Machine learning is a branch within the field of artificial intelligence and computer sciences. It describes a computer capable of learning and improving its performance using data, without being previously programmed to do so. The machine surveys and studies data to construct algorithms that can detect connections and make predictions.
In order for machine learning to be successful, you have to have access to large amounts of data. If you want to teach a machine to identify specific features on an image (e.g. facial recognition), the machine has to be exposed to as many images as possible. The fewer images it has seen, the harder it will be to identify mistakes.
What is machine learning?
Machine learning, as described above, refers to when a computer has the ability to learn from experience instead of executing generic tasks it has been programmed to perform. This means, that the machine is also able to provide better results for its tasks by collecting and utilizing experiences from earlier tasks.
Hereby, the machine is able to become more intelligent over time and by surveying more and more data. This is why machine learning has become an aspect of artificial intelligence that is used in many diverse ways.
Machine learning and legal tech
The legal tech sector has already begun to adopt technologies that imitate human behavior (meaning artificial intelligence), including machine learning that analyzes and detects patterns in its own behavior. You can, for example, use it to analyze data in contracts. If an AI receives a large amount of data in the shape of earlier contracts and furthermore on how these contracts are executed, the technology could - by using machine learning - learn to detect patterns of how successful the contracts turn out.
In some instances, machine learning is used to try to determine the outcome of disputes. This will make it easier to decide, whether to enter into a settlement or to go to court. In the long term, artificial intelligence and machine learning can help to change and automate many of the more manual processes involved in legal work. They will be able to scan and read documents more quickly and thereby reach conclusions more quickly. However, a machine can not be neutral, since it depends on the information it receives. It might be more consistent, but its evaluations will always be based on data that can not be neutral.
Moreover, there are a number of ethical and legal issues regarding the use of artificial intelligence and machine learning. Firstly, it is inappropriate if the machine holds knowledge, it can withhold from people. Secondly, there are many legal questions regarding responsibility, that have yet to be answered.
Digitalization is nonetheless a chance for the legal industry to become more efficient and to have more time to offer legal services and counsel to clients - to become more client-centric.