Me-We-It: An Open Standard for Responsible AI

This is an Open Suggestion designed to clarify the process of building AI by exposing the steps that go into creating it responsibly. It is written from the frontlines by the actual builders, users, and stakeholders who have seen the value and damage Artificial Intelligence (AI) can deliver. The goal is to set a healthy tone for the industry while making the process understandable by the public to illuminate how we can build more ethical AI and create a space for the public to freely ask any question they may have of the AI and data science community.

Today we're seeing many doomerism narratives that play into hysteria and obfuscate the structures of AI instead of focusing on clear, accountable communication that enables honest discussion and assists decision making. The creation of AI can be a technically involved process but the standard approaches to teach machines and the outputs created can be monitored and validated in this simple framework that enables everyone to have a seat at the table regardless of a person's data science background.

Now more than ever, it's necessary to share how AI learns so that we can hold each other accountable without severely restricting innovation. The development of AI has the potential to bring about significant benefits, including increased efficiency, improved decision making, health discoveries and the ability to tackle problems that were previously impossible to solve. However, AI can also force human moderators to witness horrible content, disadvantage the disenfranchised, amplify data privacy and safety concerns, steal intellectual property not created for the process, and perpetuate biases that cause harm. Without careful consideration and planning, we risk creating AI systems that worsen the very problems we seek to solve.

Open Suggestions Framework

These are the first questions and considerations we believe every AI team and individual builder should ask every day to ensure we are releasing more ethical AI models. They are intended to be communicated in simple language without technical jargon to ensure the process can be understood by every audience and will be translated over time into every local human language where we can find volunteers to support. We know we are unlikely to get this completely right, especially when dealing with a technology that requires continuous tracking, but with your help each iteration will bring meaningful improvements. This is version 1 of many future versions that developers can use when assessing our work. The community will help it as we collect more questions from the public and suggestions from the data science community to refine the list and capture the necessary steps that should be taken to clarify and validate our intentions.

As policy makers frantically race to catch up with regulation, and the EU AI Act signals it may add GPAI (General Purpose AI) to the high risk category, we are here to set an actionable standard every team can use immediately that also clarifies how AI is built so we can reduce silos and discuss as a group. Instead of an Open Letter, this is an Open Suggestion from a group of experienced technologists, data scientists, researchers, and people concerned with the impact of AI.

This Open Suggestion will live as a free online forum, and we invite new suggestions and approaches under the important banner of registering intent. The steps are isolated based on the core elements of building AI (Training, Building, Testing) and the actors who engage in the process to help clarify the importance of silo reduction: Me, We, It.

Me - The questions each individual who is working on the AI should ask themselves before they start and as they work through the process.

We - The questions the group should ask themselves — in particular, to define the diversity required to reduce as much human bias as possible.

It - The questions we should ask individuals and the group as they relate to the model being created and the impact it can have on our world.

Step 1. Training - Data Selection and Ingestion

Me - The necessary questions to ask myself before starting this part of the process. Answers should be saved so I can look back at how my thought process evolves.

  • What are the reasons for me selecting this training data? How does that selection align with my intention for this model?
  • How was this training data sourced?
  • Is there any protected or copyrighted material in the training data such as Personally Identifiable Information (PII), Payment Card Industry (PCI) data, and Protected Health Information (PHI)?
  • Have I considered data protection or privacy legislation (such as GDPR and CPRA)?
  • Have I considered any other systems for managing data sources?
  • Do I have experience in using similar data for AI or Machine Learning models in the past or is this the first time I am using this data source?
  • If I've used this data previously, were there any issues that resulted from the models that were trained on this data historically?
  • If this is the first time I've used this data, what are my expectations for the impact this data
    will have on the models outputs?
  • Have I used a Model Card to communicate risks? How will this document be updated with the collaboration team?
  • What do I hope the data will do to this model? What is my intention of the outcome? How do I expect the training data will impact that performance?
  • Are there any features that could act as instrumental variables (eg. granular neighbourhood level data) for disenfranchised populations? If so, do I have sufficient controls to ensure that I am not perpetuating biases that can be learned from the training data?
  • Can I summarise what is in this training data so as to capture the essence of the data in a way a non-data scientist can understand?
  • Do I feel rushed or pressured to input data from questionable sources?
  • Can I cite my source of the training data?
  • What biases may be acting on my selection of this data?
  • Am I considering biases I have that I don't understand? Am I sharing my logic with a larger group who can help me identify my bias being deployed when selecting data?
  • How do I think this training data will benefit this model?

We - The questions we should ask ourselves as a working group before starting this part of the process. Answers should be saved so we can look back at how our thought process evolves.

