Meet: Dr Robert Laidlow

As one of the first AI+ Fellows to join King's College London in December 2025, Laidlow brings a distinctive perspective to creative AI: that of a composer who believes performance spaces offer essential testing grounds for how humans might interact with intelligent machines across all aspects of life.

Dr Robert Laidlow is an AI+ Fellow at King’s College London. These interdisciplinary fellowships are central to King’s £18 million strategic investment in academic excellence and demonstrate King's commitment to transforming AI research and innovation across all disciplines.

Laidlow's path reflects an evolving relationship with technology and sound. Starting as a jazz player and performing with synthesizers in rock bands during school, he moved into notated composition for ensembles in his early twenties. After studying at Cambridge and the Royal Academy of Music, he completed a PhD at the Royal Northern College of Music exploring artificial intelligence in contemporary classical music, working in collaboration with the BBC Philharmonic. He then spent three years as a Career Development Fellow in Composition at Jesus College, Oxford, before joining King's as an AI+ Fellow in the Department of Music.

His 2025 work TECHNO-UTOPIA, commissioned by BBC Radio 3 and the Berlin Radio Symphony Orchestra (RSB), first performed by the BBC Philharmonic, exemplifies his approach. The piece is a concerto for orchestra and soloists performing on piano, synthesizers, and AI-embedded instruments – but crucially, it was trained exclusively on approximately 2,500 hours of BBC Philharmonic recordings.

"In one sense, this is a lot of data, but it's not a lot in comparison to the millions of hours used by commercial models," Laidlow notes.

The piece features an entirely new instrument called the Stacco, developed with interaction designer Nicola Privato at the Intelligent Instruments Lab in Iceland. The instrument uses four magnets tracked by magnetometers to control an eight-dimensional ‘latent space’ – essentially a map of all possible sounds the AI learned from the archive. What makes this fascinating is that these dimensions don't correspond neatly to musical parameters humans recognise.

"If a person was categorising sounds, one dimension might be volume, another might be pitch," Laidlow explains. "Machine learning analyses music using statistical methods that are distinct from how we hear music." The Stacco allows performers to physically manipulate magnets to navigate this alien sonic landscape, creating sounds that emerge from the AI's fundamentally non-human way of organising music while still under the expressive control of a human performer.

This interest in AI's non-human characteristics runs through his work. His 2024 piece Tūī, named after a mimic songbird from New Zealand, trained machine listening software on birdsong rather than human performance, forcing musicians to discover unusual performance techniques – growling into flutes, using wrong fingerings on clarinets – because "machines hear differently to us."

In Post-Singularity Songs, created with soprano Stephanie Lamprea, Laidlow explored language models and voice synthesis. When they created a vocal clone of Lamprea's voice, they were struck by its uncanny quality. "It feels like it's constantly inhaling, never exhaling," he observes. "The network doesn't know what a human body is, so this isn't a problem for it, but it sounds very strange and inhuman to us."

This work addresses what Laidlow sees as a critical gap in the creative AI landscape. "It's commonly reported by industry technology leaders that it would be impossible to train musical AI models without using vast datasets of existing human art," he notes.

His concerns extend beyond copyright to the creative ecosystem itself. Many orchestral musicians rely on session work for films and television to subsidise their performance work. "If that bedrock is eroded, we could see significant knock-ons in places you wouldn't expect," he warns.

Laidlow is particularly excited about the AI+ Fellowship's interdisciplinary structure. "Composers are a little like magpies – we take lots of ideas from lots of places, spin them around, and put them in our music," he says. At King's, he plans to push further into deliberately designing non-human AI systems, exploring how machines can reveal genuinely new creative possibilities.

For Laidlow, the concert hall is a laboratory for the future as much as it is a venue for music.