Introduction

Today’s world, in all its manifestations, is strongly influenced by the globalization and the liberalization of the means of communication. The development of new technologies and their inclusion in all fields of activity have transformed the way in which individuals perceive the transmission of information. In a world more connected than ever before, journalists are the official authorities responsible for disseminating the information to the public. However, in the online environment, almost anyone can assume the role of the journalist, due to the high amount of data that are made public and the existence of a variety of applications that are easy to use and free of charge. However, the changes suffered in this field are just part of an amalgam of changes that take place in all the fields of activity. The new systems capable of performing tasks better and faster are now obliging humans to adapt and either learn to work along with the machines or find new jobs that could better fit in the current context. Professions are becoming more and more specialized, tasks frequently involve using a computer or operating a machine, and the knowledge acquired during years of study is progressively being replaced by new knowledge that only proves useful in a particular company for a particular job. In large cities, the onset of adulthood inevitably brings with it, much more frequently than in the past, the integration of young adults into corporate structures, where they are forced to work a chaotic and exhausting schedule in order to move up the endless pyramid of increasingly important jobs that require them to acquire a new set of skills, which demand new knowledge in order to operate increasingly complex systems.

In this dynamic, one’s main role is to develop the necessary mechanisms that allow him to adapt:

The common refrain for the expansion of AI systems and process automation is that we are living in a time of beneficial human-AI collaboration. But this collaboration is not fairly negotiated. The terms are based on a significant power asymmetry—is there ever a choice not to collaborate with algorithmic systems? When a company introduces a new AI platform, workers are rarely allowed to opt out. This is less of a collaboration than a forced engagement, where workers are expected to re-skill, keep up, and unquestioningly accept each new technical development (Crawford, 2021, p. 58).

The progressive automation of workplaces leads individuals to perform a limited number of duties, that are usually done by operating a system through certain commands. Starting from the idea that the AI also has certain limitations, in order for a particular task to be performed with maximum effectiveness, a collaboration between machines and humans is required, a process conventionally referred to by researchers as “human-AI symbiosis” (Jarrahi, 2018, p. 7). According to a 2017 study on “Artificial Intelligence, Robotics and their Impact on the Workplace” performed by the IBA Global Employment Institute, we are witnessing a growing need for well-trained individuals in the work field who are able to find creative solutions for work efficiency by using machines. Naturally, on the one hand, we are facing the gradual disappearance of certain professions, including those that follow a pre-established routine (accountant, service operator, clerk) and those that require a more intense physical labor (Jarrahi, 2018, pp. 31–32). On the other hand, the study shows that the most sought-after occupations will be those in the IT field, those involving adult education (organizing specific trainings for a new job or level of activity), arts, legal occupations such as lawyers, doctors and nurses. Although lawyers and doctors will benefit from the help of intelligent robots, in essence, the work they do will not change, as these professions require the creativity and intuition that only humans have.

In order to describe today’s economic field, Cedric Durand uses the term technofeudalisme, composed by the prefix tehno, which refers to the technological dimension of the 21st century, and the term feudalisme, which, refers to an organization in which there is a relationship of subordination between lord and vassals, the latter being obliged to be loyal to the ruler. According to Durand, this structure is based on the following pillars:

1) the continual reinvigoration of economic structures due to the thirst for adventure of the start-uppers; 2) the advocacy of autonomy and creativity in the workplace; 3) a culture of openness and mobility; 4) the promise of shared prosperity; and finally, 5) the ideal of an immortal State (Durand, 2020, p. 13).

Taking Silicon Valley as an example, the author brings up the phenomenon of start-ups, originally designed to provide an opportunity for young entrepreneurs to build a company, but which, in just a few years, have turned into companies with a huge budget, producing forms of entertainment for the whole world, such as: Google, YouTube, Apple, Microsoft, Facebook, etc.

In the article titled “Are Robots stealing our jobs?”, after analyzing the impact that working with robots had over the employees of some of the American states between 2010 and 2015, Eric Dahlin comes to the following conclusion:

I find no evidence to indicate that robots are displacing workers, at least not in the metropolitan areas or years included in this study. Results from the regression models provide some support for the complementary view, the view that workplaces integrate both employees and robots in ways that generate more value for human labor. Specifically, I find that robot incidence positively affects high-skill occupations. Employees in high-skill occupations are the ones that are most likely to create, develop, and program robots (Dahlin, 2015)

He then points out the fact that, when analyzing the work environment from the point of view of the relationship between the employees and the AI, we should also take into consideration the political and the economical context, which, in America, is associated with the need for people in “manufacturing jobs”. According to the researcher, the possibility that human tasks could be entirely replaced by robots is not justified, considering the fact that each job requires decision makings skills involving a combination of moral principles, ethics and empathy, that a machine could not reach, even with a thorough theoretical knowledge of these aspects.

