Networking Session #50 AI and Environment: Sustainable Development | IGF 2023

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During the discussion, participants noted issues with the plug unexpectedly turning off, causing confusion. This raised concerns as the device should not turn off without the plug, creating uncertainty about its status and available positions.

Importantly, the value of having a teacher physically present in the classroom was discussed.

The presence of a teacher enhances the learning experience and promotes better interaction with students, emphasizing the importance of in-person teaching alongside online platforms.

Previous online meetings and events, including a webinar on blockchain, were also mentioned. Participants recalled attending various events organized by the Council but noted their absence from a specific event.

These events provide opportunities for knowledge exchange and networking.

Additionally, it was noted that one of the panelists was removed from the discussion. The inclusion of a video sent by a participant indicated the sharing of multimedia content during the conversation.

In conclusion, the discussion focused on technical issues with the plug, the significance of face-to-face teaching, previous online events, and the incorporation of multimedia content. Gratitude and appreciation were expressed at the conclusion of the discussion.

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Artificial Intelligence (AI) technologies have the potential to significantly contribute to creating greener cities and regions by optimizing energy usage, handling power fluctuations, improving energy storage, and predicting energy demand. By analyzing complex and multifaceted datasets, including real-time data on energy consumption, water use, and weather, AI systems can make energy consumption more efficient and reduce unnecessary wastage.

This can lead to substantial energy savings and a reduction in carbon footprint.

Local and regional elected representatives play a crucial role in environmental governance. Recognizing the link between the fundamental right to the environment and good governance at the local and regional levels, the Congress emphasized the importance of considering the environmental issue in their decision-making processes.

The Congress is working on raising awareness among elected representatives by sharing good practices regarding the environment and AI through handbooks and guidance for smart cities and regions. This highlights the vital role that local and regional governance plays in addressing environmental concerns.

In the realm of public transportation, incentive-based systems can prove effective in managing capacity and reducing the need for extra transport capacity and investments.

Such systems often offer different prices for train or bus tickets depending on the transport capacity, thereby encouraging people to choose less crowded public transport options. The implementation of AI-based systems has been observed to increase the modal shift from road to public transport, promoting more sustainable and efficient transportation practices.

The Swiss Energy Park is a unique initiative that encompasses three types of energy production: hydraulic power, solar panels, and wind crafts.

By analyzing the consumption and production of energy in the region, the Swiss Energy Park allows for a comprehensive understanding of energy needs and facilitates targeted efforts in energy conservation. It is noteworthy that climate change can significantly impact energy production, as seen in instances where insufficient water for hydraulic power resulted from a lack of rainfall.

This demonstrates the interplay between environmental factors and energy production, highlighting the importance of sustainable energy solutions.

Furthermore, AI has the potential to contribute significantly to combating environmental issues and reducing carbon footprint. It plays a vital role in managing public transport, leading to a decrease in carbon emissions.

Additionally, AI technologies assist in managing resources in energy parks, allowing for better mitigation of the effects of climate change. These AI-driven solutions have the potential to revolutionize environmental conservation efforts and promote sustainable development.

However, the implementation of AI in policymaking comes with challenges, particularly in terms of privacy protection and data security.

Deploying smart grid systems that manage energy consumption requires access to personal routines, raising concerns about the transparency of personal information if the system is hacked. Protecting privacy and preventing data breaches are essential considerations when integrating AI technologies into policymaking processes.

Overall, AI technologies present tremendous opportunities for creating greener and more sustainable cities and regions.

By optimizing energy usage, managing public transport, and analyzing environmental data, AI has the potential to significantly reduce carbon footprint, enhance energy efficiency, and promote sustainable development. However, it is crucial to balance the use of AI with care, ensuring responsible energy consumption and safeguarding privacy.

The involvement of local and regional elected representatives is pivotal for effective environmental governance and the successful integration of AI solutions in addressing environmental challenges.

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AI systems have the potential to enable sustainability and transform climate modeling, according to one of the speakers. They argue that tools like carbon-aware computing can shift compute tasks to data centres with higher availability of carbon-free energy. Additionally, they highlight the Climate Trace project, which harnesses AI to track greenhouse gas emissions.

These examples demonstrate how AI can contribute to addressing environmental issues and promoting sustainability.

However, another speaker raises concerns about the increasing computing needs of AI systems and their potential environmental impacts. They explain that direct environmental impacts result from AI compute, along with the resource’s life cycle.

Furthermore, they point out that indirect impacts may arise from AI applications, which can lead to unsustainable consumption patterns. This argument suggests that as AI becomes more prevalent, it could exacerbate environmental challenges.

In response to the potential environmental impacts of AI, another speaker emphasises the need for common measurement standards and expanded data collection.

They argue that without comprehensive data and consistent measurement frameworks, it is difficult to track and analyse the environmental impact of AI effectively. This highlights the importance of developing robust methods to assess the environmental implications of AI technologies.

