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The plethora of government tax, fiscal, and trade digital transformation initiatives are each occurring within a single country domain. A preliminary analysis of this growing digital transformation demand reveals multi-country interest in key tax, fiscal, and trade technology initiatives, including digital identification, multi-party data sharing, e-invoicing, distributed systems (e.g., blockchain) applied to global trade, and artificial intelligence / data systems to improve governmental decision-making. Absent intervention, these initiatives will continue as single-country initiatives, duplicative technology solutions will be developed, and intergovernmental technology interoperability will be sub-optimized.

Our idea is for The Prosperity Collaborative to lead an effort to convert certain aspects of this global digital demand to DPGs immediately available to multiple jurisdictions, playing a key leadership role in advancing DPGs for tax, fiscal, and trade systems within governments, as a practical solution for the Concept of AI-Government, conceived by Boston Global Forum and Michael Dukakis Institute. Our Collaborative builds and leads a multi-stakeholder consortium focused on developing and advancing DPGs in this important space. We could call this new organization the Digital Tax and Trade Consortium (DTTC). This new multi-stakeholder DTTC would be comprised of multilaterals, anchored by The World Bank, and ideally including the UN, OECD, ADB, etc.; fintech providers, World Economic Forum, technologists (principally, Microsoft), philanthropists, and leading policymakers.

Chair/Moderator: Mr. Ramu Damodaran, Chief Academic Impact of the United Nations.
Keynote speaker: Professor Alex Sandy Pentland, MIT
Dr. Tomicah Tillemann, Executive Director of the Digital Impact and Governance Initiative (DIGI) at New America
Mr. Jeff Saviano, EY Global Tax Innovation Leader
Mr. Anders Hjorth Agerskov, Lead Public Sector Specialist at the World Bank Group


Is it right, and this will be my last and third remark, to take the multilateral agreement on the Law of the Sea, which is a United Nations Agreement, as a model for our work on AI? The multilateral agreement on the Law of the Sea is the biggest binding convention of the United Nations. And I would say, having in mind the ambition to have as many countries on board as possible as a precondition for a global AI accord working, I think that makes the Law of the Sea a great model.

Second, the Law of the Sea at the time was extremely innovative in dealing with a space which was largely unexplored, out there beyond the sight of the coast, 70% of the space of the world and so deep at certain places that no men had ever seen the bottom of what was being regulated in binding international law. This was exactly the reason that states got together and agreed on, if you look at them today, amazing principles of a binding nature because everyone understood that this new frontier, the ocean being at the beginning of exploitation, deep sea mining and other forms of economic and scientific activity, needs common rules to avoid conflicts in the future.

And the United Nations and states went very far on this. They even set up a court and a dispute settlement system which today works fairly well. 

So, I think we should have our ambitions high, go beyond just repeating non-binding types of principles which we already find in the OECD code and in many ethic codes, focus on the specific nature of AI as a technology which provides us with the opportunity to set out principles on which agreement is possible, and we should aim for binding rules because we are dealing with power relations here and a matter of greatest importance both for states as well as natural persons.


This week in The History of AI at - Edward Feigenbaum, Bruce G. Buchanan, Joshua Lederberg, and Carl Djerassi began work on Dendral in 1965. This was an AI project that later also became the first expert system.

Edward Feigenbaum is an American computer scientist focused on Artificial Intelligence. He studied at Carnegie Mellon University for both his B.S. and Ph.D., with Herbert Simon, an AI pioneer, as his doctoral advisor. He would go on to work at UC Berkeley and Stanford, the latter where he became Professor Emeritus of Computer Science (since 2000). Feigenbaum received the ACM Turing Award in 1994 with Raj Reddy for pioneering in AI and demonstrating its commercial potential.

Dendral was deveveloped at Stanford beginning in 1965, after the question “Can machines think?” became popularized. Led by Edward Feigenbaum, Bruce G. Buchanan, Joshua Lederberg, and Carl Djerassi, and assisted by associates and students, the project sought to study hypothesis formation and discovery in science. “Dendral” is a portmanteau of “Dendritic Algorithm”. Many expert systems that came after, such as XCON, were derived from Dendral.

The beginning of this project is considered an event in the history of AI due to the project itself contributing much to the development of AI. Dendral itself was both a culmination of past AI interests and the sparking of new ones. Thus, the HAI initiative sees the project as a marker in the history of AI.


At the AI International Accord Roundtable April 28, 2021, Mr. Magnus Magnusson, Director for Partnerships and Outreach, UNESCO, presented “Bring Goodness and AI Ethics to AI International Accord, and view from UNESCO”. He raised “Diversity must be integrated in every single step of the AI lifecycle; from creation of algorithms to the collection of data, down to the numerous applications of AI in every aspect in today’s society: healthcare, education, transportation and so forth. This is the only way to ensure all voices will contribute to the development towards policies and frameworks for AI”.

Here is his talk:


We introduce part of the acceptance speech by the European Union Ambassador to the US Lambrinidis for the World Leader in AI World Society Award on April 28:

In Europe, we believe that there is a clear interrelation between Innovation and Fundamental Rights – that one can promote the other.

We value, champion, and thrive from innovation. Last year, as the deadly COVID-19 pandemic spread rapidly across the globe, AI demonstrated its potential to aid humanity by helping to predict the geographical spread of the disease, diagnose the infection through computed tomography scans, and develop the first vaccines and drugs against the virus.