The social context plays a very important role in the dynamics of the relationship between humans and the machines in the workplace. According to Alain Touraine

We can predict that in the centuries to come the characteristic of the 20th century will not be the enrichment of some countries or the rapid changes in techniques in most fields, but the immensely destructive role of what is known as the “great war” and totalitarianism, even if one rejects the use of the term…the world has become increasingly capitalist and an increasingly numerous population has entered market economies whose prime concern is to refuse any regulation or economic, political and social control of the economic activity (Touraine, 1998, p. 125).

What the society primarily focuses on nowadays is producing more and more, in order to satisfy the desires of the consumers who are becoming increasingly individualist. This phenomenon is compared by the sociologist with a “destruction of Society”, provoked by a redefinition of the “social reality” through the process of globalization. Now, more than ever, we are interconnected in a way that allows us to know what everyone is doing. Therefore, we tend to desire or to assume social behaviors that are not necessarily suitable for our historical, cultural and economic background, which results in the pressure felt by many individuals to find jobs that are best suited to the market’s demands, rather than jobs that would be suitable for them or give them a sense of accomplishment.

Considering the information briefly stated above regarding the reshaping of the work field in general, and starting from the premise that machines, through the process of deep learning, could only be programmed to take on jobs that require either a repetitive manual work or one based on a clear set of rules, and that do not require creativity or reflective thinking, one could be tempted to ask what would happen to the other jobs from the humanistic field, that are based on essentially human qualities, such as the field of journalism. In order to be able to offer an answer to this question, it is necessary on the one hand to analyze how the human behavior changes in regards to the society, by exploring his reactions to the physical environment and the increasing preference for the virtual world, and on the other hand, to determine the extent to which the machines could be developed in order to mimic human behavior. This process would help build a mental image of the future of journalism and news, and establish the general direction towards which the new technologies would lead its way.

Starting from these premises, the aim of the present article is to analyze the future of journalism in the context of the emergence of Artificial Intelligence in our lives, with a particular emphasis on the collective mental and the development of a new virtual identity which changes the way we perceive the online news. In order to address the two main points stated above, regarding the nature essentially humanistic of the journalistic profession and determine to which extent intelligent systems could be implemented in order to adapt it to the digitized society, it is important to understand the how the artificial intelligence works, its overall impact on the society, along with the behavioral changes it produces, and subsequently analyze how the news are delivered nowadays.

The shift towards a more digitized journalism

Jon Von Neuman associates the basic functions of the computer with the human brain, presenting the latter in terms conventionally attributed to computer machines. According to him, “The handiest observation about the nervous system is that its functioning is prima facie digital” (Von Newman, 2012, p. 53). Based on this observation, the mathematician associates the transmission and reception of nerve impulses with bit streams, memory with “flip-flop” circuits (Von Newman, 2012, p. 71), the genes with constituent parts of the “analogue area” (Von Newman, 2012, p. 77), with the digital one represented by nerve impulses, and axons with parts of code (Von Newman, 2012, p. 79). Von Neuman thus sets the stage for an approach to digital machines from the perspective of the similarities they have with their own creator. In this sense, humans take on the role of demiurge, whose creation is fundamentally similar to him, but communicates through a different language. The essential point in this dynamic is that the man controls the machines both in terms of the degree of development or power, and in terms of the limits that can be overcome only insofar as the machine is fed with information. However, the degree of functionality of these machines is calculated according to the precision with which they perform the logical mathematical operations:

all the experience of calculating machines shows that, if such a machine has to deal with tasks as complicated as those which the nervous system has to solve, it is necessary to give it the possibility of a fairly high degree of precision, because it is to be expected that the reckoning will be long, and during long calculations, not only do errors accumulate, but also those committed previously during the calculation are amplified by the subsequent parts of the calculation; therefore, a considerably greater precision is required than the physical nature of the problem would seem by itself to require (Von Newman, 2012, p. 82).

With this observation, of colossal importance for all subsequent studies, Von Neuman pertinently argues the idea that, although created in the image and likeness of man, a calculating machine can evolve only to the extent that man finds the necessary resources to improve it, thus setting the stage for further discoveries in this field.

