Reported by Al Jazeera
The US company is using Kyiv’s unique war data to train its controversial technologies.
Months into Russia’s full-scale invasion of Ukraine , Palantir’s CEO Alex Karp became the first chief of a major Western Big Tech company to personally visit Kyiv.
President Volodymyr Zelenskyy said in June 2022 that he was “delighted” to receive the support of such a company in the fight against Russia “on the digital front line”.
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The Florida-based software development firm’s partnership has paid off.
Ukraine has since become the first nation in modern history to systematically collect battlefield data, a crucial asset for training military artificial intelligence (AI) to recognise patterns and make predictions.
The trove of real-world combat data obtained from video and sensor feeds over four years of conflict is helping Ukraine monitor, predict and respond to Russian attacks with the help of Palantir’s products.
Yet observers say the data is also boosting the capabilities of the United States corporation whose technologies are implicated in human rights abuses, including in Israel’s genocide in Gaza , raising questions about the growing leverage that private tech corporations are acquiring over sovereign states.
Palantir was founded in the aftermath of the 2001 attack on New York’s World Trade Center to help the US defence industry build a single data environment from which to monitor and respond to incoming threats.
To reflect such a mission, the company was named after a stone in JRR Tolkien’s The Lord of the Rings that grants powers that border on omniscience.
Yasir Atalan, deputy director of the Futures Lab at the Center for Strategic and International Studies (CSIS), said Palantir makes “different forms of data talk to each other”.
In the military context, data from missiles, radars, the automatic identification system (AIS) and open sources is gathered on one screen, offering a “larger view of the battlefield”, Atalan said.
Similar solutions are available to governments for civil purposes, including border control, health services, tax and revenue – and mass surveillance.
With more data, systems use statistical learning to recognise patterns to make accurate predictions, enabling military systems to make split-second, automated…