aiandinclusion.org Open in urlscan Pro
128.103.64.94  Public Scan

Form analysis
0 forms found in the DOM

Text Content

Artificial intelligence and related technologies have begun to shape important
parts of the digital economy and affect core areas of our increasingly networked
societies. Whether it be transportation, manufacturing, or social justice, AI
has the potential to deeply impact our lives and transform our futures in ways
both visible and hidden. The promise of AI-based technologies is enormous, and
benefits range from efficiency gains to unprecedented improvements in quality of
life. The challenges, however, are equally staggering, for example creating
uncertainty surrounding the future of labor and the shifts in power to  new
structures outside the control of existing governance and accountability
frameworks. More specifically, the uneven access to and impact of AI-based
technologies on marginalized populations run the disturbing risk of amplifying
global digital inequalities. These groups include urban and rural poor
communities, women, youth, LGBTQ individuals, ethnic and racial groups, people
with disabilities – and particularly those at the intersection of these
identities.

A complex set of issues exist at the intersection of AI development and the
application divide between the Global North and the Global South. Some of the
thematic areas include health and wellbeing, education, and humanitarian crisis
mitigation, as well as cross-cutting themes such as data and infrastructure, law
and governance, and algorithms and design, among others. We are examining the
core areas and cross-cutting themes through research, events, and
multi-stakeholder dialogues. The following materials are informed by the
multitude of these efforts, which incorporates perspectives from a wide array of
experts in this emerging field.








We’ve created this site as a means to showcase the many dimensions of AI and
inclusion as a part of our broader Ethics and Governance of AI initiative
carried out in conjunction with the MIT Media Lab. It reflects what we’ve
learned from our collective work on AI and inclusion over the past year, with
partners such as the Institute for Technology and Society Rio and collaborators
from the Global Network of Centers. It includes a number of resources produced
from the the Global Symposium on AI and Inclusion, which convened 170
participants from over 40 countries in Rio de Janeiro last November to discuss
the most significant opportunities and challenges of AI. The research, findings,
and ideas presented throughout the webpage both illuminate key takeaways from
our work and will serve as a roadmap for our continued work on AI and inclusion
intersected with our AI and governance efforts.

 

Within the site you will find foundational materials on the themes of AI and
inclusion including descriptions of overarching themes, key research questions,
the initial framing of a research roadmap, as well as some of the most salient
opportunities and challenges identified pertaining to AI, inclusion, and
governance.

 

We're eager to hear and learn from you. Please meet the team behind this
collaborative effort here, who can also connect you with our global
collaborators and friends.

 



When considering the social impact of AI, conceptualizing inclusion may become
even more difficult because AI systems are powered by pattern recognition and
classification, which, broadly speaking, often drive exclusionary social
processes. Because of this, AI has feedback effects on the notion of inclusion
itself. There are questions that we should be asking in order to further shape
our own views and understandings as to how to conceptualize AI. This reading
list is meant to serve as a starting point for exploring the ways in which we
may think about the very notion of social inclusion/exclusion itself in the age
of AI, as well as the complex ways in which autonomous systems interface with
various dimensions of inclusion and questions that arise at this intersection.

Reading List

In preparing for the Global Symposium on AI and Inclusion, the organizers
conducted a survey amongst participants about the challenges, opportunities,
application areas, and dimensions of inclusion of interest to be further
explored at the event. The Pre-Event Survey Responses document is a brief look
at the survey responses, with a particular focus on comparisons between the
Global South and the Global North. In total, we captured 150 responses to the
survey, and categorized regions as the following: Global South (Latin
America/Caribbean, Asia, Sub-Saharan Africa, and Northern Africa), and Global
North (Europe, North America, Oceania). A few main geographic discrepancies in
the perception of the greatest challenges and opportunities of AI that emerged
from the survey. Though these survey responses draw from a limited sample, they
demonstrate the differing approaches to AI and its societal implications across
geographic region, highlighting the need for greater cross-cultural
collaboration and dialogue on the development, deployment, and evaluation of AI.

