1Every day we hear news about the formidable developments in artificial intelligence, its current and potential applications, and the profound labor, economic and social impact that its progressive implementation in various professional sectors is causing and may cause in the immediate future. Undoubtedly, the growing assumption by algorithmic systems of certain tasks hitherto performed exclusively by humans (from the automation of clinical diagnoses to the performance of stock market operations, including autonomous driving), has raised delicate ethical and legal questions that the jurist, attentive to reality, has prepared to confront.
22 In this context, the introduction of predictive coding tools has made it possible to alleviate these tensions in the procedural system. These tools use active learning algorithms that “learn” the criteria of legal relevance in relation to a particular case by analyzing a subset of statistically significant documents that are previously “coded” manually (i.e., each of them classified as “relevant” or “not relevant”) by a lawyer knowledgeable about the case30 . Based on these examples, the system generates a predictive model that subsequently applies all the documents in the set to be reviewed, classifying them as relevant or not relevant and prioritizing them by assigning each of them a specific degree of probability of relevance, which makes it possible to directly discard those that do not reach a certain minimum degree of probability.
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We all imagine a time when AI is practically personified. We perceive a future in which robots will be humanoids with the ability to learn, perceive and act like a person.
True, machines already understand verbal commands, distinguish images, drive autonomous cars, and beat us when we play against them. How long might it be before they walk among us?
The US government report focuses on what we might call general intelligence tools: machine learning and deep learning. This is the technology that has managed to play ‘Jeopardy’ well or beat the human masters of ‘Go’, the most complicated game ever invented.
These current artificial intelligence systems are capable of handling large amounts of data. They perform complex calculations very quickly, but they lack one element that will be key to building the intelligent machines we envision having in the future.
The most basic types of AI systems are purely reactive. They do not have the ability to form memories. Nor can they use past experiences on which to base current decision-making.
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The IEEE, created in 1963, is the largest association in the field of electrical and electronic engineering, whose objective is the advancement of technology and education in these areas, as well as in computer science and similar disciplines. The organization is composed of more than 423,000 members throughout more than 160 countries and produces 30% of the literature.
The researcher César Montenegro of the Intelligent Systems Group (ISG) research group was the winner of the “Aguathón”, a competition that seeks to model the behavior of the level of the Ebro River as it passes through the city of Zaragoza, based on the levels observed at the Ebro station in Tudela. A total of 89 groups have registered for the contest.
“The collaboration between the three entities has been very positive. Each of them has contributed the best of their knowledge on the subject and, in the end, the result has been very satisfactory because it represents a big step in the development of the Industry 4.0 concept and in the ‘collaborative robot’ project. The collaborative environment is becoming increasingly important worldwide, eliminating barriers in the work environment, and projects like this one highlight this new revolution in the work environment,” said Basilio Sierra, professor at the Faculty of Computer Science. The video shows the skills incorporated in the prototype.
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An artificial intelligence arms race is a competition between two or more states to equip their military forces with the best “artificial intelligence” (AI). Since the mid-2010s, many analysts have argued that such a global arms race to improve artificial intelligence has already begun.
China published a position paper in 2016 questioning the adequacy of existing international law to address the eventuality of fully autonomous weapons, becoming the first permanent member of the UN Security Council to address the issue. In 2015, the United Kingdom government issued a position paper on the issue of artificial intelligence (AI).
In 2015, the UK government opposed a ban on lethal autonomous weapons, stating that “international humanitarian law already provides sufficient regulation for this area,” but that all weapons employed by the UK armed forces would be “under human supervision and control.”
The South Korean Super aEgis II machine gun, introduced in 2010, is used in both South Korea and the Middle East. It can identify, track and destroy a moving target at a distance of 4 km. While the technology can theoretically operate without human intervention, in practice security measures are installed to require manual entry. A South Korean manufacturer states, “Our weapons do not sleep, as humans must.They can see in the dark, as humans cannot. Therefore, our technology fills the gaps in human capability,” and they want to “reach a point where our software can discern whether a target is a friend, an enemy, a civilian or a military.”