Disappointment in AI?

The way we understand Legaltech.

2018 was characterized by disappointments in the results of using artificial intelligence in the direction of legaltech. I think in 2019 frustration will only increase.Despite the fact that there will be a huge number of finished products based on artificial intelligence.

Why do law firms, individual lawyers, and the entire legal market become frustrated?

In one of my articles, I quoted one of the three laws of Arthur Clarke: ”Any sufficiently advanced technology is indistinguishable from magic.”

Dear friends! You can not take a quote literally! Technological progress is not a magic wand, but hard work.

The reasons for the lack of results and, as a result, disappointment, lie not in the capabilities of artificial intelligence, but in your heads. Yes, it is in your heads.

It is impossible to imagine that after the company decides to introduce artificial neural networks into its technological process, approves the budget and hires a programmer, we will immediately get the result.

We won`t get it soon.

But why?

Artificial intelligence or artificial neural network?

The first thing we need to do is to separate the terms: artificial intelligence and artificial neural networks. Artificial intelligence is more of an academic term. This is the tool that is not yet available, and on which the best minds and institutions of our time are working. AI can think and learn by itself, so you just give it a task and then wait.

The AI will find the solution. If the AI does not have enough knowledge or information to solve the problem, it will find needed data on its own. Like a living person, AI can make a mistake when solving a problem, but after trials and errors it’s made, the result of AI can be comparable with the result of a person. What do we get when we use AI? — The same human factor. Let’s name it `Artificial factor`.But the essence does not change, the artificial factor, as well as the human factor, will make mistakes and sometimes give the wrong answers. Therefore, let the scientists continue researching Artificial Intelligence, solve its learning tasks, and we will observe the results with interest. Usage of AI in business is impossible today. Attempts to use artificial intelligence are kind of experimental.

Artificial neural networks is another story.This is a product that is absolutely ready and which is already widely used. Artificial neural networks are in fact a manager who is trained to solve a narrow problem.If an artificial neural network is trained to answer customers’ phone calls, then you can not give it a task to write a business letter or calculate an accounting report. It does not know how. Just like you do not hire a specialist in social networks for the position of an accountant, it isn’t damn effective. For each job, you hire particular professional; in the same way, an artificial neural network can perform only one (or several similar) narrow task. Neural networks can perform much better with one task. They do not get tired, do not get nervous and do not get sick. So when we are talking about using AI in business, we are talking about using artificial neural networks. We will not be able to change the traditional terminology that has come into life in numerous articles, but we must understand this fundamental difference between Artificial Intelligence and artificial neural networks.

We use an artificial neural network.

You have decided to make your business technologically advanced. Or you need to reduce the costs of your business.You made the decision to use artificial neural networks and not to be disappointed in the result. Great, where do you start then?

Definitely not from the high-profile meeting.

In your company, all employees have their own responsibilities. It doesn’t matter whether job responsibilities are defined verbally or printed in the contract. These official duties are the first step for using artificial neural networks. These are the functions that the program will perform when you turn it on.

Let’s analyze the introduction of artificial neural networks with an example.

Run a program that will help your secretary. We analyze the job description of the secretary and write a task for the neural network: The neural network should read the received letter and prepare an answer to it. After approval of the chief, the neural network must send a response to the recipient.

During the first stage, when we receive a letter, we need a neural network to recognize information from the text and the picture (the sender’s logo).We choose a ready neural network from a set of available solutions and we receive sorting of letters. Let your secretary describe the algorithm by which she/he sorts incoming emails. For example, from contractors to the production department, from the bank to the chief, and so on. In the same way will make a neural network, after text recognition.

Once the neural network recognized the letter from someone, it can already begin to generate a response, in which the sender of the letter is in the recipient’s place. It is simple and obvious, hardly arguable. At the second stage, after recognizing the text of the letter, the neural network is able to understand the context by the keywords and context: they ask you to pay the bill, sign a contract or change the time of the meeting etc. After analyzing the text and understanding of the context, neural network can already compose a draft letter. Now it can be checked and sent. And all this takes 10–20 seconds. Neural network can prepare the answer to the letter faster than you can actually read that letter itself. Be sure to check the result of the neural network, correct its errors and very soon, you will see that errors appear less and less, and the neural network begins to use your style of answers. How can you be disappointed in such a miracle?

The main thing is to be ready to spend time on a rigorous technical task for an artificial neural network, do not be lazy to teach it (correct errors) and you will get 21st century-satisfaction from the results.

Looking forward to your comments and I am ready to help with a technical task for the use of neural networks. Popularization and practical application of artificial neural networks is a very interesting activity.