  • What is the group's intent for training this model?
  • Who collaborated in the process of building the training data strategy and selection?
  • Is the team of people who are working on selecting the training data from a diverse set of backgrounds and experiences to help reduce the bias in the data selection?
  • What are the likely biases inherent in this team that selected the training data?
  • Does the whole team understand where the train data came from? Can they explain it back in their own words?
  • Is a Model Card being used to communicate risks? Did each contributor create their own document
    that can be shared with the larger team?
  • Have we considered the EU AI Act or any other regulation being proposed or that is already in place?
  • Is there any protected or copyrighted material in the training data such as Personally Identifiable Information (PII), Payment Card Industry (PCI) data, and Protected Health Information (PHI)?
  • Have we considered data protection or privacy legislation (such as GDPR and CPRA)?
  • Have we considered any other systems for managing data sources?
  • What percentage of the training data are we saving for testing? How are we selecting it?

It - The questions we should ask ourselves of the algorithms or models before starting this part of the process. Answers should be saved so we can look back at how our thought process evolves.

  • Do we have means to compensate should part of this data set be discovered to be illegal, unreliable, or unacceptable at some point in the future?
  • What data is needed to train thoughtfully and with intention?
  • Is the full data set of known origin, explainable, and beneficial for the model?
  • What are the likely biases inherent in the data?
  • Is there any personal identifiable information, protected data, or copyrighted material?
  • Am I prepared to handle liability for the model if part of the data set causes any legal issues in the future?
  • What are potential unintended uses or consequences, including subsequent level outcomes that the training data could teach the model?
  • What are the likely biases that could be amplified through the training data being added to the model?

Step 2. Building - Creation or Selection of Algorithms and Models

Me - The questions I should ask myself before starting this part of the process. Answers should be saved so I can look back at how my thought process evolves.

  • What do I intend for this model to do? Why am I training it?
  • If I am running reinforcement learning, how will this model optimise in the live environment? Is it possible my selection of outcomes to test is biased?
  • If I am deploying transfer learning, what are the possible biases that the transferring process will uncover?
  • If I am running ensemble models or systems that train each other, is there a chance that new bias or bad data collection practices will enter the system?
  • How do I think this model will perform? What are some examples of desired outputs I am hoping to see?
  • What are my human biases that impacted my goals and reasoning?
  • If I didn't write the model from scratch, where did it come from? How was it initially trained?

We - The questions we should ask ourselves as a working group before starting this part of the process. Answers should be saved so we can look back at how our thought process evolves.

  • Whom did I collaborate with in the process of training this model and building the strategy?
  • What human biases are in this group? Have we considered whether the working group is diverse enough to capture differing points of view?
  • Who were the collaborators building the model and strategy?
  • Who are the stakeholders? Are all the stakeholders engaging in this step of the process?
  • Have we considered the EU AI Act or any other regulation being proposed or that is already in place?
  • Were these models trained on any protected or copyrighted material such as Personally Identifiable Information (PII), Payment Card Industry (PCI) data, and Protected Health Information (PHI)?
  • Have we considered data protection or privacy legislation (such as GDPR and CPRA)?
  • Have we considered any other systems for managing data sources?

It - The questions we should ask ourselves of the algorithms or models before starting this part of the process. Answers should be saved so we can look back at how our thought process evolves.

  • Where did the model come from or was it developed from scratch?
  • What is the intended use of the model once it is trained?
  • If we didn't create the model ourselves, do we understand the intent of the original creator of the model?
  • What are potential unintended uses or consequences, including subsequent level outcomes?
  • What are the likely biases that could be amplified through the model?
  • Do we have examples of models with similar data being deployed previously? What were the intended and unintended outcomes?
  • What are the possible dangers of the model? Do we have a plan for the worst case scenarios?
  • What type of precautionary measures have we put into place?
  • Who controls the model?
  • How will continued compliance with laws and regulations be monitored and implemented?
  • How will biases be discovered and resolved?
  • How can the model be shut down? Under what circumstances must that happen?
  • Are there any self-interested stakeholders or realities of funding that may stop that from happening?
  • What are the contractual requirements that will dictate the management and usage of this model?

Step 3. Testing - Managing Test Data and Tagging

Me - The questions I should ask myself before starting this part of the process. Answers should be saved so I can look back at how my thought process evolves.