Pre-Event Survey Responses

The 170 attendees of the Global Symposium on AI & Inclusion stand together in
front of the the Museum of Tomorrow in Rio de Janeiro.

Andres Lombana, a fellow at the Berkman Klein Center, greets Ezequiel Passeron,
executive director of Faro Digital. The two are both participants in Digitally
Connected, a collaboration between UNICEF and the Berkman Klein Center to
analyze digital and social media trends among young people globally.

ITS Rio Director Ronaldo Lemos speaks with Maja Bogataj Jančič, director of the
Intellectual Property Institute, Ljubljana, Slovenia and Alek Tarkowski, PhD.
director of Centrum Cyfrowe, Warsaw, Poland and co-founder and coordinator of
Creative Commons Poland.

Chinmayi Arun, research director at the Center for Communication Governance and
assistant professor of law at National Law University (NLU), both in Delhi,
moderates a session on advancing equality in the Global South.

A panel responds to the keynote speech delivered by Ansaf Salleb-Aouissi,
lecturer in computer science at Columbia University, on the history of AI. She
said we can use lessons learned during the early years of AI to promote more
inclusive AI today.

Keynote speaker Nishant Shah, Dean of Research at ArtEZ University of the Arts,
Hamburg, Germany, speaks on inclusion in the age of AI. Shah called for
considering human and technology factors together when trying to make AI more
inclusive.

Nagla Rizk, founding director of Access to Knowledge for Development (A2K4D) in
Cairo, emphasized that making AI more inclusive requires new datasets developed
by citizens of emerging economies, and reducing reliance on datasets released by
government agencies.

Alex Gakuru, executive director of the Content Development and IP (CODE-IP)
Trust in Kenya, passes the microphone.

Ciira Maina, Senior Lecturer at Dedan Kimathi University of Technology in Nyeri,
Kenya, said among other things that we need to disseminate educational materials
and other resources that promote AI awareness, particularly in the Global South.

Participants mingle during a reception and poster session featuring some of the
participants’ projects, as well as an exhibition by Harshit Agrawal – a research
assistant and artist at the MIT Media Lab.

Carlos Affonso, director of ITS Rio, thanks the panelists for their
participation in a session on data and economic inclusion and introduces the
subsequent breakout sessions.

Participants walk from the main auditorium to a breakout session. Participants
chose two breakout session themes out of ten total based on their interests and
nature of work.

The breakout session focused on data and infrastructure in the age of AI
convenes in the Museum of Tomorrow’s Exhibition Lab and makerspace on the
symposium’s second day.

The breakout session on business models in the age of AI, moderated by Susan
Aaronson, a professor and senior fellow at George Washington University,
convenes in the museum courtyard.

Daniel Calarco de Oliveira, president of International Youth Watch, listens
during the breakout session on Humanitarian Crisis Prevention & Mitigation. The
session focused on how AI technologies might help prevent humanitarian crises
and speed response times.

Kathleen Siminyu, data scientist at Africa's Talking and a Co-Organizer of the
Nairobi Chapter of Women in Machine Learning and Data Science, walks past by a
Museum of Tomorrow sign.

João Duarte, data science manager at Somos Educação, Brazil; Kọ́lá Túbọ̀sún,
Founder of the Yorùbá Names Project, Nigeria; Debora Albu of ITS Rio; and
Pranesh Prakash, Policy Director of CIS Bangalore, India, walk from the
auditorium to a cluster group session.

Agustina del Campo, director of the Center for Studies on Freedom of Expression
and Access to Information (CELE), Universidad de Palermo, Argentina, engages
with other members of a cluster group meeting.

A cluster group meets on the second day of the symposium in the Museum of
Tomorrow mezzanine to identify major challenges and opportunities of AI.

Luis Camacho Caballero, research projects manager at Pontifical Catholic
University of Peru, and Michael Best of United Nations University-Computing and
Society work with their cluster group to identify major global opportunities
presented by AI.

