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Do good with data and AI

At Capgemini, we believe that data and AI can greatly contribute to achieving a sustainable world.

With the 2030 Agenda for Sustainable Development and its related 17 Sustainable Development Goals (SDGs), the United Nations (UN) established a crucial call for action by all states, recognizing the urgency to end poverty and other deprivations through impactful strategies that improve health and promote inclusive education, reduce inequality, and foster economic growth – while tackling the climate crisis, promoting access to affordable, sustainable energy, ensuring peace, and fighting disinformation.

Because we are convinced by the transformative power of data and AI to build positive futures for our people, our society and our planet we are leveraging data and AI in various ways to achieve a sustainable future:

  • Since 2020, Capgemini contributes to accelerating the UN’s sustainable development goals with its participation in the AI for Good Global Summit. This year we will  focus on how data and AI can help protect and sustain global forests’ ecosystems, register here.
  • AETA (Acoustic & Electromagnetic To AI) Earthquake Prediction Algorithm, Capgemini has been collaborating with Peking University Shenzhen Graduate School, Shenzhen Valley Ventures (SVV) and Shenzhen MSU-BIT University through its AIE Shenzhen and Data & AI team to build an AI platform to support the algorithms and data generated in AETA 2022
  • Our annual Global Data Science Challenge, which, in 2020, focused on using AI to identify and track the sperm whale population
  • FARM 2.0, an intelligent data platform developed at Capgemini’s Applied Innovation Exchange (AIE) in the Netherlands to resolve global food shortages.
  • Since 2021, Capgemini has been partnering with Teens In AI a non-profit organization to empower the next generation of data and AI talent and contribute to fostering diversity of minds, leading to more inclusive tech design, driving fairness in AI systems, and reducing algorithmic biases.

By using latest technologies & Innovative solutions, how data ecosystems can help us in achieving the sustainable development goals and keep us stay on track? Check on our experts when they share their insights and experience with building data ecosystems in areas such as health, smart cities, environment, and labour dynamics. Learn more here.

Data ecosystems, a stepping stone towards the Sustainable Development Goals

Capgemini experts, public organizations, society and business stakeholders explored in this session how data-sharing can provide insights that help steer new strategies in achieving a more sustainable future.

AI for Good

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AI for Good – let’s protect our forests

Capgemini at AIForGood 2022: 3rd of November 2022, Thursday ,2:00 PM [CET] onwards.

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AI4Good – Applying AI towards the Sustainable Development Goals

Below are our sustainable business solutions that help build positive futures for humans and society.

AI in education can be used to enhance student learning outcomes, promote personalization, and improve access to education, particularly for girls and vulnerable children. In Capgemini’s four PublicGoesAI playgrounds, AI technology works in the four following ways to enhance teaching and learning solutions.

Our approach

  • Intelligent automation of teaching materials and processes – Intelligently automating curricula and routine tasks to allocate more time to the most crucial aspect of education and gain efficiency
  • AI-based interaction with students and teachers – Augmenting interaction with children through the use of scalable AI-based educational chatbots, offering personalized advice and support to children and youths, specifically students with disabilities and health impairments, in their learning process
  • AI for detecting educational failures – Identifying patterns with the help of machine learning techniques to detect real-time anomalies and help prevent individual failures with long-term impact, such as student drop-out
  • Augmenting decision-making with AI – Helping educational leaders and schools leverage data and insights to make more informed decisions, such as personalizing training programs, and to predict educational underperformance.
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Artificial intelligence can transform existing food and agricultural systems, rendering them more efficient. AI-based early warning systems can flag food shortages, helping decision makers avert situations such as those leading to malnutrition. AI technologies such as machine learning can improve crop management, enhance crop quality, and maximize output.

With its strong partner ecosystem, Capgemini aims to harness the power of AI in each of the following steps of the food system to tackle world hunger:

  • For those who produce food, AI can help to identify weather patterns and to optimize the use of land, leading to sustainable agriculture.
  • For those who consume food, AI can build on conversational AI to facillitate better interaction with those in need.
  • For those who distribute food, the intelligent use of data brings insights on how to best feed the population with the available resources, also minimizing waste and foreseeing food shortages.
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Aware of the current challenges related to the accuracy and crucial value of valid information, several countries have begun to consider the potential of AI to nurture healthy knowledge ecosystems and protect their citizens. By combating threats such as disinformation with the help of AI, they encourage the dissemination and acceptance of AI technologies to raise awareness of cybersecurity and fake news.

