Jessica Schulz | 03/16/2021
Can artificial intelligence contribute to climate protection?
In February 2021, the German AI Association published a position paper on “How Artificial Intelligence can promote climate protection and sustainability”. It describes a seven-point plan that shows concrete steps to effectively contribute to climate protection with AI. The following article summarizes the position paper.
Click here for the original source: KIBV Climate Position Paper (German)
In order to achieve the urgently needed reductions in CO2 emissions, much hope is placed in artificial intelligence. Artificial intelligence has the potential to accelerate the development of new technologies, to make processes more efficient and thus more energy-saving, and to enable necessary decisions to be made at an early stage through accurate forecasts.
The AI Association sees great potential especially in the energy industry, agriculture and infrastructure, which is still largely untapped. In the energy sector, for example, AI can help to find optimal locations for renewable energies, to make them more efficient through accurate weather forecasts or to ensure their continued operation through AI-supported inspections. Above all, however, high potential is seen in the area of predictive maintenance, i.e. the regular monitoring of energy plants. The downtimes of wind power plants, for example, can be reduced by 50% through predictive maintenance.
In agriculture, artificial intelligence is already being used in agricultural robotics, weather forecasts or early warning systems for plant infections. But also there is still untapped potential that can be exploited.
The best-known use of AI is probably in the field of autonomous driving, but it is also already in use in the intelligent control of buildings or automated traffic control. Further developments and innovations are also necessary in order to be able to use the enormous savings potential.
The potential is enormous but there are obstacles as well. The AI Association currently struggles with the so-called “monopolization of data”. This means that necessary data is not collected (or not allowed to be collected) or existing data is not exchanged. However, qualitative and quantitative high-quality data are the prerequisite for the development of AI algorithms. If there is no data, no AI technology can be developed – the necessary algorithms arise from existing data and for this reason it cannot be separated. Certainly, it is inevitable that the data is used and processed in a GDPR-compliant manner – in this way, monopolization can be prevented and AI innovations promoted at the same time.
Furthermore, the legal situation regarding the use of artificial intelligence has not been clear to date; the best-known example is again the area of autonomous driving (keyword liability).
The German Association for AI has therefore developed a seven-point plan on what needs to be done in order to be able to use artificial intelligence efficiently for climate protection.
- Consistent collection of data
The consistent collection of data in all areas including the corresponding legal regulations.
- Public availability of data
Data relevant to climate protection must be available for public and companies have to be obliged to hand over data to public institutions.
- Cross-sectoral cooperation
The creation of an overarching platform for cooperation between research, nature conservation, public institutions and companies for sustainability projects.
- Sustainability rating of companies
Companies should be assessed in terms of their sustainability. If they fulfil these criteria, they should be given priority for funding and financing measures.
- Promotion of sustainable projects
Projects that contribute to reducing emissions or to achieving the two-degree target should be given priority in the allocation of funding.
- Promotion of innovation for climate protection through competitions
Innovations are needed to achieve the climate protection goals. These can be promoted through competitions.
- Minimizing negative impacts and rebound effects
The training of AI algorithms is often accompanied by high energy consumption. Guidelines are needed to weigh the benefits against the harms. In addition, rebound effects (too frequent or intensive use) should be avoided.
Artificial intelligence thus offers a great deal of untapped CO2-saving potential. Nevertheless, the long-term sustainable application of the technology is essential to enable an efficient contribution to climate protection. In addition, an awareness must be created that the development of AI also produces emissions and that methods of reduction must be developed for this as well.
With its position paper, the German AI Association provides a well-founded proposal on how the development of AI can be promoted short-term in order to contribute to climate protection as quickly as possible. This should clarify and emphasize the importance of AI in the area of climate protection in politics, business and media.
Excursus: About the German AI Association (KI Bundesverband e.V.)
According to its own information, the German AI Association (KI Bundesverband) represents AI entrepreneurs in politics, business and media. Its goal is to create a sustainable AI ecosystem in Germany and Europe. Further information on the AI Association can be found here: German AI Association (German Website)