  • Is the data I'm using for testing sufficient for analysing how the model performs?
  • Is user testing in the live environment being considered? How will the model be adapted if it turns out that the user behaviour outcome is unwanted?
  • What do I think is the best approach for evaluating the outcome of this model before I speak with the larger group about our approach?
  • Am I confident that the team and I are aware of the impact our work can have? Have we thought about all the potentially bad outcomes that could result from our work that we should be testing for before we go live?
  • Do I believe we have been thorough in our testing strategy and deployment to ensure we have unearthed any issues that could arise from the models outputs?
  • Did the results of the training data and feedback from taggers match the original intent I had when creating the model? If not, what differed and how do I know it differed?

We - The questions we should ask ourselves as a working group before starting this part of the process. Answers should be saved so we can look back at how our thought process evolves.

  • How do we evaluate the performance and outcomes of this model?
  • Are we aware of where the testing data comes from? Is the testing data appropriate to be representative in relation to the vastness of the training data?
  • If the data is tagged by people, who are the people? Are they being humanely treated?
  • Before they tag the data, what instruction did taggers receive that might impact their opinion?
  • What questions are the taggers or working group asking of the data?
  • Does the tagging strategy align with the training data and model creation strategy?
  • Is there an appropriate amount of diversity on my data tagging team?
  • What human biases might impact the tagging or testing process?
  • Is user testing in the live environment data being collected? How will it feed back into an iterative process?
  • Is the user group a diverse audience that is representative of the future total user group?
  • Is it possible that bias is a programmatic result of the model?
  • Whom did we collaborate with in the process of building the testing or tagging data strategy?
  • Are product teams involved in the process of retrieving user data and sharing human logic with the larger group?
  • Was the intention of the working group realised now that the model has run and been tested? (If not, explain in detail with quantifiable data.)

It - The questions we should ask ourselves of the algorithms or models before starting this part of the process. Answers should be saved so we can look back at how our thought process evolves.

  • Did the results of the test or tagged data match our intent for the model outputs?
  • If we are testing our models to determine accuracy, how much do the results we are seeing match up with the core intent of what the model will do?
  • Will we now tune the model based on the outputs of the testing or tagged data? (If so, start the process from Step 1.)
  • If deploying reinforcement learning, how can model outcomes amplify bias and influence new data from users?
  • Have we considered the output of the model against the EU AI Act or any other regulation being proposed or that is already in place?
  • Have we tested for protected or copyrighted material in the output of the model such as Personally Identifiable Information (PII), Payment Card Industry (PCI) data, and Protected Health Information (PHI)?
  • Have we considered data protection or privacy legislation (such as GDPR and CPRA)?
  • Have we considered any other systems for managing data sources?

Signatures:

Elizabeth Rothman Esq.
Harvard Law School and the World Intellectual Property Organization (WIPO) Instructor Patentx - AI Intellectual Property Law Attorney Artificial Inventor Project, Principal Attorney Law Office of Elizabeth Rothman

Douglas Rushkoff
Professor of Media Studies, Queens College - Host, Team Human

Dr Cory Doctorow (hc)
Author, activist - BoingBoing, EFF, WEDF, MIT Media Lab

Dr. Saeed Aldhaheri
Director, Center for Futures Studies - University of Dubai

James Ellison
Sr. Manager, Product Management - UL

Ravi Meta
Co-Founder @ Outpace, Previously CPO @ Tinder - Product @ TripAdvisor, Facebook, Xbox

Serene
Concert Pianist | Founder & CEO - Snowstorm

John Marshall
Executive Director - World Ethical Data Foundation

Swathi Young
Women in AI, Washington, D.C. Ambassador, Adjunct Subject Matter Expert and Instructor on Big Data and Management - George Mason University, CTO Sustainchain

Camila Manera
Chief Data Officer Libraodepases - former Data Scientist Manager at The Walt Disney Company

Mike T. Ramirez
Digital Product Management - Bank of America

Raiya Kind
Senior Computational Linguist for NLU in Machine Learning - Google

Rania Kim
Artist + Researcher - -

Rebecca Fiebrink
Professor at the Creative Computing Institute - University of the Arts London

Vince Lynch
CEO - IV.AI

Matt Jung
Co-Founder & Managing Partner - Ember Co.

