Imagine a world where all of your legal problems could be resolved by a team of highly advanced, super intelligent computers at a fraction of the human cost – well, thanks to CaseCrunch, you could now be living in it.
CaseCrunch, a legal tech start-up based in the UK that utilises AI deep learning technology to formulate algorithm-based predictions on the outcome of legal cases, recently challenged 112 lawyers from separate firms across London to test their skills and see if they were able to beat the computer.
The Lawyer Challenge, which ran in London from 20th-27th October, presented each legal professional with a set of unique scenarios regarding claims of miss-sold PPI and asked them to decide whether or not the case could be won based on their knowledge of the subject.
Astonishingly, out of the 775 predictions submitted in the contest, the final results judged by the Financial Ombudsman Service under the FOIA proved victorious for the AI CaseCruncher Alpha which achieved an accuracy level of 86.6% – over 20% higher than the lawyers who only managed to achieve 62.3%.
Managing Director, Jozef Maruscack, Marketing Director, Rebecca Agliolo and Scientific Director, Ludwig Bull are all co-founders of the company which is believed to have been started during their time studying Law at the University of Cambridge.
Commenting on the results of the event, the CaseCrunch announced:
“The main reason for the large winning margin seems to be that the network had a better grasp of the importance of non-legal factors than lawyers.
“Evaluating these results is tricky. These results do not mean that machines are generally better at predicting outcomes than human lawyers. These results show that if the question is defined precisely (such as – was this complaint about PPI mis-selling upheld or rejected by the FOS), machines are able to compete with and sometimes outperform human lawyers.
“This experiment also suggests that there may be factors other than legal factors contributing to the outcome of cases. Further research is necessary to establish this proposition beyond the specific parameters of this experiment.
“The use case for systems like CaseCruncher Alpha is clear. Legal decision prediction systems like ours can solve legal bottlenecks within organisations permanently and reliably.”
Though they seem a tad self-deprecating when commenting on their success, it cannot be denied this is still a massive achievement for the start-up and it will be very interesting to see where they go from here.
