Did you know that your sentence structure, use of emojis, speed of keystrokes or choice of words reveals your age group and gender? No? Well, they do. And now is the software AiBA, which manage to identify potential harmful conversations within 20 chat messages, on its way to the market.

By Anja Lillerud, May 1, 2022

Cyber grooming is a major threat to children and youths on the Internet. By impersonating young people through fake online accounts, adults reach out to kids and teenagers on chat and gaming platforms with the intention of making friends with them. Over time they build a trust-based relationship with the children before it turns in to a living nightmare for the young ones.

– The cyber groomers’ purpose is to encourage the kids to send sexualized pictures and nudes of themselves. If they receive any, they demand more. After massive pressure and threats of spread, and in despair to try to avoid the nude photos going viral many young people send new pictures to please the groomer, tells Hege Tokerud, CEO and co-founder of AiBA.

Some relationships escalate because cyber groomers manage to persuade the kids and teenagers to meet in person. Such encounters very often lead to physically sexual assaults.

A proactive solution

By using AI, AiBA trains algorithms to detect potential cyber grooming conversations at an early stage when a connection on a gaming or chat platform where the AiBA solution is implemented, is established. If one is identified, the software alerts the platform owners to make them aware that measures ought to be done.

To ensure the reliability and that correct measures are taken, a human resource is verifying the warning before measures are activated.

– What makes AiBA unique, is the proactive approach to the problem. Our goal is to stop grooming as soon as possible when a relationship to a child is established. Earlier we could detect and identify cyber grooming within 40 chat messages. Now we can do it in less than 20, explains Tokerud.

Expert in behavioural biometrics

Behind the technology presented in AiBA, hides the result of years of research on behavioural biometrics. Structure of sentences, use of emojis, speed and rhythm of keystrokes, and choice of words are elements related to age and gender.

Professor and researcher at Norwegian University of Science and Technology (NTNU), Patrick Bours, is an expert in continuous analysis and behavioural biometrics and had the idea of commercialising the research results.

The technological implementation is done by Inmeta, a Norwegian consulting company in Crayon group, specialized in digital and data driven innovation. The company has more than 200 advisors and consultants based in Oslo, Trondheim, Hamar and Bergen:

– When Hege contacted us for a collaboration on developing the technology needed to realize the AiBA project, there was no doubt. We wanted in! This is a kind of project that matters, and Inmeta want to make footprints, says Henrik Slettene, Manager AI and Machine Learning in Inmeta.

Over the last 7 years Inmeta has delivered 150 machine learning projects to more than 50 companies in both private and public sector. With 25 dedicated data scientists and business advisors focusing solely on the Artificial Intelligence domain, Inmeta addresses the complete value chain including strategy development, data platforms, data science and analytical model development, AI operationalization and business change and development.

No legislation in Europe

Access to behavioural biometric data is crucial to be able to train the AiBA algorithm to detect and identify cyber groomers. Paradoxically, lack of data is one of the major challenges the project faces.

– We experience that some gaming enterprises are reluctant to involve in AiBA because they fear to get linked to cyber grooming in a negative way. Still, everyone acknowledges that cyber grooming is a big and growing problem, and we urge the industry to change their approach to the subject, says Tokerud.

In the United States, the industry is regulated by a law obliging the companies to secure their users. A similar legislation has been attempted to be introduced in the EU without success. The industry argue that the legislation will be too resource-intensive to comply with and hence, it will be a dormant legislation.

– But now we have a solution, Tokerud points out.

– Your children are safe with us

Two global gaming companies targeting children and youths are pilots in the AiBA project. They are going to implement the software, test it on their game platforms and give valuable feedback to improve the product.

– They think the other way around regarding the company’s name being related to cyber grooming. It is important to them to communicate to parents worldwide that “your children are safe on our platforms”, says Tokerud.

The efforts from the two pilots are crucial to train and improve the AiBA algorithm. In addition, the project also have a collaboration with the Norwegian police to discover if the software can be used to detect cyber grooming conversations in ongoing investigations.