John Kilpatrick
Design Director - WhatsApp, ex-Amazon, ex-Samsung, ex-Founder/CEO

Chris Paterno
CEO - Heard

Colin Hayhurst
CEO - Mojeek

Heather Owen
Senior Manager Technical Support - Zebra Technologies

Ian Campbell
Senior Product Director Product Management, NFL+ - National Football League (NFL)

Neal Parikh
Head of Sustainability - Ericsson

Quinn Comendant
Founder–engineer - Strangecode

Anna Babkina
Head of Partnerships - World Ethical Data Foundation

Benjamin Mugumya
Head Of Marketing, Graphics & Branding - Kamada & Sons Designers, Soroti District

Brett A. Fulkerson-Smith
Associate Professor of Philosophy - University of Guam

Brian Lynch
Co-Founder Hero AI - Practice Lead, Analytics and Insights at TD

Brian Malika
Founder And Director - One More Percent

Carlos Guadián
Analyst - K-Government

Christophe Petit
Director - Ethical AI Training Organization

Dana Kathlen Redeña
Enterprise Solutions Engineer - -

Daniel Sonesson
CEO - Quickbit

David C Traub
Co-Founder, Creator - Multiple entities touching on AI (beginning in the 80s)

Ellie D. Norris
R&D IT Director, Data & Analytics Strategy - -

Elvira Vanerfors
Senior Compliance Officer & Group MLRO - Quickbit

Felipe Murillo
VP Data Science - IV.AI

Jackie Hart
CEO - ExO Institute for Coordination

Jacob Kes
Senior Quant Developer - -

Jesper Sundstrom
Head of Growth - Quickbit

John Martin
CTO - IV.AI

Lia Raquel Neves
Founder & Scientific Director - EITIC

Matt Freemantle
Director - Prohibition Partners

Micaela Barrientos
Engineer and Theologian - Universidad Católica

Michael Goldman
Managing Partner - Columbus Street Partners

Mitchell Cohen
Security and Dark Web Research Analyst - Raymond Chabot Grant Thornton - VARS

Richard Lees
Programmer - -

Richard Stanton
Developer - -

Sander Venema
Data Protection Officer - World Ethical Data Foundation

Sergio M.L. Tarrero
President - Alianza Futurista

Tobias Gourlay
Journalist - Journalism

Tudor Boloni
Chief Strategy Officer - OpenExO Inc

Yoshito
Kawabata - University of Guam

Zalina Khestanova
Visual artist - Chamber of Fine Arts of Greece

PIERINO HRISTOV
Mr - AIC owner

Sarah
Clarke - Owner, Infospectives Ltd

Jason Thompson
Consultant - MasonBreese -

Tony Russell
Founder - fammerly

Lorenzo Belenguer
AI ethics researcher -

Ravi Veesam
Cyber Security Consultant - Security Framework

Angela Pause
Senior Writer - University of Waterloo

Colin Chambers
Senior Engineer - Health and Safety Executive

Adrian Maguire

Pedro Huichalaf Roa
Abogado - Centro de investigación en ciberseguridad de la Universidad Mayor

Aalya Dhawan
Director of Content, Marketing and Communications - Women in ai

Matthew Palmer
Digital Lead - Plymouth Marine Labs

Dr Syed Mohd Uzair Iqbal
Assistant Professor - Symbiosis Law School, Pune SIU

Thomas Boyer
UX Design Manager -

Ana María Castillo
University of Chile

Charlie Pownall
AIAAIC - Founder

Casper
Grathwohl - President, Oxford Languages

Klara Krieg
AI Trainee - Bosch

Octavio
Executive Director - Ciudadanía Inteligente

LUIS ROJAS
CEO - Eng.

Gwendoline Clavé
Legal & IT Translator - Clavoline Traduction

Kari Solberg
Data architect - SV

kyungjae cho

Alex Monaghan
Dr - Independent consultant and writer

Jorge Barron

Robert de Groot
Privacy advocate - Partnerships, Copyright Delta

Alex
Engineer -

Stuart Millar
Applied AI/ML - Rapid7 LLC

Audrey Schomer
Analyst -

Edgar Roman-Rangel
Professor - Instituto Tecnologico Autonomo de Mexico

Brad Evans
Director / Machine Learning - (I love this! Thank you!)

Elliott
Data Solutions Manager, EMEA - Elsevier

Jacob Whittaker
LLM lead - Artifical Intelligence

Tadej Fius
CTO - Datafund

Nick Lynch
Data lead - Curlew Research

Alex Simm
Associate Director, Research Advisor - Taysha Consulting, WEDF

Natasha Montagu

Michael Forde
Digital Product Lead - Poui Technologies Inc.

