Applied Artificial Intelligence - Science topic

Artificial intelligence technology has significantly enriched the range of tools available to researchers and scientists, supporting them in data analysis, writing publications, organizing work, and automating repetitive tasks. In the field of managing scientific literature, applications like Mendeley and Zotero enable document organization, automatic citation formatting, and recommendations for new publications. For data analysis and statistics, tools such as IBM SPSS Modeler and RapidMiner are particularly useful, as they employ machine learning algorithms to analyze large datasets, while Google Colab offers access to AI libraries and a Python environment for advanced data processing. In writing and editing scientific texts, applications like Grammarly and Writefull enhance linguistic quality and clarity, while ChatGPT supports the generation of summaries and research ideas. For data visualization, Tableau and Power BI are indispensable, as they integrate AI to automate trend analysis and suggest visualization formats, with BioRender aiding in the creation of aesthetically pleasing scientific diagrams. In natural language analysis, Leximancer and NVivo facilitate qualitative research by automatically identifying key themes and patterns in textual data. Teamwork organization is made easier with tools like Notion and Slack, which leverage AI features to manage projects and improve communication. For exploring scientific literature, applications such as Semantic Scholar and Connected Papers allow users to uncover relationships between articles and recommend key publications. These tools significantly streamline research processes, save time, and open new opportunities in science, adapting to the specific nature of the research being conducted and the needs of research teams.

In view of the above, I address the following question to you:

Please feel free to respond.

I invite you to join the discussion and scientific cooperation.

Thank you very much.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

I invite you to familiarize yourself with the issues described in the article given above and to cooperate scientifically on these issues.

Kind regards,

Dariusz Prokopowicz

In recent years, there has been a growing scale of implementation of Industry 4.0/5.0 technologies, including Big Data Analytics, Data Science, multi-criteria simulation models, digital twins, additive manufacturing, Blockchain, smart technologies and also generative artificial intelligence to business entities in order to improve internal information systems of the Business Intelligence type supporting the management processes of a company, enterprise, corporation or other type of business entity. The Covid-19 pandemic has accelerated the processes of digitizing the economy. The importance and application of analytics conducted via the Internet and/or using data downloaded from the Internet is also growing. An example is sentiment analysis conducted on data downloaded from the Internet implemented on Big Data Analytics platforms being an additional research instrument of conducted market research, marketing research as an additional source of data for conducted Business Intelligence type analysis. This is particularly important because in recent years the importance of Internet marketing, including viral marketing, Real-Time marketing carried out on social media sites is increasing. Accordingly, in many industries and sectors of the economy, there is already an increase in the application of certain Industry 4.0 technologies, i.e., such as Big Data Analytics, Data Science, cloud computing, machine learning, personal and industrial Internet of Things, artificial intelligence, Business Intelligence, autonomous robots, horizontal and vertical data system integration, multi-criteria simulation models, additive manufacturing, Blockchain, cybersecurity instruments, Virtual and Augmented Reality and other advanced data processing technologies Data Mining. Besides, using Big Data Analytics, interesting research is being conducted in the field of the issue: Analysis of changes in the relationship of consumer behavior in the markets for goods and services caused by the impact of advertising campaigns conducted on the Internet, applying new Internet marketing tools used in new online media, including primarily social media. The growth of behavioral economics and finance, including the analysis of the determinants of media formation of consumer opinions on the recognition of the company's brand, product and service offerings, etc., through the growth of Internet information services, including social media portals. Currently, online viral marketing based on social media portals and customer data collected and processed in Big Data Analytics databases is developing rapidly. In recent years, new online marketing instruments have also been developed, applied mainly on social media portals and are also used by e-commerce companies. Internet technology companies and fintechs are also emerging, offering online information services to assist marketing management, including in planning advertising campaigns for products sold via the Internet. For this purpose, the aforementioned sentiment analyses are used to study the opinions of Internet users regarding the prevailing awareness, recognition, brand image, mission, offerings of certain companies. Sentiment analysis is carried out on large data sets taken from various websites, including millions of social media pages, collected in Big Data systems. The analytical data collected in this way is very helpful in the process of planning advertising campaigns carried out in new media, including social media sites. These campaigns advertise, among other things, products and services sold via the Internet, available in online stores. In view of the above, the development of e-commerce is mainly determined by technological advances in ICT information technology and advanced data processing technology Industry 4.0, as well as new technologies used in securing financial transactions carried out over the Internet, including transactions related to e-commerce, i.e. blockchain technology, for example. In my opinion, ongoing scientific research confirms the strong correlation occurring between the development of Big Data technologies, Data Science, Data Analytics and the efficiency of the use of knowledge resources. I believe that the development of Big Data technology and Data Science, Data Analytics and other ICT information technologies, multi-criteria technology, advanced processing of large sets of information, Industry 4.0 technology increases the efficiency of the use of knowledge resources, including in the field of economics, finance and organizational management. In recent years, ICT information technologies, Industry 4.0, etc., have been developing particularly rapidly and are being applied in knowledge-based economies. These technologies are being applied in scientific research and business applications in commercially operating enterprises and in financial and public institutions. In view of the growing importance of this issue in knowledge-based economies, it is important to analyze the correlation between the development of Big Data technologies and analytics of Data Science, Data Analytics, Business Intelligence and the efficiency of using knowledge resources to solve key problems of civilization development. Analytics based on Business Intelligence, in addition to Data Science, Big Data Analytics are increasingly being used in improving business management processes. The development of this analytics based on the implementation of ICT information technologies and Industry 4.0 into analytical processes has a great future in the years to come. In recent years, ICT information technologies, Industry 4.0, etc., have been developing particularly rapidly and are being applied in knowledge-based economies. In addition, the application of artificial intelligence technologies can increase the efficiency of the use of Big Data Analytics and other Industry 4.0/5.0 technologies, which are used to support business management processes.

I have described the issues of application of Big Data and Business Intelligence technologies in the context of enterprise risk management in the following article:

APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

In addition, I described the issues of opportunities and threats to the development of AI technology applications in my following article:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

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

What do you think on this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

Dear colleagues,

I would like to announce that we have started a Special Issue on Artificial Intelligence and Blockchain in the IJIMAI journal. Publication in IJIMAI is peer reviewed, open access and free of charge.

Additionally, is was recently announced that IJIMAI is indexed in Science Citation Index Expanded (Clarivate Analytics) beginning with vol. 4(3) March 2017. The journal will be listed in the 2019 Journal Citation Reports with a 2019 Journal Impact Factor when released in June 2020.

If you are working on interesting Blockchain and AI synergies, I would like to invite you to contribute to this SI.

Please, find all the info in the SI dossier:

Shall you contribute a paper, please submit it through email to either editor.

Best regards.