– Developing a software like this is extremely demanding and challenging and a never-ending task. Someone will always try to find a way to fool the system putting us in constantly need of data from authentic chat logs, explains Slettene.

Patrick Bours is attending the AI+ conference together with data scientist Saghar Asadi from Inmeta and they will talk more about the research and technology behind AiBA.

In the coming years – few or many – AI (Artificial Intelligence) will affect us on a daily basis. Just how and to which extent is difficult to say, but areas such as transport, city planning, and decision-making are certain to benefit from artificial intelligence.

By Lars Martin Johannessen, April 29, 2022

In the upcoming future, the green and efficient future, we can no longer afford to be wasteful when it comes to energy. We can no longer afford to be wasteful when it comes to food. We can no longer be wasteful when it comes to nature. We can no longer be wasteful. In this context, we cannot afford any more bad choices. History books will reflect on our time as either a turning point, or a tipping point. What we do in the coming years could be era defining for humanity. Success or failure in the short terms. This obviously will not happen on its own. Research, demanding work, and most important, decisions will generate our outcome.

Decisions to go green, to capture carbon, investment in holistic solutions for a better future for all. Though decisions. So, who will have the guts and the knowledge to firmly stand behind their decision or choice, knowing that it represents either rescue or catastrophe? Because we can no longer afford the wrong answers to our problems. This is where any decision maker would be a lot more comfortable knowing that the choice they are making is the right one, obviously. Artificial intelligence proposes a solution here. Let it do the math, calculate the outcomes, describe the scenarios related to the different options. Here is your blueprint, this is how you save the world, this is how you destroy it.

Democracy or technology?

Perhaps the notion that AI could give us all the answers we need is somewhat utopian in nature. There are several questions related to how something like this would be implemented and put to use. The aspect of relinquishing power and responsibility to software is also highly debatable from a human point of view. Then there is the issue with so called black box AIs. Many would argue that transparency in decisions is a key aspect of any solid democracy. A software that produces answers and solutions without explaining its work and processes may deter people from embracing it.

There are ongoing projects who set out to solve this issue, displaying how artificial intelligence uses data to determine and find the best outcome. Yet, there is still the feeling that technology is evolving faster than our collective comprehension of it. The merging of software and politics will be controversial, and it should be. The percentage of people who fully understand AI and its ramifications are borderline insignificant compared to the overall population. This is in its own a democratic issue of immense importance.

I had to look this up.

He who designs, rules?

There are also questions related to abuse – how are we sure that the AI is programmed to benefit you and me, and not the owners who made it? In today’s volatile misinformation landscape, would we know if someone managed to tamper with the databases used in the decision-making process, or somehow alter the outcome in one way or another? Then again, the democracy we see in civilized societies around the world is not without fault, abuse, or corruption either. The question is most likely how we build an artificial intelligence that is incorruptible, which doesn’t inherit the bias from its creators.

If and when we manage that, the arguments against merging AI and democracy are rapidly decaying. The fact probably is that we can’t afford to let lack of knowledge in the general population hinder us from taking advantage of a tool which potentially could help solve some of our greatest challenges. There is good reason to believe that the future will be supported by artificial intelligence in terms of augmented decision-making. We are pressed on time, we are pressed on getting it right, and this might be the window of opportunity that artificial intelligence needs to merge into our lives.

With revenue that has been increasing for 20 years, Eye-share AS has found the solution on how to meet customer demands.

By Anja Lillerud, April 22, 2022

When being responsible for the daily income and expenses of a company, you depend on having total control of and knowing the causality of the figures presented to you.

Eye-share’s portfolio of three main products is designed to meet economical professionals’ demands for a more efficient way of working without compromising accuracy. The eye-share Capture solution is an Optical Character Recognition (OCR) system enabling automatic data extraction by digitizing text from documents from sources such as paper, image and PDF files. Eye-share Workflow solution offers a complete automated Purchase-to-Pay solution giving full overview and control through a user-friendly and cloud-based software platform. The eye-share Portal solution is a supplier portal for better collaboration between the buyer and the supplier through digital interaction in the purchasing process.

