Simply speaking the Artificial Intelligence is some kind of the Digital Brain with all possibilities to process the data in a very fast way using algorithms.
The two issues are especially very significant.
The first one. How to prepare the AI, all kinds of the high quality machine learning to be advanced and useful?
We have to teach them. The key is accessibility of all kinds of data: structured and non structured (the last ones: very often used in the companies in many industrial processes).
If we deliver as more as possible data to train AI they will become more and more effective by aggregation processed data which allow for creation algorithms.
And again it will allow for the next processes of analytical efforts.
This is the best way to optimise many manufacturing processes, all kinds of services, all relations with clients in the real time.
Optimisation means make it better, faster, much more adjusted to the individual expectations of consumers. It is the perfect example of the possibility to shorten many processes.
Something, which is now working and developing step by step, stage by stage, in the consecutive way is changing its nature:
starting to work in parallel. At the same time it is the good and symbolic example of shaping the products and services due to our personal needs as users, consumers, workers, citizens, patients in the healthcare.
What is the most important additionally? All those effective and efficient processes initiated by AI can be possible only thanks to the chain of the Internet of Things. It requires the proper 5 G infrastructure as a basis for the ultrafast connectivity.
The new competitive advantage of using the AI in many industrial and economic activities is coming from the unique possibility as prediction is.
The predictive opportunities are enormous and paradoxically unpredictable. The model is the same when we are using the AI for optimisation of all kinds of processes. As more data we can deliver as much more precise the result will be.
So, everything is about data. The second issue.
Everything is about data, but at the same time is also about the new model of relations between AI and humans.
It is not only the question of the scale of replacing people by machine learning and robots in many areas.
There are many fears and threats related to the impact of the AI on labour market and workplaces.
But if we want to avoid many misunderstandings and social tensions we need to start the explanation: what is going on with AI and us as humans?
We have to understand the problem. What are the threats, but what are the opportunities and how should we be prepared to these new challenges.
It requires the digital literacy in the broad sense addressed to all generations, all social groups, all professional groups, all differentiated culturally groups.
The digital literacy related to the AI development should be focused not only on skills, which will be needed in the new types of jobs under the AI influence.
It also should be focused on competences (crucial for the new model of adaptability to the new requirements in jobs ongoing changes) and attitudes.
The last ones are meaningful to prepare humans for the new model of interactions with all kinds of robots: automated machines, learning machines, high quality Artificial Intelligence.
The AI should not replace us rather we should learn how to cooperate with the AI.
It requires the skills for communication (language, vocabulary, translation and trust). It requires to understand all psychological and ethical dimensions of the model of interaction between us and AI. It should raise the problem of values.
Our ethical needs and principles are linked to the values. The values are linked to cultural patterns – different in many nations and continents. And, cultural patterns – very often are related to the religious values.
So, debating on the future interactions between humans and super smart robots we need to raise all those problems, and solve…. them.
It means that we need to have proper framework: institutional (how they need to cooperate), regulatory (what will need the strong rules, at which areas it would be better to have the soft law: co-regulation, self-regulation, codes of conducts, guidance), educational (new adaptability as a key goal for educational systems), promotional (clear messages and communication allowing to avoid the redundant growth of uncontrolled fears).
The last point. If we want to change the industries and open them for all benefits of AI functioning we need to build the trust.
It is clear that we should take care on secure, protected privacy, explainable, transparent system of the AI development, which at the end will give us the control.
Because technology is for humans, not humans for technology.