.
Food products are thus in perpetual motion, moving from their place of birth as soon as possible towards a wide variety
In the last decade, Artificial Intelligence (AI), including siblings machine learning and deep learning, has been growing by leaps and bounds. More importantly, the technology has been deployed effectively in a wide range of traditional sectors bringing real transformational change while raising fundamental socio-economic (joblessness, more inequality, etc.) and ethical (bias, discrimination, etc.) issues along the way. As it stands today, AI, understood as a set of still-evolving technologies, seems poised to become a general-purpose technology that could leave no stone untouched.
As with other digital technologies, most developing countries face the daunting challenge of harnessing AI to foster national human development Prima facie, AI looks mostly like software, code that one can
The Evolution of Digital identity
The emergence of digital technologies provided the ground to shift from traditional systems based on physical identity. In the past, both foundational and functional identity mechanisms were centralized with individuals getting a physical document containing relevant personal attributes required by the issuing entity. Document management was totally in the hands of the end-user who used them as proof of identity to make claims in person.
The Internet and the digitalization of biometrics and other personal attributes propelled new ways of issuing and managing personal identity. This process started around the end of the last century and allowed Internet companies to start issuing online identities to its users. It also promoted efforts to release functional
Like previous technologies, such as the Internet, for example, blockchains have been driven by a high degree of techno-optimism not yet backed up by on the ground impact or reliable evidence. Undoubtedly, the technology, which is still rapidly evolving, has enormous potential in many sectors and could promote human development if harnessed strategically.
One of the many blockchain innovative traits is the use of sophisticated cryptographic tools to generate unique identities for individuals interacting within the distributed network. In principle, such identities can be pseudo-anonymous, immutable, secure and directly created and managed by their owners – thus not need for centralized or federated intermediaries This, in principle, make blockchains an ideal candidate to propel
In this sequel post, I will look at the various components of the UNDESA e-government index and then introduce the EIU democracy index to explore potential interlinks between the two,
The e-government development index (EGDI) comprises three distinct components 1. Online services. 2. Telecom infrastructure. And 3. Human capital. While the last two are obtained from external data sources (ITU, UNESCO, UNICEF), the first one is directly developed by the UN. A combination of website checking and a questionnaire sent to UN member states is used to generate the required data – albeit the data is not publicly available. The e-participation index comes from the same source.
The telecom index relies on user access to the Internet, mobiles, analog phones, and broadband. The human
Running on the coattails of the now infamous dot-com bubble, e-government first saw the light of day before the end of the last Millennium. At that time, where hype overtook the tech scene yet again, adding ‘e’ (as in electronic) to almost any theme became quite fashionable. First in the scene was e-commerce (and e-business) which foreshadowed the 1994 launching of Amazon, among others, followed by its successful IPO three years later. Surely, governments could also master the emerging digital technologies to improve their core functions while fostering increased efficiency, transparency, and accountability. Most governments in industrialized countries quickly jumped into the e-government wagon while emerging economies such as Estonia, Singapore, and South Korea were determined not to
Blockchain technology development has been accompanied by a substantial increase in related research. The latter usually trails new technology innovations, but it does tend to catch up in the short-term. Ten years after the emergence of blockchains, there is plenty of ongoing academic and other research. Keeping track of its volume requires some sort of collaborative effort among different actors. Enter the Blockchain Research Network, BRN.
Created last Summer, BRN is an independent network open to all researchers regardless of affiliation. Furthermore, BRN is not linked to any academic institution or business organization, nor does it plan to be. It is thus decentralized, working ins the same fashion as traditional Open Source networks. To date, BRN has over 400 registered members who
Infrastructure development has been one of the main concerns of Internet promoters. It is usually posited as one of the key obstacles impeding universal access to the global network. Digital divide concerns and calls to connect the next billion are perhaps the best-known examples of such worldview. For the record, this is not an Internet-only issue. Many technologies face a similar conundrum and few, such as radio and television, can claim almost universal access. Mobile technologies, touted by some as the fastest spreading technology ever, are still struggling to reach such goal.
The issue of technology diffusion is undoubtedly much more complicated than just infrastructure development. Indeed, it is a multidimensional one that involves many variables and parameters. In this light, the Inclusive
A recent piece in MIT’s Technology Review nicely summarizes the issue of bias in AI/ML (AI) algorithms used in production to make decisions or predictions. The usual suspects make a cameo appearance including data, design and implicit fairness assumptions. But the article falls a bit short as it does not distinguish between bias in general and that which is unique to AI.
Indeed, I was surprised to see the issue of problem framing as the first potential source of AI bias. While this might occur in some cases, this is not an issue that only pertains AI projects and enterprises. For example, large multinational drug companies indeed face a similar challenge. Nowadays, almost none of them are investing in developing new antibiotics to stop the spread of the so-called superbugs nor have any interest