Final survey report on ai perspective and challenges of developing nations by shreedeep rayamajhi

1 | P a g e Report on AI Perspective and Challenges of Developing Nations
Shreedeep Rayamajhi | Rayznews| Learn Internet Governance
Executive Summary
Today, Artificial Intelligence (AI) is used in various sectors like healthcare, finance, education and
security for achieving better growth and development. The AI development is influencing the global
economy in such a way that it’s evolving into a culture.
The random growth and development have resulted in gaps of standard values where other externalities
are aspiring to create a variation of abnormalities. Especially, in the developing and lower economies
there are limitations of knowledge, resource and infrastructure and due to these deficiencies, the digital
divide gap is widening between the countries.
Although technology may change the industry’s efficiency and effectiveness but ultimately what matters
is how our societies and communities are adapting at grassroots level. As there are considerable
uncertainties about AI and its overall process. The Trust factor for AI is still a challenge to overcome.
Similarly, the delegation of decision-making, lack of transparency, and lack of standards have outpaced
the development of governance and policy norms which needs to be mitigated with proper values.
There is a greater need of a global AI governance system that is flexible and standard enough to address
the cultural differences and bridge gaps across nations.
With such hindrances, AI has become a daunting topic especially for the developing nations where there
are lack of policies and regulation. The statement itself can be reframed with issues of Data Protection,
Definition of Data, Privacy, Freedom of Expression (FoE), Big Data etc. Still today a lot of the developing
nations and other lower economies lack basic definition and other technical standards where
externalities are promulgating in creating a discriminatory condition.
Although, AI is a part of our lives, knowingly or unknowingly, we use various AI algorithms for fastening
our services. From Facebook to google to other reputed organizations, all use and harvest user data for
imprinting and profiling the pool of information. This information and its use are hidden from the users
creating a sense of mistrust and contradiction. Different AI strategies have been created by different
countries where no two strategies are similar, this has created a proliferation of power and standards.
The survey was done to highlight the current knowledge and understanding of developing nations
internet leaders and it highlight the current threat of AI politics that is emerging with in gaps that aspires
between the developed and developing nations.
Reality of today is AI drives the opportunities for leveraging businesses in various field of advance data
analytics, software designing, market prediction and language capabilities for creating new business
models. The challenges that AI faces is the process of designing a governance mechanism for AI
ecosystem which is part of the cycle of market development and evolution of AI in the future.
“AI needs a vision for future. A vision which is beyond the limitation of control, power and
manipulation. AI needs governance with the human values of creating a better tomorrow focusing
inclusion, equality and trust. “

ITU Data:
Source: ITU (1)
ITU estimates that at the end of 2018, 51.2 per cent of the global population, or 3.9 billion people, were
using the Internet.
Individuals using the Internet in Millions
Source: ITU (1)
Region 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Africa
15 19 24 30 37 54 68 85 107 132 164 190 213
Arab States
26 33 46 55 65 84 93 106 120 135 151 162 173
Asia & Pacific
345 395 505 616 728 873 989 1,110 1,239 1,397 1,552 1,697 1,813
Commonwealth
of Independent
States (CIS)
26 33 43 49 56 94 111 139 153 163 174 183 191
Europe
279 302 343 372 395 410 419 434 447 461 472 490 501
The Americas
318 348 387 405 428 456 483 526 541 567 612 637 662

Developed/Developing Nations, according to the UN M49* (2)
Developed Nations Developed Nations
Albania
Andorra
Australia
Austria
Belarus
Belgium
Bermuda
Bosnia and Herzegovina
Bulgaria
Canada
Croatia
Czech Republic
Denmark
Estonia
Faroe Islands
Finland
France
Germany
Greece
Greenland
Hungary
Iceland
Ireland
Israel
Italy
Japan
Latvia
Liechtenstein
Lithuania
Luxembourg
Malta
Moldova
Monaco
Montenegro
Netherlands
New Zealand
Norway
Poland
Portugal
Romania
Russian Federation
San Marino
Serbia
Slovakia
Slovenia
Spain
Sweden
Switzerland
The Former Yugoslav Rep. of Macedonia
Ukraine
United Kingdom
United States

