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According to ArtTactic, an art market analysis firm, the sales of artwork by African makers grew by an impressive 44.1% to reach $72.4 million in 2021. African art is increasing in popularity, and this is also made clear by their survey that shows that 70% of global art experts hold a positive view of the African art market for the future.
This increase in the popularity of African art is also evident in the number of successful exhibitions by African artists globally. For example, Ghanaian sculptor El Anatsui’s solo exhibitions in the US & South Korea garnered widespread critical acclaim, while Nigerian painter Njideka Akunyili Crosby’s works have been showcased at prestigious venues like the Whitney Museum of American Art in New York.
However, like any growing industry or community, there are still some challenges. Some of these challenges are due to general infrastructural challenges that are common across various industries in Africa while others are not. For example, it can be difficult to find detailed, accessible documentation about the works of old African masters. This makes it hard for people to get context about certain Artists & their works.
It can also be difficult to find new and emerging artists. You see lots of beautiful paintings online and in public spaces but it can still be hard to find the artists behind them especially when they’re not properly signed or credited. You may also be interested in certain painting styles but may not be able to find artists with similar styles.
These are some of the challenges that Eko Adetolani and his team are aiming to solve with WMTA. WMTA is a project dedicated to improving how African art is documented, identified & recognised using technology.
The first phase of the project has been the development of a platform that helps art enthusiasts and collectors identify the artist behind paintings that they find interesting.
Leveraging artificial intelligence, the platform scans photos of paintings, analyses the brushwork, palettes, and composition – the artistic fingerprints and uses that data to predict the artist behind the painting.
A demo of how it works.
I spend a lot of time appreciating paintings from African
artists & at some point, I could tell you who made a painting
just by looking at the styleEarlier in the year, I
started exploring a way for computers to do the
samePOC feat some of my favourite artists#buildinpublic
pic.twitter.com/WhL4ulY17R— Eko of Lagos. (@Eko__A) December 8, 2023
Eko says that the platform can recognise the painting styles of over 80 African artists, including the likes of Ben Enwonwu, Yusuf Grillo, Duke Asidere, Anthony Azekwoh, Jekein Lato-Unah, Chigozie Obi, Shuta Bug, and Dennis Osadebe, among others.
Speaking about what the project means to him, Eko said, “I’ve always been involved in art, and for me, this is my way of supporting the Art community how I can, with the power of technology.”
“We’ve released the beta version and we’re gathering feedback to improve the machine learning model. We have a goal for the platform to be able to recognise the work of about 1,000 African artists,” Eko added.
As the project continues to evolve, it will be fascinating to observe the use cases that emerge. Could the search data help galleries identify market trends? Could it change how collectors discover new artists? Could this become a useful tool in teaching Art education & history across African schools?
Only time will tell, but it’s exciting to think about the possibilities of the project.
You can check out the beta version of the platform here:
beta.whomadethisartwork.com and join their mailing list for updates. Artists, galleries, art enthusiasts and art lovers who are interested in getting involved can reach out via team@whomadethisartwork.com
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