European companies and innovators have been at the forefront in every aspect of that effort. The winner of last year's Future Unicorn Award, presented annually by the European Union to start-ups with the greatest potential, was awarded to a Danish company, Corti, which uses AI and voice recognition to help doctors predict heart attacks.

Clearly, the possibilities and opportunities for AI are immense – from turning on wind turbines to produce the clean energy for our green transition, to detecting cyber-attacks faster than any human being, or cancer in mammograms earlier and more reliably than trained doctors. We hope that AI will even help us to detect the next infectious outbreak, before it becomes a deadly pandemic.

We want AI to do all of these great things.
At the same time, just as in every technological evolution that has come before it, we must prepare for the unexpected. With the increasing adoption of AI, our rights to privacy, dignity, freedom, equality, and justice are all at stake. These are fundamental to our lives as Europeans, and enshrined in the European Charter of Fundamental Rights.
If it is our aspiration to create machines that are able to do more and more of our thinking, selections and decision-making, we must also take care to ensure they do not make the same mistakes that we humans have been prone to make.  Let me offer two examples to illustrate the point:

  1.  First – the use of facial, voice, and movement recognition systems in public places can help make our lives more secure. However, it can also allow governments to engage in mass surveillance, intimidation, and repression, as China has shown, in the most cynical and calculated way, in Xingiang. 
  2.  Second – the use of AI in recruitment decisions can be helpful. However, if a computer compares resumes of senior managers and concludes that being male is a good predictor of success, the data simply reflects bias – a bias within our society, which historically has favored men for leadership positions. We do not want AI to reinforce existing biases by copying and infinitely replicating them. 

These are just two examples that illustrate why we must not become bystanders to the development and deployment of AI. If we, the major world democracies, do not move to establish a regulatory framework, if we do not move fast, smart and strategically to build alliances and set standards for human-centric, trustworthy, and human rights-respecting AI with countries big and small from all over the world, I dread to think who might.


What Does the future of Taxation Look Like?

On May 6, 2021, Mr. Anders Hjorth Agerskov, Lead Public Sector Specialist at the World Bank Group, presented “Future of Taxation” at the United Nations Centennial Roundtable:
Tax administrations will become “invisible” – as data is captured seamlessly in real time

Data transfer from accounting systems will be automated through an Application Programming Interface and tax information will increasingly be embedded in blockchain enabled smart contracts, requiring no or minimal human intervention.

AI driven robotic decision-making will increase – but risks need to be managed!

Decisions within the tax administration are being automated. Such efforts will initially be based on Robotic Process Automation and later on more advanced algorithmic decision-making made possible by robust and federated Artificial Intelligence solutions and expert systems incorporating tax and case law.

Data and digital solutions will allow for a new generation of taxpayer services and experiences These may include prefilled tax returns, taxpayers’ access to their own filing information, taxpayers’ sharing of data with banks to expedite credit approvals, and privacy preserving queries on the tax file by researchers and local communities. The touchpoints will be personalized rather than developed solely from the perspective of the tax administration’s internal procedures. The focus will be on promoting user adoption and building trust.

Tax administrations’ mandate will expand – they could become governments’ data warehouse That means providing economic data for monitoring the economy; verifying compliance under social, (COVID-19 related) stimulus, and other programs; supporting the modelling of economic policy across agencies; and promoting transparency.

Ecosystem and stakeholder management will come to the fore
This is due to the increasing importance of collaboration with tech firms and tax advisers to build interfaces to the taxation system and through a shift in the deployment of resources from operations to systems design and maintenance.
The United Nations Centennial Roundtable was hosted by AIWS Innovations at AIWS City on May 8, 2021.



According to a recent World Economic Forum report, 50% of all employees will need reskilling by 2025. In the U.S. government alone, 18.2% of the federal government retired in 2020. Another 34% will be eligible for retirement by the fiscal year 2023. Our workforce demands are urgent.

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are increasingly adopted even without our knowledge. Their potential seems limitless. Jobs in AI range from data scientists and subject matter experts to data engineers and data analysts to economists, technical writers and ethicists. With this new frontier and the fact that these tools touch every aspect of our lives, leaders across the workforce spectrum see this as an all-hands moment.

In anticipation of this major workforce pivot, federal government leaders collaborated with Harvard, Johns Hopkins, the Naval Postgraduate School, NavalX and hundreds of industry and government stewards. Through the American Council for Technology and Industry Advisory Council (ATC-IAC), the AI Working Group met for the last two years to develop the following frameworks to help U.S. government agencies adopt, implement and educate AI technologies as well as evaluate ethical outcomes of AI.

At every stage, it is necessary to question everything relating to the consumption of AI. These four guides serve as valuable tools to help lead government and industry on bias, fairness, transparency, responsibility and interpretability of AI.

To support for AI technology and development for social impact, Michael Dukakis Institute for Leadership and Innovation (MDI) and Boston Global Forum (BGF) has established Artificial Intelligence World Society Innovation Network ( In this effort, MDI and BGF invite participation and collaboration with governments, think tanks, universities, non-profits, firms, and other entities that share its commitment to the constructive and development of full-scale AI for world society. This initiative is to develop positive AI for helping people achieve well-being and happiness, relieve them of resource constraints and arbitrary/inflexible rules and processes, and solve important issues, such as SDGs.

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