When artificial intelligence is in evidence and promotes economic, social, and cultural impacts, human skills must be enhanced and praised in relation to artificial intelligence. This chapter was written based on qualitative methodology and exploratory studies by reading current reports and articles at the time of writing. The objective was to highlight a reflection on the learning experience about four behavioral profiles. The potential of artificial intelligence was highlighted, as well as upskilling and reskilling for the professions of the future. It was concluded that understanding the world should be contained in learning experiences and different behavioral profiles have dissimilar ways of thinking and acting. The lack of knowledge regarding the operationalization of artificial intelligence can weaken human options in digital and physical transformation.
Top1. Introduction
Fascination, fear, anxiety, and insecurity have been experienced in contexts that integrate the knowledge society with the economy and artificial intelligence in relation to questions or commands to obtain digital products or answers in interaction on mobile devices in mobilities that require speed and productivity, as well as creativity or disruptive innovations. Professions of the present with projection into the future tend towards greater interaction between human beings and machines, but the results are not yet known, only, for the most squeamish, these interactions are true dystopias.
The evidence is present in articles. Heikkilä (2023), for example, wrote about artificial intelligence language models that are rife with different political biases. The text is based on research that shows that artificial intelligence models also change over time, because companies update data sets and training methods, however the content has a reflective character, because people are using the answers from artificial intelligences as if they were great ideas.
It is a risk to absorb prejudices in texts articulated with the juxtaposition of ideas that are presented in a coherent and highly credible manner. Artificial intelligence is not credited with low qualifications or disqualifications, even though, in common sense, people claim that artificial intelligence can increase the risks of demotivation in acquiring skills and consequently disqualification and low qualifications tend to occur, mainly among younger people.
Modestino, Shoag and Ballance (2016, p. 28) wrote in an article that there was a low qualification for basic skills such as leadership and project planning and for specialized skills such as the development and use of software, therefore, it is believed that artificial intelligence is not the cause of disqualification and low qualification, because, even at a time when there were no artificial intelligences with a user-friendly interface, employers perceived disqualification and low qualification.
The low qualifications mentioned in the areas of leadership, project planning and software development and use are perceived by humans. When the programmed machines for recruitment and selection are more calibrated, perceptions may be different. Tepšić (2020, p. 39) wrote that the advances seen in computer vision include detecting people's expressions or body posture and human behavior are included in recommendations for improving interaction between humans and machines and respecting values and human ethics.
In hiring, there is emotional intelligence and artificial intelligence was not created with empathy and lack of judgment programming. The context of Human Resources and the use of artificial intelligence is one of the knots that must be untied in relation to the behavioral profile, recruitment, and selection in companies. This perception must be part of the list of public policies for work and income generation, even though hard skills may occur in training and the time may be long to acquire skills and technical skills, governments must have the metrics market to determine which training programs will receive public funding.
On the other hand, higher education institutions need to review the prescribed curricula in courses so that new skills and abilities, as well as power skills, are taught and learned in higher education courses. Governance is social and technological, since the technological disruption that is within the reach of (cyber) society is a disruption, according to Hopster (2021, p. 2), of a techno-social nature, because such technologies play roles that affect social dynamics and technique of society. The author includes socially disruptive technologies as technologies and Mengalli and Carvalho (2023, p. 9) added that the concept involves the effects on society and human cognition.
Generative artificial intelligence can be understood as techno-social disruptions or socially disruptive technologies in the sense that Hopster (2021, p. 1) wrote that they are linked to the social sphere in practices and relationships, in addition to being part of people's sensory experience. The way artificial intelligence is used to generate texts, audiovisuals, codes, and digital solutions has changed the way people interact with mobile devices. It is believed that it will be an opportunity to teach prompts so that the solutions generated can be further refined.