Artificial Intelligence

Artificial Intelligence is, along with blockchain, one of the technologies that will transform the field of law and finance throughout the first half of the 21st century. However, its application raises many questions: to what extent are AI systems compatible with data protection legislation? Can chatbots such as ChatGPT or Google Bard execute certain tasks hitherto entrusted to lawyers? What legal requirements must be met to enter the Ministry of Economy's AIsandbox?

The boom of virtual currencies is a reality. Thus, the acquisition, holding and transmission of virtual currencies by professionals and individuals, constitutes a manifestation of economic capacity registered by the Tax Agency, which generates tax obligations that must be respected and complied with in order to avoid requirements and/or penalties by the Tax Agency.

In our opinion, there are three major technologies of the Fourth Industrial Revolution that have the capacity to bring about profound transformations in the legal field: distributed protocol technology, artificial intelligence and quantum computing. The first of these is the basis of the token economy as well as a multitude of projects using distributed databases, such as in the field of freight traffic, energy, or many others. The second is artificial intelligence, to which this page is devoted. The third is quantum computing, whose progress threatens to overthrow most of the cryptographic algorithms on which distributed protocol technology and the token economy are based.

The expression "Artificial Intelligence" was coined by the computer scientist Jim McCarthy in the 1950s to refer to all those human cognitive tasks that could be performed (or imitated) by a computer. To this discipline belonged areas as heterogeneous as fuzzy logic, natural language processing or artificial vision.

Within the artificial intelligence techniques, those that are achieving the highest performance and efficiency are those of deep learning(deep learning), in which small computing units, called artificial neurons, interconnect with each other, creating a lattice structure that is capable of finding patterns in data. The learning of these networks is done through a training process, in which the network is fed with a large amount of data in the form of images, text or numbers.

Of the deep learning architectures, two require special attention from the legal field: convolutional networks andtransformers.

Convolutional networks

Convolutional networks are the basis of most computer vision algorithms. Since 2014 they have been capable of performing person identification tasks with superhuman efficiency, and therefore have an ever-increasing capacity to intrude into the individual's sphere of privacy. In our opinion, the implementation of a permanent video surveillance system combined with the use of an AI network capable of identifying individual persons would be digitally equivalent to the continuous presence of an agent who would be verifying without interruption the identity of all passers-by on a street, with the corresponding erosion of the principle of individual privacy recognized by Article 18 of the Spanish Constitution.

The field of intellectual property is also affected by the new artificial vision systems. Some of them, such as the famous Midjourney, are capable of generating artificial images of extraordinary complexity and aesthetic value. This raises the following questions: 

can copyright be levied on AI-generated images? If yes, 

who would they belong to? 

To the algorithm or machine that generated them?

to programmers? 

Or maybe to the hardware owners? 

would there be a moral right of authorship in this case?

As has already been pointed out, these convolutional networks (and deep learning networks in general) must be trained with an enormous amount of data in order to function properly. Unlike what happens with (ordinary) serial programming, in deep learning systems the programmer only partially determines the behavior of the network: he determines the general structure and the hyperparameters of the network. The rest of the parameters are fixed during training. In the latter process, the network must absorb information (entropy) from the images or texts presented to it. This information is stored in turn in matrices of synaptic weights, which determine the intensity of the connections between the different artificial neurons and the behavior of the network as a whole. At this point, questions of a legal nature arise once again: since the information from which the neural network is fed ultimately comes from the training images, 

what would happen if the latter were subject to copyright? 

Could the authors of the images used during the training claim some kind of compensation from the owners and users of the system?

 

Transformers

The second networks to which we were referring, the transformershave revolutionized natural language processing systems, and are the basis of the best machine translation systems in existence today and of chatbots such as the famous GPTChat (from OpenAI), LaMDA, Google Bard (from Google). In the legal field, they could be used to draw up documents, carry out legal argumentation tasks or register rights and documents in public registries. In the latter case, they could even be combined with blockchain technology and virtual reality systems. Think of the case of a hypothetical fully algorithmic registry system, running in the Metaverse and capable of performing registry qualification tasks. In this system, the documents to be registered would be presented to a transformer, which would extract the legal information from the document and structure it according to a template. A smart contract would then check the validity of the transfer and, if valid, would proceed to the registration of the property or right in rem by issuing an NFT.

As the computational power of AI and its ability to process semantic information increases over time, so will its power to reason through legal concepts. It is very likely that if general artificial intelligence is ever achieved (some futurist authors consider that this will happen around 2050 or 2060), deep learning systems will already be capable of performing tasks attributed until now to judges and other legal operators. In the final analysis, the famous Moravec's paradox paradox states that the first jobs to be displaced by AI will be precisely those that require greater cognitive skills, such as those of lawyers or programmers.

Unlike blockchain technology, which is fully consolidated, artificial intelligence is a discipline still in full development, and has only been applied in a very limited way in the legal field. In this regard, it should be noted that the Spanish Ministry of Economy has just launched a test bed(sandbox) that will serve as a test for the future European Regulation on Artificial Intelligence, the articles of which will probably come into force in January 2014. The sandbox will be controlled by the Secretary of State for Digitalization in Artificial Intelligence (SEDIA) and will be endowed with a budget of 4.3 million euros.

 At Vicox Legal we are open, not only to offer advice to our clients, but also to participate in research projects with universities or specialized companies in the sector.

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