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Channel 4’s “Alternative Christmas Message for 2022” will be delivered by a robot in a speech generated entirely by AI.

A human-shaped robot called Ameca will lead the programme which will cover the highs and lows of the year gone by.

The broadcast, which will run after the King’s annual Christmas message at 3pm, will also see the robot being questioned about humans.

According to Channel 4, Ameca says we should be “neither happy nor sad about 2022” and “take it as a learning opportunity, a chance to change the way we think about the world and a reminder to help those in need whenever we can.”

Engineered Arts, a British company based in Cornwall, developed the robot which is capable of ultra-realistic reactions and can smile or frown, blink, scrunch its nose and even wink.

The speech will use AI software that generates answers from millions of different inputs to give a human-like response, and nothing Ameca says has been written or scripted by a human.

Channel 4’s chief content officer, Ian Katz, comments: “As we look to a future in which artificial intelligence is set to have an increasingly prominent role in our lives, Ameca’s Alternative Christmas Message is a vivid illustration of both the power and limitations of this technology.

“Despite Ameca’s remarkably lifelike facial expressions, I suspect most viewers will come away reassured that humans are not about to be displaced by AI robots any time soon.”

Last year, the Alternative Christmas Message was delivered by a deepfake of the Queen.

Channel 4 said the intention was to give a “stark warning” about fake news in the digital age.

During the message, the fake queen tried its hand at a TikTok viral dance challenge and referred to a number of controversial topics, including the decision by the Duke and Duchess of Sussex to leave the UK and allusions to the Duke of York’s decision to step down from royal duties.

OpenAI’s Chat GPT chatbot was released last month and quickly garnered attention for its detailed responses and articulate answers across many domains of knowledge. Its uneven factual accuracy was identified as a significant drawback.

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