How can AI make a difference to sustainability? This is a very topical question as COP26, the 26th United Nations Climate Change Conference, gets underway in Glasgow on Monday. Linking these two major trends of key importance for the future of humanity: climate change and the mastery of digital technology is more than relevant. During discussions at this year’s edition of Web Summit, experts discussed how to link these issues for sustainability.
By Steny Solitude, founder of Perfect Memory
On Tuesday 2 November 2021, the conference “AI is answering the call of sustainability” was held, moderated by Dan Jeavons, VP Computational Science and Digital Innovation at Shell, Hege Skryseth, Executive VP of Kongsberg and Junta Nakai VP of sustainability & financial services at Databricks. These experts discussed the role of AI and data in the energy transition. To do so, they discussed concrete solutions and identified best practices. They also celebrated success stories and highlighted how innovation in AI and data management is helping to accelerate progress towards sustainability.
Artificial intelligence to reduce CO2 emissions
AI makes many use cases possible to fight climate change. AI technologies can have a huge impact on sustainability and in particular on CO2 emissions. The current energy system needs to be optimized in order to combat the amount of CO2 we emit. At the conference, Junta Nakai gave a concrete example from Databricks:
“One of our customers runs one of the largest logistics companies in the world. Every morning, they activate algorithms to optimize their drivers’ routes. They have calculated that by saving one kilometer per day on 1,000 trucks that deliver, millions and millions of tonnes of CO2 are saved per year.
AI can play a crucial role in reducing these emissions but also in designing and optimizing the future energy system. The latter will have to be more diversified and better distributed, based on highly localized production and diversification of energy sources. After focusing on wind power and photovoltaics, the European Union, and in particular the Member States to the west of it (France, Germany, Belgium, etc.), is focusing increasingly on hydrogen to decarbonize the electricity and mobility sectors.
Too much information ‘kills’ information: The Big Data challenge
Sustainable development can benefit from artificial intelligence, provided that the quality of the data used and the respect of confidentiality are guaranteed. AI needs to be fed with quality data before it can be operational. However, this data is not always accessible or affordable at a low cost. Insufficient data quality can lead to distortions, discrimination or erroneous conclusions that will not contribute to the achievement of development goals.
Achieving such a level of data control requires many human and technical resources. Information sources have become extremely numerous and this plethora of information poses a real challenge. How can we continuously import hundreds of documentary sources in various formats in order to understand them, extract usable data, synthesize them, analyze them and generate alerts according to precise usable rules? In short, behind the question of AI at the service of sustainability, there is clearly a Big Data issue.
Not to mention the nuance between what companies say they do and what they actually do, explains Dan Jeavons
“There needs to be an independent check on what a company says it does and what it actually does. This requires the whole data ecosystem to work seamlessly, to be more integrated, merged and silos eliminated.”
Perfect Memory is a startup that provides semantic technologies to facilitate access to and exploitation of knowledge in organizations. The DNA of this company is to identify, collect, process and structure data in order to transform it into information that can be understood and exploited by all the players in companies and their ecosystems.
Without data analysis, AI for sustainable development is a pious hope, It is necessary to monitor the proper application of companies’ societal commitments. Data is so abundant that it has become almost impossible for specialized services to analyze it. New tools based on semantic technology offer a pre-decisional analysis that saves a lot of time.
In conclusion, it is clear that development actors need to actively engage in a dialogue with data protection authorities and all stakeholders. Appropriate responses, based on shared values and digital technologies, need to be developed. Responsible use combined with consistent application of data protection principles can contribute to the success of AI applications in sustainable development: If we can build the digital platforms that enable CO2 transformation, we will have a real impact on climate change and drive the structural change our society needs.
