Opportunities and challenges through the use of AI in the environmental sector

One of the key global challenges is the climate crisis. It has been with us for some time and is manifested, among other things, in the increase in climate-related extreme weather events. Even in Germany, we are not spared extreme storms, floods and heatwaves, which lead to interruptions in energy and water supplies, for example. Politicians in Germany recognised the importance of this issue several years ago and numerous initiatives and funding programmes have been launched since then. As already described in my colleague Sascha Tash's blog post on "AI in environmental protection - an overview of how it works and application scenarios", AI could help us tackle the climate crisis in the long term, but what specific opportunities and challenges does this present?

Opportunities in the context of environmental protection

A great opportunity to counter the effects of the climate crisis in Germany through AI lies in the reliable forecasting or prediction of environmental events. For example, AI systems can be used to improve early warning systems for extreme weather events, which can significantly reduce negative social, ecological and economic impacts. For example, the timely prediction of a developing forest fire can prevent the destruction of the habitat of many species. In addition, human lives can also be saved by preventing or containing a forest fire.

In this context, various professional groups can be usefully supported by AI systems. For example, helpers in disaster and civil protection can obtain a better picture of the situation and make more efficient decisions during time-critical operations. In addition, farmers can work more efficiently and conserve resources overall with the help of comprehensive AI systems through precision farming and, for example, concentrate on other, non-AI-supported areas of their work using GPS-controlled field robots that take over the harvest.

In addition, it can be observed that many AI systems in various application areas, such as fertilisation and irrigation of plants in the context of smart agriculture and forestry, aim to significantly reduce energy and resource consumption, which in turn contributes to achieving sustainability goals in terms of reducing greenhouse gas emissions and air and water pollution.

As with other digitalisation technologies, the use of AI systems is creating new professional fields and jobs that deal with the research, development, implementation and operation of AI systems. This is particularly clear in light of the German government's AI strategy, which is already actively endeavouring to train skilled workers in this field and make the occupational field more attractive overall.

Overall, it can be said that AI systems offer numerous opportunities for our society in general and for the environment in particular in connection with tackling the

If you would like to find out more about possible application scenarios for AI in the public sector, you are welcome to take a look at our website on the topic of "AI in the public sector: possible applications in everyday public administration".

Challenges for the economy and society

Even if many AI systems in the environmental sector are designed to conserve energy and resources, it should not be neglected that AI requires correspondingly high computing power for the rapid evaluation of large amounts of data, which in turn can lead to high energy and resource consumption in AI data centres. This aspect is already recognised at all levels and is being addressed, for example, in the federal government's Green IT initiative launched by the BMUV. The aim is to reduce the energy consumption of the federal administration through improved energy efficiency, ensure the procurement of sustainable information and communication technology and provide annual monitoring of the energy consumption data of federal IT. My colleague Lynn Nguyen has already shed more light on this in her blog post: Green IT: sustainability in public administration. adesso supports the office of this initiative as a project management partner for the entire duration of the project and is responsible for the annual data collection and analysis of the federal government's ICT energy consumption. We are also responsible for assessing the current status of implementation of the Blue Angel criteria in the federal administration's data centres.

Another challenge is the potentially high cost of developing and implementing AI systems. Depending on the individuality and complexity of the system, costs can arise that are not affordable for smaller authorities or private aid organisations. Policy initiatives and funding may enable organisations with smaller budgets to use AI, but this will not be possible in all cases.

In the context of the costs involved in deploying an AI system, the large amount of training data required should not be overlooked. AI initially requires a very large amount of data in order to be able to make reliable predictions and decisions. For example, when predicting extreme weather events, historical and current data from satellite images, weather stations and other sources must be accessed, which can be very costly.

Just as the use of AI systems offers society the opportunity for new jobs, it can also trigger fears of job losses. Individuals and entire occupational groups could fear being replaced by AI or not being able to keep pace with the necessary adjustments to occupational fields. The development, construction and use of AI systems will therefore require appropriate retraining or new training programmes, which will first have to be developed and established. Older members of society in particular could feel under pressure as a result.

Finally, it will be a challenge to consider AI in terms of digital ethics and to introduce appropriate regulations. The United Nations' AI ethics treaty and the German government's AI strategy already address the challenges and risks arising from the use of AI for our society to some extent. Issues such as avoiding discrimination, protecting privacy, data protection and much more must be comprehensively developed and enforced for business and society in order to create or maintain trust in the technology.

Conclusion

AI applications are already being used successfully in disaster and civil protection, agriculture and forestry and other areas of application and are being actively promoted by politicians to help tackle climate change. Companies are also increasingly focussing on the potential applications and concrete implementation of AI. Nevertheless, the challenges described above, such as the high consumption of energy and resources and society's fears of job losses, must not be neglected. We must continue to address the issue and both politics and business must create a targeted awareness of the opportunities and progress of AI in the environmental sector. By developing values, principles and rules for both companies and private individuals, a transparent and responsible approach to AI can be ensured. In the future, we will encounter the use of AI systems more and more frequently in both our professional and private lives, so a willingness to engage with new technologies is essential. This is the only way we can use our knowledge and experience to optimise existing AI systems and also develop and implement further possible applications to protect and preserve our planet.

You can find out more about exciting topics from the world of adesso in our previous blog posts.

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