ΑΙhub.org
 

AIhub monthly digest: October 2022 – Nigerian sign language, a simple voting rule, and robotic control algorithms

by
27 October 2022



share this:
Panda and tiger reading

Welcome to our October 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 learn about a Nigerian sign language dataset, hear from researchers working on different robotic control projects, and dig into the latest governmental AI policies.

A sign-to-speech model for Nigerian sign language

Steven Kolawole created a pioneering dataset for Nigerian sign language, in collaboration with a TV sign language broadcaster and two schools in Nigeria. He used this dataset of over 8000 images to create a model to convert sign language to text or speech. In this interview, Steven told us about the goals of this research, his methodology, and how the work has inspired research in other languages.

Plurality veto: A simple voting rule achieving optimal metric distortion

Fatih Erdem Kizilkaya and David Kempe won a distinguished paper award at IJCAI-ECAI 2022 for their paper Plurality veto: A simple voting rule achieving optimal metric distortion, which considers the problem of creating a voting system that best represents the preferences of the voters. In this blog post, Fatih explains their method by means of simple examples.

Developing a gradient-based control method for robotic systems

In their recent paper, Training efficient controllers via analytic policy gradient, Nina Wiedemann, Valentin Wüest, Antonio Loquercio, Matthias Müller, Dario Floreano, and Davide Scaramuzza propose a gradient-based method for control of robotic systems. First authors Nina Wiedemann and Valentin Wüest told us more about their approach, the motivation for the work, and what they are planning next.

Accelerating laboratory automation through robot skill learning

Reinforcement learning has become a compelling tool for training robots to autonomously acquire behaviours and skills. In this blog post, Gabriella Pizzuto writes about her research applying model-free reinforcement learning to the laboratory task of sample scraping.

What happens when we mix multi-agent systems, robotics, software engineering, and verification and validation?

In the first in a series of posts from the Autonomy and Verification Network, Rafael Cardoso and Angelo Ferrando explain the links between multi-agents systems, robotics, verification and validation. They also provide a summary of the Agents and Robots for reliable Engineered Autonomy (AREA) workshop, the most recent edition of which took place at IJCAI-ECAI 2022. Stay tuned for further posts from the network.

United States blueprint for an AI bill of rights

On Tuesday 4 October, the White House Office of Science and Technology Policy released a blueprint for an AI bill of rights. The aim is “to help guide the design, development, and deployment of artificial intelligence (AI) and other automated systems so that they protect the rights of the American public.” The bill outlines five protections that everyone in America should have with regards to artificial intelligence. Find out more here.

European Union liability rules for artificial intelligence

At the end of September, the European Commission released a proposal for an Artificial Intelligence Liability Directive (AILD). It forms the next step in the development of a legal framework for AI, following on from the 2020 white paper and the 2021 proposed legal framework.

For some expert analysis on the European approach to regulation, these two articles from The Digital Constitutionalist are well worth a read:

New edition of the AAAI magazine

The fall 2022 issue of the AI magazine, a publication from the Association for the Advancement of Artificial Intelligence (AAAI), is available to read here. It includes articles on neurocompositional computing, the application of AI in the auditing profession, and an opinion piece on intelligent textbooks.

UK AI Standards Hub launch

Wednesday 12 October saw the launch of the UK AI Standards Hub. The aim of the Hub is to help stakeholders across industry, government, civil society, and academia understand, use, and develop standards. As well as the website, which hosts the Standards Database, policy and research databases, training materials and forums, the Hub initiative will also focus on live events, research and international engagement.

Call for nominations for two awards

ACM SIGAI is currently calling for nominations for two awards:

  • ACM SIGAI autonomous agents research award. This award is made for excellence in research in the area of autonomous agents. It is intended to recognize influential researchers in the field. Find out how to nominate here.
  • AAAI/ACM SIGAI doctoral dissertation award. This award recognizes and encourages superior research and writing by doctoral candidates in artificial intelligence. More details can be found here

AfriSenti – a shared task competition for African languages

To promote natural language processing (NLP) research for African languages, a shared task competition has been launched. Afrisenti-SemEval is based on a collection of Twitter datasets in 14 African languages for sentiment classification. You can find out more about the three different tasks that form the competition, and how to get involved, 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:


Related posts :



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

Abeba covers biases in data, the downstream impact on AI systems and our daily lives, how researchers are tackling the problem, and more.
21 November 2024, by

Dynamic faceted search: from haystack to highlight

The authors develop and compare three distinct methods for dynamic facet generation (DFG).
20 November 2024, by , and

Identification of hazardous areas for priority landmine clearance: AI for humanitarian mine action

In close collaboration with the UN and local NGOs, we co-develop an interpretable predictive tool to identify hazardous clusters of landmines.
19 November 2024, by

On the Road to Gundag(AI): Ensuring rural communities benefit from the AI revolution

We need to help regional small businesses benefit from AI while avoiding the harmful aspects.
18 November 2024, by

Making it easier to verify an AI model’s responses

By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.
15 November 2024, by




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association