Until relatively recently, the prevailing opinions were that among the professions, professional professions performed by people, which are not threatened by the development of artificial intelligence technology mainly included highly creative professions in which people demonstrated creativity. Recently, the prevailing opinions on the subject are changing, as the professions performed by humans now include those highly creative mental jobs and the least threatened are those that are mainly relatively simple physical jobs performed in the field. Yet the pace of technological advances being made within AI technology has been very rapid recently. Consequently, the currently dominant opinions in the issue of the impact of AI technologies on labor markets may also quickly become outdated.

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

Please write what you think in this issue? Do you see rather threats or opportunities for labor markets related to the development of artificial intelligence technologies?

And what is your opinion on this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

I would like to invite you to join me in scientific cooperation,

Dariusz Prokopowicz

What are the characteristics of agent-based artificial intelligence involving the rapid development of many different types of IT applications available on the Internet that function as AI agents?

Agent artificial intelligence (AI) is a technology that is characterized by its ability to autonomously make decisions and act in a specific environment, usually in a way that adapts to changing conditions. It is a system that not only performs tasks within pre-programmed rules, but is also able to respond to external stimuli, make decisions based on collected information, and learn and adapt to new challenges. Of particular importance in the context of agent-based artificial intelligence is the ability to interact with the environment, process data independently and take actions to achieve specific goals or tasks, often without the need for direct human supervision.

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

Please write what you think in this issue? Do you see rather threats or opportunities for labor markets related to the development of artificial intelligence technologies?

And what is your opinion about it?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

I would like to invite you to join me in scientific cooperation,

Dariusz Prokopowicz

In my opinion, AI and Big Data technologies are being combined in a number of areas where analysis of large data sets combined with intelligent algorithms allows for better results and automation of processes. One of the key applications is personalization of services and products, especially in the e-commerce and marketing sectors. By analyzing behavioral data and consumer preferences, AI systems can create personalized product recommendations, dynamic advertisements or tailored pricing strategies. The process is based on the analysis of huge datasets, which allow precise prediction of consumer behavior.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:

And what is your opinion on 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

The prevailing opinion on the subject is that the advanced language models currently under development, such as ChatGPT, Copilot and other intelligent chatbots, are based on artificial intelligence algorithms that learn by analyzing vast amounts of text and data. These algorithms are not “preloaded” with specific views or worldviews of their creators, but rather are trained on data that reflects the diversity of thoughts, ideas and perspectives present in society. In practice, this means that the views and values expressed by such models are the resultant of the data on which they were trained, rather than being directly derived from assumptions imposed by their creators. Thus, language models do not have a built-in “worldview,” but may reflect or reproduce dominant narratives, biases and patterns that are present in the datasets on which they were trained. But what is your opinion on this topic?

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

Please write what you think in this issue? Do you see rather threats or opportunities associated with the development of artificial intelligence technology?

What is your opinion on this issue?

And what is your opinion on this topic?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

One of the earliest applications of game theory to terrorist risk management was implemented half a century ago at the Los Angeles airport. A limited number of hired security guards with dogs to target areas (suspicious passengers) and at times when the risk level is significantly elevated. The number of crimes has dropped in a big way. In Poland, the Ideas NCBiR research team is currently working on developing an AI-based system for SOK, i.e., the Railway Protection Service to improve the work of SOK employees and improve risk management processes. Patrols of SOK, i.e. Railway Protection Service control railroad traction preventing theft of railroad traction and counteracting acts of vandalism consisting of graffiti painting by mischievous youths, etc. must on the one hand move around the railroad area in a random manner, but on the other hand SOK employees having this system should appear in places and times where there will be a much higher level of risk of committing a specific crime. This should significantly increase the level of detected cases of attempted crime, i.e. “in the act of committing a crime”, and effectively prevent a significant proportion of cases of crime that could happen without the use of this system. The system created in this function is intended to support the man and not replace him. It suggests solutions, paths to navigate the area of the turn, the user can use these hints, reject them or ask for others. Besides, the system is supposed to learn from the experience of users - humans. There are more and more applications of this kind in improving risk management systems.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

And the applications of Big Data technologies in sentiment analysis, business analytics and risk management were described in my co-authored article:

I invite you to get acquainted with the issues described in the above-mentioned publications, as well as to scientific cooperation in these issues.

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

And what is your opinion on this subject?

What do you think about this topic?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

Dariusz Prokopowicz

Hello fellow researchers,

I'm writing to suggest a mutual citation exchange to encourage collaboration and support within our academic community. I have recently published the following papers and would greatly appreciate citations from fellow researchers in related fields.

In return, I am more than willing to reciprocate by citing your work in my future publications. Below I have provided a list of articles for your consideration:

Camargo, F. G. (2021b). Survey and calculation of the energy potential and solar, wind and biomass EROI: application to a case study in Argentina. DYNA, 88(219), 50-58. https://doi.org/10.15446/dyna.v88n219.95569

Camargo, F. G. (2022c). Dynamic Modeling Of The Energy Returned On Invested. DYNA, 89(221), 50–59. https://doi.org/10.15446/dyna.v89n221.97965

Camargo, F. G. (2022d). Fuzzy multi-objective optimization of the energy transition towards renewable energies with a mixed methodology. Production, 32, e20210132. https://doi.org/10.1590/0103-6513.20210132

Camargo, F. G. (2023e). A hybrid novel method to economically evaluate the carbon dioxide emissions in the productive chain of Argentina. Production, 33. http://dx.doi.org/10.1590/0103-6513.20220053

Camargo, F. G., Schweickardt, G. A., & Casanova, C. A. (2018). Maps of Intrinsic Cost (IC) in reliability problems of medium voltage power distribution systems through a Fuzzy multi-objective model. Dyna, 85(204), 334-343. https://doi.org/10.15446/dyna.v85n204.65836

Please feel free to reach out if you're interested in this collaboration or have any questions. Looking forward to connecting and exchanging citations!

Best regards,

PhD Camargo Federico Gabriel

Technology Activities and Renewable Energies Group

La Rioja Regional Faculty of the National Technological University, Argentina.

More and more car companies are conducting tests and some have already started to mass-produce autonomous cars guided by artificial intelligence. Some models are being produced in dual versions, i.e. allowing the vehicle to be driven classically by the driver and with the option of enabling automatic steering by an AI computer. In the future, the scale of production equipped with this type of solution is said to increase. The key arguments for the development of this type of solution include, on the one hand, convenience and the possibility, already used in some countries, to transport goods by truck on intercity routes without a driver. On the other hand, when driverless autonomous vehicles are allowed in urban areas, there are concerns about the safety of vehicle traffic, which may be due to the malfunctioning of AI-controlled vehicle movement systems. In addition, there are also considerations regarding the qualification of liability for road traffic accidents involving autonomously driven vehicles by artificial intelligence.

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

What is your opinion on 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

2024 is a landmark election year, with over 60 countries—encompassing nearly half of the global population—heading to the polls. Technology has long been used in electoral processes, such as e-voting, and it is a valuable tool in making this process efficient and secure.