20 years of progress

To be able to solve these challenges that unstructured, unavailable data represents to important economy fundtions, Eye-share has since 2001 been working closely with their costumers to improve their products and the technology behind – and succeeded in doing so.

– The company has experienced great growth over the past years with increased revenues and a lot of development potential, and last year we were awarded the Gazelle award for the second time. With more than 100 employees Eye-share has both national and international enterprises in the portfolio which we are very proud of, says Kai-Ronny Mydland, R&D Director at Eye-share.

A significant Eye-share customer is NorgesGruppen, one of Norway’s leading trading houses within retail, with more than 20.000 inbound invoices per day and an automation degree of 90 percent. A perfect example of an enterprise committing to automation and how crucial the accuracy and reliability of technology is when handling many transactions within a short time frame.

There is no room for failure.

From black box to “glass box”

The key factor in developing a reliable AI-software and building a trust-based relationship with the end user, is by enabling explainable artificial intelligence (XAI). XAI brings the traditional AI technology from a black box perspective without the possibility to verify the result, to a transparent level which allows the user to control and validate the results both during and after the process, which instils trust, efficiency, and reliability.

– XAI shows you the connections and choices made along the way, which are the reasoning behind the result. In our experience this enables the enterprises to outline their financial resources in a better way since they adopt to the AI solution much faster. Trust is key, if they do not trust the outcome and the results from the AI processing, they will stick to manually maintaining rules for as long as they can, explains Mydland.

The black box technology is often subject of great debate regarding trust and reliability. The AI process finds all its answers in the data, but how do you know if you can trust the results presented to you? With XAI the user is given insight and control.

– Different opinions regarding AI

The Eye-share software suite is a designed to support the financial business role. Automation has always been important. Despite technological changes and opportunities in new technology, the company experiences that one of the biggest jobs now is to convince the customers of the benefits using artificial intelligence and help them adopt the technology in their company.

– When meeting the market, we encounter different opinions regarding AI. For many, it is difficult to let go of hands-on control and have confidence in technology and the software. By showing them how we use XAI and our results, most companies realize how much they can benefit from the technology, says Mydland.

At the international conference AI+ in Halden 3-4 May, the Eye-share employed advisor and AI enthusiast Jan Erik Gausdal will be talking about XAI and the Eye-share software.

– We find it important to participate on arenas regarding AI and the use of this technology. AI+ is an interesting conference gathering both national and international actors in the industry and we are attending to discuss, learn, inform, and enlighten, says Kai-Ronny Mydland, R&D Director at Eye-share.

In his new book “AI for the Sustainable Development Goals” Henrik Skaug Sætra describes how AI can contribute to achieving the UN’s Sustainable Development Goals by 2030. But just as important: he argues that AI may also turn into sustainability’s – and society’s – worst enemy, if not handled right.

By Anja Lillerud, 29 March 2022

The world has gathered around the United Nation’s 17 Sustainable Development Goals (SDGs), aiming to achieve them by 2030.

The goals deal with issues such as justice, economic growth, climate, health, food and water, work and education, consumption and production, equality, clean energy, innovation, no poverty and zero hunger.

As a topic obtaining great interest around the world and having an increasing importance in most areas in the society, artificial intelligence (AI) is now often considered an important factor in accomplishing these goals.

But:

– AI is only a part of the solution, emphasizes author and professor Henrik Skaug Sætra.

He is an associate professor at the Faculty of Computer Science, Engineering and Economics at Østfold University College (ØUC), but on 1 April 2022, Sætra enters the position as leader for ØUC’s focus area “The digital society”.

In February, his book “AI for the Sustainable Development Goals” presenting both sides of how AI can and cannot contribute to fulfilling the SDGs, was published.

– Changes are needed

– I have tried to see the whole picture. Both advantages and disadvantages with the development and use of AI and which threats and challenges emerge with this technology, explains Sætra.

For example, AI algorithms can be trained and taught to help us develop systems and infrastructure to reduce greenhouse gas emissions. But that requires energy; hence the use of AI also causes greenhouse gas emissions.

So, how do we know whether AI gains the sustainability or not?