Gregor Žavcer
Director - Swarm Foundation

Alexander Dittel
Privacy lawyer -

Frazer
CX QA Engineer - Technology-based

Shabih Ahmed Arif
Partner Actuarial Consulting - Prima Consulting

Jin
Mr - Myoung-ji

Emma Lau
Data architect - open society

Wojciech Kowalczyk
System Analyst - Institute for Innovative Educational Technologies/ Instytut Innowacyjnych Technologii Edukacyjnych

Lisel Engelbrecht
Executive Head - -

Steve Dorward
Enterprise Architect -

Rachel Quirk
PhD - Machine Learning

Brent Lassi
CISO - Emplifi.io

Richard Cowell
Infrastructure engineer -

Anthony Corliss

Andrew Csizmadia
Senior Lecturer in Computer Science - Newman University

Dasol Hong
CEO - TechToolkit

Alison McDougall-Weil
Previously Google Senior UXR, Research Lead. University of Cambridge. University of Oxford. -

Maraki Aberman
Statistics - Technology

Ms. D Carpenzano
Engineer - Artifical Intelligence

Kristina Podnar
Digital Policy Consultant - NativeTrust Consulting, LLC

Carolina Aguerre
Professor - Universidad Católica del Uruguay

L Brown
Data and AI - Stanford

Ibrahim Akar
Solutions Architect - Citi

Eleanore Carson

Nandakishor Reddy Pulagam
Senior Professional Data Scientist -

Marc Atherton
Partner -

Jayden Macdonald
Masters Student, Researching Ethical AI Practices - Tsinghua University

Kathrin Cresswell
Senior Lecturer - University of Edinburgh

Charlie Wilson
Founder - RUE

Sophie Carr
CEO & Founder - Octoped Tutor

John burnam
Founder - Redfern analytics

Louis Coiffait-Gunn
Director of Policy and Public Affairs - Publishers Association

alec horsman
Creative director - Eightcreate

Shaun Hides
Dean of Faculty - Coventry University

Dr Nick Bradshaw
Founder - South African AI Association (SAAIA)

Rainer Bock
Director - Sharp Intake of Breath

Patrick Wall
Creative Technology Director -

Nestor Albuquerque
IT Consultant - DFM Consulting

Dylan Mouratsing
Global Chief Data Officer - mSix&Partners The&Partnership

Cristian
developer - -

Nicholas Oatridge
Director - FOS Ltd

Hugo Lebus
EdTech Specialist -

Khesha Patel
Equality, Diversity, Equity and Inclusion Project Manager - PA Media

Rob Healey
CEO - Formiti Data International UK

Nick Fox
Mr - Lead data architect, Emerald Publishing

Per Axbom
Design Strategist, Teacher and Digital Ethics Advocate - Independent

Anne-Marie Eklund Löwinder
Founder & CEO - Amelsec

Deepti Karan Weiss
Disability Inclusive Development Practitioner - Independent Consultant

Romie Kind
Creative Industries - Swissnex in SF

Steve Dorward
Enterprise Architect -

Lucy K Wills
Founder - Health Heard

Stanley Sebastian Joseph
Chief Technology Officer - AyataCommerce

Daniel Situnayake
Head of Machine Learning - Edge Impulse Inc.

Caroline Ball
Academic Librarian - University of Derby

Neil Raden
Managing Partner - Hired Brains Research

Timothy Wiles
Technical Director -

Raziq Rauf
Writer - Independent

Dr. Nigel Rata
CISO - Royal Holloway University of London

Farhad Khadim
Privacy Specialist - Centennial College

Debra J Farber
Privacy & Ethical Tech Advisor - Shifting Privacy Left

Mike de Sousa
Content Philanthropist: Writer, Composer, Artist. - Art Lover VIP

Maria Sourbati
Senior lecturer and AGEAI project lead, University of Brighton, UK - University of Brighton

Heather Walker

Ivana Bartoletti
Privacy professional, author and Founder, Women Leading in AI Network -

Michael Levitz
Business Development - IV.AI

Emma Chau

Mario Zaharioudakis
Entrepreneur - Restaurant Business, Previously in Fintech

Peter Warren
Editor - www.futureintelligence.co.uk

Graham Ockhuizen

Nathaniel Hansen
Director - The Socializers

Leah Piper
senior risk manager -

Inge H A Pettersen
Mr. - Equinor

Steven Garner
Founder, Grandeo Limited - AI Ethics and Due Diligence

Christian DEPLANTE
Dr - EAGE

Liam Ried
Software Enginner - Enzai Technologies

Tom Clark
Founder - Associate

Deborah Y
Data Governance Lead - DAMA UK

Christopher Neal
President - OwlTree Logic

Eddie Harrison
Mr -

Sam Black
Executive Director of Delivery - The Skills Network

subhas patel
Digital Innovation Consultant -

Mark Pearce
Architect, Developer, Author, Director - Delta Capita

Mikkel Bue Lykkegaard
Dr - digiLab

Michael Buisman
Strategic Solutions - Data & AI - Independent Thinker in AI

Philip Morris
Head of Business Development (Videogames), Europe -

Rikhu Surya
Software Engineer -

Joshua Bailey
Data Scientist - Relative Insight

Xiao Yang
University of Edinburgh

Mark Humphries
Chair - DAMA UK

Steve Hulme

Traian Mihaescu
Professor - Universitatea de Medicina și Farmacie "Grigore T Popa" Iași

Meta
Mr. - Citizen

Ravinder Singh
Dr - Government

Nishal RAMADAS
CEO - Hy-Met

Daniel Reece
Senior Manager Application Security - Burberry. ex-IBM.