Julia Cavalcanti (ITS Rio), Leyla Keser, Founder and Director of the Istanbul
Bilgi University IT Law Institute, and Stephane Hilda Barbosa, Researcher at the
Getulio Vargas Foundation Law School in São Paulo (FGV/SP), converse during a
cluster group session.

Lucas Santana, head of marketing at Evelle Consultoria & Desabafo Social,
Salvador, Brazil, and Monique Evelle, CEO of Evelle Consultoria, walk together
during a break on the second day of the symposium.

Mimi Onuoha, artist and researcher at the Eyebeam Center, a nonprofit in
Brooklyn, NY, presents her talk about the need for art to interpret AI, and for
members of diverse professions to have access to AI.

ITS Rio Director Ronaldo Lemos speaks at the public event on possible future
trajectories of AI to create a more just and inclusive society.

Sandra Cortesi, director of Youth and Media at the Berkman Klein Center,
discusses the impact of AI-based technologies on children and young people.
Cortesi emphasized throughout her talk how technologies have radically
transformed the ways in which youth perceive and interact with the world around
them.

Two participants walk in the public section of the Museum of Tomorrow after the
closing remarks.

1 - 26

<

>



The Global Symposium, co-hosted on behalf of the Network of Centers by ITS Rio
and the Berkman Klein Center for Internet & Society, involved over 170
participants from more than 40 countries around the world and took place over
the course of three days (November 8-10, 2017) at the Museum of Tomorrow in Rio
de Janeiro, Brazil. The Symposium was organized with the support of the Ethics
and Governance of Artificial Intelligence Fund, International Development
Research Centre (IDRC), and the Open Society Foundations, in collaboration with
the Museum of Tomorrow.

 

For more information on the logistics and themes of the Global Symposium on AI &
Inclusion, please see the links to the right.



Event Website

DotPlot, An interactive visualization that shows the global perception of AI &
inclusion from the participants

Write-ups about the event:

Charting a Roadmap to Ensure Artificial Intelligence (AI) Benefits All, Berkman
Klein Center

The real danger of Artificial Intelligence is not what you think, João Duarte

Bibi Reisdorf at the Global AI & Inclusion Symposium in Rio de Janeiro, Bianca
Reisdorf

Global Symposium on Artificial Intelligence & Inclusion, Lucas Anjos and Odélio
Porto Júnior

Top takeaways from the Global Symposium on AI and Inclusion, Aparna Ashok

Grounding conversations about AI and inclusion within a shared, contextualized
understanding of fundamental concepts at play is crucial, as doing so allows us
to begin conceptualizing best approaches to mitigating potential risks and
maximizing the benefits of AI based on that shared understanding of AI’s
societal interplay. The following three overarching themes and critical issues
emerged both from the research leading up to as well as the conversations that
took place at the Global Symposium on AI and Inclusion.

 

The video on the right features both Ansaf Salleb-Aouissi (Columbia University),
who frames the history of AI and how we should view inclusion  starting from a
technical perspective, and Nishant Shah (ArtEZ University of the Arts), who
discussed inclusion in the age of AI, calling for a breakdown of the dichotomy
between the human element and the technological element.

 

Full Session Videos

   

 * Exploring the intersection of “AI and Inclusion”
   
   It is necessary to critically engage with the ways in which we define the
   fundamental concepts of AI as well as inclusion. As Nishant Shah argues, we
   must reckon with the history and impact of AI-based technologies and
   conceptions of inclusion, and draw attention to their mutually constitutive
   intersection in order  to look beyond just computation to the actual lived
   realities of the computed. Simultaneously, we must grapple with the
   definition of inclusion in a technological context. From a technical
   development process perspective, Ansaf Salleb-Aouissi articulates the need to
   recognize a “4D Framework” — develop, de-identify, decipher, and de-bias — in
   developing AI that is both inherently more inclusive and that helps advance
   social inclusion. As we continue to examine all aspects of AI and inclusion,
   we must recognize the need for a new vocabulary to discuss the novel ways in
   which AI and inclusion interact.