Sætra gives some answers in his book by presenting the obvious consequences and the positive potentials for each of the 17 SDGs, aiming to make his readers understand why the solution to achieve the UN’s sustainability development goals cannot be AI alone.

– We need to change the industry’s infrastructure. Today big data is disproportionately accessible to a few major stakeholders, such as Google, Apple, Facebook, Amazon, and Microsoft. That conflicts with several of the SDGs saying the data should be universal, available, and not too expensive so even poor countries are able to develop their own technology and use this in a beneficial manner, Sætra says.

– Must be used right

Working on the book and as an employee at ØUC, the author and professor has concluded that the world is unlikely to have fully achieved the SDGs by 2030. The latest UN climate repost published in March 2022, shows that if we continue as we do today, we will not even be close to reaching them.

– Together with political determination and power of action, resources and funds, sensible use of AI can be a crucial part of the solution. If the technology is not being used right, it may instead complicate the transformation required. I am not convinced the world society will be able to make all the changes described in UN’s 17 sustainable development goals because they are so ambitious, says Sætra.

He finds it important and useful to highlight such complex and elaborate field of expertise through a conference such as AI+.

– At this conference you gather politicians, professionals, investors, stakeholders, and others who are interested in the topic and users of the technology. The politicians representing the citizens need to know how to use and regulate AI, the developers need to know how to create useful and reliable technology, and those who implement the technology in their business need to know what questions to ask to implement and use the right type of AI, says Henrik Skaug Sætra.

NOTE: Henrik Skaug Sætra is one of the speakers at AI+ 2022.

Used correctly and in the right circumstances, artificial intelligence has the power to help businesses in the private sector as well as the public sector become more efficient and most importantly; more sustainable.

By Research Director at Institute for Energy Technology Tomas Nordlander and journalist Mari Kristine Buckholm

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The history of artificial intelligence (AI) goes back to the Dartmouth Conference in New Hampshire in the summer of 1956. That is when the word was first coined. The conference gathered some of the key researchers in the United States, who were computer scientists, to look at the potential of the computer. The researchers had already started looking into making the computer intelligent before that, but the Dartmouth Conference is considered to be the founding event of artificial intelligent as a field.

From that time until now, we have had AI winters and AI springs. Every time there is an AI spring, like 1956, we have a lot of funds coming in. Several companies put a lot of money in, and a lot of promises as well, but some of these promises are not realistic. For example, in 1956, they were talking about the autonomous car and the universal translator, and it was promised to be ready in 10-15 years. But, as we all know, 15 years later there were no autonomous cars.

What happens next is that people get disappointed when AI does not deliver, and almost all the funding stops. A lot of good researchers leave the field and move to other fields. So, every time the AI winter comes, we lose a lot of excellent AI researchers.

Then the spring comes again, because someone has gotten a breakthrough, and the funding comes back. Also, every time we have an AI spring, the charlatans show up as well. People who do not really have AI experience, capabilities or AI products come because there is a lot of money involved. They also make promises, which lead to disappointment – and affect the AI hype.

The lasting AI spring

Today, we are in the middle of an AI spring, but there are still some cold winds. The difference this time, compared to previous AI springs that have turned into winter, is that we have available data from Internet-of-Things (IoT), we have mature algorithms, and we have processing power in the cloud. All this makes the current AI spring unique, and I think it is here to stay. With that said, there will be a lot of disappointments as well, where people are promised gold, but get coal in return.

This is why it is important to remember the history of AI. When I bump into young people around 25-35 years old, they tend to think that AI is only about deep neural network and that everything written about AI that is older than 10 years, is irrelevant. That is a huge mistake. You might think that the autonomous vehicle came from the DARPA (Defense Advanced Research Projects Agency) Grand Challenge or Tesla, but in the 1980s there were autonomous Mercedes Benz cars driving on the highways of France, Germany and Denmark, using AI.

We had cars driving autonomously already in the 80s and people do not know. We have so much more to learn from the history of AI, but people are too short-sighted back in time. Some of the most relevant research papers are not as young as five years old; they might in fact be 20-40 years old.

Hence, if you wish to focus on AI, do not ignore research and results of AI that is older than 5-10 years. You will only do yourself a disfavor and create more work than you need to do.

