INTERNATIONAL CONFERENCE ON

AI for People:

Towards Sustainable AI

20-24 November 2021, Online


Enter the conference!


Program

The conference aims to be accessible for anyone interested in artificial intelligence for the societal good. For this reason, some sessions will be more introductory and other more advanced.

The program is still being updated. Below you can read about the sessions that are already confirmed:

Keynote Sessions see Keynote Speakers

Roundtable Sessions Special Events Workshops Paper Presentation Sessions See Sessions



Tentative Schedule

Check the current version below or directly access it here.

All sessions will take place in the Lecture Hall in Gather Town.

Keynote Speakers

Roundtable Sessions

Roundtable Sessions will also be a chance for the public to ask questions and get engaged with the organizations working in several fields. Each organization will present itself through one panelist, and then the floor will be open for questions from the moderator and from the public.


Roundtable on AI and the Environment

This roundtable will bring together five organizations working at the crossing of AI & Environment to discuss common challenges and opportunities.

Participants:

Roundtable on AI & Civic Participation and Rights

This roundtable will bring together three organizations working at the crossing of AI & Civic Participation and Rights to discuss common challenges and opportunities.

Participants:

Roundtable on AI Governance

This roundtable will bring together three organizations working at the crossing of AI & Governance to discuss common challenges and opportunities.

Participants:

Roundtable on AI Ethics

This roundtable will bring together two organizations working at the crossing of AI Ethics to discuss common challenges and opportunities.

Participants:

Special Events

Watch-Party: Coded Bias

Coded Bias explores the fallout of MIT Media Lab researcher Joy Buolamwini’s discovery that facial recognition does not see dark-skinned faces accurately, and her journey to push for the first-ever legislation in the U.S. to govern against bias in the algorithms that impact us all.

In this session, we will watch Coded Bias together and have a discussion session open to everyone.


Lecture on Catalog of the Post-human

Jessica Charlesworth and Tim Parsons will discuss Catalog for the Post-Human, a satirical installation at the Venice Architecture Biennale that uses the future of work and human enhancement to draw attention to the nature of our post-human condition.
Read more


Getting to know AI for People

AI for People is a non-profit association born out of the idea of shaping Artificial Intelligence technology around human and societal needs.

Learn about all the activities of AI for People in this interactive session.


Exercise in Collective Intelligence

The exercise in Collective Intelligence is a way to capture the participants’ thoughts into a sort of final “Conference Manifesto”. By using Miro Board the participants, aided by the conference team, will write down on the Miro Dashboard their comments as well as their thoughts about the “Risks/Opportunities” and “Ideas for Change/Recommendations” on each of the conference themes; AI & the Environment, AI & Civic Participation And Rights, AI Governance and AI Ethics. The final product of this common thought process will be made public and it will represent a real, collective conference output.


Workshops

Workshop on AI & Environment by Pi School

Leveraging NLP to achieve environmental sustainability

Mapping the environmental capabilities of EU countries to check if they match the need for clean technology as implied by the European Green Deal is becoming crucial. One way to achieve this is to retrieve geo-localized documents describing R&D activities across the EU and the world. Under a contract with the Joint Research Center (JRC) of the European Union, we carried out a project, Patents4IPPC, consisting of building an Information Retrieval (IR) engine (Github) capable of fetching relevant patents based on specific subsections of some official documents. Following recent advances in the field of Natural Language Processing (NLP), we build a retrieval system based on the Transformer architecture. We will give an overview of the project and take the opportunity to explain NLP pipelines and good practices.

The workshop will be given by Cristiano De Nobili and Francesco Carriagi after a brief introduction about Pi School by Sébastien Bratières, Pi School Director of AI.

Workshop Leader:
Cristiano De Nobili

Cristiano De Nobili is a Theoretical Physicist (Ph.D. @SISSA) now Lead AI Scientist at Pi School, working mainly on environmental impactful projects. Machine and Deep Learning Lecturer. Previously NLP & Deep Learning Scientist @ Samsung's Bixby project. Science communication enthusiast and civil pilot.