 * Reframing “Inclusion” to embrace self-determination
   
   It is important to understand the influence of western values within the AI
   discourse and how this may contribute to bias in global systems —
   technological and social. One important criticism of the traditional concept
   of inclusion is that it places the burden of “performing” inclusion on the
   underrepresented communities themselves. Rather than simply incorporating
   these communities into global conversations about AI, or “throwing money” at
   engineers within these communities to support inclusive development,
   policymakers must enable these communities to actively drive the discussion
   and deployment that shape their experiences. Self-determination constitutes
   an alternative to or amendment of the inclusion paradigm, offering agency and
   space for underrepresented individuals to represent themselves and guide the
   systems and policies that affect them.

 * Rewriting old AI narratives to encompass new AI capabilities
   
   We must also reconcile the differences in speed at which the AI discourse
   progresses and the speed at which new AI capabilities are developed. As
   technological advancements are often made at a more rapid pace than
   developments in the discourse surrounding them, there is a tremendous
   potential to exacerbate existing divides and create new ones. This gap points
   to an urgency to collaborate quickly and meaningfully across regions and
   sectors in order to understand and mitigate potential risks at the
   intersection of AI and inclusion.

Through our research and convening efforts we have identified a series of open
research questions which serve as a starting place for forward-looking research
road map. These research questions are closely linked to stages of technical
development for AI systems. For that reason, we have clustered these questions
into a matrix, vertically by the stages of developing an AI system and
horizontally by mechanisms for intervention. The structure of the matrix, in
addition to a brief description of each category, is outlined below for
reference, along with key questions for each cell in the matrix. For more
detailed information on the methodology for categorizing research questions,
greater background on where they are drawn from, and the full research matrix,
please refer to our full research memo.

Can we study past AI evolutionary cycles to predict future AI trajectory?

 

To what extent should we be looking for technical solutions for social problems?

To what extent does the development of new categories as a way to forward
inclusion further entrench repressive notions? How does AI deal with this?

 

How can we incorporate an international human rights framework into AI
development?

 



How do different communities define “Artificial Intelligence” and how does it
influence varying perceptions including fear and excitement surrounding the
future of AI?

 

Explaining AI behavior and decision-making is not a trivial task -- how do we
trust AI without always fully understanding its functionality, and what are the
implications of that "blind" trust?

How can we align incentives between companies and activists to make profitable
and beneficial AI?

 

What are ways to empower software experts from the Global South? Funding?

 

How can youth be stakeholders and more involved in building the AI world?

 

How do we include more individuals in AI systems without erasing difference
through normalization and universalization?

 

 

Can business conciliate their aim of collecting data with protecting the data of
users?

 

Is it possible for us to de-situate AI from the undeniable structure of
societies based on surveillance capitalism?Give AI applications/uses a public
good? Should it be publicized and insofar controlled?

 

How will we make certain that we work together collaboratively in the age of AI
to define and defend the public interest? How can we meaningfully collaborate?

 

What does the current global framework of AI production/use look like? Who are
the major players, what are their initiatives, and how can we lift up more
grassroots initiatives?

 

How can we improve education systems -- especially in engineering -- to promote
more inclusive and ethical AI? Should this improvement in engineering education
include moving away from logic back into mathematics and will this curriculum
require new forms of engineering?

 

Can we work with makerspaces to include AI into their offerings? Those places
can host online courses in groups (marginalized youth) and can be hubs for
cutting edge digital education & creativity

 

How do we democratize access to education, particularly technology-focused
education, in the context of lower-income countries that speak little or no
English?

 

How do education tools for expanding knowledge and use of AI currently reach
populations globally, and how can expanding access to educational resources
positively reflect back in AI systems?

How does privilege manifest itself in the means of education chosen by different
groups/stakeholders? What is the prevailing narrative about AI and technology in
the classroom, and who shapes it?

Is there a need for a (legal) definition of AI? Is this definition defined at a
local, national, or universal level? Is it binding? What stakeholders decide on
the definition?

