In a plan approved by German Chancellor Angela Merkel, Germany has announced its plan to invest €3bn ($3.4bn) to boost the nation's AI capabilities and research over the next six years. The decision was reached by Merkel's cabinet following a two-day seminar which delved into the many digital challenges Europe's largest economy faced.
One such challenge Germany faces is the fact that it has not focused on AI research and development with the same fervor that other nations such as the US and China have over the last few years.
"Today, Germany cannot claim to be among the world leader in AI," confessed Merkel in a press conference following the seminar. "Our aspiration is to make 'Made in Germany' a trademark also in AI and to ensure that Germany takes its place as one of the leading [AI] countries in the world."
The $3.4bn the German government plans to invest in AI over coming years is expected to be matched by private sector companies, bringing the total investment to €6bn ($6.8bn). Other facets of the new AI strategy include a commitment to build 12 new AI R&D centers and create 100 university chairs also focused on developing AI capabilities.
Many industry experts have acknowledged that Germany is indeed at risk of falling behind the technological curve with regards to AI. A recent survey by a German digital association called Bitkom claimed only 11% of the nation's firms currently utilize AI. This is largely due to the relatively small pool of data accessible by firms looking to develop AI applications, a notoriously data-intensive process.
"The volume of usable, high-quality data must be significantly increased if the goals of this strategy are to be met," explained the strategy document.
However, the German government is still airing on the side of caution with regards to privacy concerns. While the strategy document does propose the launch of a larger, EU-wide data pool, it would rather it was not at the expense of "personal rights, the right to informational self-determination and other basic rights", but instead focused on pooling data from industrial machines instead.