A similar approach from the point of view of the technique used to illustrate the functionality of artificial intelligence belongs to Norbert Wiener, who, in his work “God and the Golem”, approaches this subject also through a comparative study, but from the perspective of the creation myth. Starting from the premise that the reproductive process is a specific characteristic of living beings and taking up the idea that machines are created by man in his image and likeness, the researcher asks to what extent they can become creators themselves. He gives the example of chess players, who are not limited to a series of automatic moves based on predetermined rules, but require a much more complex process, involving anticipation and adaptation to the opponent’s moves. In this sense, the learning process also occurs during the game, and is associated with the players’ ability to decode each other’s modus operandi. In this particular case, given that the machine operates on the principle of “deep learning”, which involves learning all the moves made by all the chess players over time, it is not excluded that it can apply this process even during the game, thus identifying the logical process carried out by the opponent

you can in no way prevent a mechanical player from playing in a more intelligent way. For that, he has to keep the history of previous games. Then, at the end of each game or sequence of games of a certain type, the mechanic will be used in an entirely different way (Wiener, 2019, p. 23).

Two pertinent examples of this are the 1997 chess match in which Deep Blue defeated world champion Garry Kasparov in chess, or the 2016 match between Alpha Go and Lee Sedol. In conclusion, being able to assimilate such a large amount of information in such a short period of time, artificial intelligence is able to develop reasoning even in different situations that arise spontaneously, by correlating already known information with new patterns.

According to Marvin Minsky, the idea of consciousness, although almost impossible to define, naturally involves a complex process of introspection, which relies on the individual’s ability to correctly decode certain signals transmitted to him from the outside world. However, the human mind was essentially designed to perform certain basic functions, used primarily in the struggle for survival, and consciousness in its pure form is very difficult for even the human mind to access:

consciousness is connected with our most immediate memories. This means that there are limits on what consciousness can tell us about itself – because it can’t do perfect self-experiments. That would require keeping perfect records of what happens inside one’s memory machinery. But any such machinery must get confused by self-experiments that try to find out how it works-since such experiments must change the very records they are trying to inspect! We cannot handle interruptions perfectly. This doesn’t mean that consciousness cannot be understood, in principle, it only means that to study it, we’ll have to use the less direct methods of science, because we cannot simply look and see (Minsky, 1985, p. 56).

In order for a machine to succeed in emitting such reasoning it must go through the same processes. Starting from the Heideggerian idea of self, Susser attempts to argue and explain Dreyfus’s theory on the limits of artificial intelligence to show that, in essence, the processes that the machine cannot carry out are the same, but have been perceived from different perspectives:

In sum, on Dreyfus’s account the body anchors us at the center of a perspective; it opens up a world. And it does so in three ways: first, by acting as a sensorial sieve, limiting at the outset what about the physical world can be perceived; second, by structuring the immediate environment around possibilities for action; and third, by pre-reflectively orienting movement toward the optimal relationship to (and understanding of) a given situation or some object in view (Susser, 2013, p. 282).

Susser points out that both Dreyfus and Heidegger attribute the limitations of the machine to the process of adaptability to a given context, a trait inherent to human beings, since only they can learn from experience. In this sense, Susser brings up the concept of “know-how” (Susser, 2013, p. 279), which makes the transition from simply identifying certain things or contexts and defining them, to a certain behavior that the individual adopts depending on the situation. The possibility of developing such a capability among machines is also contained in “The Framing Problem”, which means that “Determining the appropriate context for understanding some phenomenon always requires appealing to another, larger context” (Susser, 2013, p. 280). Accordingly, in order for a particular sign, word or message to be interpreted, it is necessary to place it in a certain context, created by experience, which refers to the set of situations that one encounters. Moreover, the human being possesses a characteristic whose importance is particularly noticeable in moments when he is placed in very unfamiliar situations that resemble those of the past, but are essentially different, namely intuition.

In his paper “The Myth of Artificial Intelligence”, Erik J. Larson takes up Turing’s findings and raises the possibility of a machine capable of developing its own human-like intuition, thus overcoming the limiting and problem solving view of solving certain mathematical problems that are difficult for the human mind. Artificial Intelligence was created by surpassing the basic role of the traditional machine and equipping it with certain value judgments, allowing it to simulate human intelligence in a way that is even closer to reality:

To achieve their goals, what we now call intelligent machine systems must learn something specific. Researchers call this process equipping the machine with certain ‚value judgments’. This does not have the same negative connotation as when thought of in a broader social context, it does not mean that the machine is hard to argue with or has certain pre-fabricated concepts in the general sense of the word. Machine learning bias means that the system is designed and programmed to learn a certain thing (Larson, 2021, p. 28).

