Harris will attend an AI summit at a UK estate that was a base for World War II codebreakers

Harris will attend an AI summit at a UK estate that was a base for World War II codebreakers

Technology

She’s scheduled to leave on Tuesday and return on Nov. 2

Follow on
Follow us on Google News

WASHINGTON (AP) — Vice President Kamala Harris will attend a summit on artificial intelligence in the United Kingdom next week, shortly after President Joe Biden issues a highly anticipated executive order on an emerging technology that has generated excitement and fear.

She’s scheduled to leave on Tuesday and return on Nov. 2, and she’ll be accompanied by her husband, Douglas Emhoff, according to her office.

Harris will deliver a speech outlining the Democratic administration’s approach to artificial intelligence on Nov. 1 before attending a summit on the topic the next day. Emhoff is expected to participate in events with civil society groups and young leaders focused on science learning, gender equity and countering hate.

Kirsten Allen, a spokeswoman for Harris, said the goal is a future “where every person is safe from the harms of AI and where every person can share equally in its benefits.”

Governments around the globe are racing to set guidelines for artificial intelligence. Besides Biden’s executive order, the European Union is putting the final touches on a comprehensive set of regulations that targets the riskiest applications for the technology.

U.K. Prime Minister Rishi Sunak hopes to carve out a prominent role for Britain on the issue, and next week’s summit will be held at Bletchley Park, a historic estate north of London that once served as a base for World War II codebreakers. Teams at what’s dubbed the spiritual home of modern computing were able to crack the Nazis’ Enigma cipher, helping to end the war.

The summit will focus on the risks from what’s known as frontier artificial intelligence, which is cutting edge systems that can carry out a wide range of tasks and pose unknown risks to public safety. These systems are underpinned by large language models, which are trained on vast pools of text and data.