The role of international organisations, such as the OECD, is highlighted by one speaker in facilitating cooperation on AI and climate change.

They argue that these organisations serve as the connective tissue that brings countries together to tackle complex issues that transcend borders. By fostering collaboration and knowledge-sharing, international organisations can play a critical role in addressing the global challenges posed by AI and climate change.

AI’s potential contributions to various sectors, including the environment, agriculture, and healthcare, are recognised by one of the speakers.

They explain that AI is a general-purpose technology with broad applications, and its diffusion is increasing across different countries in various sectors. This highlights the versatility and potential positive impact of AI on multiple industries.

The concerns regarding the negative impacts and risks of AI are acknowledged, but there is a belief that breakthroughs enabled by AI can help save the planet.

Despite the potential drawbacks, the positive practical applications of AI are highlighted by one speaker. They suggest that while it is important to address the environmental impacts and risks of AI, it should not overshadow the potential benefits it can offer in addressing global challenges.

To address the challenges associated with measuring and understanding the environmental impacts of AI, one speaker proposes the establishment of measurement frameworks.

They argue that as AI scales up and is applied on a larger scale, it becomes crucial to have standardised methods to assess and evaluate its effects accurately. This suggests a proactive approach to addressing potential negative impacts through robust measurement practices.

Adhering to the principles-based approach of the OECD is advocated by one of the speakers as a way to responsibly implement AI.

They emphasize principles such as transparency, engagement, and a human-centred approach to ensure that AI technologies are developed and deployed ethically and in alignment with societal values. This underscores the importance of ensuring the responsible and accountable use of AI.

Finally, the importance of public involvement and understanding of the benefits and risks of AI is highlighted in the policy-making and system development process.

One speaker advocates for the integration of public input and transparent parameters into AI-related decisions. This suggests that inclusive and participatory approaches can help address concerns and build trust in AI technologies.

In conclusion, the different perspectives presented in the summary demonstrate the complex relationship between AI and the environment.

While AI systems have the potential to enable sustainability and contribute to various sectors, concerns about their environmental impacts and risks should be addressed. Common measurement standards, international cooperation, and responsible implementation are crucial in harnessing the potential of AI to address global challenges such as climate change.

Public involvement and understanding are also important in shaping AI policies and systems.

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The workshop focused on the relationship between artificial intelligence (AI) and the environment, with speakers highlighting various aspects and potential benefits. One key point discussed was the use of AI in preserving healthy ecosystems. Efficient energy management was identified as an area where AI-based systems have been successfully implemented, citing the example of Switzerland using AI to manage the capacity of public transport and discourage overloading.

Real-time data on energy production and consumption was also mentioned as a crucial tool for dealing with the effects of climate change and managing energy resources more efficiently. This application of AI in energy management was seen as a way to improve environments.

Another important aspect was the responsible use of AI to serve its purpose in preserving the environment.

The speakers emphasized the need to ensure that AI tools are used in line with their intended purpose and argued that AI should be applied responsibly to help preserve healthy ecosystems. This sentiment was supported by the idea that every human right ultimately depends on a healthy biosphere, and AI could be a helpful tool in achieving this goal.

The workshop also emphasized the significance of international cooperation and the sharing of best practices for achieving environmental sustainability.

The speakers stressed the importance of collaboration and the need to share knowledge and expertise on AI’s impact on the environment. For instance, the Council of Europe was mentioned as working with international organizations like the OECD to study the impact of AI in sustainable urban systems.

The speakers highlighted the importance of data analysis to track and analyze the environmental impact of AI, as well as the need for common measurement standards to ensure comparability.

Furthermore, the speakers acknowledged the potential benefits of AI in supporting the green transition and addressing climate change.

They mentioned that AI can be applied to research across numerous disciplines, aiding the transition to a greener world. Examples were given of AI being used in fields like environmental impact, transportation, and material science. The positive sentiment towards AI’s potential in supporting the green transition was evident throughout the discussion.

In conclusion, the workshop provided valuable insights into the connection between AI and the environment.

The responsible use of AI to preserve healthy ecosystems, the importance of international cooperation, and the potential benefits of AI in supporting the green transition were all key takeaways. The speakers expressed a positive sentiment towards the potential of AI in addressing climate change and achieving environmental sustainability.

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AI and data science have demonstrated their potential to be key enablers in the global transition to achieving net zero emissions. Several notable examples highlight the positive impact of AI in various areas related to climate action.

One such example is DeepMind’s collaboration with Google, where AI was employed to significantly increase the energy efficiency of Google’s data centres.

Through AI techniques, DeepMind managed to enhance the energy efficiency of these facilities by an impressive 30-40%. This advancement is significant as data centres are known to consume vast amounts of energy, and optimizing their efficiency can lead to substantial reductions in greenhouse gas emissions.

Another remarkable application of AI can be seen through the efforts of the Climate Trace Coalition.

By utilising AI and satellite imagery, they were able to enhance the accuracy of global emissions inventories. This improvement is crucial in our collective efforts to effectively monitor and manage greenhouse gas emissions, enabling better decision-making and targeted interventions.