Mark Lynch
CEO & Founder -

kieran Billingham
Senior Data Scientist - University of Bristol

Mohamed Rizal Yacob
Strategic Research Consultant -

Gosia Wojas
Artist -

TehminaGM
Ms -

Paul Fryer
Mr - Founder & CEO - it.fit

Jack Oonk
Mr. - Food for All Charity

Susana Domingos

paul stewart fryer
mr - interested

Emma Shapiro
Editor-At-Large - Don't Delete Art

Gerd Leonhard
CEO - RSA

Adrian Timberlake
Mr - Researcher and Developer of AI Edge solutions

Alan Nye
Mr - The World

Alex Marples
COO and Practitioner -

Jennie Terry
Ms - human being

Sue Turner
Founder - AI Governance Limited

Cyrus Hodes
Co-founder - AIGC Chain

Paul Excell
Chair - AI4C

Shoshana Bloom
Ms - Equiti Health Limited

DJ Jones
Chief Product Officer -

Kassim Mwitondi
AI/ML Developer - Sheffield Hallam University

Richard McNeil
Mr. - Writer

Waqar Ahmed Riaz
Writer, Digital Mentor - ex Unilever, ex Samsung Group -

Patricia Lee
ANN - Specialist

Nikita Samarin
Privacy Researcher - University of California, Berkeley

Tim Shepard
Compsci - Cambridge

Daniela Pinto
Database Administrator - N/A

W Watts
- - OASIS User Council

Catherine Keegan
Legal representation - Civil Society

Mohammed
Dr - Consultant engineer

Lizzy Harris

Taher Aboueleid
Vice-president at the court of appeal - Egypt - Ministry of justice

Anupam Singh

Todd E. Pierce
Attorney/Free Speech Advocate - Project for the Study of American Militarism

Mehrab
Head of Strategy - LedgerFi.io

Marcelle Roubanian
CMO - Technology/AI/ML, Future Thinking

Michael King

Mariana Moura Santos
Founder - Chicas Poderosas INC

Omar Farooq Hussain
CEO - MangoGTM Group LLC

Mohamed Sadek
FOUNDER - com-iot technologies

Shail Khiyara
President & COO - AI Thought Leader, Operator, Board Member

Faran Dilshad Qureshi
Managing Director - IT industry

Haythem Hammour
Cybersecurity Product Marekting Manager - Splunk

Rayhan TAJI
CEO Supernovae - Saeed Al Dhaheri

Ahmed Sibari
Mr - Emotech Ltd

Steve McNeil
Statistician - Messy data

Xrisi Efstratiou
AI modeling - LLM

Mariana Solano
Data Scientist - -

Ana Paula Moritz
PhD student - University College Dublin

James W
US Federal Employee

Tara Maritzer

Silvana Fumega
Project Director - Global Data Barometer

Kemly Camacho
General Coordinator - Cooperativa Sulá Batsú

Martin Gould
Director of Research - Global Initiative for Inclusive Information Communication Technologies

David Wearing
PhD and European Patent Attorney - Independent

Corey Cohen
N/A - N/A

Viktoriia Antonova
Senior System Analyst MDM - JSC Tander

Oliver Gale
CEO - Panther protocol

Stan
CEO - Xrom Group

Cloélia Tissier

César Rosales
Consultant on technology and democracy - Multilateral organizations

Serene
Concert Pianist | Founder - Snowstorm

Celsus Tushabe
Engineer - Uganda

Tiffany Greenidge
- - -

Giovanna Ochoa
Marketing IV - -

Mathieu Leclerc

Chris Kelly
Human Rights Researcher - NGO

Sam Marshall
PhD - Machine Learning

Esther Kiernan
Archivist - Human Rights

john bowsher
analyst - finance

Anna Cooper
100% DL nerd - Medical AI

Mona
Mariam -

Bassem
Product Development Manager -

Brynn Kelly
machine learning/data science - Multiple

Michael Gaio
Founder - Mythic Systems

Eduardo Paz
Dev Lead - FOSS

Waltzer
Coder - Things Linux

Jake Cohen
Academia - (Suspicious of robots)