Also based on Turing’s predictions for the future of machines, Ray Kurzweil makes a grim prediction for those who relate to Artificial Intelligence with a certain skepticism, fueled by a sense of fear, namely

Machines will convince us that they are conscious, that they have their own agendas, which deserve our full respect. We will start to believe that they are conscious to the same extent that we believe about each other that we are conscious…They will embody human qualities and pretend to be human. And we will believe them (Kurzweil, 2012, p. 95).

Based on these remarks, and taking into consideration the core process of Artificial Intelligence, machines are very similar to humans. The impressive amount of data that they are capable of storing helps them mimic human behaviors, learn different languages and store information on specific fields of activity, as well as accumulating information about relevant past events in a very short period of time, which makes them also capable of predicting what could happen in certain situations by rapidly calculating all the possibilities that they have learned so far. Nowadays, the increasing number of applications that provide us with instant experiences leads to a change in the individuals’ identity, which progressively becomes fragmented between the physical and the virtual body. Castells refers to this radical change by introducing the concept of “new society” (Castells, 2000, p. 693). According to him, it consists of three main fields, namely: the technology, which involves the emergence of the new technology which leads to “the formation of new forms of social organization and social interaction along electronically based information networks” (Castells, 2000, p. 693), the globalization, understood as the technological, organizational, and institutional capacity of the core components of a given system to (e.g. the economy) to work as a unit in real or chosen time on a planetary scale (Castells, 2000, p. 694), and the culture manifested “in an interactive electronic hypertext, which becomes the common frame of reference for symbolic processing from all sources and all messages” (Castells, 2000, p. 694).

Castells therefore pictures a society which finds itself in a perpetual transition between the real and the virtual world, which makes it assume new behaviors and manifest different expectations, depending on the ever-changing social context.

In this dynamic, where everything is interconnected – the individuals’ need for progress leads to the apparition of more specialized systems and, in turn, their way of functioning produces a shift in the humans’ behavior that originates in the individuals’ inherent self-regulating mechanism – the way in which the news are delivered, and the subjects of interest to the public also play an important role that needs to be analyzed. Although the social media platforms grant the access to an impressive amount of people all around the world, a power relationship becomes increasingly obvious in today’s society. According to Van Dijk, each category of people exercises its particular power over the domain it specializes in. However, this is not the case with social media:

who has preferential access to journalists, who will be interviewed, quoted and described in news reports and whose opinions will thus be able to influence the public? That is, through access to the mass media, dominant groups also may have access to, and hence partial control over the public at large (Van Dijk, 1996, p. 86).

During time, social media has become the place where individuals exercise their power, often based on economic and political reasons. In an attempt to clarify this topic of interest, Van Dijk stresses out the importance of the influence exercised by powerful individuals over the media:

we may assume with the critical theorists that media practices usually remain within the boundaries of a flexible, but dominant consensus, even when there is room for occasional dissent and criticism. Fundamental norms, values, and power arrangements are seldom explicitly challenged in the dominant news media. In fact, this latitude of dissent is itself organized and controlled. Opposition, also by the media, is limited by the boundaries set by the powerful institutions, and may thus also become routinized (Van Dijk, 1996, p. 43).

In the study “Gender and Work in Journalism”, Nicoleta-Elena Apostol defines journalism as a semi-profession, justifying her opinion by the fact that “journalists have not obtained – and they have not systematically sought to obtain in the last decades – the necessary help to regulate their own occupation” (Apostol, 2018, p.22). This observation is based on the lack of a pre-established and generally accepted code of ethics that applies to all journalists, regardless of the institutional framework in which each of them carries out their profession. In this respect, the world of journalism remains an open field in which everything and nothing is possible, with a freedom of expression that cannot be sanctioned, but which can be limited according to the interests of the heads of journalistic organizations. According to the author, authoritarian regimes have greatly limited the freedom of expression of journalists, who have not made enough progress in this direction since 1989:

For an occupation to develop its activity in an autonomous way, it is not enough to have a culture, but it requires a structure, an institutional framework that can offer the necessary resources to nourish professionalism (Apostol, 2018, p.33).

However, nowadays, the new technologies are managing not only to progressively rectify this situation, but also to encourage the creation of groups that adhere to all kinds of opinions, which they present as absolute truths.