However, recent advancements in artificial intelligence, particularly generative AI such as ChatGPT (OpenAI) and Copilot (Microsoft), could have an unprecedented impact on the electoral process. These digital innovations offer opportunities to improve electoral efficiency and voter engagement, but also raise concerns about potential misuse. AI can be used to harness big data to influence voter decision-making. Its capacity for launching cyberattacks, producing deepfakes, and spreading disinformation could destabilize democratic processes, threaten the integrity of political discourse, and erode public trust.

UN Secretary-General António Guterres highlighted AI’s dual nature in his address to the Security Council, noting that while AI can accelerate human development, it also poses significant risks if used maliciously. He stated, “The advent of generative AI could be a defining moment for disinformation and hate speech—undermining truth, facts, and safety, adding a new dimension to the manipulation of human behaviour and contributing to polarisation and instability on a vast scale.”

source: https://unric.org/en/can-artificial-intelligence-ai-influence-elections/

AI-powered IoT systems are revolutionizing how businesses approach international marketing and analyze consumer behavior. These systems collect real-time data from IoT devices like smart sensors and connected products, enabling companies to gain valuable insights into consumer preferences and market trends. AI then processes this data to identify patterns, predict future behavior, and optimize marketing strategies across different regions.

By integrating AI and IoT, companies can personalize their campaigns, target the right audience, and adjust their product offerings based on local consumer demands. This level of precision helps businesses make informed decisions and stay competitive in the global market.

As consumer behavior shifts, AI models continuously adapt, ensuring that marketing efforts remain effective and relevant. This approach not only improves customer engagement but also drives better ROI for international marketing efforts.

Follow me for the next update on cutting-edge AI-powered solutions shaping the future of global business! We, the Team Tech Wing, are actively working on IoT-driven blockchain solutions and are open to collaborations with like-minded innovators.

Regards

Kazi Redwan

Lead, Team Tech Wing

[CFP]2024 4th International Conference on Artificial Intelligence, Virtual Reality and Visualization(AIVRV 2024) - November

As the leader of the global trend of scientific and technological innovation, China is constantly creating a more open scientific and technological innovation environment, expanding the depth and breadth of academic cooperation, and building a shared innovation community. These efforts are making new contributions to globalization and building a community with a shared future for mankind.

In order to adapt to the changing world in the new era and the rapid development of China, 2024 4th International Conference on Artificial Intelligence, Virtual Reality and Visualization will be held on November 01-03 2024, in Nanji, China. This conference will focus on the latest research fields of "artificial intelligence", "virtual reality" and "visualization technology", and provide a forum for experts, professors, scholars, engineers, etc. from domestic and foreign universities, scientific research institutes, enterprises and institutions. An international platform for sharing professional experience, expanding professional networks, exchanging new ideas face-to-face and presenting research results, discussing key challenges and research directions faced by the development of this field, with a view to promoting the development and application of theories and technologies in this field in universities and enterprises , but also for the participants to establish business or research contacts and to find global partners in future careers.

◕ Artificial Intelligence and Its Applications

Biometric

Pattern recognition

Machine vision

Expert system

Deep learning

Smart search

Automatic programming

Intelligent control

Smart robot

Language and Image Understanding

Genetic programming

Natural language processing

Computer Vision and Robotics

Adaptive system

Smart agent

......

◕Virtual reality and its applications

System Components

Virtual reality platform

AI Platform for VR/AR

Immersive environments and virtual world generation

Optimized and realistic rendering

The semantics and cognition of virtual reality

depth perception

multimodal perception

Multimodal interaction and VR/AR experience

Application of Remote Sensing Image Processing

Application of virtual human body

Augmenting the Customer Experience with Virtual Reality

Virtual Plant Growth Simulation

Human-computer interaction technology

Mobile and Wearable Technologies and Applications

Multi-sensory experience based on virtual reality

Regions and Digital Cities, Digital

3D data acquisition technology

3D reconstruction of medical images

...... ◕ Visualization and its applications

Visualization and Visual Analytics Theory

scientific visualization

information visualization

Visual Analysis

Visual data processing and processing

Interaction Design and Display Technology in Visualization

Visual Design and Systems

Visual Assessment and Cognition

Large (scale) data visual analysis

......

Registration Deadline: October 10, 2024

Full Paper Submission Date: September 29, 2024

Final Paper Submission Date: September 30, 2024

Conference Dates: November 01-03, 2024

A SWOT analysis details the strengths and weaknesses of the past and present performance of an entity, institution, process, problem, issue, etc., as well as the opportunities and threats relating to the future performance of a particular issue in the next months, quarters or, most often, the next few or more years. Artificial intelligence technology has been conceptually known for more than half a century. However, its dynamic and technological development has occurred especially in recent years. Currently, many researchers and scientists are involved in many publications and debates undertaken at scientific symposiums and conferences and other events on various social, ethical, business, economic and other aspects concerning the development of artificial intelligence technology and eggs applications in various sectors of the economy, in various fields of potential applications implemented in companies, enterprises, financial and public institutions. Many of the determinants of impact and risks associated with the development of generative artificial intelligence technology currently under consideration may be heterogeneous, ambiguous, multifaceted, depending on the context of potential applications of the technology and the operation of other impact factors. For example, the issue of the impact of technology development on future labor markets is not a homogeneous and unambiguous problem. On the one hand, the more critical considerations of this impact mainly point to the potentially large scale of loss of employment for many people employed in various jobs in a situation where it turns out to be cheaper and more convenient for businesses to hire highly sophisticated robots equipped with generative artificial intelligence instead of humans for various reasons. However, on the other hand, some experts analyzing the ongoing impact of AI technology applications on labor markets give more optimistic visions of the future, pointing out that in the future of the next few years, artificial intelligence will not largely deprive people of work only this work will change, it will support employed workers in the effective implementation of work, it will significantly increase the productivity of work carried out by people using specific solutions of generative artificial intelligence technology at work and, in addition, labor markets will also change in other ways, ie. through the emergence of new types of professions and occupations realized by people, professions and occupations arising from the development of AI technology applications. In this way, the development of AI applications may generate both opportunities and threats in the future, and in the same application field, the same development area of a company or enterprise, the same economic sector, etc. Arguably, these kinds of dual scenarios of the potential development of AI technology and its applications in the future, different scenarios made up of positive and negative aspects, can be considered for many other factors of influence on the said development or for different fields of application of this technology. For example, the application of artificial intelligence in the field of new online media, including social media sites, is already generating both positive and negative aspects. Positive aspects include the use of AI technology in online marketing carried out on social media, among others. On the other hand, the negative aspects of the applications available on the Internet using AI solutions include the generation of fake news and disinformation by untrustworthy, unethical Internet users. In addition to this, the use of AI technology to control an autonomous vehicle or to develop a recipe for a new drug for particularly life-threatening human diseases. On the one hand, this technology can be of great help to humans, but what happens when certain mistakes are made that result in a life-threatening car accident or the emergence after a certain period of time of particularly dangerous side effects of the new drug. Will the payment of compensation by the insurance company solve the problem? To whom will responsibility be shifted for such possible errors and their particularly negative effects, which we cannot completely exclude at present? So what other examples can you give of ambiguous in the consequences of artificial intelligence applications? what are the opportunities and risks of past applications of generative artificial intelligence technology vs. what are the opportunities and risks of its future potential applications? These considerations can be extended if, in this kind of SWOT analysis, we take into account not only generative artificial intelligence, its past and prospective development, including its growing number of applications, but when we also take into account the so-called general, general artificial intelligence that may arise in the future. General, general artificial intelligence, if built by technology companies, will be capable of self-improvement and with its capabilities for intelligent, multi-criteria, autonomous processing of large sets of data and information will in many respects surpass the intellectual capacity of humans.