Derek Lackey
Managing Director -

Priah (Priya) Shah
Statistician - Silicon Valley escapee

Prajesh K
Data Scientist - Indian Institute of Science

Joseph O'Brien
NN/DL architect - Sometime Google

Justin
Mac - Software Engineer

Zoe Moran
Compsci - N/A

Shawn Ford
Incident response and privacy lawyer - Henri & Wolf

Douglas
Student - Medicine

Seka Isaac
Data Scientist - Caltech

Logose Dorcus Laura
Student -

Lumu Mahad
Student - Computing

Henry Tumusiime
Student - Fine Arts

Nsubuga Ronald Kalinzi
Computer Science student - Bachelors of Computing

Ssentongo Daglus
Dev - LCC

Rhoda Najjuma Kuteesa
Student - Petroleum Geoscience

Namigadde Martinah
Student - Social Sciences

Muyambi Jordan
Developer - Telecommunication engineering

Mbaziira Owen
Computer Scientist - Department of AI, KYU

Frank Muller
Director - Data Science

Kathryn Body
PhD - University of Bristol

Kirill Markin
Head of AI Lab - SOAX

Emily Fi
game dev - various companies

Annie Machon
WEDF board member, author, ex-MI5 - WEDF, Sam Adams Associates

Zenia Tata
CEO - Zenia Tara inc

Faisal Saeed Al Mutar
Founder and President of Ideas Beyond Borders -

ruth bonet
data scientist -

Namanya swaibu
Mr. -

Andrew Mukago
Student - Computer Science, KIU

Ihangu Derrick
Mr - Civil engineering

Akoragye Meryel
Student - Tech and Society

Tawoda Edmon
Documentalist - Civil Society

Natumanya Omega
Student - Civil Engineering

Kamugisha Steven
Engineer - Flexi home engineer kampala

Colin Delamere
mr -

Kamugisha Steven
Engineer - Machine Learning

Nuwagaba Demiano
Student - AI and Business

KARIGIRWA BRENDAH
Social work and social administration - NAMUGONGO

Tehond edmod
Journalist - Jinja

Steven Owomugisha
Student - Medicine student at KIU

Abdou MFOPA P.
Chief Executive Officer & Founder - CamOne Sarl - Cameroon

Joshua Long
Head of Marketing - Mojeek

Nakato Daphine
Student - Journalism and Mass Communication

Francisco Brito
Chief Data Officer - IV.AI

James Sellmann
Dean - University of Guam

Wadada Kennedy
Student - -

Twesigye Ian
Student - Anglican

Kizza
Postgraduate - Machine Learning

Nicholas Tusime
Studend - Computer science,Makerere University-uganda

Ainomugisha Wasswa
Professor - Procurement & Logistics

Naluyima Shakirah
Student - Kiu

Obadiah Eric
Student - -

Wojciech Bednaruk
Human - Humanity

Chase Kyazike
Researcher - Media company

Frank Aine
Journalist, News Editor - East Africa

Nagawa
Data Scientist - Cosmology

Sserwadda Moses
Developer - Dalaware construction company

Miria Wanyeze
Teacher - Godmark High school Mukon

Sali paskale
Engineer - IT technician

Kaliisa Gonzaga
Student - Technology, Kenya

Kamugumya Taison
Lead at jeebflims - Mbarara

Karungi medrine
Law student - UCU

Ainebyona Mark
Journalist - Socioeconomics

Kaboggoza Ronald
Professor - Medicine

Katasi Evelyn Elizabeth
Student - Nsambya Medical School

Arun Marsh
Founder - AMP video

Omirambe James
Journalist - Impact Pictures

Kelly Tumwesigye
Student - Makerere University

Mike Tumwesigye
Developer - JAT Properties

Nabbaale Deniz
Student - Medicine

Ssekabira Ronald
Engineer - -

Phillip Kyohirwe
CEO, Prof. - Care Club Malaba

Onen Pius
Photographer - Cinelab Akademie

Kizza Desire
Medical Practice - -

Daglas Mukiibi
Student - Kyambogo University

Daglas Mukiibi
Student - Kyambogo University

Ayebare Dorothy
Student - KU

Dakota Hart
Student - University of Oxford / Sarah Lawrence College

Chris Ssema
student - Busitema University

Gideon
Student - Lubaga Medical School

Kivumbi Nasser Sultan
Student - IUIU KC University

Nayiga Gloria
Developer - Luweero Information and Communication centre

Denis Ongu
Professor - Gulu University

Philippe van Nedervelde
CEO & Founder - E-SPACES

John Mujuni
Professor - Kabale University

Onesmus Ayinebyona