Online journalism

In order to analyze and attempt to predict the future of journalism in the context of the AI development, one should firstly be aware of the main responsibilities defining the work performed by the journalist, out of which, the most important is the process of investigation that not only implies reviewing, comparing and contrasting resources, but also analyzing the online trends and types of material that appeal to the public. Since investigation is the first and probably the most important stage of writing an article, journalists are sometimes confronted with a situation in which they need to conduct an exhaustive research on a certain subject, which requires the time and energy that could negatively impact the article, by either delaying its publication, or providing incomplete information. This requires reviewing a high number of different resources, available on different platforms, corroborate the facts and publish an article that should be both informative and objective. Another task that could sometimes become too laborious is the transcription of the interviews. As well as the investigation, the interviews are also part of the research conducted before the publication of the article, which can also impact the news making process. In order to facilitate this process, some news agencies have already started to use the help of the AI. In the article “How Artificial Intelligence can save Journalism” Patrick White mentions “The Canadian Press” and the “Agence France Presse” as two of the most important news agencies that have already integrated AI in the process of producing the news: “AI robots analyzing large databases can send journalists at Boomberg News an alert as soon as a trend or anomaly emerges from big data” (White, 2020). Francesco Marconi also stresses out the positive role of the AI in the process of news making by their capacity of facilitating the data gathering process:

implement data-driven decisions, foster collaboration among the editorial team and the rest of the newsmakers, and look beyond the industry to find and implement best practices that help teams better understand their audiences, new technologies, and generation shifts (Marconi, 2020, p. 54).

Considering AI’s capacity of memorizing and synthesizing an impressive amount of information in only a few seconds, by collaborating with such intelligent machines, the work of the journalists could become more efficient, thus insuring a faster delivery of the news. Society’s preferences for certain subjects is constantly shifting and the trends initiated on the social media platforms are gaining more popularity than before, as more people are starting to gain popularity online. Using this as a premise, in order for an article to be considered good and to acquire visibility, it needs to address as much as possible these new emerging needs and social media trends. What does this mean for the journalists? Will they have to stay constantly connected in order to be able to keep up with the society or will the machines take their place? Li Lestrade, the head of Content Development, Mitt Media attempts to answer this question by affirming:

A really good robot text can have a bigger impact and be more read than a really good news article, but only if its a topic reader really cares about. Each article reaches a smaller group of readers on average, but in total, we get an exchange on par with anything written by our most-read reporters (WNIP, 2019).

According to her, bots can only surpass the work of a journalist if the readers manifest a higher interest on the discussed topic. This means that, the extent to which the machines could fully take on the role of the journalist greatly depends on the subject it presents. An interesting topic prevents the reader from unconsciously searching for flaws in the article. However, a more difficult or sensitive topic should be covered by humans, since it is not capable of “selling itself”, and therefore needs a creative mind in order to stand out. As fascinating as they are, machines also have limitations that can be detected especially in domains that require a higher level of creativity in order to produce content. This is the case of journalism, where the final result represents a combination between research and delivery, out of which, the second one, besides the writing skills, requires complex qualities, such as: a deeper understanding of both the situation and the context in which it occurs, empathy for the people and situations described, creativity in emphasizing the most relevant details and developed communication skills. Just by taking into consideration the communication skills as an example of a characteristic only belonging to humans, one could argue that there are already robots capable of engaging in a dialog, which would not be false.

The act of communication involves more than the simple act of delivering a message, but also gestures, a certain tone of voice, an appropriate choice of words that is meant to attribute a certain signification to the message, the language itself, that not only reflects the complexity of one’s vocabulary, but can reveal parts of one’s identity. By taking into consideration the aspects only briefly presented that make humans irreplaceable by the machines, one can conclude that there is no need to take the example of the Luddites and take radical measures against the AI, but use it in order to facilitate our existence.

Even though the AI is becoming increasingly powerful, acquiring knowledge and developing capacities that could make them resemble to humans at a superficial look, there are some characteristics that are only inherent to human beings and that are too complex to be reproduced by the machines. In the article “Why not a sociology of the machines? The case of sociology and artificial intelligence”, Steve Woolgar attempts to demonstrate the progressive evolution of the AI in solving problems, by giving the example of the test performed by Turing in order to establish the limits of the artificial intelligence compared to the human one:

The difficulty comes when the distinction between surface signs and underlying reality is expressed as a fundamental and inviolable principle of scientific procedure. In this view, the distinction between “what it is to be intelligent” and “how we tell something is intelligent” corresponds to a distinction between the metaphysical essence of an entity (what it is to be an X) and its epistemological apprehension (how we know something is an X) (Woolgar, 1985, p. 562).

