ΑΙhub.org
monthly digest
 

AIhub monthly digest: August 2022 – cross-lingual transfer, philosophy of cognitive science, and #DLIndaba


by
30 August 2022



share this:
Panda and tiger reading

Welcome to our August 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we continue our conference coverage, chat to winners of best paper awards, and listen to some interesting podcasts.

New voices in AI

In the latest episode of new voices in AI, host Joe Daly talks to Dimitri Coelho Mollo about his work on philosophy, cognitive science and AI.

Faithfully reflecting updated information in text

Wouldn’t it be handy to be able to automatically update information in an outdated article? Well, Robert Logan, Alexandre Passos, Sameer Singh and Ming-Wei Chang designed an algorithm to do just that in their paper FRUIT: Faithfully Reflecting Updated Information in Text. This work won them a best new task award at NAACL 2022 (Annual Conference of the North American Chapter of the Association for Computational Linguistics). In this interview, Robert tells us about their methodology, the main contributions of the paper, and ideas for future work.

Evaluating cross-lingual transfer

Dan Malkin, Tomasz Limisiewicz, Gabriel Stanovsky received an outstanding new method paper award at NAACL 2022 for their work A balanced data approach for evaluating cross-lingual transfer: mapping the linguistic blood bank. We spoke to Dan, who told us about multilingual models, the cross-lingual transfer phenomenon, and how the choice of pretraining languages affects downstream cross-lingual transfer.

ICML invited talks

The 39th International Conference on Machine Learning (ICML 2022) took place in Baltimore last month. There were four invited talks at ICML 2022 which we summarised these in two posts:
#ICML2022 invited talk round-up 1: towards a mathematical theory of ML and using ML for molecular modelling
#ICML2022 invited talk round-up 2: estimating causal effects and drug discovery and development

Mihaela van der Schaar on machine learning for medicine

The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJACI-ECAI 2022) took place from 23-29 July, in Vienna. As part of the conference there were eight fascinating invited talks. In this post, we summarise the presentation by Mihaela van der Schaar, who talked about some of the opportunities for machine learning in medicine.

Deep Learning Indaba returns

After a two year pandemic-enforced break, Deep Learning Indaba returned this year, taking place from 21-26 August. This is the annual meeting of the African machine learning community with the mission to strengthen African machine learning. Find out what the attendees got up to in our tweet round-up of the event.

Oriel FeldmanHall on reinforcement learning

In the latest episode of Computing Up, Oriel FeldmanHall (Brown University), joins hosts Michael and Dave in a wide-ranging discussion starting with what reinforcement learning does and doesn’t mean. She turns the tables to ask what computer scientists do and don’t get wrong about mind and brain and learning in general.

Radical AI podcast: Should the government use AI?

How does the government use algorithms? How do algorithms impact social services, policing, and other social services? And where does Silicon Valley fit in? In the latest episode of the Radical AI podcast, hosts Dylan and Jess interview Shion Guha about how governments adopt algorithms to enforce public policy.

Watch the talks from the ACM Conference on Fairness, Accountability, and Transparency

For those who weren’t able to attend the ACM FAccT conference, the organisers have made videos of all of the keynote talks, panel discussions, tutorials, and research talks available on YouTube. You can find the links to the playlists here.

How does the proposed UK AI regulation compare to EU and Canadian policies?

In this edition of her EuropeanAI newsletter, Charlotte Stix presents an analysis of the UK’s proposal for AI regulation compared to the EU’s AI Act and Canada’s Artificial Intelligence and Data Act. You can find the archive of her newsletters, which cover topics relating to AI governance, here.


Our resources page
Forthcoming and past seminars 2022
Articles in our UN SDGs 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:



Subscribe to AIhub newsletter on substack



Related posts :

RWDS Big Questions: how do we balance innovation and regulation in the world of AI?

  06 Mar 2026
The panel explores the tensions, trade-offs and practical realities facing policymakers and data scientists alike.

Studying multiplicity: an interview with Prakhar Ganesh

  05 Mar 2026
What is multiplicity, and what implications does it have for fairness, privacy and interpretability in real-world systems?

Top AI ethics and policy issues of 2025 and what to expect in 2026

, and   04 Mar 2026
In the latest issue of AI Matters, a publication of ACM SIGAI, Larry Medsker summarised the year in AI ethics and policy, and looked ahead to 2026.

The greatest risk of AI in higher education isn’t cheating – it’s the erosion of learning itself

  03 Mar 2026
Will AI hollow out the pipeline of students, researchers and faculty that is the basis of today’s universities?

Forthcoming machine learning and AI seminars: March 2026 edition

  02 Mar 2026
A list of free-to-attend AI-related seminars that are scheduled to take place between 2 March and 30 April 2026.
monthly digest

AIhub monthly digest: February 2026 – collective decision making, multi-modal learning, and governing the rise of interactive AI

  27 Feb 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

The Good Robot podcast: the role of designers in AI ethics with Tomasz Hollanek

  26 Feb 2026
In this episode, Tomasz argues that design is central to AI ethics and explores the role designers should play in shaping ethical AI systems.

Reinforcement learning applied to autonomous vehicles: an interview with Oliver Chang

  25 Feb 2026
In the third of our interviews with the 2026 AAAI Doctoral Consortium cohort, we hear from Oliver Chang.



AIhub is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence