What are the main aspects of considering the impact of the development of artificial intelligence on the situation of labour markets in the future?

I have been pointed towards this type of model by my dissertation supervisor. However, I have not been able to find much online about if there is a specific functionality in SPSS for running this kind of model.

Does anybody know how I would go about running a LPM in SPSS?

Thank you.

The quality of the formation and control of the implementation of the current and forward-looking socio-economic policy of the state and/or a local government unit is determined not only by strictly factual considerations concerning the specific conditions and determinants of the country's economic development, the phase of the business cycle in which the economy is, the level of economic growth and prosperity in individual accounting periods in relation to the planned economic policy and the draft state budget, the prosperity of the global economy and international economic relations, etc., but also by the level of reliability, implementation of the objectives of the state and/or a local government unit. but also the level of reliability, achievement of objectives, consideration of certain principles, including public service ethics, reduction of the scale of corruption and embezzlement of public funds, etc. Bearing in mind the aforementioned issues, which significantly affect the quality of implementation of a socio-economic policy programme planned for a specific period of time, it is possible to engage artificial intelligence to shape and control the implementation of current and prospective socio-economic policy of the state and/or local government unit. Of course, it would be up to humans to accept the final shape of the socio-economic policy programme proposal designed by artificial intelligence and to control its implementation. But in a situation of an appropriate increase in transparency and fuller implementation of public functions, the involvement in the role of a multi-criteria, intelligent system designing specific socio-economic policy programmes and their implementation and control of their implementation could significantly increase the effectiveness of the overall economic policy of the state, including issues of reliability, public transparency, improving the process of building a welfare economy. In the process of shaping specific socio-economic policy programmes, in addition to artificial intelligence, business analytics implemented on computerised analytical platforms Business Intelligence and Big Data Analytics may be involved, as well as, as required, other information technologies of the current fourth technological revolution, Industry 4.0 technology. The aforementioned new technologies can also be particularly helpful in developing forecasting models for estimating current and prospective levels of systemic financial risks, economic risks, the indebtedness of the state's public finance system, systemic credit risks of commercially operating financial institutions and economic entities and forecasting future financial and economic crises. Data on the aforementioned systemic risks and forecasting of trends in the economic situation can be helpful for planning the shape and implementation instruments of socio-economic policy for the following quarters and years. Besides, artificial intelligence technologies and other Industry 4.0 technologies may also help in the precise determination of the appropriate budgetary, fiscal and monetary policy instruments for designing interventionist, anti-crisis, pro-development, Keynesian socio-economic policy programmes, i.e. programmes precisely tailored to certain diagnosed determinants shaping the current and prospective economic situation.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this subject?

Please respond,

I invite you all to discuss,

Thank you very much,

Best wishes,

Dariusz Prokopowicz

Year after year, microprocessors will be developed to process ever faster and ever larger data sets. More and more perfect artificial intelligence solutions will also be built, and successive generations of artificial intelligence will be created, e.g. much more perfect than what is currently offered, for example, by the technology on which ChatGPT was developed, which is offered on the Internet in open access. However, the ever-increasing computational capabilities of ICT information technology and the ever-larger, multi-terabyte datasets that can be efficiently processed do not yet ensure the success of a specific, highly intelligent outcome. An important issue is the use of increasingly sophisticated, multi-criteria, complex analytical models, including models composed of multiple algorithms and equipped with the capacity for self-learning and self-improvement using large amounts of data and information retrieved from, for example, the Internet. But it cannot be ruled out that perhaps in the future, a constantly improved artificial intelligence equipped with new Big Data Analytics solutions and full access to data on the Internet may prove to be more intelligent, but it will not be smarter than humans even if it is equipped with a kind of artificial awareness in the future. Perhaps citizens will receive on their smartphones in the future a kind of much more enhanced personal advisors than those currently in use, who will provide highly professional answers to the various questions asked by smartphone users on the basis of data available on the Internet and processed in real time on the Big Data Analytics platform and on the basis of the new generations of machine learning, deep learning and artificial intelligence technology used in these automated advisory solutions. And beyond that, whether such solutions can significantly deepen the issue of new cybercrime techniques and new cyber security systems.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this subject?

Please respond,

I invite you all to discuss,

Thank you very much,

Warm regards,

Dariusz Prokopowicz

The fourth technological revolution currently underway is characterised by rapidly advancing ICT information technologies and Industry 4.0, including but not limited to technologies learning machines, deep learning, artificial intelligence. Machine learning, machine learning, machine self-learning or machine learning systems are all synonymous terms relating to the field of artificial intelligence with a particular focus on algorithms that can improve themselves, improving automatically through the action of an experience factor within exposure to large data sets. Algorithms operating within the framework of machine learning build a mathematical model of data processing from sample data, called a learning set, in order to make predictions or decisions without being programmed explicitely by a human to do so. Machine learning algorithms are used in a wide variety of applications, such as spam protection, i.e. filtering internet messages for unwanted correspondence, or image recognition, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks. Deep learning is a kind of subcategory of machine learning, which involves the creation of deep neural networks, i.e. networks with multiple levels of neurons. Deep learning techniques are designed to improve, among other things, automatic speech processing, image recognition and natural language processing. The structure of deep neural networks consists of multiple layers of artificial neurons. Simple neural networks can be designed manually so that a specific layer detects specific features and performs specific data processing, while learning consists of setting appropriate weights, significance levels, value system for components of specific issues defined on the basis of processing and learning from large amounts of data. In large neural networks, the deep learning process is automated and self-contained to a certain extent. In this situation, the network is not designed to detect specific features, but detects them on the basis of the processing of appropriately labelled data sets. Both such datasets and the operation of neural networks themselves should be prepared by specialists, but the features are already detected by the programme itself. Therefore, large amounts of data can be processed and the network can automatically learn higher-level feature representations, which means that they can detect complex patterns in the input data. In view of the above, deep learning systems are built on Big Data Analytics platforms built in such a way that the deep learning process is performed on a sufficiently large amount of data. Artificial intelligence, denoted by the acronym AI (artificial intelligence), is respectively the 'intelligent', multi-criteria, advanced, automated processing of complex, large amounts of data carried out in a way that alludes to certain characteristics of human intelligence exhibited by thought processes. As such, it is the intelligence exhibited by artificial devices, including certain advanced ICT and Industry 4.0 information technology systems and devices equipped with these technological solutions. The concept of artificial intelligence is contrasted with the concept of natural intelligence, i.e. that which pertains to humans. In view of the above, artificial intelligence thus has two basic meanings. On the one hand, it is a hypothetical intelligence realised through a technical rather than a natural process. On the other hand, it is the name of a technology and a research field of computer science and cognitive science that also draws on the achievements of psychology, neurology, mathematics and philosophy. In computer science and cognitive science, artificial intelligence also refers to the creation of models and programmes that simulate at least partially intelligent behaviour. Artificial intelligence is also considered in the field of philosophy, within which a theory is developed concerning the philosophy of artificial intelligence. In addition, artificial intelligence is also a subject of interest in the social sciences. The main task of research and development work on the development of artificial intelligence technology and its new applications is the construction of machines and computer programmes capable of performing selected functions analogously to those performed by the human mind functioning with the human senses, including processes that do not lend themselves to numerical algorithmisation. Such problems are sometimes referred to as AI-difficult and include such processes as decision-making in the absence of all data, analysis and synthesis of natural languages, logical reasoning also referred to as rational reasoning, automatic proof of assertions, computer logic games e.g. chess, intelligent robots, expert and diagnostic systems, among others. Artificial intelligence can be developed and improved by integrating it with the areas of machine learning, fuzzy logic, computer vision, evolutionary computing, neural networks, robotics and artificial life. Artificial intelligence (AI) technologies have been developing rapidly in recent years, which is determined by its combination with other Industry 4.0 technologies, the use of microprocessors, digital machines and computing devices characterised by their ever-increasing capacity for multi-criteria processing of ever-increasing amounts of data, and the emergence of new fields of application. Recently, the development of artificial intelligence has become a topic of discussion in various media due to the open-access, automated and AI-enabled solution ChatGPT, with which Internet users can have a kind of conversation. The solution is based and learns from a collection of large amounts of data extracted in 2021 from specific data and information resources on the Internet. The development of artificial intelligence applications is so rapid that it is ahead of the process of adapting regulations to the situation. The new applications being developed do not always generate exclusively positive impacts. These potentially negative effects include the potential for the generation of disinformation on the Internet, information crafted using artificial intelligence, not in line with the facts and disseminated on social media sites. This raises a number of questions regarding the development of artificial intelligence and its new applications, the possibilities that will arise in the future under the next generation of artificial intelligence, the possibility of teaching artificial intelligence to think, i.e. to realise artificial thought processes in a manner analogous or similar to the thought processes realised in the human mind.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this subject?

Please respond,

I invite you all to discuss,

Thank you very much,

Best regards,

Dariusz Prokopowicz

There is a growing body of data suggesting that innovative startups may be created using the next generation of ChatGPT-like smart tools and/or whose business activities would be helped by such smart tools and/or certain new business concepts would be based on such smart tools. On the one hand, there are already emerging Internet startups based on artificial intelligence systems specialized in specific areas of creating textual, graphic, video, etc. elaborations that are variants of something similar to ChatGPT. On the other hand, arguably, some of these kinds of solutions may in the future turn into a kind of online business advisors generating advice for entrepreneurs developing new innovative startups.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

Dariusz Prokopowicz