The metaphysical essence of the entity, commonly referred to as the soul is a particularity of the living creatures. However, given its extremely abstract nature which makes it impossible to prove or to analyze the way in which intelligence influences it, in order for a test to make the difference between a human being and an all-knowing machine, its questions should require a high degree of EQ from the respondent’s side.

The technological boom and the diversification of the means of transmission of information have opened the way to fake news that have monopolized the online press, making the public increasingly unable to differentiate them from real news. Another consequence of the intrusion of new technologies into journalism is the decision of most newspapers to limit themselves to the online version, despite the paper version, that no longer meets the expectations of an audience who wants to be able to get the information as quickly as possible only with a click. Faced with this reality, we ask ourselves the following question: How much of the information we find so bluntly exposed online is objective?

Aware of the danger represented by the constant reinterpretation of information, some social media websites have started to use bots in order to identify the sources of fake news and disclose their names to the public in order to prevent further dissemination of fake news. An example of this initiative is illustrated by the partnership between Facebook and FactCheck.org (Kiely, 2017). Facebook provided financial support to the platform in order to investigate and determine the websites that are actively spreading fake news. The websites mentioned in the list are followed by a hyperlink and a small description that is meant to clarify whether they are actively publishing fake news or if they are just using real news and caricaturize the facts. The purpose of this initiative is to grow awareness and to help the users better make the difference between what to trust and what they should avoid. Even though this initiative prevents people from trusting certain websites and develops their capacity of selection, the open access platforms still encourage the public to actively modify and publish information that reflect a personal opinion rather than an objective presentation of the facts from the perspective of a witness. However, the Facebook News Feed is designed in such a manner that it allows users to publish and consume content very easily and fast, which also involves the news: “By August 2017, according to a research by Pew Research Center, two-thirds of Americans obtained their news from social media, with a majority relying on Facebook” (Whittaker, 2019, p.60).

When faced with such an impressive amount of information coming from different sources, one can either believe everything, or develop what Mikael Klintman calls “knowledge resistance” (2019). According to him, this phenomenon describes one’s reluctance to believe even information supported with hard evidence. Thus, the society finds itself in the difficult position of no longer being able to discern between the reality and the illusion of a reality so veridical and so eloquently described by the media that it could easily pass as the truth. However, considering the fact that all decisions are based on the experience, knowledge or a context a priori created, one can only accept the reality that feels most familiar:

A great part, perhaps the greatest part, of the business of our reason consists in the analyzation of the conceptions which we already possess of objects (Kant, 2014, p. 53).

Therefore, taking into consideration the multitude of backgrounds and cultural identities that intertwine within the society, it is only logical to assume that, as the Latin saying so bluntly states, Quot capita, tot sententiae, suus cuique mos est (“So many heads, so many minds, each has his own way) (Terence), when looking for a piece of information online, one can find countless resources on the same topic, especially if it is a political one. The tools one uses nowadays in order to publish content online are very diversified, ranging from social media platforms, to editing Wikipedia pages. However, as Dan Gillmor keenly remarks, by taking into account today’s technology, one still needs to have at least a basic knowledge of computers in order to benefit from an increased visibility, which limits in one way or another the access to the platforms, while also functioning as a selective method. On the other hand, technology is developing at a higher pace and the majority of social media platforms allow users to create and publish content without having to exercise their knowledge of informatics:

The reporter of the future-amateur or professional-will be equipped with an amazing toolkit. But reporting is more than collecting facts, or raw data (Gillmor, 2004, p.163).

Conclusion

Considering the arguments briefly stated in this paper, and the everyday influence exercised by the Artificial Intelligence over the society, we become witnesses to a digital revolution that touches all the areas of activity, which accelerates the human’s evolution process. Whether consciously or unconsciously, under the influence of its own creation, the individual develops new characteristics, which make him more efficient than ever. In the specific sector briefly described in these pages, namely the journalistic field, the use of the new technologies plays an essential role, mainly because they make news travel faster and further. The physical boundaries imposed by the body are disappearing in the online environment, which enables us to connect with other individuals at a global level, and helps us acquire a limitless amount of information, which inevitably also increases our self-awareness. However, it is important to be aware that the purposes for which we use the Artificial Intelligence need to be also in line with the ethical principles.

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