Data, Analytics & Artificial Intelligence
As AI and large-scale data move to the centre of commercial life, they increasingly sit at the centre of disputes. Our experts analyse AI and machine-learning systems, algorithmic decision-making, data provenance and integrity, and the behaviour of automated platforms. We make opaque systems explainable, setting out objectively how they were built, how they operated, and what the evidence shows.
What we cover
- AI and machine-learning systems
- Algorithmic decision-making
- Data provenance and integrity
- Behaviour of automated platforms
- Making opaque systems explainable
Making AI and machine-learning systems explainable
Disputes involving artificial intelligence often founder on a single problem: the system is treated as a black box that no one can account for. Our experts open that box. We examine how a model was designed, trained and deployed, what data it learned from, and how it behaves in practice, and we explain the result in terms a court can follow.
That extends to questions of accuracy, bias and reliability: whether a model performed as claimed, whether its outputs were reasonable given its inputs, and whether the way it was built and validated met the standard a competent developer should have applied.
Algorithmic decision-making and automated platforms
Automated systems increasingly make or shape decisions that end up in dispute: pricing and ranking algorithms, recommendation and moderation systems, fraud and eligibility scoring, and the platforms that run them at scale. Our experts analyse how these systems reached the outcomes complained of and whether those outcomes can be justified on the evidence.
We reconstruct the logic and data flow behind an automated decision so that its behaviour can be examined objectively rather than accepted or attacked on assertion alone.
Data provenance, integrity and governance
Where data itself is the asset or the issue, its origin and integrity matter as much as its content. Our experts assess where data came from, whether it was collected and processed lawfully and as described, and whether it has been altered, degraded or mishandled along the way.
This underpins disputes over data ownership and use, the scraping and reuse of datasets, and the training of AI systems on third-party material, all areas where the technical facts are developing as fast as the law around them.
What our analysis delivers
We turn opaque systems into clear, impartial evidence: CPR Part 35 compliant reports, technical assessments for pre-action strategy, joint statements with opposing experts, and testimony that holds up under cross-examination. Throughout, we are careful to separate what the technology demonstrably did from what remains uncertain.
We have experts in this area
A bench of court-tested specialists ready to be instructed. Profiles are anonymised; full CVs and availability are provided on request.