Workshop Leader:
Francesco Cariaggi

Francesco Cariaggi holds a Master's degree in Computer Science from University of Pisa, Italy. He currently works as a Deep Learning engineer at Pi School, where he helps businesses grow with the help of Artificial Intelligence.

Workshop on Artificial Neural Networks (introductory)

Gentle introduction on Artificial Neural Networks (ANN). We will start from a Biological Neural Network (BNN) and build our way towards ANNs and the purpose of ANNs will be described in a non-mathematical way.

At the end of this session you will know:

  1. What an ANN is.
  2. What the objective of an ANN is.
  3. What it means when we ‘train’ an ANN

Workshop Leader:
Mehran Bazargani

Mehran is a post-doctoral researcher at the school of Computer Science, Insight SFI Research Centre for Data Analytics at University College Dublin (UCD), and he is the founder of ML-Dawn. His research interests fall in the realm of machine learning, specifically, anomaly detection, active learning and interpretability. You can find his publications on Google Scholar.

Workshop on Neural Networks for Tumor Detection

We will go through some code in Python and Pytorch, where the objective is to create an Artificial Neural Network (ANN) for the task of tumor detection in brain MRI images.

At the end of this session you will know:

  1. What the general approach to coding an ANN is in Pytorch. (e.g., dataset classes, dataloaders, torch models,…)
  2. In practice, how training the ANN will improve its performance, and how we can measure this improvement (e.g., accuracy, confusion matrix)
  3. What it means when a model ‘overfits’, in practice and what we can learn from it

Workshop Leader:
Mehran Bazargani

Mehran is a post-doctoral researcher at the school of Computer Science, Insight SFI Research Centre for Data Analytics at University College Dublin (UCD), and he is the founder of ML-Dawn. His research interests fall in the realm of machine learning, specifically, anomaly detection, active learning and interpretability. You can find his publications on Google Scholar.

Workshop on Sustainable AI

Measuring the sustainability of AI

Many hopes are put onto AI systems regarding sustainability efforts. While AI certainly has immense potential for contributing towards protecting our planetary boundaries, questions regarding the sustainability of AI are less prominently addressed. That is worrisome because the development, implementation and use of AI systems often comes with huge energy consumption, unfair working conditions and intransparent as well as biased applications. In order to move from mostly abstract discussions of the sustainability of AI, in our project "SustAIn" we are developing a sustainability index for AI systems to serve as a rating system. During the workshop we will be working with sustainability indicators for AI and will attempt to develop a methodology for ranking AI systems.

Workshop Leader:
Anne Mollen

Dr. Anne Mollen is policy and advocacy manager at AlgorithmWatch as well as project manager for „SustAIn - Sustainability Index for Artificial Intelligence“. After her studies in communication and political sciences, she worked in several research projects working on the interrelation between digital media technologies, society and democracy.The focus in her policy work lies on automated decision making systems in the area of labour, online platforms and the sustainability of AI.

Workshop on AI Governance

Over the past 4 years, there has been a mushrooming of initiatives to ‘govern’ AI and to ensure we achieve 'Responsible AI'. But what does this mean? And what does it imply for us? In this workshop, I will make an attempt to explain the What, Why, and So What of AI governance. I will cover the relevant aspects of the big picture and the practical implications, with examples to walk through the story, for both the technically inclined and the not-as-technically inclined.

Workshop Leader:
Nicolas Moës

Nicolas is an economist by training focused on the impact of Artificial Intelligence on geopolitics, the economy and industry. He is the Brussels-based representative of The Future Society, where he has monitored European developments in the legislative framework surrounding AI.

Workshop on AI Ethics
From What to How: the practicalities of AI Ethics

The workshop will cover the basic concepts of AI ethics, what the purpose is and how ethical issues are identified before moving on to focusing on the limitations of current normative approaches and how these limitations might be overcome.

Workshop Leader:
Jessica Morley

Jessica is a graduate researcher at the Oxford Internet Institute and the policy lead at the DataLab in the Nuffield Department of Primary Care Health Sciences. Her research focuses on operationalising AI ethics, particularly in the healthcare domain.

Paper Presentation Sessions

Session 3
22nd Nov, 11:00 CET


Session 4
23rd Nov, 11:00 CET


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