Developing Nations Developing Nations
Afghanistan
Algeria
American Samoa
Angola
Anguilla
Antigua and Barbuda
Argentina
Armenia
Aruba
Azerbaijan
Bahamas
Bahrain
Bangladesh
Barbados
Belize
Benin
Bhutan
Bolivia (Plurinational State of)
Botswana
Brazil
British Virgin Islands
Brunei Darussalam
Burkina Faso
Burundi
Cambodia
Cameroon
Cabo Verde
Cayman Islands
Central African Rep.
Chad
Chile
China
Cocos Keeling Islands
Colombia
Comoros
Congo (Rep. of the)
Cook Islands
Costa Rica
Côte d'Ivoire
Cuba
Cyprus
Dem. People’s Rep. of Korea
Dem. Rep. of the Congo
Djibouti
Dominica
Dominican Rep.
Ecuador
Egypt
El Salvador
Equatorial Guinea
Eritrea
Eswatini
Ethiopia
Falkland (Malvinas) Is.
Fiji French Polynesia
Gabon
Gambia
Georgia
Ghana
Grenada
Guam
Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Hong Kong, China
India
Indonesia
Iran (Islamic Republic of)
Iraq
Jamaica
Jordan
Kazakhstan
Kenya
Kiribati
Korea (Rep. of)
Kuwait
Kyrgyzstan
Lao P.D.R.
Lebanon
Lesotho
Liberia
Libya
Macao, China
Madagascar
Malawi
Malaysia
Maldives

Mali
Marshall Islands
Mauritania
Mauritius
Mayotte
Mexico
Micronesia
Mongolia
Montserrat
Morocco
Mozambique
Myanmar
Namibia
Nauru
Nepal (Republic of)
Neth. Antilles
New Caledonia
Nicaragua
Niger
Nigeria
Niue Northern Marianas
Oman
Pakistan
Palau
Palestine**
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Puerto Rico
Qatar
Rwanda
Sao Tome and Principe
Samoa
Saudi Arabia
Senegal
Seychelles
Sierra Leone
Singapore
Solomon Islands
Somalia
South Africa
Sri Lanka
Saint Kitts and Nevis
Saint Lucia
Saint Vincent and the Grenadines
Sudan
Suriname
Syrian Arab Republic
Taiwan, Province of China***
Tajikistan
Tanzania
Thailand
Timor-Leste
Togo
Tokelau
Tonga
Trinidad and Tobago
Tunisia
Turkey
Turkmenistan
Turks & Caicos Is.
Tuvalu
Uganda
United Arab Emirates
Uruguay
Uzbekistan
Vanuatu
Venezuela
Viet Nam
Virgin Islands (US)
Yemen
Zambia
Zimbabwe

* Note: The M49 is a standard for area codes used by the United Nations for statistical purposes,
developed and maintained by the United Nations Statistics Division. Based on the M49, countries are
classified according to macro geographical regions and sub-regions, and selected economic and other
groupings, see: http://unstats.un.org/unsd/methods/m49/m49regin.htm
** Palestine is not an ITU Member State; the status of Palestine in ITU is the subject of Resolution 99
(rev. Busan, 2014) of the ITU Plenipotentiary Conference.
*** Taiwan, Province of China, is not listed separately in the UN M49 but included in China. It is shown
separately here since ITU data on China do not include Taiwan, Province of China, data.
Source: ITU (1)
Source: https://www.tractica.com/newsroom/press-releases/artificial-intelligence-software-revenue-to-
reach-59-8-billion-worldwide-by-2025/

Information about the Survey:
Date of Survey 19/12/2018 to 31/02/2019
Survey form Google docs
Link https://goo.gl/forms/QtcKlldqMC5qyJ1j2
Target Group Internet users and community
Survey type Questionnaire
Participation number 54 Participants
Methodology:
The survey was done using google doc application where people were invited to attend the survey.
Various links were set-up on social media sites like Facebook, Twitter and LinkedIn for inviting people for
the participation. Various AI communities from different regions were contacted for the responses as
well.
During this survey the participants were asked various questions in terms of Artificial Intelligence (AI),
their basic understanding, knowledge, challenges and various other social indicators of user behavior.
The selection of participants has been random including invitations sent and shared. Participants from
various fields and sectors have contributed in voicing the current problems and suggestions of their local
knowledge and understanding about AI.