 

How can we harmonize data protection regulations and the rights to explanation
with complex AI models that are not self explanatory and are nonlinear as deep
neural networks? How can the right of data removal be articulated in the AI
context without causing undertilting and misrepresentation of class?

 

How can we force non-democratic countries to abide by the governance systems of
AI and what are the implications of a lack of global guidelines/standards?

 

How do we include AI ethics into the global policy frameworks we build?

 

What will labor policies look like when most of the population works in informal
conditions brought on by the AI age? How can these policies best protect
workers?

 

As AI is going to be able to predict diseases, how do we mitigate violations of
privacy and bioethics that discriminate against individuals based on existing
conditions or even their predisposition to health conditions?

AI is a hard design material due to its dynamic nature. How can we design
something that is constantly changing? How do we explore “what-if” scenarios of
unknown?

 

Who is “the reasonable” man we should configure AI systems around? Does such a
person exist? If so, what does this person look and act like?

 

What are ways that we can use algorithms, particularly in search engines, to
disseminate legitimate helpful health information that promotes positive health
behavior?

In what respect can businesses from the Global South provide AI applications
that businesses from the Global North cannot?

 

When and how does AI lead to price discrimination or “personalized pricing?”

What are the kinds of human-auditable control mechanisms that can be built into
decision making algorithms?

 

Can we develop technical  models (test cases or databases)  to ensure that the
AI & Inclusion discourse progresses?



Defining the Development Stages of an AI System (Horizontal):

 * Design: This stage includes both the technical design of AI-based
   technologies (e.g. how data will be collected in the model, the target
   audience of an AI tool) as well as design of systems that govern AI and the
   implications that must be considered before moving on the the development
   process.
 * Development: The development stage is the production phase of an autonomous
   system that follows the design process. Questions in the development category
   pertain to the building of more inclusive tools/methods into AI-based
   technologies, frameworks of AI development, and what AI tools are being
   developed for whom.
 * Deployment: The deployment stage covers the distribution, utilization,
   ubiquitousness, and implementation of AI-based technologies within society at
   multiple levels including the local, national, and global ecosystems.
 * Evaluation/Impact: The evaluation/impact phase encompasses the measurement
   and understanding of the impact of AI technologies, including ways to
   evaluate the effects of autonomous systems on different agents within
   society.

Defining the Mechanisms for Intervention (Vertical):

 * Defining and Framing (“Back to First Principles”): This encompasses questions
   examining the fundamental ways in which concepts related to AI and inclusion
   are defined.
 * Bridge-Building: This mechanism contains questions related building
   infrastructures such as networks and liaising between multiple stakeholders.
 * Educating: These questions highlight both the education of AI-based
   technologies as well as the impacts that AI may have on education.
 * Tool-Building: This mechanism contains questions pertaining to the building
   and usage of tools that use AI technologies.
 * Policy-Making: These questions pertain to the sets of principles, guidelines,
   laws, or regulatory frameworks that govern AI.

When it comes to prioritizing research questions as well as proposing solutions
derived from them, our work on AI and inclusion suggests that it is vital to
distill the greatest opportunities and challenges decision-makers face while
grappling with AI-based technologies, particularly in Global South contexts.
Although a number of action items and constructive approaches are warranted,
three primary considerations emerged as integral to addressing the opportunities
and challenges at the intersection of AI and inclusion found in the research
questions. Please use the text box to the right to explore themes in these
opportunities and challenges.

   

 * Efforts to answer these questions may differ by method, expertise, and
   region. Therefore, there is a need to devise specific sets of solutions for
   specific types of problems concerning AI-based technologies and their
   implications. A broad-strokes approach to formulating solutions for AI and
   inclusion challenges is ineffective, as the complex nature of problems at
   this intersection call for a targeted, multivalent approach. Meanwhile,
   clustering similar research questions and issues may serve as a way to
   harmonize discussions surrounding AI and inclusion, aligning normative goals
   using the levers of individual agency and/or ecosystem-driven approaches.