Definitions of AI

Through the years, there have been many attempts to define what artificial intelligence is. The simplest and most common definition, but a problematic one, is “intelligence demonstrated by machines and software”. The problem is that we do not have a universally agreed upon definition of the word intelligence. If you and I have two different views of what intelligence is, it means we would also have two different views of artificial intelligence.

Therefore, a more comprehensive definition that does not contain the word intelligence would be better: “Machines and software that try to achieve a goal or solve a problem in a changing environment using reasoning, memory, planning, scheduling.” That is artificial intelligence.

Machine learning, on the other hand, is a group of AI techniques (some statistical techniques also belong under the machine learning umbrella). It enables a system to automatically learn and progress from experience without being explicitly programmed.

The most important reason why people and companies should have competence within AI today, is that AI has the potential to help with digitalization. For the Institute for Energy Technology (IFE), digitalization means how organizations use digital technology to enable them to do more with less effort and get it done quicker, safer, and cheaper. If AI can help with that, you will get a competitive advantage compared to those who do not utilize it. Basically, it is about staying in the game and being competitive.

It is also necessary to remember that AI might not always be the solution. There are some problems where people apply AI, when other techniques like statistics or mathematical modelling are way better. I have seen instances where people choose to apply AI to a problem simply because it attracts funding, but they end up using the wrong technique to the problem. They would have had a much more efficient solution if they used mathematical modelling instead.

Nevertheless, used correctly and in the right circumstances, AI has the power to help a large number of businesses in the private sector as well as the public sector become more efficient and most importantly; more sustainable.

When is AI the solution?

We have several examples of smart use of AI in the Cluster for Applied AI. Many of our cluster members already utilize artificial intelligence in a way that is both efficient and environmentally friendly. In the following, I will present the most relevant cases.

At IFE, we produce medicine for prostate cancer. It is a radioactive medicine that is given intravenously to patients, but it has a half-life of two weeks. This means that from we produce it, we have two weeks to give it to the patients, otherwise it does not work. We deliver this medicine from our facility at Kjeller to the entire world, and it must reach the patients, wherever they are, within two weeks. The medicine is kept in a vial and we need to identify if there are dust or particles that make it necessary to discard it.

Previously, this was done manually by people looking at and shaking them against light to check. First of all, they would get a small dose of radiation, which is not dangerous, but not great either. Secondly, it is hard for the human eye to detect these particles. Now, we have project where we use a robot hand to shake the vials and we use machine vision with AI to identify the particles, which can do the job faster, more accurate, and safer than humans, which means better medicine reach the patient faster.

A second example is that of eSmart Systems. The software company uses AI to detect maintenance needs on the masts of power lines. Previously, when you were inspecting powerlines, you would rent a helicopter and fly along the power lines with a camera and/or binoculars to try to identify what might be broken. This is traditionally known as one of the more dangerous helicopter trips that you can take. There is always high risk involved when working close to power lines, but this method also has a high carbon footprint.

eSmart Systems’ solution is to use drones to inspect instead. These drones can be autonomous or controlled by man and are equipped with a camera connected to artificial intelligence which analyses the power lines and masts in real-time. This means that the operator will know exactly which mast to go to, what tools and parts to bring, and which error to climb up and fix. The AI has been fed with a broad spectrum of images showing all different kinds of masts and potential errors and trained to detect and identify all types of errors. It can recognize and analyze 200 000 images in one hour, whereas a human being would need one year to analyze 100 000 images.

Before, the utilities left a big carbon footprint, there was more risk involved with the helicopter, it was more expensive, and they still did not get as accurate information.

The third example from the cluster is Husqvarna’s production of saw blades for chain saws in Sarpsborg, Norway. They are interested in AI to look at the quality early in the production line. Very often, if there is a mistake early in the production line, they want to detect it as quick as possible. Because when you build a product and it is faulty early on, but you do not know, you invest more money and time building things on top of it. In the end, after spending a lot of time and resources, you find out it does not hold the standard and must throw it away.