Research Objectives:
The basic objective of this survey is to understand the common knowledge and understanding of
Artificial Intelligence in developing nations citizen. With this survey we have tried to map the various
indicators that are creating a gap in between the developed and developing nations. Technology has
given a benefit to the developed nations where as in the developing nations due to lack of
infrastructure, policy and regulation data has been an issue of protection and concern. The gap in the
definition and adaptation of data has been a huge challenge for locals where AI has been a focal point
for multinational organizations for business purpose.
This report deals with the basic objective of understanding the capacity of normal person in terms of
their knowledge and adaptation of AI in developing nations.
➢ Finding the basic knowledge and understanding of AI
➢ Highlighting the problems and challenges of AI
➢ Participation and inclusion in AI process
➢ Creating better scenario of AI facilitation
➢ Identification of measurable AI indicators
➢ Adaptation and mitigation of AI
➢ Importance of AI governance
➢ AI Impact in developing nations
➢ AI gaps and politics
➢ AI integration behavior
According to McKinsey, corporations invested between $20 billion and $30 billion globally in 2016. This
included both internal research and development (R&D) and acquisitions. Tech giants such as Alibaba,
Amazon, Baidu, Facebook, and Google account for more than three quarters of total AI investment to
date. From 2011 through to February 2017, these companies were behind 29 of 55 major merger and
acquisition deals in the United States of America (USA) and 9 of 10 major deals in China

Findings of the Survey:

Problems and Challenges of Developing Nations:
Artificial intelligence has become a common name due to the various internet organization. People have
started to accept the use of AI in their daily lives. Though the acceptance of AI is very limited with in the
use of technology but every now and then when the AI comes into discussion of policy and leadership,
AI has been a challenge of substantive issues of policy, legality, governance, and ethical considerations.
Despite, the fact that AI is being used through various platforms like Facebook, Google and many other
technology companies’ people are unaware of their operations. This is creating a lack of understanding
among the people about the real fact and condition of AI. AI needs proper values and trust environment
where it can grow and flourish to create better opportunities. One thing we all must understand is
technology is for the people and people set the values of the use and values of diversity and inclusion
must be collaborated.
The major challenges are listed below:
1. Global Politics
2. Adaptation and Mitigation
3. Participation and Inclusion
4. AI Standardization and Governance
5. AI Vision
1. Global Politics: Artificial intelligence and its deployment has been a challenge with diverse set of
values of market, security and politics. AI has been nurtured in a limitation of how it has been
developed. Many countries have forwarded their strategies focusing on different aspects of AI
policy, scientific research, skills and education, public and private sector adoption, ethics and
inclusion, standards and regulations, and data and digital infrastructure. But with limitation, no two
strategies are the same. Reality is the gaps of the knowledge, resource and infrastructure has
created an assumption of rise of various mentality, theories and alliance creating a preconception of
what AI is or how it should be governed. The limitation of accepting the dynamic and generalizing
the concept has created a commitment of collaboration. This has created a vacuum in between the
developed and developing nations. The big IT organizations are manipulating the policies and law in
creating their own niche market of competition and manipulation. The global politics is hugely
fueled by lack of resource and infrastructure which has been pushed by the conspiracy theory of AI
global domination.
How can AI be dominating the world when we the people have not understood the true meaning
and value of technology. Why are we thinking more about technology domination when we are not
even talking about setting the basic values of AI?
The assumption of the global politics certainly creates a sense of power and control as the data and
information are the main tools of AI and future.
2. Adaptation and Mitigation: From the point of view of developing nations where there is lack of
knowledge, resources and infrastructure, the question of AI adaptation is a big hindrance. The part
that currently is a challenge is the notion of acceptance regarding the values that has been passed
on. The lack of clarity and diversity in assuming has resulted in a greater issue of widening the digital

