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Big Data and AI

What is Big Data and AI?

The amount of data available around the world is growing continually. When traditional methods no longer suffice for processing these large and complex quantities of data, people refer to this data as big data.

Artificial intelligence (AI) can help evaluate these quantities of data efficiently and in a targeted manner. AI refers to computer programs that can automatically recognise interrelationships, make decisions and also learn. AI applications first need to be developed and trained using large quantities of data, for example, so that they can translate languages on their own or predict changes in the climate or in the health sector.

Video: Big Data and AI (english subtitles available)

 

Big Data and AI in the Corona response

Data technologies and Artificial Intelligence are already heavily used to help in the battle against COVID-19:

  • Data analytics supported by AI is having a predominant role in monitoring of the infections, deaths and recovery rates all over the world. Institutions have managed to draw the trends that Covid-19 has in different countries and conditions. Data collection, monitoring and analysis technologies are also needed in developing countries in order to track the virus progress and adapting the response and mitigating measures.
  • Artificial Intelligence is being used to detect coronavirus through computerized tomography scans analysis. Imaging departments in healthcare facilities are being overwhelmed with the increased workload created by the virus. This solution improves CT diagnosis speed. Some big tech companies claim to have built AI powered analysis systems able to read scans in seconds giving a 96% accurate diagnosing of the virus. In African countries, lacking of specialised doctors and labs, these technology can be disruptive.
  • Intelligent tracing and mobile technologies are being used by governments all over the world to track people movements and prevent further expansion of the virus. The EU needs to support African governments in using the large amount of mobile data available considering the privacy-conscientious use of mobile phone data. Technology solutions are available allowing tracing people movement taking into account the risks of misuse of personal data.

Questions 1/5

Are larger quantities of data already being used in your field, such as in the form of satellite data, drone data, mobile communications data or target-group-related data from the World Bank or other donors?

Questions 2/5

Have you already encountered AI or big data initiatives that could be of interest to your field as well, and you would like to learn more about them?

Questions 3/5

Could the data accruing in large amounts in your field be collected and made accessible to the public so your development goals can be better achieved (taking data privacy into consideration)?

Questions 4/5

Have there already been attempts in your field to blend different types of data (e.g., internal data, open data, purchased data and user data)?

Questions 5/5

Are you responsible for projects in areas pertaining to the environment or nutrition security in which it is important to monitor forests, animal and plant species or changes in the soil?

Results

Since you answered %s questions with Yes, you should consider using AI and big data in your projects. Department 112 in the BMZ and the digitalisation sector project at the GIZ will be happy to advise you (sv-digital@giz.de).

Results

You have answered No to all the questions. The Smart Development components offer basic approaches for the correct implementation of digitisation as standard in development cooperation. Please feel free to find out about the other components. Department 112 of the Federal Ministry for Economic Cooperation and Development (BMZ) and the sector programme Digitisation for Sustainable Development will be happy to advise you.

Picture 1/2: Umuganda is a concept rooted in the Rwandan culture of self-help and cooperation. Traditionally, this concept has been used for community involvement and collective efforts to build the physical infrastructure in Rwanda.
Picture 2/2: The App Child Growth Monitor provides a turning point in measurement and data processing for malnourished children under the age of 5. It is a foolproof solution based on a mobile application that uses augmented reality combined with artificial intelligence. By determining weight and height through a 3D scan of children, the app can immediately detect malnutrition.

Usage potential for our key topics

What advantages do big data and AI offer the German development cooperation?

AI and big data can also improve the information base in order to make data-based decisions. It is often the case that certain types of data are already being used in the development cooperation’s projects. This concerns remote sensing data from satellites or drones, language data from smartphone applications, mobile communications data, all kinds of environmental data or large quantities of text, among others. A differentiation can be made between two application areas in this instance. AI and big data can be used both for project monitoring and during immediate project implementation.

Analysing big data can, for instance, be used to improve impact monitoring. Forest protection projects can also benefit from the evaluation of satellite data, among other things. It can show not only whether the measures taken have lead to a reduction in deforestation but also when and where the reduction took place. This makes it possible to make additional conclusions about the local impact and helps structure the measures even better and more purposefully.

In addition, AI applications can be included in project implementation. Artificial intelligence makes it possible to automatically detect plant diseases, for instance. All it needs is a photo of the plant taken with a smartphone. The AI-supported analysis then indicates not only the disease but also the appropriate countermeasures.

Artificial intelligence thus offers great possibilities for the German development cooperation. AI-based applications can be quickly and inexpensively extended to include many users. The quick processing of large quantities of data can recognise interrelationships that have gone unnoticed to date and make them accessible to the responsible parties as decision aids.

AI applications are trained using existing datasets. Therefore, using them can increase the inequalities and discrimination contained in the data. Data protection and corresponding capacity expansion on site should also be considered on an ongoing basis.

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