Furthermore, Unisat’s Flood AI tool has contributed to improving disaster response in Asia and Africa.

By leveraging AI, this tool has enhanced the ability to predict and respond to floods, ultimately aiding in mitigating the devastating impacts of such natural disasters. This application of AI demonstrates its potential to assist in building resilience and safeguarding vulnerable communities against the effects of climate change.

Despite the promising opportunities AI and data science offer, there are challenges that need to be addressed for their wider application.

The two main frustrations hindering progress are data discovery and data access. The process of discovering relevant data and accessing it efficiently can be cumbersome and time-consuming, impeding the adoption and effectiveness of AI and data science solutions.

To overcome these frustrations, several strategies are proposed.

Firstly, the development of improved data discovery tools is crucial for facilitating easier access to relevant datasets. Additionally, better regulation is needed to ensure that data is appropriately shared, while still protecting privacy and maintaining security. Furthermore, the establishment of commercial data markets, coupled with financial incentives, can encourage companies to share their data, unleashing its potential for AI-driven solutions.

The Centre for AI and Climate is actively working towards developing an intelligent data catalogue specifically tailored for climate action.

Their efforts align with the need for a more organised approach to data discovery and accessibility, providing a consolidated platform for researchers, policymakers, and organisations to access and utilise relevant climate data.

In addition to supporting climate action, AI is expected to play a significant role in digitally managed energy systems.

It has the potential to optimise investment decisions for asset developers, ensuring efficient allocation of resources towards sustainable energy infrastructure. Moreover, electricity networks can leverage AI to make informed decisions regarding which energy sources can connect to the grid and what upgrades are necessary, thus improving the overall efficiency and reliability of energy systems.

However, it is essential to maintain a balance between automation and democratic input in these digitally managed systems.

While the increased use of AI may lead to a more automated electricity system, human control and democratic participation remain crucial for accountability and fairness. By involving stakeholders and ensuring democratic input, it becomes feasible to limit the level of automation and prevent potential negative consequences.

In summary, AI and data science have demonstrated the potential to significantly advance efforts towards achieving net zero emissions.

Various examples showcase the positive impact of AI, from enhancing energy efficiency in data centres to improving disaster response and enhancing the accuracy of emissions inventories. However, addressing challenges related to data discovery and data access is crucial to unlocking the full potential of AI.

With improved regulation, commercial data markets, and the development of intelligent data catalog solutions, AI can be effectively utilised in climate action and digitally managed energy systems.

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Professor Yamagata is at the forefront of designing urban systems to enhance resilience in the face of climate change. His team harnesses the power of the Internet of Things (IoT), big data, and artificial intelligence (AI) technologies to achieve this goal.

They have focused their research on studying the Tokyo city center and its surrounding areas.

Using IoT, big data, and AI technologies, Professor Yamagata’s team aims to comprehensively understand urban emissions and develop sustainable strategies for policymakers and building owners.

They employ machine learning techniques to estimate dynamic carbon mapping and portray emissions resulting from various urban activities. This approach utilizes abundant sources of data such as occupancy information, people’s mobility patterns within buildings, sensor data, and transport measurements.

Professor Yamagata emphasizes the significance of being prepared and implementing preventive measures to mitigate the risks posed by heatwaves.

By combining hazard maps with precise location information of workers, the team can accurately assess exposure levels to heatwave risks. In areas identified as high-risk, they can deploy sufficient ambulances in advance to potentially save lives of those vulnerable to heat-related illnesses.

Another crucial aspect of Professor Yamagata’s work is his belief in enhancing walkability in cities to promote the health and well-being of citizens.

By utilizing big data and AI, his team can analyze walking behavior in cities, identifying ways to improve the flow of people and enhance the overall health and well-being of urban residents.

The team also recognizes the importance of visualizations as a tool to aid in understanding sustainable urban systems.

These visualizations are being developed collaboratively, involving stakeholders such as policymakers. Policymakers are particularly keen to see policy options directly in these visualizations, requiring granular details regarding different options such as energy management, urban planning, and digitalization. Therefore, involving policymakers in the application of AI technologies is crucial to address their specific needs.

Additionally, involving policymakers in the use of AI is a key research question for Professor Yamagata’s team.

Understanding the benefits that systems can provide to users is another important consideration. If users cannot perceive the advantages, privacy concerns may arise. Therefore, it is crucial to ensure that users clearly see and appreciate the benefits of these systems.

In summary, Professor Yamagata’s work focuses on designing urban systems that are resilient to climate change.

Utilizing IoT, big data, and AI technologies, his team conducts research on understanding urban emissions, developing strategies for policymakers and building owners, addressing heatwave risks, promoting walkability, and visualizing sustainable urban systems. The involvement of stakeholders, including policymakers, is necessary for successful implementation, and it is important to ensure that users perceive the benefits of these systems without privacy concerns.