divide.
Though situations are changing with developing nations coming up in the technology world but still
there is great need of adaptation in terms of various aspect of understanding the vitality of data and
information from the very basics. Developing nations need to understand their importance, role and
representation in terms of developing the basic values as well.
Mitigation can be an issue which can be further processed with
➢ Better awareness and capacity building
➢ Better law and policy
➢ Research and study about AI acceptance and other basic indicators
It may look simple with adaptation, but the issues of mitigation can be an issue that has been
related with the technological gaps. The social cultural values and the economical aspect can be of
greater issue that needs country specific values and solution.
3. Participation and inclusion: The current lack of participation and study of developing nations has
impacted the AI growth and development which has become more constraining towards the
developing nation. Participation and inclusion in developing values, policy making, and
collaboration has become a question of standardization. Every country has their own policy and set
of values with the acceptance of their socio-cultural behavior. Failing to mitigate the standard
creates multi-dimensional layer of gaps where externalities incubates. These include gaps of
discrimination and unfair competition.
Similarly, the concept of AI governance is more lacking the values of open and multistakeholder
approach where greater intervention is required to create better values of trust and collaboration.
Better facilitation environment must be created for participation and inclusion.
AI needs acceptance of human values and social cultural value only then it can be pervasive.
4. AI standardization and Governance: AI is expanding its capabilities and areas in reinventing the
concept of efficiency and effectiveness. Today businesses have streamlined production and even
transforming skillsets of the next generation workers to create better standards. The traditional
values and practices are changing influencing the overall human behavior. From country to country
the basic values are different, in such practices, inconsistency and clashes can be an issue of
concern where AI can be a converging in critical issue of how the situation can be dealt with. Digital
technologies are changing and challenging our society, the challenges related to AI are the
autonomous systems and algorithms that are often presented and discussed in practical issues of
policy, legal, governance, and ethical considerations which creates a convergence but with
limitation of standardization values it disrupts the overall process.
To ensure transparency, accountability, and clarity for the AI ecosystem, there is a need of
multistakeholder dialogue process among the various stakeholders to discuss governance
mechanisms that ensures AI and autonomous systems while harnessing the full potential of this
technology.
AI certainly needs standardization in terms of its core values and process of how it should be used
to protect and save lives than to create discrimination. There needs to be good discussion started
about AI ethics which should focus on increasing transparency, educating the public. The AI needs

to standardize the basic human values of openness, collaboration and trust and create better
governance practice for all.
5. AI Vision: The current development and growth of AI has been random and haphazard, it needs
definite vision and values upon which it can further work to make it universal and acceptable. The
governance structures for AI and algorithmic decision-making systems occur in multiple layers
creating a complex matrix which creates legal and ethical challenges
There is greater a need of broader AI vision in terms of developing the trust and collaboration. AI
for humanity can be one of the visions that can harness the interest and vitality of the various
stakeholder to work towards creating a uniform vision for all.
This vision needs to be accepted and endorsed in every possible way of adapting values of
openness, equality, inclusion, diversity, human values etc.
Issues of AI:
1. Stakeholders from both the private and public sector have essential roles to play in ensuring
that AI can achieve its potential for social good. Collectors and generators of data, whether
governments or companies, could grant greater access to NGOs and others seeking to use the
data for public service and could potentially be mandated to do so in certain cases. To resolve
implementation issues will require many more data scientists or those with AI experience to
help deploy AI solutions at scale. Capability building, including that funded through
philanthropy, can help: talent shortages at this level can be overcome with a focus on accessible
education opportunities such as online courses and freely available guides, as well as
contributions of time by organizations such as technology companies that employ highly skilled
AI talent. Indeed, finding solutions that apply AI to specific societal goals could be accelerated if
technology players dedicated some of their resources and encouraged their AI experts to take
on projects that benefit the common good (3) Awareness and Capacity Building
2. Ethical considerations must be prioritized in the design and deployment of AI (4) Ethic and Core
Values
3. There is a high risk that the benefits of AI will be unevenly distributed within and across societies
exacerbating current and future digital divides (4) Digital Divide
4. Organizations using AI in decision-making should ensure that the decision-making process is
explainable, transparent and fair (14) Transparency
5. AI solutions should be human-centric. As AI is used to amplify human capabilities, the
protection of the interests of human beings, including their well-being and safety, should be
the primary considerations in the design, development and deployment of AI (14) Human
Values
6. Europe is the largest publisher of AI papers. In 2017, 28% of AI papers on Scopus were affiliated
with European authors, followed by China (25%) and the U.S (17%) (5) Resources
7. Current instruments do not address the risks and opportunities presented by AI, by generalized
AI. We can ultimately foresee that there could be an international ‘soft law’ put in place,
potentially a Convention on AI.” Many participants called for a “democratization of AI” in terms

