Just how artificial is Artificial Intelligence? Facebook created a PR firestorm last summer when reporters discovered a human “editorial team” – rather than just unbiased algorithms – selecting stories for its trending topics section. The revelation highlighted an elephant in the room of our tech world: companies selling the magical speed, omnipotence, and neutrality of artificial intelligence (AI) often can’t make good on their promises without keeping people in the loop, often working...
In much of machine learning, data used for training and inference undergoes a preprocessing step, where multiple inputs (such as images) are scaled to the same dimensions and stacked into batches. This lets high-performance deep learning libraries like TensorFlow run the same computation graph across all the inputs in the batch in parallel. Batching exploits the SIMD capabilities of modern GPUs and multi-core CPUs to speed up execution. However, there are many problem domains where the size and structure...
Michael S. Pardo and Dennis Patterson (University of Alabama School of Law and European University Institute) has posted The Promise of Neuroscience for Law: 'Overclaiming' in Jurisprudence, Morality, and Economics (Patterson, Dennis, and Michael S. Pardo (eds.). Philosophical Foundations of Law and Neuroscience. Oxford University Press, 2016, 231-248) on SSRN. Here is the abstract:
Claims for the relevance and importance of neuroscience for law are stronger than ever. Notwithstanding persuasive...
The results from this analysis show that the likelihood of cert grants may be at least somewhat affected by when petitions are filed. There are periods of time both according to the calendar and according to the number of petitions filed that may play a role in the likelihood of a cert grant. The length of time that the Court sits on cert petitions may also indicate a decreasing likelihood of a cert grant, at least according to data from the 2015 and 2016 Supreme Court Terms. While Supreme...
Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. Our model leverages the random forest method together with unique feature engineering to predict nearly two centuries of historical decisions (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice...
Recently, Lemonade reported a claim handling world record. The insurer reported a claim settlement speed record – 3 seconds and no paperwork.
According to the insurer, a policyholder submitted a theft claim for a $979 Canada Goose Langford Parka on Dec 23, 2016. Within seconds, AI Jim, Lemonade’s artificial intelligence claims bot, reviewed the claim, cross referenced it with the policy, ran 18 anti-fraud algorithms on it, approved it and sent wiring instructions to the bank, informing the policyholder...
Technology advances in both law and the wider world will mean greater reliance on analytics in legal technology.
Big data is just getting, well, bigger. And while legal technology’s progress has been slow in relation to technology changes in the wider world, legal professionals are increasingly turning to one technique to handle emerging big data challenges of the day.
That approach is data analytics—a practice in which data is extracted for categorization and analysis by a variety of techniques...
Service (getservice.com) is my favorite new company. In fact, my experience using Service was so positive that it has impacted the way I’m thinking about legal disruption — and Service isn’t even a legal tech company per se. But before I explain the broader implications, first a word on Service.
So, as the annual Legaltech show in New York approaches (which, this year, has rebranded as Legalweek), some of the companies I’m following most closely are tech enabled service companies...