Student - Electrical Engineering

Anyijukire Onesmus
AI engineer - Galaxy tech- Gulu branch,uganda

Toni
founder of a design studio - Contributer

Arinda Allan
Developer - Ginx tech-uganda

Anitah Bamukunda
Student - IT

Emmanuel Mugabe
University Student - -

Ariho Patience
Data scientist - SMI-Kabale main branch

Tusiime Frank
Student - Central Uganda

Kawuma Isaac
University Student - Department of Economics

Ikiriza Ngabirano
Developer - Manson tech-iganga

Nampala Rebecca
Student - Fashion and design , YMCA

Juma Shabul
AI engineer - Ibanda-uganda

Amwiine Albert
Developer - AMS - fortportal branch

Nabaggala Joviah
Student - Neural Networks

Jogoo Luis
PhD - Risk Identification and Mitigation

Nabaggala Joviah
Student -

Derrick kamugisha
AI engineer - Mbalaba-kenya

Ntege Joshua
Student - Bachelor of commerce

Joshua Mugabi
Student

Groot Baker
Professor - Mubs main campus

Aine Romeo
Developer - Pullux groups- Lira branch

Nagasha john
Civil engineer - IT department

Aine Bashemera
Student - Science and Technology - Kyambogo University

Corey Eastwood
Bookstore Owner - Human Relations Bookstore, Brooklyn

Brian Mugalula
Student - Makerere University

Ashemeza
developer - AI

Lindah
- - Business administration

Ashemeza
developer - masindi

Mercy kushaba
Developer - Smart X - Mukono

Hope Avery
Lawyer - Law

Nicholas Mugwanya
Medical Student - Kabale School of Medicine - Western Uganda

Vicent Kitonsa
Student - Logistics

Patrick Yiga
Student - KYU- civil engineering

Sammy_c_cashi
Producer - Music

Martha Ainomuwhezi
Electrical engineer - Tororo-uganda

Nahula Eunice
Data scientist - Delux group - Mbale

Jon Martin
Models - Data / AI

Kitandwe Andrew Gideon
Managing director - GREEN LAND HUMAN RESOURCE CONSULTANCY

Kisha
Academic researcher - Federal University of Technology, Owerri, Nigeria

Rosemary
Student - University, Kenya

Henrination Andromeda
Data scientist - Boda Boda banja

Mugasha Keneth
Logistics and Management - Oskan Foods

david bush
Students - Makerere University Kampala Uganda

Immaculate
Professor - African Union

Morris Ainembabazi
AI engineer - Kampala-uganda

Daniel Musinguzi
Director - PRA - UGANDA

Edgar Umeri
Student - KCL

Sylivia Mubangizi
Student - MUST

Mulwanyi Kefah
Developer - Kampala

Patrick Arinda
AI engineer - Uganda

Brian
Student - Rwanda

Joseph Ssebunya
Data scientist - Uganda

Amia Gift
Developer - Kampala

Bugton Didus
AI engineer - Kampala

Ubaldo Arinda
AI engineer - Kampala

Eunice
Developer - Mbarara

Pascal
Student - Mbarara

Vee
Developer - Kampala

Paolo Bianchi
Machine Learning - University of Milan

Mukundane andrew
Student - MUBS

Kaima
Full Stack Developer - Jinja

KYOMUHENDO peace
Student - Mengo

Ahebwe
Developer - Kampala

Wandera Henry
Data scientist - Verma co

Deborah Olukan
PhD Student - University of Leeds

Tumwebaze geofrey
Journalist - Uganda

Pamela
Student - Banda

Jonathan Grace, Serugga
Student - U Delaware

John Phillip Ibanez
Head of Engineering - APAC - IV.AI

Frank Wei
Data analyst - Environmental Science

Jacob Masoudi
Full Stack Engineer - IV.AI

Leah Arsenault
Data Analyst - IV.AI

Justin Catino
VP Strategy and Analytics - IV.AI

JEROME ASILO
Fullstack Developer - IV.AI

James Keinerugaba
Scientist - Uganda

Cherry
Sales - IV.AI

Darius Ariho
CEO - JAT Properties

Brian Bills
Developer - Uganda

Medard
Journalist - Uganda

Federico
VP Operations - iv.ai

Jeff Mugerwa
Developer - Eminent- Uganda

Uri Fernandez
EVP Global Operations -

akamumpa
student - kampala

Martin
Faryy - Engineer

Innocent Tumwesigye
Student - Makerere University-Uganda

Ampaire
Student -

Rhodes Atukwase
Developer - Child Network Organization

Ashley Mann
Machine Learning - \o/

435
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