AI expert witness for litigation

You may be considering hiring an AI expert witness for your litigation, arbitration or a tribunal, where the outcome depends on detailed aspects of artificial intelligence.

At Fast Data Science we have a number of professionals in our team with over 10 years of experience in academia and industry, who can be hired as AI expert witnesses in the UK or worldwide.

What does an expert witness do?

An expert witness is a person who has expert knowledge in a particular field, and who gives an impartial opinion to a court or tribunal on matters within their expertise. The opinion of an expert witness is accepted by a judge due to their skills or qualifications in that field.

In England and Wales, expert witnesses are employed with a judge’s permission in various capacities such as litigation, arbitration, and tribunals.

AI Expert Witnesses at Fast Data Science

At Fast Data Science we have a number of data scientists in our team, and our main focus is natural language processing (NLP). The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in an area of NLP, Computer Speech, Text and Internet Technology, and conducted his research project on pleonastic pronouns using unsupervised learning. Since completing his postgraduate studies he has worked exclusively in data science, maintaining a constant focus on NLP, although he has occasionally worked in computer vision and other areas of data science, including a stint consulting for Tesco, predicting customer purchases.

Thomas Wood founded Fast Data Science Ltd in 2018 to deliver data science consultancy focussing on natural language processing problems in large organisations that deal with lots of text data, such as healthcare, pharma, insurance and legal. In 2020 Fast Data Science diversified out to offer services in AI due diligence, and AI expert witnesses.

What is AI?

Ask an AI expert witness.

There are a number of definitions of AI. Back in the 1950s, researchers defined artificial intelligence as any task performed by a machine, which was previously considered the domain of human intelligence.

Modern definitions tend to differentiate between narrow AI and general AI. Most commercial applications of AI today are narrow AI, meaning that they can perform a small range of tasks. Consider a chatbot which can book a flight, parry rudimentary small talk, but do little else. General AI, meaning an AI able to respond to new situations as a human would, and do anything from drive a car to play chess, to learning a new sport, is still mostly the preserve of science fiction, such as HAL in the film 2001: A Space Odyssey.

One of the problems that AI experts face when communicating with laypeople is the conflation of narrow AI with general AI. Experts are divided as to when general AI will become a reality.

AI Expert Witnesses in the UK

In England and Wales, the Crown Prosecution Service and the Civil Justice Council have published guidance on the use of expert witnesses in civil and criminal cases.

Expert witnesses can be contrasted with fact witnesses. The evidence given by an expert witness must be tendered as opinion rather than fact.

“Expert evidence is admissible to furnish the court with information which is likely to be outside the experience and the knowledge of a judge or jury.”

Ministry of Justice (England and Wales), Criminal Practice Direction V Evidence 19A Expert Evidence

For further information about expert witnesses, please refer to the following resources:

  • Crown Prosecution Service guidance to the use of expert evidence in criminal cases.
  • Civil Justice Council guidance for expert evidence in civil claims.

What is expert evidence?

Natural Language Processing applications in healthcare Natural Language Processing applications in healthcare

Expert evidence is simply the opinion of the expert. An expert witness assists a court in reaching a decision by providing independent technical analysis in their field of expertise, and an opinion on the issue at hand.

Expert evidence is admissible in Court when there are open questions that require the input of an expert. The Court has the power to permit or exclude expert evidence. In some large complex cases, each party may instruct their own expert witness, and a Court may allow the appointment of more than one expert.

Our AI expertise

Our data scientists have expertise in many areas of AI, in particular natural language processing, and including:

  • Simple vanilla models, such as Bag of words, tf*idf, cosine similarity. These often serve to provide a baseline performance before progressing to more advanced models.
  • Slightly more sophisticated models, taking word order into account, such as NLP pipelines, lemmatisation, parsers, chunkers.
  • Cutting-edge models such as deep neural networks
  • Clustering and unsupervised techniques
    • Latent Dirichlet Allocation – LDA is useful for extracting topics from a set of unstructured documents, for example, legal documents, survey responses, factory error reports, etc, where there is just an abundance of documents but no accompanying structured data or labels which could make the NLP task easier.
  • Search engines and search term recommendation systems
  • Google Natural Language, AWS, Microsoft Azure
Natural Language Processing word cloud
Topic detection is a technique used by NLP data scientists to explore and discover common themes in a set of unstructured documents such as factory error reports.

Experts in technologies

Our data scientists primarily use the following technologies:

  • TensorFlow – deep learning framework best known for neural networks
  • Spacy – a simple Python library allowing quick modelling with deep learning
  • Scikit-Learn
  • Keras – a user friendly wrapper for TensorFlow
  • Python NLTK – Natural language processing toolkit
  • R

Some of our past clients

We have worked on a number of AI projects in the past, including:

  • Providing expert due diligence consulting on the acquisition of an AI company by a wind power consortium, investigating the company in detail from a technical standpoint,
  • Building a topic detection system for factory error reports, which identified common errors such as temperature excursions, damaged packaging,
  • Assisting a pharmaceutical company in predicting the costs of clinical trials.

Please check out our portfolio of case studies, or look at the list of past clients from the top menu, for more information.

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