Husqvarna wishes to know early in the process if the tolerance, width and height of the product is perfect. If it is not, they will discard it early on. Hence, the company uses AI to detect faults early in the production process, so that they do not invest or use resources unnecessary.

A fourth example is predictive maintenance. Here, IFE has been using AI techniques since the 1980s to assist in safety critical industries. We predict when failure will occur (based on sensor inputs such as vibrations, sound, and electrical profile used) which allow for optimal selection of time to do maintenance. For example, predictive maintenance is used on large water pumps for nuclear installation.

From the public sector, the most relevant examples of smart, and in some cases lifesaving, use of AI are within healthcare. For example, AI can be used to predict breast cancer and help identify tumors. It can analyze databases of people’s medical records to identify pre-diabetics, so that measures can be made and medicine given to prevent them from ever becoming diabetic. Of course, today we have laws and regulations that prevent the sharing of medical records, but these things could be evaluated against how much it is worth.

AI can also be used to analyze what some schools are doing correctly in terms of teaching and learning compared to other schools, or to make sure that elderly can stay at home as long as possible with the help of smart sensors.

AI in the future

To sum up, there are many ways that AI can help both private businesses and entire sectors, including the public sector, to become both more efficient and more sustainable. As discussed, AI is nothing new. The reason why AI is in the wind again, seemingly for good this time, and has become a popular buzzword all over the world, has a combined explanation.

Every time there has been an AI spring, it is because one of the AI techniques has made significant progress. In the 1980s, it was a so-called expert system (computer program that emulates the decision-making ability of a human expert) that suddenly started being able to handle industrial problems which gave the industry a huge benefit. Thus, the AI spring blossomed, before it became winter once again.

What initiated the current AI spring, is neural networks and the progress we have made within that field. A neural network model is originally inspired in design by the human brain (but it is not an artificial brain) and is programmed to recognize patterns. We have managed to, in several different areas, use neural networks with a higher degree of accuracy than humans. For example, a neural network can learn how to play chess against itself and get better and better, until it is better than any human chess player.

Even though we have had great success with neural networks, the focus should shift to other AI techniques as well – which could work very well with neural networks. Because AI is much more than machine learning. The latter has the downside that it is “black box”, which means that we cannot see how the knowledge is represented in the AI model. But a big part of AI techniques and algorithms are “white box”, that people have forgotten a little bit about, where you can actually explain the reasoning for everything. In the future, the important thing will be to combine them.

Going forward, everyone should to gain more knowledge about AI. Attending courses is one thing, but what we really need, are initiatives like Siva’s Catapult centers and Cluster for Applied AI, where people and companies can connect, ask questions, test products, share knowledge and experience, and establish collaborations.

If we succeed in creating such a national AI team and work together instead of competing against each other, we will be able to create value within our own borders and become a force to reckon with internationally as the world enters the AI age.

Together, Smart Innovation Norway, Institute for Energy Technology, eSmart Systems, and Halden Municipality have created a leading conference on applied artificial intelligence, AI+. The goal is increased knowledge of the technology’s value and more green jobs.

By Mari Kristine Buckholm, 23 March 2021

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“Artificial intelligence (AI) is an enabling technology with an enormous potential to make existing processes more efficient, contribute to the development of innovative solutions and products, and to contribute to more sustainable development. Nevertheless, it is still an area where many people feel that they lack knowledge of what is possible. Therefore, our community wants to contribute to increased value creation by making the technology better known to more players,” says Marianne Jansson Bjerkman.

She leads the Cluster for Applied AI network, which is managed by Smart Innovation Norway. The cluster is co-host of the digital conference AI+ together with Smart Innovation Norway and the cluster partners Institute for Energy Technology (IFE), eSmart Systems and Halden municipality.

Together with Østfold University College, these actors form the unique AI community in Halden, an open competence environment that collaborates across sectors and complements each other seamlessly.

Leading the way in Norway

“It is important to have a national artificial intelligence community. In Halden, we have companies that are so strong in this area that it is important to lead the way. The intention is to connect a large network and get more attention around what we are doing, and also more opportunities,” comments Knut Johansen, CEO of software company eSmart Systems.

