NORA.startup webinar #15: Sustainable AI

Curious about sustainable AI? Join our next NORA.startup webinar, where we have invited Solve Sæbø, Professor in statistics and Prorector of education at the Norwegian University of Life Sciences, Laurence Habib - Professor/Chair of Department of Computer Science at OsloMet – Oslo Metropolitan University and Thomas Leira, Co-founder of to introduce and discuss sustainable AI and what we can do to make AI more sustainable. 

Register by following the link below:

Registrering for webinar 


What is sustainable AI? What does the concept sustainability mean for and in AI? Sustainable AI has recently emerged as an umbrella term relevant to a plethora of various topics, policy and industry, including AI and smart cities, green AI, AI and carbon emissions, AI and sustainable policies, AI and human rights (ethical, equality, inclusion, diversity), AI and economic sustainability, AI and environmental sustainability… the list goes on and on. Incorporating sustainability in AI brings many opportunities, yet also challenges. According to Solve Sæbø, 

“What we need is AI that is energy efficient, that learns quickly, preferably from little data. It should also be dynamically learning. We should to a large extent be able to manage biases and ethical/moral aspects, and we should also know the uncertainty associated with the decisions that AI makes for us”.

How can we make AI more sustainable, both in use and development, and where do we start? Join our next NORA.startup webinar, where we will take a deep dive into the dawn of sustainable AI, explore and unravel the concept, and discuss how AI can be a crucial tool and vehicle to ensure future sustainable development. 

Want to know more about sustainable AI? Read Solve Sæbø’s blog post on “How to make AI more sustainable”. We also recommend checking out and attending Sustainable AI, the first conference ever held on the topic! 



Solve Sæbø - Pro Rector of education and professor in statistics at the Norwegian University of Life Sciences. 
Solve Sæbø is Professor in statistics and Prorector of education at the Norwegian University of Life Sciences. After 20 years of statistical teaching and research Sæbø has grown a special interest in the statistical and algorithmic aspects human cognition, and how this can support and inspire, both human and artificial learning. Sæbø is also a representative in the National Committee for Agenda 2030 in the university sector in Norway, and he therefore also has special focus on sustainability issues in general and the technological divide in particular as an obstacle to reach the sustainability goals. More on this matter can be found at his blog on metacognition:

Laurence Habib - Professor/Chair of Department of Computer Science at OsloMet – Oslo Metropolitan University

Laurence Habib is a professor and currently the head of the department of Computer Science at OsloMet – Oslo Metropolitan University. She is also a Faculty Fellow at the School of Leadership Studies at Fielding Graduate University. She holds a business degree from EDHEC Business School, as well as an MSc and a PhD in Information Systems from the London School of Economics and Political Sciences (LSE). Her research interests includes domestic technologies, learning technologies and the universal design of technology. She is also a member of the Nordic Center for Sustainable and Trustworthy Artificial Intelligence.


Thomas Leira - Co-founder

Thomas Leira has 8 years of experience from business development and product management from various positions in Telenor, Telenor Digital, and DNV GL. For the past two years he’s helped co-found and build Vake, a company specialising within maritime domain awareness, using satellite sensors, data fusion and machine learning to verify all vessel movements, including those that are turning their mandatory trackers off. Vake’s vision is to make ocean activity safer and more transparent.


Illegal fishing, assets protection, and environmental crimes are maritime challenges faced by governments and businesses around the world. The vastness of the sea and the limited traceability of ships create large information gaps, adding to the complexity of these challenges. Satellite images could fill in some of the blanks, but the images are just as vast as the oceans themselves. To get actionable insights from this data is laborious work – this is where we come in.

We use machine learning to automatically detect ships in satellite images. The result of our sole maritime focus is in a specialized algorithm capable of generating training data. This makes us uniquely flexible in terms of dat a source, scalability, and the degree of human verification. Creating one-of-a kind maritime insight suited to your needs.

Read more about NORA.startup at, and don't forget to apply for membership if you meet the criteria.

Published May 14, 2021 5:44 PM - Last modified June 10, 2021 12:03 AM