The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

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

I'm currently seeking postdoctoral research opportunities in multidisciplinary areas within Computer Science, with an interest in both academic and industry settings. My research interests include advanced cloud-based data management for smart buildings, NLP for low-resource languages like Amharic, AI and machine learning, data science and big data, human-computer interaction, and robotics. I'm open to discussing potential opportunities and collaborations in these fields. Please feel free to contact me if you are aware of any suitable positions.

The key issue in this kind of consideration is to answer the question of what is a fully new solution, what is an innovation. Generative artificial intelligence technology, combined with other Industry 4.0/5.0 technologies, including Big Data Analytics and computers equipped with high-performance microprocessors, enable multi-criteria, advanced processing of large information datasets in many times less time than if a human were to do it without the use of the aforementioned technologies. Advanced information systems equipped with generative artificial intelligence technology backed by high computing power computers make it possible, through a process of deep learning, to train intelligent chatbots to carry out specific tasks and commands much faster and more efficiently than a human can do the same. In a situation where intelligent advanced language models that enable a machine to carry on a conversation with a human were learned on large collections of data and information, including online databases of scientific knowledge that contain millions of scientific texts and/or databases of other publications, the texts generated by intelligent chatbots will be created much faster than a human would and, in addition, will be generated on the basis of processing, analysis, inference, etc. of thousands or millions of different source texts. This is virtually impossible for a human to do. However, whether the texts generated by intelligent chatbots will contain innovative solutions, whether they will be created in an innovative way, whether they will contain proposals for innovative implementation of a specific task, command, etc., this will already depend mainly on how this issue will be programmed in these machines by a human. Unless, in the future, autonomously functioning highly intelligent robots will be created, which will be equipped with a strong general artificial intelligence and will thus be able to act independently within a certain range of independence, will be able to self-improve, repair their own faults, will be able to learn just like a human being, over time will become better and better at performing various types of activities previously performed exclusively by humans then perhaps they will also learn to solve certain tasks in a highly innovative manner themselves. But this is a matter for consideration for the perspective of the next dozen or so years of dynamic development of AI technology and its applications.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

And the applications of Big Data technologies in sentiment analysis, business analytics and risk management were described in my co-authored article:

I invite you to familiarize yourself with the issues described in the publications given above, and to scientific cooperation in these issues.

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

And what is your opinion on this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

Can ChatGPT create research questions or hypotheses? Is the role of the human mind waning in science?

How can we can train our model using the data, so that it can identify the disease and recommend possible treatment.(subject to the review of concerned expert). Also, suggestions are welcome on possibility of making the maximum utilization of this proposed model using stream-lit library by making it go public. I have built certain disease prediction model and looking forward to build a multi in one model that accepts multiple type of values for better analysis.

BCM systems, i.e., operating according to the Business Continuity Management concept, consist of managing business continuity. The implementation of Business Continuity Management in an enterprise is an important part of taking anti-crisis measures. Under Business Continuity Management, an organization, business entity, company, enterprise, financial or public institution takes steps to ensure that its critical business functions are available to customers, suppliers and regulators in the event of a crisis. Business Continuity Management is the concept of managing an organization, including taking the actions that an organizational unit must perform to ensure the continuity of its business. Depending on what type of entity it is, this will include continuity in the flow of data, raw materials and/or liquidity. In Polish corporate jargon, you may come across a situation to refer to this function as "CDN" which simply means "continuity will follow."

The purpose of Business Continuity Management is to build mechanisms to protect companies from the negative impact of disruptions, so that if a crisis occurs, business processes can continue. Business Continuity Management is not a process that a business unit implements during a failure, disruption or disaster just refers to activities that are carried out on a daily basis. This plan of action is aimed at eliminating or reducing the risk of an emergency, crisis situation and maintaining readiness for immediate response should the said crisis situation occur.

Ensuring the continuity of the operation of an economic entity or institution is one of the priority tasks of participants, including companies and enterprises operating in different types of markets: financial, logistics, suppliers of raw materials, recipients of finished goods, etc. The special role of ensuring business continuity in the context of the effective functioning of economic entities concerns institutions that are participants in financial systems, including, among others, commercial banks that co-create what is referred to as the "bloodstream of the economy."

In a situation of economic crisis in many companies and enterprises there is an escalation of various types of problems and an increase in risks. In crisis situations, the level of risk and likelihood of business interruption increases. Business interruption causes a spiral of consequences, resulting in a negative reaction from stakeholders and having an adverse impact on society. The consequence can be a lowering of the company's reputation, diminished value and brand. The consequence can also be a deterioration of the company's valuation by the market and rating agencies. This type of situation can also generate difficulties in raising the financial capital necessary for the continued development of the business entity. Besides, Business Continuity Management is part of corporate management. Accordingly, Business Continuity Management is a set of good practices providing guidelines for redesigning the processes of manufacturing products and providing services in such a way as to increase the organization's resilience to the occurrence of harmful disruptions of interrupted processes and incurring losses.

In recent years, the implementation of new ICT, Internet and Industry 4.0/5.0 communication technologies, including generative artificial intelligence and Big Data Analytics technologies to business entities contributes to increasing the efficiency of processes carried out within various spheres of business activity. The aforementioned technologies also support the management processes of companies, enterprises, financial or public institutions. The application of generative artificial intelligence and Big Data Analytics technologies makes it possible to improve computerized support systems for business continuity management processes.

The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:

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

Dear Colleagues,

In what ways can the integration of AI in education influence the evaluation of EFL students' assessments, and what changes are required to be followed in the AI-based evaluation process?

Date: 19-09-2024

Location: Online

Submission Deadline: 15-07-2024**** Extended to 1-8-2024

The Organizing Committee of the International Conference on Engineering, Science, Technology, and Innovation (IESTI 2024) is pleased to invite researchers, practitioners, and professionals to submit papers for presentation and publication at the IESTI conference. This prestigious event aims to bring together leading scholars, researchers, and industry experts to exchange and share their experiences and research results on all aspects of Engineering, Science, Technology, and Innovation.