 * The temporal aspect of identifying issues and formulating solutions was at
   the crux of the conversation on seizing opportunities presented by AI while
   identifying effective solutions to potential problems. Specifically, AI’s
   rapid growth and multifaceted societal implications warrant a
   reconceptualization of the time structure of the AI research agenda. We
   cannot simply “act now,” nor can we afford to “wait for the time it takes to
   conduct research;” rather, we must do both simultaneously. This approach, of
   course, must account for different temporalities and goals for different sets
   of problems and solutions, modeling itself on larger social movements that
   successfully build momentum and involvement on global and local levels
   without following a traditional chronological agenda commonplace in academia.

 * In terms of collaboration, all questions should ideally be explored with a
   diverse group of individuals from varying sectors and geographic regions in
   order to break down constrictive silos. However, certain questions in
   particular necessitate a co-research approach by nature; these types of
   questions include, among others: how to expand funding for Global South
   initiatives; the ways in which behavioral expectations vary geographically;
   the democratization of AI education; and the global governance of AI systems.
   Working towards true and organic interdisciplinarity encourages more
   meaningful integration of varying perspectives that may yield more inclusive
   AI development and a less hierarchical global AI power structure.

As we consider future opportunities and challenges related to AI & inclusion, it
is vital to continue incorporating global perspectives so that we may progress
into a truly inclusive future. To this, we have interviewed a number of key
global players working on these issues for their input in 120 seconds.
Interviewees include, among others, Carlos Affonso, Director of ITS Rio, and
Nagla Rizk, Founding Director of Access to Knowledge for Development (A2K4D).
The full set of videos and additional resources are listed below.

 




Learn more:

 * Global Network of Internet and Society Research Centers
 * AI-themed Berkman Buzz
 * Outputs from related BKC events:

 * * Berkman Klein Center YouTube playlist on AI
   * AI Advance Write-up
   * Seoul AI Dialogue Workshop Overview
   * China-US AI Dialogue Workshop Overview

 * The following are resources (in Portuguese) suggested by ITS Rio to further
   explore the topic of AI & Inclusion.
   * IA transformará o Direito, mas o Direito transformará IA?
   * IA e inclusão: uma oportunidade para o Sul Global
   * Quem responde pelos danos causados pela IA?
   * O debate sobre personalidade jurídica para robôs
   * Robôs criativos e um novo desafio para direitos autorais

This project is supported by the Ethics and Governance of Artificial
Intelligence Initiative at the Berkman Klein Center for Internet & Society. In
conjunction with the MIT Media Lab, the Initiative is developing activities,
research, and tools to ensure that fast-advancing AI serves the public good.
Learn more at https://cyber.harvard.edu/research/ai.

The team at the Berkman Klein Center working on issues related to AI & Inclusion
includes (click on each photo to learn more):



Urs Gasser

Executive Director

Amar Ashar

Assistant

Director of

Research

Ryan Budish

Assistant

Director of

Research

Sandra Cortesi

Director of

Youth & Media

Elena Goldstein

Project Coordinator

Levin Kim

Project Coordinator

Jenna Sherman

Project Coordinator

Key collaborators include the Institute for Technology and Society Rio, which is
currently the main coordinator of the Global Network of Centers and the hosts of
the November 2017 Global Symposium on AI & Inclusion. The team at ITS Rio
working on AI & inclusion includes, among many others, the following:



Carlos Affonso Souza

Co-Founder and Director

Fabro Steibel

Executive Director

Ronaldo Lemos

Co-Founder and Director

Celina Bottino

Project Director

Beatriz Laus Nunes

Project Assistant and Researcher

Eduardo Magrani

Coordinator of

Law and Technology

For more information about the network of experts, practitioners, policymakers,
and technologists who have contributed to the dialogue on AI & inclusion, as
well as the donors that have supported it, please see the Global Symposium on AI
& Inclusion website.






Ethics and Governance of AI initiativeInstitute for Technology and Society Rio
Global Symposium on AI and Inclusion






   
 * 
 * 
 * 



   
 * 
 * 
 * 







   
 * 
 * 
 * 



   
 * 
 * 
 *