He explains how the initiators of the conference contribute and complement each other as follows:

• Smart Innovation Norway is incredibly important in managing the conference and making it work professionally through its network and cluster initiative Cluster for Applied AI.
• IFE has been involved in applied research for many years and has a network of energy companies and organizations in countless countries, which is essential in this setting.
• eSmart Systems brings in the industrial business part. The company is out in the market with its applications, taking it from applied research and into reality.
• Halden municipality has been a strong supporter in all these activities. The municipality has been the first to adopt new solutions from the AI community and serves as an important testing arena.

40 years with AI

Dr. Tomas Nordlander, Research Director at IFE, points out that the Halden environment’s AI strengths are not only about competence and long experience in the field, but rather that the businesses have had a uniquely solid cooperation over many years.

“It is the multiplayer. We have several organizations that have been working within artificial intelligence and applied artificial intelligence for almost 40 years. IFE was one of the few organizations in the world that started implementing AI solutions in safety-critical industries, such as oil, gas and nuclear power plants, almost 40 years ago,” he says.

During AI+, IFE contributes with expertise from many areas of artificial intelligence, including knowledge of the development and implementation of applied AI. In addition, IFE can assist with knowledge boost on AI and opportunities for both local and national companies.

“We are also deeply involved in national AI strategies and advisors for private and public investment organizations,” notes Dr. Nordlander.

A forward-leaning municipality

For Halden municipality, AI+ is an important step towards fulfilling the vision of the community plan for 2018-2050, which points to three main challenges that need to be solved.

The first is about creating new jobs in Halden at the same time as more people become employed. Number two is about increasing the level of education of citizens while also preventing young people from dropping out of school. The third and final is about the climate challenge that the whole society must contribute to solving.

“As a municipality, we are facilitators and a driving force for the success of businesses and academia in Halden. We believe that the AI+ initiative can help us solve all three of our main challenges, and especially the first. At the same time, Halden aims to be Norway’s most innovative municipality, and this is a good fit,” says Jens-Petter Berget, Head of Department for Community Development in Halden municipality. He adds:

“It is nothing but fantastic to have this competence environment in our municipality!”

For useful and good purposes

The research and innovation company Smart Innovation Norway exists with the purpose of creating green jobs and helping to solve the climate crisis.

“We are working to leverage technology and ensure that it is used to solve societal problems and create jobs. That is exactly what AI+ does. The conference aims to disseminate information about the technology, show what opportunities it provides and how this can help create sustainable jobs. AI is like all other technologies; it can be used for good purposes and less good purposes. It is the useful and good application of artificial intelligence that we want to spread through the conference,” explains Kjell Reidar Mydske, CEO of Smart Innovation Norway.

AI+ will be held for the second time on 19-20 May 2021 and the ambition is to make the initiative an annual, magnificent event in Halden. The following day, Friday 21 May, an academic sister conference organized by Østfold University College and IFE, called ICAPAI, will be held – targeting those who have more professional interests in artificial intelligence.

When AI+ 2021 was held on Wednesday and Thursday last week, it was with a varied and highly relevant program full of quality speakers. First up was Norway’s Prime Minister.

By Mari Kristine Buckholm, 25 May 2021

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“Data and artificial intelligence will be important for solving the challenges of the future. Therefore, I am pleased that this ambitious conference can be held even if we are in the midst of a pandemic. But AI is also important to combat the pandemic. Over the next two days, you will discuss topics that will shape society in the years to come. I hope you get an interesting and productive conference!”

This is what the Prime Minister of Norway, Erna Solberg, told participants from both Norway and abroad when she opened AI+ 2021 on Wednesday morning.

Changed view of AI

The conference was organized for the second time on 19 and 20 May and the goal was to offer both Norwegian and international environments and companies a competence and collaboration arena within applied artificial intelligence (AI), which will lay a solid foundation for succeeding with data-driven economy and innovation in the future.

The digital event was broadcast from the Simulation Centre in Halden and led by journalist, meeting leader and writer, Ruth Astrid Sæter.