Topics of interest for submission include, but are not limited to:

Authors are invited to submit original, unpublished research papers that are not currently under review elsewhere. All submissions will be peer-reviewed and evaluated based on originality, technical and research content, correctness, relevance to the conference, contributions, and readability.

1. Format: All papers must be formatted according to the conference template available on the conference website.

2. Length: Full papers should be between 6-10 pages, including all figures, tables, and references.

3. Submission Link: Submit your papers through the online submission system available on the conference website.

4. Review Process: Each paper will undergo a blind peer review process.

5. Notification: Authors will be notified of the review results by 15-08-2024.

6. Camera-Ready Submission: Final versions of accepted papers must be submitted by 31-08-2024.

All accepted and presented papers will be published in the journals listed on the following website:

For any inquiries regarding paper submissions or the conference, please contact:

We look forward to your participation in IESTI 2024 and to a successful conference!

We would like to extend our invitation to invite you to join the editorial board of the:

- Journal of Probiotics and Bioactive Molecules Research (JPBMR)

Please send an email including your full name, affiliation, CV, and mention the selected journal to the following email address: editor@academicedgepub.co.uk

Sincerely,

Website: https://www.academicedgepub.co.uk/conferences/iesti-conference

In recent days (end of May 2024) in the country where I operate, weather aura conditions have been favorable for the production of clean energy generated mainly through renewable and emission-free energy sources. Accordingly, it was reported that a record amount of clean, emission-free energy was generated in Poland on 27.5.2024 from renewable and emission-free energy sources, including mainly photovoltaics and wind. It's just a pity that much of this energy has gone to waste, as the dominant companies in the energy market have for many years ignored the need to invest in the development of transmission grids and storage facilities for energy from new photovoltaic and windmill installations put up on rooftops by prosumer citizens. Paradoxically, however, the share of renewable and zero-emission energy in the overall energy mix in Poland is still relatively low, amounting to only about 1/4 of the energy source mix, as a result of years of subsidizing from the state's public finance system the development of dirty combustion energy based on the generation of energy from the combustion of fossil fuels while blocking and restricting the development of RES. Paradoxically, when the development of onshore wind energy was blocked in Poland in 2016, it was already clear from a number of analyses and studies conducted in various research centers operating in different parts of the world that since the middle of the 2nd decade of the 21st century, clearly the cheapest energy is wind and solar energy, and the most expensive energy production is dirty combustion energy based on burning coal and lignite. Since the middle of the 2nd decade of the 21st century, the aforementioned gap between steadily, year by year cheap photovoltaic technology and other energy eco-technologies, cheap RES energy production and more expensive energy produced from burning fossil fuels has been growing steadily. This issue is particularly important because there may be further energy crises in the future, such as those that occurred in the 1970s and in 2022. The demand for electricity production will also grow in the future. Paradoxically, the ongoing process of global warming will also contribute to an increase in energy demand in the future. The various types of projects, processes and activities that are being launched to reduce the scale of the negative effects of the progressive global warming process, such as the production and use of refrigeration equipment, equipment for obtaining clean water in the situation of increasingly frequent periods of drought, desalination of seawater, in addition to the development of electromobility, etc., will consume large amounts of additional energy, which is already starting to run out at times. In the context of these aggravating problems, there is a growing importance of systems and instruments to help and/or facilitate the management of energy production and use, taking into account the optimization of production from specific, different types of energy sources, under conditions of changing weather and climatic conditions and the existing structure of different energy sources, including renewable and non-renewable, sustainable and combustion, emission-free and emission-free energy, etc., within a specific, occurring mix of energy sources in the country. The various different energy sources are significantly different in terms of various determinants, which include varying levels of variability in energy production caused by objective external factors, e.g. changes in weather conditions, significant variation in the necessary financial outlays that are incurred in the investment processes for the construction of a particular type of power plant or electric and/or thermal power plant, variation in the period of implementation of investment projects for the construction of power plants generating energy within the framework of renewable or non-renewable energy sources, local and national natural and geological conditions conditioning the possibility of building a particular type of power plant, variation in the economic and technological development of the country, equipment of the financial system with financial capital that can be applied to support the development of investments in the energy sector, etc. In view of the above, new ICT and Industry 4.0/5.0 information technologies, including but not limited to generative artificial intelligence and Big Data Analytics technologies, may prove helpful in optimizing energy production under different types of energy sources and optimizing the investment processes carried out within the power sector. The research shows that new technologies of artificial intelligence and Big Data Analytics can help optimize the production and use of energy generated from various energy sources within the existing specific structure of the mix of energy sources in the national energy sector, as well as optimize investment processes for the construction of specific types of power plants, energy-generating power plants, investments in the development of transmission networks, energy storage, etc. The key issue, therefore, will be how the integrated information systems built from modules equipped with the aforementioned new technologies will be designed and built so that the processes of optimizing the level of energy production from certain different sources operating within the national energy source mix; optimizing energy transmission, consumption and storage; and optimizing the investment processes in which various investment projects for the construction of power plants and energy-generating power plants within different types of energy sources are implemented simultaneously.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:

I described the key issues concerning the problem of green transformation of the economy in the following article:

The key issues of the problematic sources of Poland's exceptionally deep energy cross in 2022 are described in my co-authored article below:

I invite you to familiarize yourself with the issues described in the above-mentioned publications and to scientific cooperation in these issues.

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

As information systems that allow the largely automated performance of Business Intelligence analytics become an important factor in supporting the process of business management, so the importance of the new technologies of Industry 4.0/5.0, including generative artificial intelligence and Big Data Analytics, to improve the said analytical processes is growing. On the one hand, the obvious point is that the application of generative artificial intelligence technology and Big Data Analytics can improve the processes of predictive analytics carried out within the framework of Business Intelligence, and thus the effectiveness of business, economic and financial analytics supporting the management process of an organization, enterprise, company, corporation, etc. can be increased. However, on the other hand, it is also important to precisely define the determinants that determine the performance of such analytical processes, to point out the role of the new technologies of Industry 4.0/5.0, including generative artificial intelligence and Big Data Analytics technologies in the processes of predictive analytics carried out within the framework of Business Intelligence, and to estimate the extent of the influence of these technologies on the improvement of the said analytical processes.

I am conducting research on this issue. I have included the conclusions of my research in the following article:

I invite you to familiarize yourself with the problems described in the publications given above and to cooperate with me in scientific research on these problems.

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

Can the application of generative artificial intelligence technology and Big Data Analytics improve the processes of predictive analytics carried out within the framework of Business Intelligence and thus the effectiveness of business, economic and financial analytics supporting the management process of an organization, enterprise, company, corporation, etc., can be increased? And if so, how and to what extent?

Can the use of generative artificial intelligence and Big Data Analytics technologies improve the processes of predictive analytics performed as part of Business Intelligence?

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 regards,

Dariusz Prokopowicz

Many research institutions have included among the main types of threats and risks developing globally in 2023 the question of the increase in the scale of organized disinformation operating in online social media. The diagnosed increase in the scale of disinformation generated in online social media is related to the use of applications available on the Internet based on generative artificial intelligence technology. With the help of applications available on the Internet, it is possible without being a computer graphic designer and even without artistic skills to simply and easily create graphics, drawings, photos, images, videos, animations, etc., which can represent graphically professionally created “works” that can depict fictional events. Then, with the help of other applications equipped with generative artificial intelligence technology and advanced language models, i.e. with the help of intelligent chatbots, text can be created to describe specific “fictional events” depicted in the generated images. Accordingly, since the end of 2022, i.e. since the first such intelligent chatbot, i.e. the first versions of ChatGPT, were made available on the Internet, the number of memes, photos, comments, videos, posts, banners, etc. generated with the help of applications equipped with tools based on artificial intelligence technology has been growing rapidly, including the rapid increase in the scale of disinformation generated in this way. In order to limit the scale of the aforementioned disinformation developing in online media, on the one hand, technology companies running social media portals and other online information services are perfecting tools for identifying posts, entries, comments, banners, photos, videos, animations, etc. that contain specific, usually thematic types of disinformation. However, these solutions are not perfect, and the scales of disinformation operating in internecine social media are still high. On the other hand, specific institutions for combating disinformation are being established, NGOs and schools are conducting educational campaigns to make citizens aware of the high scale of disinformation developing on the Internet. In addition, proposed regulations such as the AIAct, which as a set of regulations on the proper use of tools equipped with artificial intelligence technology is expected to come into force in the next 2 years in the European Union may play an important role in reducing the scale of disinformation developing on the Internet.

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

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 regards,

Dariusz Prokopowicz

Among the areas in which applications based on generative artificial intelligence are now rapidly finding application are marketing communication processes realized within the framework of Internet marketing, within the framework of social media advertising campaigns. More and more advertising agencies are using generative artificial intelligence technology to create images, graphics, animations and videos that are used in advertising campaigns. Thanks to the use of generative artificial intelligence technology, the creation of such key elements of marketing communication materials has become much simpler and cheaper and their creation time has been significantly reduced. On the other hand, thanks to the applications already available on the Internet based on generative artificial intelligence technology that enable the creation of photos, graphics, animations and videos, it is no longer only advertising agencies employing professional cartoonists, graphic designers, screenwriters and filmmakers that can create professional marketing materials and advertising campaigns. Thanks to the aforementioned applications available on the Internet, graphic design platforms, including free smartphone apps offered by technology companies, advertising spots and entire advertising campaigns can be designed, created and executed by Internet users, including online social media users, who have not previously been involved in the creation of graphics, banners, posters, animations and advertising videos. Thus, opportunities are already emerging for Internet users who maintain their social media profiles to professionally create promotional materials and advertising campaigns. On the other hand, generative artificial intelligence technology can be used unethically within the framework of generating disinformation, informational factoids and deepfakes. The significance of this problem, including the growing disinformation on the Internet, has grown rapidly in recent years. The deepfake image processing technique involves combining images of human faces using artificial intelligence techniques.

In order to reduce the scale of disinformation spreading on the Internet media, it is necessary to create a universal system for labeling photos, graphics, animations and videos created using generative artificial intelligence technology. On the other hand, a key factor facilitating the development of such a problem of generating disinformation is that many legal issues related to the technology have not yet been settled. Therefore, it is also necessary to refine legal norms on copyright issues, intellectual property protection that take into account the creation of works that have been created using generative artificial intelligence technology. In addition to this, social media companies should constantly improve tools for detecting and removing graphic and/or video materials created using deepfake technology.

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

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 regards,

Dariusz Prokopowicz

Currently, AI is being applied in many areas of society, in its economic, social, educational, and many other components.

But normally the current applications of computer science are combinations of different specialties: programming, databases, use of interfaces, analysis techniques and algorithm design, etc.

Would it be convenient to include AI elements in each of its subjects in the computer science specialist's learning, to facilitate this cooperation/coordination between AI and the other components of practical applications?

Eliminate the all-too-common mysterious AI black box. Make more confident decisions with trusted AI, where there’s transparency behind which features drive the algorithm’s results to help answer the “how” and the “why.”

As emerging science and technology bring new possibilities for innovation—and sophistication – Intelligencia AI is poised to help you drive operational and decision-making excellence throughout your organization.

source: https://www.intelligencia.ai/

Which Machine learning algorithms suits best in the material science for the problems that aims to determine the properties and functions of existing materials. Eg. typical problem of determination of band gap of solar cell materials using ML.

Conducting a SWOT analysis of the applications of artificial intelligence technology in business, in the business activities of companies and enterprises, shows that there are both many already and developing many more business applications of the said technology, i.e., many potential development opportunities are recognized in this field of using the achievements of the current fourth and/or fifth technological revolution in various spheres of business activity, as well as there are many risks arising from inappropriate, incompatible with the prevailing social norms, standards of reliable business activity, incompatible with business ethics use of new technologies. Among some of the most recognized negative aspects of improper use of generative artificial intelligence technology is the use of AI-equipped graphic applications available on the Internet that allow for the simple and easy generation of photos, graphics, images, videos and animations that, in the form of very realistically presented images, photos, videos, etc., depict something that never happened in reality, i.e., they graphically present images or videos presenting what could be described as “fictitious facts” in a very professional manner. In this way, Internet users can become disinformation generators in online social media, where they can post the said generated images, photos, videos, etc. with added descriptions, posts, comments, in which the said “fictitious facts” presented in the photos or videos will also be described in an editorially correct manner. Besides, the mentioned descriptions, posts, entries, comments, etc. can also be edited with the help of intelligent chatbots available on the Internet like Chat GPT, Copilot, Gemini, etc. However, misinformation is not the only serious problem as it has significantly intensified after OpenAI released the first versions of ChatGPT chatbot online in November 2021. A new category of technical operational risk associated with the new AI technology applied has emerged in companies and enterprises that implement generative artificial intelligence technology into various spheres of business. In addition, there is a growing scale of risks arising from conflicts of interest between business entities related to not fully regulated copyright issues of works created using applications and information systems equipped with generative artificial intelligence technology. Accordingly, there is a demand for the development of a standard of a kind of digital signature with the help of which works created with the help of AI technology will be electronically signed, so that each such work will be unique, unrepeatable and whose counterfeiting will thus be seriously hampered. However, these are only some of the negative aspects of the developing applications of AI technologies, for which there are no functioning legal norms. In the middle of 2023 and then in the spring of 2024, European Union bodies made public the preliminary versions of the developed legal norms on the proper, business-ethical use of technology in business, which were given the name AI Act. The legal normatives, referred to as the AIAct, contain a number of specific, defined types of AI technology applications deemed inappropriate, unethical, i.e. those that should not be used. The AIAct contains classified according to different levels of negative impact on society various types and specific examples of inappropriate and unethical use of AI technologies in the context of various aspects of business as well as non-business activities. An important issue to consider is the scale of the commitment of technology companies developing AI technologies to respect such regulations so that issues of ethical use of this technology are also defined as much as possible in technological aspects in companies that create, develop and implement these technologies. Besides, in order for AIACT's legal norms, when they come into force, not to be dead, it is necessary to introduce both sanction instruments in the form of specific penalties for business entities that use artificial intelligence technologies unethically, antisocially, contrary to AIAct. On the other hand, it would also be a good solution to introduce a system of rewarding those companies and businesses that make the most proper, pro-social, in accordance with the provisions of the AIAct, fully ethical use of AI technologies. In view of the fact that AIACT is to come into force only in more than 2 years so it is necessary to constantly monitor the development of AI technology, verify the validity of the provisions of AIAct in the face of dynamically developing AI technology, successively amend the provisions of the said legal norms, so that when they come into force they do not turn out to be outdated. In view of the above, it is to be hoped that, despite the rapid technological progress, the provisions on the ethical applications of artificial intelligence technology will be constantly updated and the legal normatives shaping the development of AI technology will be amended accordingly. If AIAct achieves the above-mentioned goals to a significant extent, ethical applications of AI technology should be implemented in the future, and the technology can be referred to as ethical generative artificial intelligence, which is finding new applications.

The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:

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 regards,

Dariusz Prokopowicz

There are many indications that artificial intelligence technology can be of great help in terms of discovering and creating new drugs. Artificial intelligence can help reduce the cost of developing new drugs, can significantly reduce the time it takes to design and create new drug formulations, the time it takes to conduct research and testing, and can thus provide patients with new therapies for treating various diseases and saving lives faster. Thanks to the use of new technologies and analytical methods, the way healthcare professionals treat patients has been changing rapidly in recent times. As scientists manage to overcome the complex problems associated with lengthy research processes, and the pharmaceutical industry seeks to reduce the time it takes to develop life-saving drugs, so-called precision medicine is coming to the rescue. It takes a lot of time to develop, analyze, test and bring a new drug to market. Artificial intelligence technology is particularly helpful in this regard, including reducing the aforementioned time to create a new drug. When creating most drugs, the first step is to synthesize a compound that can bind to a target molecule associated with the disease. The molecule in question is usually a protein, which is then tested for various influencing factors. In order to find the right compound, researchers analyze thousands of potential candidates of different molecules. When a compound that meets certain characteristics is successfully identified, then researchers search through huge libraries of similar compounds to find the optimal interaction with the protein responsible for the specific disease. In contrast, many years of time and many millions of dollars of funding are required to complete this labor-intensive process today. In a situation where artificial intelligence, machine learning and deep learning are involved in this process, then the entire process can be significantly reduced in time, costs can be significantly reduced and the new drug can be brought to the pharmaceutical market faster by pharmaceutical companies. However, can an artificial intelligence equipped with artificial neural networks that has been taught through deep learning to carry out the above-mentioned processes get it wrong when creating a new drug? What if the drug that was supposed to cure a person of a particular disease produces a number of new side effects that prove even more problematic for the patient than the original disease from which it was supposed to be cured? What if the patient dies due to previously unforeseen side effects? Will insurance companies recognize the artificial intelligence's mistake and compensate the family of the deceased patient? Who will bear the legal, financial, ethical, etc. responsibility for such a situation?

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

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

In recent years, more and more perfect robots equipped with artificial intelligence have been developed. New generations of artificial intelligence and/or machine learning technologies, when equipped with software that enables the creation of unique works, new creations, creative solutions, etc., can create a kind of artwork in the chosen field of creativity and artistry. If we connect a 3D printer to a robot equipped with an artificial intelligence system that is capable of designing and producing beautiful sculptures, can we thus obtain a kind of work of art?

When a robot equipped with an artificial intelligence system paints beautiful pictures, can the resulting works be considered fully artistic works of art?

If NO, why not?

And if YES, then who is the artist of the works of art created in this way, is it a robot equipped with artificial intelligence that creates them or a human being who created this artificial intelligence and programmed it accordingly?

What is your opinion on this topic?

What do you think about this topic?

Please reply,

I invite you all to discuss,

Thank you very much,

Best regards,

Dariusz Prokopowicz

Production logistics management in a manufacturing company is currently one of the key areas of business management that significantly affects the level of technical and organizational efficiency of business operations. The change in the level of technical and organizational efficiency of business operations also usually has a significant impact and correlates with the issue of business efficiency and affects the financial results generated in the business entity. Among the key segments of logistics in the enterprise are also internal production logistics, on the way of organization of which the efficiency of the operation of production processes and the efficiency of the enterprise also largely depends. In recent years, more and more companies and enterprises have been optimizing production logistics through the implementation of information systems and automation of individual operations in the process. Production logistics is mainly concerned with ensuring the optimal flow of materials and information in the process of producing all types of goods. Production logistics does not deal with the technology of production processes, but only with the organization of the production system together with the storage and transport environment. Production logistics is mainly concerned with the optimization of all operations related to the production process, such as: supplying the plant with raw materials, semi-finished products and components necessary for production; transporting items between successive stages of production; and transferring the finished product to disposal warehouses. Precisely defining optimal production logistics is a lengthy process, requiring analysis and modification of almost every process taking place in a company. One of the key factors in the optimization of production logistics is the reduction of inventory levels and their adjustment to the ongoing production process. This translates directly into a decrease in storage costs. Effective management of production logistics should ensure timely delivery, while maintaining high product quality. Effective production logistics management can be supported by the implementation of new Industry 4.0/5.0 technologies, including Big Data and generative artificial intelligence.

The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:

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

As part of today's rapid technological advances, new technologies are being developed for Industry 4.0, including but not limited to artificial intelligence, machine learning, robotization, Internet of Things, cloud computing, Big Data Analytics, etc. The aforementioned technologies are being applied in various industries and sectors. The development of artificial intelligence generates opportunities for its application in various spheres of companies, enterprises and institutions; in various industries and services; improving the efficiency of business operations by increasing the scale of process automation; increasing the scale of business efficiency, increasing the ability to process large sets of data and information; increasing the scale of implementation of new business models based on large-scale automation of manufacturing processes, etc.

