ΑΙhub.org
 

Focus on affordable and clean energy: call for contributions


by
09 July 2021



share this:

We are launching the next topic in our focus series on the UN sustainable development goals (SDGs). In August we will start publishing posts relating the goal of “affordable and clean energy”, which is SDG number 7 on the UN list.

AIhub focus issue on affordable and clean energy

Would you like to get involved?

We are looking for researchers, users and stakeholders to write, or talk, about their work. If you are interested in communicating your research efforts to a wider audience then please do get in touch. Likewise, if you would like to make recommendations for people or specific topics we should feature, just send us an email.

The UN’s aim with this goal is to ensure access to affordable, reliable, sustainable and modern energy for all. In this focus issue we’ll be considering any AI work, or opinion and discussion pieces, relating to these topics.

The deadline for contributions is 15 August 2021.

About the UN Sustainable Development Goals

The Sustainable Development Goals (SDGs) are a collection of 17 interlinked goals designed to be a “blueprint to achieve a better and more sustainable future for all”. The SDGs were set in 2015 by the United Nations General Assembly and are intended to be achieved by the year 2030.

The 17 SDGs are: (1) No Poverty, (2) Zero Hunger, (3) Good Health and Well-being, (4) Quality Education, (5) Gender Equality, (6) Clean Water and Sanitation, (7) Affordable and Clean Energy, (8) Decent Work and Economic Growth, (9) Industry, Innovation and Infrastructure, (10) Reducing Inequality, (11) Sustainable Cities and Communities, (12) Responsible Consumption and Production, (13) Climate Action, (14) Life Below Water, (15) Life On Land, (16) Peace, Justice, and Strong Institutions, (17) Partnerships for the Goals.

The world bank have created a series of interactive visualisations to display some key measures relating to each SDG. See the one for affordable and clean energy here. Access the whole series here.

Read articles on our previously featured topics

Good health and well-being
Climate action
Quality education
Life below water
Reduced inequalities



tags: ,


AIhub is dedicated to free high-quality information about AI.
AIhub is dedicated to free high-quality information about AI.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

When AI art has no author: Study finds generated images often can’t be traced to training data

  14 Sep 2026
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

AI in nature conservation: powerful tool or dangerous shortcut?

  11 Sep 2026
AI provides opportunity for future biodiversity conservation but introduces risks .

Improving the process for large-scale recommender systems: an interview with Haruka Kiyohara

  10 Sep 2026
Credit-assigned policy gradient for early stage retrieval in two-stage ranking.

The Machine Ethics podcast: Data Collective with E.M. Lewis-Jong

Ben chats to E.M. Lewis-Jong about the promise of AI and making human connection easier, speech recognition and supporting linguistic diversity, making useful technologies that have a purpose, and more.

AI for ethology: an interview with Isla Duporge

  08 Sep 2026
Deep learning is becoming a powerful tool for understanding animal behaviour and tracking populations.

AI in cardiology: The path to practical application carries risks

  07 Sep 2026
Can artificial intelligence help us better combat cardiovascular diseases? Legal researcher Hannah van Kolfschooten urges caution, as there are still many legal issues that need to be resolved.

AI-powered camera system offers low-cost way to monitor bumblebees

  04 Sep 2026
Researchers have developed a semi-automated method that uses remote cameras to survey bumblebees and potentially other insects.

Interview with Noah Golowich – theoretical foundations for learning in games and dynamic environments

  03 Sep 2026
Noah Golowich tells us about his research into the theory of decision making and learning in games, which have applications in Multi-Agent Reinforcement Learning.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence