How will the AI ​​perceive time

Artificial intelligence: This goes too far!


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Beginning with the present day, the world ceaselessly produces an ever more exact copy of itself. Its nature is duplicated in the form of digital data streams with increasing richness of detail, which depict more and more diverse situations in real time. The growing number of sensors on the surfaces of our physical, private and professional existence, combined with the efficiency of artificial intelligence (AI), creates the industrial horizon of our time - and that of the third decade in the 21st century. The phenomena of reality are recorded and immediately quantified, creating a space with a practically infinite variety of functions.

The AI ​​is currently provided with triple competence. On the one hand, it can handle all kinds of situations interpret. At the beginning of the 1990s, so-called expert systems were created that were able to automatically derive diagnoses of the status of certain systems from data material. For example from jet engines.

The following decade saw a leap in what is known as data mining: programs learned at high speed Capture data correlations and thus Exposing trendsthat until then had eluded human perception. For example, the creditworthiness of a loan seeker can be calculated several years in advance based on numerous criteria.

The AI ​​is also able to formulate recommendations. For example, it can suggest that a company should give preference to a certain subcontractor based on a number of parameters. Another application is the smartphone. Its geographic location allows users to see offers in the immediate vicinity that are tailored to their profile. After all, the AI ​​is used to autonomous decision making empowered, even able to act without human control , when, for example, automatic trading systems in high-frequency trading buy or sell securities independently.

All of these systems master self-learning, that machine learning, and therefore perfect themselves continuously. With this still quite new ability, the behavior of a system is not determined in advance by its program, rather it is the basis from which the level of competence is regularly increased according to the experience of the system.

First and foremost, it is the powerful, money, manpower and infrastructure companies in Silicon Valley that are at the forefront of AI research and development. For example Alphabet, whose laboratories are working with Google Brain, DeepMind and a number of other projects on the automated interpretation of language. Or IBM, whose system Watson designs structures for automated knowledge. Or Facebook and Microsoft, who are working on image recognition software or chatbot programs that can communicate with users. They all want to dominate the market of the rapidly growing "cognitive computer science", which takes the place of the programming and its forerunner, the computing computer science. It heralds the now emerging era of symbolic superiority of algorithmic evaluation and decision-making in human affairs.

The Google Car is particularly symbolic: the sensors in the car record vast amounts of data, mainly those relating to the immediate surroundings and other vehicles. They also have access to information such as road maps and tap data from a large number of servers, such as reports of traffic disruptions. Uninterrupted and in real time, new options for action are derived from the various data. This system corresponds entirely to the most recent mission of artificial intelligence: It should compensate for our inadequacies and guide us safely through the best of all worlds.



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The human factor is neutralized. This is because the vehicle uses AI to analyze the facial expressions of its occupants, interprets their physical or mental state or the conversations between the passengers, and then carries out a wide range of activities to stimulate not much different from an animator in the holiday club. If, for example, fatigue is detected, the system suggests a stop at the nearest pharmacy or a break in a hotel or restaurant that matches the profile of the passengers. Perhaps it also stimulates a meeting with friends who are nearby. The optimal congruence of things through omniscient systems creates exactly the perfect world that was previously beyond the human imagination.

At the same time, the AI ​​is moving step by step towards the guide human decision-making. The Watson variant from IBM, designed for use in the healthcare sector, analyzes the patient's medical records. She makes diagnoses, writes prescriptions, lists the side effects and controls them for each individual case. She reads the scientific articles available online and is constantly expanding her specialist knowledge by collecting and evaluating appropriate information. Some health insurances are already giving preference to this apparently objective and cold assessment over medical competence.

Eric Sadin

is a writer and philosopher. His latest book is called La Silicolonisation du monde - L’irrésistible expansion du libéralisme numérique (L’échappée, October 2016). Sadin regularly publishes commentaries in French daily newspapers.

BakerHostler, one of the most important American law firms, uses Ross, a program that sifts through mountains of documents and puts each case into a larger context. Ross is always up to date and cites any decision deemed relevant if it could become relevant to the ongoing proceedings. The principle is reminiscent of the clone Mimi, female figure in the Swedish series Real Humans, who works in a law firm in a row. Your superiors panic when important clients appear unannounced to review momentous decisions. Mimi immediately connects her cerebral processors to databases and, thanks to her high processing speed, puts together a flawless dossier of the relevant legal cases in front of her amazed colleagues at the speed of light.