By leveraging automation and analytic skills, information environments and their misuse can be tackled with AI through:

  • Identification – AI-based identification of disinformation and accurate responding
  • Analysis – Analyzing behavior on social media to identify disinformation and prevent malicious networks as well as the dissemination of fake news
  • Dismantling – Providing guidance on facts and virtual assistance with the help of conversational AI.
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The emergence of artificial intelligence can pave the way towards pursuing the United Nations’ Sustainable Development Goals for protecting our environment. AI technologies and algorithms are being developed to monitor pollution levels, reduce energy consumption, and better understand the effects of climate change. Governments around the world, both on the local and central level, are embracing AI in their program and strategy roadmaps for the protection of our environment. Leveraging AI and IoT technologies together can help enhance environmental sustainability.

Capgemini seeks to serve governments and public organizations in their quest to build sustainable territories by leveraging data, AI, and analytics expertise for good in the areas of:

  • Distributed energy grids – AI can predict the demand and supply of energy, improve storage, and assist in its efficient use.
  • Smart cities – AI- and IoT-based public services in cities will create sustainable cities and environments. This will greatly improve living conditions and improve the lives of citizens all over the world.
  • Smart agriculture and food – AI-augmented agriculture is resource efficient and climate resilient. It can ensure that supply gaps because of poor farming practices can be curbed to a considerable extent.
  • Biodiversity monitoring – AI is frequently used in forestry management and species detection to assess the impacts of environmental changes.
  • Climate monitoring – Climate informatics is the use of AI to predict the climate and effects of climate change. This field of AI helps augment decision-making in various other areas, such as disaster management and daily weather reports.
  • Smart disaster mitigation – By not only predicting disasters, but then focusing on resource prioritization to mitigate aftereffects, AI possesses significant capabilities for avoiding unforeseen consequences.
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States around the world, including Germany and Estonia, and institutions, including Interpol and the Council of Europe, increasingly convey great interest in AI for crime prevention and law enforcement, as recently seen in national AI strategies and initiatives. While Germany is considering AI-based analysis methods for law enforcement as part of its AI strategy, Estonia plans to use AI as a decision-making helper in small-claims cases. The UNICRI-INTERPOL report on AI in Law Enforcement highlights recommended principles and addresses requirements for the responsible use of AI. Also, the recently published progress report and a feasibility study by the Council of Europe’s Ad hoc Committee on Artificial Intelligence (CAHAI), tackling the legal framework for the development, design, and application of AI, sets out a clear roadmap based on human rights, the rule of law, and democracy.

Along with the four PublicGoesAI spheres Capgemini envisions, AI can prove to have a significant impact for citizens, courts, police, and government ministries by developing and deploying applications in the following fields:

  • Intelligent automation of juridical processes, e.g., automated decision-making and cognitive document processing
  • Interaction with citizens, e.g., virtual assistance with chatbots for citizens
  • Detection of anomalies, e.g., in crime detection
  • Data-supported help for judges in decision-making processes, e.g., intelligent deployment of resources and prosecution analytics.
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Data and AI offer numerous opportunities to transform the delivery of health care, profoundly and rapidly. The technology is essential in a range of health applications and is already being used to augment practitioners’ capabilities to detect and efficiently treat diseases. In addition, AI can assist patients in their healthcare journey – from real-time advising to scheduling appointments – and it can facilitate the allocation of resources and capacities within hospitals and healthcare facilities.

From the US to Korea and Australia, several countries have resorted to AI- and big data-driven tools to predict, manage, and combat the COVID-19 virus. At the same time, governments worldwide have started implementing health-focused initiatives in their respective AI strategies.

  • AI for research – Improving the analysis of human tissues and optimizing the treatment of diseases
  • AI for contextualization – Allowing faster and more effective decision-making when facing injury cases.
  • AI as an engineering tool – Augmenting the capabilities of healthcare practitioners to make diagnoses
  • AI for operations – Predicting and monitoring patterns and dynamics, supporting the organization in its short- and mid-term strategy
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