of access to data, transparency in who owns the data, pooling of data and how should that data
be used for the good of all (9) Standard Governance Process
8. In theory, widespread adoption of automation or robots may make some jobs redundant.
However, two clarifications are essential. First, automation or robots are not the same as AI,
which means AI should not be held accountable for all job loss by automation or robotics (10)
Accountability
9. Research is urgently needed on the AI governance problem: the problem of devising global
norms, policies, and institutions to best ensure the beneficial development and use of advanced
AI (11) Research and Study
10. AI politics focuses on the political dynamics between firms, governments, publics, researchers,
and other actors, and how these will be shaped by and shape the technical landscape (11)
Political Dynamics
11. To ensure transparency, accountability, and explainability for the AI ecosystem, our
governments, civil society, the private sector, and academia must be at the table to discuss
governance mechanisms that minimize the risks and possible downsides of AI and autonomous
systems while harnessing the full potential of this technology (8) Multistakeholder Process
12. AI technologies are evolving rapidly, they are still in the development stages. A global AI
governance system must be flexible enough to accommodate cultural differences and bridge
gaps across different national legal systems (8) Adaptation and Mitigation issues
13. The initial usage of AI in developing countries has been at a micro level -- solving small, specific
problems in a defined industry. As machine learning advances and there is a higher utilization of
AI, we will see more complex issues being targeted and resolved. When duly adopted, AI can
positively impact our everyday lives not just in disaster intervention, education, health care and
agriculture but can also help in mitigating poverty, malnutrition and pollution. It’s therefore
high-time for NGOs and governments, especially in developing nations, to leverage AI’s true
potential and create a snowball effect (13) AI Expansion
14. Some contentious uses of AI could have such a transformational effect on society that relying on
companies alone to set standards is inappropriate — not because companies can’t be trusted to
be impartial and responsible, but because to delegate such decisions to companies would be
undemocratic (16) Standardization and Equality
15. This report makes clear that the path to a transformative but also a safe, trusted and inclusive AI
will require unprecedented collaboration between government, industry, academia and civil
society (12) Collaboration and Trust
16. The Ethics and Governance of Artificial Intelligence Initiative aimed at bolstering the use of AI for
the public good through evidence-based research that provides guidance for decision-makers
across the private and public sectors; fostering a network of interdisciplinary researchers
focused on AI ethics and governance-related issues; and strengthening relationships between
industry, academia, civil society, and government (16) Practical Approach

