Data show that on the one hand, the relationship between the African continent and Western countries is getting worse. On the other hand, Russia and China increase their relations with Africa by providing them with digital and technical infrastructure and using their military and economic predominance. But could these data have been a fundamental part of solving the slacking relationship between Western and African countries?
During this year’s Munich Security Conference from 17th to 19th February, Katharina Schüller (CEO, STAT-UP) was invited by Dr. Zoe von Finck (Podcast-Host “ichbinsofrei”) to discuss the question “Did we lose Africa?” together with Dr. Florence Gaub (Special advisor to the EU’s foreside commissioner).
To answer the question, we must have a look at the data. During the UN general assembly in 2022, many Africans abstained from condemning the Russian war on Ukraine. Also, the African countries’ votes were significantly pro-China, which could be a result of Xi Jinping’s massive diplomacy campaign. Since starting his reign in 2013, China has been very active in visiting states and trying to build diplomatic relations.
There’s a lot more data that could be interpreted to show the reasons for the European loss of African sympathy. For example, the Afrobarometer, which surveys African citizens about their opinions, former voting data to predict future behavior, or the so-called “hard facts” such as military and economic presence, debt, or foreign direct investments.
Standing alone, none of these data can give us the answer to whether we lost Africa or not. To get the whole picture, all the puzzle pieces must be structured and connected to each other. This can be done with so-called “self-organizing maps”, created with a tool called Viscovery.
This map contains predictions of the votes from the last UN general assembly, regarding the Ukraine conflict. The clusters are “Yes”, “No”, and “Abstain”. There were two different clusters of countries based on different characteristics, which were predicted to vote “Yes (A/B)”. By having a look at the colored parts of the map, which display the actual votes during the assembly (blue = No; red = Yes; green = Abstain), it can be seen that the prediction wasn’t that far away from reality.
As already stated, the votes themselves can’t prove a causal relationship. But what if the actual votes can be brought into correlation with other indicators? This is exactly, what these next self-organizing maps show.
In this chart, it can be seen that countries who think rather positively about Chinese influence (red), are more likely to answer “No”. On the other hand, countries who think negatively about Chinese influence (blue), rather answer “Yes”. Now let’s see what happens by combining the influence of China with the democracy index of each country. Countries, that have a lower democracy index are colored in blue, while the ones with a higher democracy index are colored in red.
By combining these indicators, the picture seems to get very clear. Of course, these data are not causal, because they can’t clearly prove voting behavior in future UN general assemblies, but they can be used as a very good predictor.
To answer the question of whether data could have been a potential factor to inhibit the diminishing European-African relationship: Data do have the potential to forecast the future behavior of countries, so it also has the potential to prevent future crises. But there are several problems that must be faced before the real predictive power of data can be used. First, there is a lack of communication between quantitative and qualitative experts. Second, there is a lack of communication between experts on both sides and decision-makers. The problem is not missing data but passing the message to the elites and making it tangible for them, so they can make it tangible for the public. This is, where tools like Viscovery come into play because they can visualize data in an intuitive way. The public always wants answers to their questions and in order to give those answers, there is a need for improved communication between experts and decision-making instances. Both sides have to get out of their comfort zone to unleash the real potential of data.