ΑΙhub.org
monthly digest
 

AIhub monthly digest: November 2024 – dynamic faceted search, the kidney exchange problem, and AfriClimate AI


by
29 November 2024



share this:
Panda and tiger reading

Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we hear from AfriClimate AI co-founder Amal Nammouchi, learn about the kidney exchange problem, and find out how to improve the interpretability of logistic regression models.

Harnessing AI for a climate-resilient Africa: An interview with Amal Nammouchi

This month, we had the pleasure of chatting to Amal Nammouchi, co-founder of AfriClimate AI, a grassroots community focused on using artificial intelligence to tackle climate challenges in Africa. Amal told us about the inspiration behind the initiative, some of their activities and projects, and plans for the future. Read the interview here.

Building trust in AI: Transparent models for better decisions

In this blog post, Danial Dervovic writes about work presented at IJCAI 2024 on improving the interpretability of logistic regression models. Danial and colleagues have proposed an augmentation to such logistic models, which makes decisions made by them more understandable.

The kidney exchange problem

In their work Parameterized Complexity of Kidney Exchange Revisited, presented at IJCAI 2024, Úrsula Hébert-Johnson, Daniel Lokshtanov, Chinmay Sonar and Vaishali Surianarayanan consider the issue of kidney donation and how to maximum the number of patients who receive a transplant. We hear from the authors about the kidney exchange problem and how they went about solving two of the open problems in this field.

Enhancing controlled query evaluation through epistemic policies

A significant data challenge concerns the sharing of information without compromising sensitive details. Gianluca Cima, Domenico Lembo, Lorenzo Marconi, Riccardo Rosati and Domenico Fabio Savo won a distinguished paper award at IJCAI 2024 for their work Enhancing Controlled Query Evaluation through Epistemic Policies, which considers the controlled query evaluation framework – an approach that safeguards confidentiality whilst still providing answers to queries. The team wrote about their research in this blog post.

Dynamic faceted search: from haystack to highlight

The number of scholarly articles is growing rapidly, and finding the most relevant information from this vast collection of data can be daunting. In their work A Neuro-symbolic Approach for Faceted Search in Digital Libraries, presented at ECAI-2024, Mutahira Khalid, Sören Auer and Markus Stocker utilise facet generation, an advanced search method that allows users to filter and refine search results. They outline three different dynamic methods that adapt and adjust facets in real-time, based on user input and the evolving nature of the dataset. You can read their blog post about this work here.

How to choose your loss function

In machine learning classification tasks, achieving high accuracy is only part of the goal. It is equally important to know how confident the models are in their predictions, a concept known as model calibration. A key factor influencing both the accuracy and calibration of a model is the choice of the loss function during training. In this blog post, Viacheslav Komisarenko explores how to choose a loss function to achieve good calibration. This is work that won him, and co-author Meelis Kull, an outstanding paper award at ECAI-2024.

The Turing Lectures: Can we trust AI? – with Abeba Birhane

The Turing Lectures series features influential figures from the world of data science and artificial intelligence. The latest lecture was given by Dr Abeba Birhane, in which she tackled the topic of biases in data and the downstream impact on AI systems, and showed how this can lead to unfair outcomes in our daily lives. You can watch the lecture here.

Everyday AI podcast back for season two

CSIRO’s Everyday AI podcast is back for a second season. Host Jon Whittle, and expert guests, delve into how AI is impacting various aspects of our lives, from healthcare and education to workplaces and beyond. You can listen to the series here.

AIhub on Bluesky

This month, we joined many of our contributors and readers on Bluesky. You can follow us @aihub.org.


Our resources page
Our events page
Seminars in 2024
AAAI/ACM SIGAI Doctoral Consortium interview series
AAAI Fellows 2024 interview series
AI around the world focus series
New voices in AI series



tags:


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.




            AIhub is supported by:


Related posts :



The Good Robot podcast: Symbiosis from bacteria to AI with N. Katherine Hayles

  13 Jun 2025
In this episode, Eleanor and Kerry talk to N. Katherine Hayles about her new book, and discuss how the biological concept of symbiosis can inform the relationships we have with AI.

Preparing for kick-off at RoboCup2025: an interview with General Chair Marco Simões

  12 Jun 2025
We caught up with Marco to find out what exciting events are in store at this year's RoboCup.

Graphic novel explains the environmental impact of AI

  11 Jun 2025
EPFL’s Center for Learning Sciences has released Utop’IA, an educational graphic novel that explores the environmental impact of artificial intelligence.

Interview with Amar Halilovic: Explainable AI for robotics

  10 Jun 2025
Find out about Amar's research investigating the generation of explanations for robot actions.

Congratulations to the #IJCAI2025 award winners

  09 Jun 2025
The winners of three prestigious IJCAI awards for 2025 have been announced.

Machine learning powers new approach to detecting soil contaminants

  06 Jun 2025
Method spots pollutants without experimental reference samples.

What is AI slop? Why you are seeing more fake photos and videos in your social media feed

  05 Jun 2025
AI-generated low-quality news sites are popping up all over the place, and AI images are also flooding social media platforms

The Machine Ethics podcast – DeepDive: AI and the environment

In the 100th episode of the podcast, Ben talks to four experts in the field.



 

AIhub is supported by:






©2025.05 - Association for the Understanding of Artificial Intelligence


 












©2025.05 - Association for the Understanding of Artificial Intelligence