“I have to say that being allowed to lead AI+ 2021 has been incredibly instructive. I knew very little about applied artificial intelligence before this. Now I have learned a little more, and I also see that there are many areas that need to work more together – both to accelerate development, but also to make sure that all the important considerations are taken,” Sæter comments after the end of the conference.

This year’s conference host admits her views on what artificial intelligence is and how the technology can be used have changed after hearing varied presentations from universities, research firms, big tech companies and small startups over the course of two days.

“That notion of ‘God, are we letting the machines take over?’ is not there as much anymore. I’m excited about when the algorithms get so smart that they’ve detected everything, what kind of acceleration will we see?”, she asks.

“Clean air for everyone”

Business developer at the startup AirMont, Ole Gabrielsen, was among the companies that pitched their solution and use of artificial intelligence for the digital audience. In addition, he participated in the panel debate on day 2.

“The conference provides the opportunity to make contacts. Since it is digital, it gets a little harder, but you are also inspired to check out new things. When you hear what Oda (formerly Kolonial.no) says about their experiences and what the Norwegian School of Economics says about innovation models, it is very useful input for us. As a new startup, we do not get this anywhere else. It is crucial to be part of such an environment early on,” says Gabrielsen.

• See the full program

AirMont’s vision is “clean air for everyone” and the company aims to ensure better air quality using artificial intelligence and sensor technology. The first product on the market is chimney sensors with a built-in digital system that will be rolled out to all households with chimneys in Halden municipality during the fall of 2021.

“The sensors use artificial intelligence to correlate research results and historical data. When collecting many datasets, such as the Norwegian Public Roads Administration, the municipality, the EU, weather and traffic data and sensor data from us, this data can be used to predict poor air quality using artificial intelligence. This would be impossible for a human being to do,” explains the business developer.

In the long term, Gabrielsen envisions that such predictions can be used to encourage residents use their fireplaces less during certain periods of time, as it is often smoke from chimneys that is the main cause of poor air quality in cities. An incentive may be, for example, that the inhabitants who do not use their fireplace, which will be possible to keep track of with the help of sensors, can get half price on the electricity during the relevant time period.

Microsoft offers aid

On the way there, however, a startup needs help, both with financing, good advice, and follow-up. Here is where giant Microsoft enters the picture. The technology company has massive expertise within digital systems and was broadly represented at the conference, both as a sponsor and partner in Cluster for Applied AI, but also as speaker and participant in the panel debate.

Izabela Hawrylko is Data&AI Solution Specialist at Microsoft and Microsoft Norway Startup Team Lead. She was Microsoft’s representative in the panel debate.

“What is most important for us is different perspectives. Being here and hearing from startups like AirMont allows us to think about how Microsoft can assist with resources and funding. By the size we have, I believe there is a responsibility to support businesses and academia. That’s why it’s important to attend conferences like this, talk to people and listen to what kind of challenges they have,” says Hawrylko.

She is concerned that there are too many people talking about artificial intelligence and wanting to test it out in their organization, without being willing to make the organizational changes required to succeed with new technological solutions.

“Technology is important, but you also need to be able to use the technology and change your organization so that you get the most out of the technology. There is no meaning in acquiring an innovative solution if you do not know how to use it or have a plan to use it. We see that artificial intelligence has been hyped up and used as a buzzword, and I hope that more companies eventually understand that one must also have a plan to adopt it,” she emphasizes.

Even bigger next year

Two of the initiators behind AI+ are Knut Johansen, CEO of eSmart Systems, and Dr. Tomas Nordlander, Research Director at the Department of Energy Technology (IFE). They were both very pleased with the implementation of this year’s digital conference and look forward to next year – which will hopefully be a physical event.

“AI+ has become a conference at the top international level. Those who participate get very good and useful input,” says Johansen.

“During the first conference this last fall, we learned a lot and we have had another conference now that have gone very well, but there is still a lot to improve. Hopefully, the third conference will be a physical event that is even bigger, and then we will have had two training rounds,” adds Nordlander with a smile.

AI+ was organized by Smart Innovation Norway, eSmart Systems, Institute for Energy Technology (IFE) and Halden Municipality, in collaboration with Cluster for Applied AI.