Conclusion:
AI is growing as the footprint of technology used in various services ranging from virtual reality
applications to speech recognition technology to visual recognition to data analysis to programming. Its
growth and adaptation has its own opportunities and challenges. What makes it more complex and
contradicting is the lack of best practices, interoperability, scalability and trustworthiness among others.
This has created a need for standardization and governance in this area.
The survey clearly shows impact of AI technology is creating substantive gaps in policy, legality,
governance, and ethic in our society. These challenges are impenetrable creating complexity in different
layers of AI ecosystem. An effective governance system for AI needs to be mechanized with collective
understanding of creating crosscutting solution with in the AI practice.
AI also raises ethical concerns to align human values and consider the need to address the
discrimination of equality, inclusion and diversity which is worsening the current and future digital
divides. Thus, effective research and studies are urgently required highlighting the role and participation
of developing nations in the AI revolution and politics.
Transparency and Accountability needs to be ensured during the AI design and deployment at the basic
level and data collection and decision-making requires clarity mitigating the risks of geopolitical
implications.
Here are some of the recommendation:
1. Better awareness & capacity campaigns about AI for developing and lower economies
2. Participation and inclusion for all
3. Various layers of governance model need to be adopted
4. Better research and surveys are required
5. Multistakeholder concept to be adopted
6. Standardization of core values for adaptation and mitigation strategy
7. AI needs proper vision with proper set of human values
8. AI requires collaborative vision
9. Trust is an important component which requires better commitment and collaboration
10. Collaborate towards lessening the digital divide
11. AI is in developing stage confining its limitation will hamper its growth and development
Looking at the current trend, AI technologies are evolving rapidly, and they should not be idealized
just for security threats and vulnerabilities. It is in developing stage, so a new thinking and a new
approach needs to be harnessed with a collaborative effort towards developing the set of core
values for addressing policy, digital divides, security and economic regulation.
It can be segregated in many ways and limiting AI to a definitive narrative can be a great challenge for
future. Having said that AI certainly needs collaborative inclusive multistakeholder environment to set
the values, so that it can harness openness, equality and standardization.

Reference:
1. International Telecommunication Union (ITU), statistics pages
2. United Nations (UN) statistics
3. MCKINSEY Global Institute, "Notes from the AI frontier Applying AI for Social Good", December
2018
4. Internet Society, “2017 Internet Society Global Internet Report Paths to Our Digital
Future”
5. Artificial Intelligence Index 2018 Annual Report
6. R. Calo, “Artificial Intelligence Policy: A Roadmap,” Social Science Research Network (SSRN), 8
August 2017
7. U. Gasser, “AI and the Law: Setting the Stage,” Medium, 26 June 2017
8. Gasser, Urs, and Virgilio A.F. Almeida. 2017. “A Layered Model for AI Governance.” IEEE Internet
Computing 21 (6) (November): 58–62. doi:10.1109/mic.2017.4180835
9. ITU, "AI for GOOD GLOBAL SUMMIT Report 2017"
10. UN ESCAPE, “Artificial Intelligence in Asia and the Pacific”
11. Allan Dafoe “AI Governance: A Research Agenda”, August 27, 2018
12. ITU, "United Nations Activities on AI"
13. Sameer Maskey, Forbes Article , “AI For Humanity: Using AI To Make A Positive Impact In
Developing Countries" August 23, 2018
14. Personal Data Protection Commission Singapore, "A Proposed Model AI Governance
Framework” January 2019
15. Berkman Klein Center for Internet & Society at Harvard University, “Ethics and Governance of
AI”
16. Google, Perspectives on Issues in AI Governance

Contact Information:
Shreedeep Rayamajhi
ICANN Wiki: https://icannwiki.org/Shreedeep_Rayamajhi
Wiki: http://www.en.wikipedia.org/wiki/Shreedeep_Rayamajhi_(activist)
Email: shreedeep@rayznews.com | rayamajhishreedeep@gmail.com
Website: http://www.rayznews.com/ | http://www.internetgovernancediplomacy.blogspot.com/
Rayznews
Link: http://www.rayznews.com/
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Learn Internet Governance is a Collaborative Community Development Program (CCDP) which focuses
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Final survey report on ai perspective and challenges of developing nations by shreedeep rayamajhi

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Final survey report on ai perspective and challenges of developing nations by shreedeep rayamajhi