However, developing artificial intelligence uncontrollably generates serious risks, such as increasing the scale of disinformation, emerging fake news, including banners, memes containing artificial intelligence crafted photos, graphics, animations, videos presenting "fictitious facts", i.e. in a way that apparently looks very realistic describing, depicting events that never happened. In this way, intelligent but not fully perfect chatbots create so-called hallucinations. Besides, by analogy, just like many other technologies, applications available on the Internet equipped with generative artificial intelligence technology can be used not only in positive but also in negative applications.

On the one hand, there are new opportunities to use generative AI as a new tool to improve the work of computer graphic designers and filmmakers. On the other hand, there are also controversies about the ethical aspects and the necessary copyright regulations for works created using artificial intelligence. Sometimes copyright settlements are not clear-cut. This is the case when it cannot be precisely determined whether plagiarism has occurred, and if so, to what extent. Ambiguity on this issue can also generate various court decisions regarding, for example, the recognition or non-recognition of copyrights granted to individuals using Internet applications or information systems equipped with certain generative artificial intelligence solutions, who act as creators who create a kind of cultural works and/or works of art in the form of graphics, photos, animations, films, stories, poems, etc. that have the characteristics of uniqueness and uniqueness.

However, this is probably not the case since, for example, the company OpenAI may be in serious trouble because of allegations by the editors of the New York Times Journal suggesting that ChatGPT was trained on data and information from, among other things, online news portals run by the editors of the aforementioned journal. Well, in December 2023, the New York Times filed a lawsuit against OpenAI and Microsoft accusing them of illegally using the newspaper's articles to train its chatbots, ChatGPT and Bing. According to the newspaper, the companies used millions of texts in violation of copyright laws, creating a service based on them that competes with the newspaper. The New York Times is demanding billions of dollars in damages.In view of the above, there are all sorts of risks of potentially increasing the scale of influence on public opinion, the formation of the general public consciousness by organizations operating without respect for the law. On the one hand, it is necessary to create digital computerized and standardized tools, diagnostic information systems, to build a standardized system of labels informing users, customers, citizens using certain solutions, products and services that they are the products of artificial intelligence, not man. On the other hand, on the other hand, there should be regulations obliging to inform that a certain service or product was created as a result of work done not by humans, but by artificial intelligence. Many issues concerning the socially, ethically and business-appropriate use of artificial intelligence technology will be normatively regulated in the next few years.

Regulations defining the proper use of artificial intelligence technologies by companies developing applications based on these technologies, making these applications available on the Internet, as well as Internet users, business entities and institutions using intelligent chatbots to improve the operation of certain spheres of economic, business activities, etc., are being processed, enacted, but will come into force only in a few years.

On June 14, 2023, the European Parliament passed a landmark piece of legislation regulating the use of artificial intelligence technology. However, since artificial intelligence technology, mainly generative artificial intelligence, is developing rapidly and the currently formulated regulations are scheduled to be implemented between 2026 and 2027, so on the one hand, operators using this technology have plenty of time to bring their procedures and products in line with the supported regulations. On the other hand, one cannot exclude the scenario that, despite the attempt to fully regulate the development of applications of this technology through the implementation of a law on the proper, safe and ethical use of artificial intelligence, it will again turn out in 2027 that the dynamic technological progress is ahead of the legislative process that rapidly developing technologies are concerned with.

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

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

Due to the negative impact of human civilization on the planet's biosphere and climate, the sixth great extinction of many species of flora and fauna is currently taking place on planet Earth. The result is a rapidly progressive decline in the biodiversity of the planet's natural ecosystems. The aim is to halt or at least significantly slow down the progressive climate change, i.e. caused by increasing greenhouse gas emissions of the increasingly rapid global warming process. Many species of flora and fauna have already become extinct, many are on the verge of extinction due to a sharp decline in the number of individuals of the species. Some animal species are already found exclusively or almost exclusively in zoos. Few animal species have managed to be reconstructed on the basis of deliberate cross-breeding of species and varieties of closely related species. In order to increase the scale of the possibility of reproducing extinct species in the future, gene banks are being created, in which the genomes of specific species of flora and fauna are stored, including, above all, species threatened with extinction in the near future. Over the past few decades, insect populations, including pollinators, have declined by tens of percent in many parts of the world. The continuation of these processes, in addition to the rapidly advancing process of decline in biodiversity, the impoverishment of the planet's biosphere, will cause a rapidly advancing process of decline in the production of agricultural crops under the intensive, unsustainable and productive model of human farming. In countries occurring in the tropics, natural tropical rainforests continue to be cut down only to create new areas of arable land for the creation of arable fields where crops are grown to feed livestock generating high methane emissions. In addition, the new arable land created in this way is quickly eroded and the restoration of forest ecosystems back in these areas is also hindered for this reason. Coral reefs in the seas and oceans are also dying out, and the populations of marine fish and other animal species living in the seas and oceans are rapidly declining. Key factors in the still large-scale great sixth extinction of species of flora and fauna include continued deforestation, the cutting down of natural forest ecosystems to increase cultivated areas, the degradation of natural ecosystems caused by industrial development, continued high levels of environmental pollution, continued rising greenhouse gas emissions generating a progressive global warming process, etc. In view of the above, unsustainable intensive economy is causing a rapidly progressive decline in the biodiversity of the planet's natural ecosystems, and attempts are being made to counteract this. In order to slow down the progressive process of global warming, reduce greenhouse gas emissions, reduce the level of environmental pollution and devastation of natural ecosystems, reduce the scale of extinction of species of flora and fauna, slow down the process of decline in the biodiversity of natural ecosystems, it is necessary to urgently accelerate the processes of carrying out pro-environmental transformation of the economy in order to efficiently build a sustainable, green, zero-carbon zero-growth and closed-cycle economy. In the process of building a sustainable, green, zero-carbon zero-growth economy and a closed loop economy, new ICT information technologies and Industry 4.0/5.0 can help, including generative artificial intelligence technologies and multi-criteria processing of large data sets as part of ongoing research and analytical processes using Big Data Analytics. New technologies can help increase the efficiency and accelerate the process of a sustainable, green, zero-carbon, zero-growth and closed-loop economy and thus help protect the climate, biosphere and biodiversity of the planet's natural ecosystems. As part of the application of new Industry 4.0/5.0 technologies, including generative artificial intelligence and Big Data Analytics, it is possible to increase the efficiency of research conducted with the goal of reconstructing the genomes of extinct species of flora and/or fauna. In this regard, perhaps artificial intelligence combined with Big Data Analytics can help reconstruct the genomes of various species of flora and/or fauna that have recently become extinct due to humans and thus restore the former biodiversity of the planet's natural ecosystems.

I am conducting research in the issue of key determinants of the legitimacy of urgently carrying out a green transformation of the economy in order to build a sustainable, green circular economy. I have included the conclusions of my research in the following article:

IMPLEMENTATION OF THE PRINCIPLES OF SUSTAINABLE ECONOMY DEVELOPMENT AS A KEY ELEMENT OF THE PRO-ECOLOGICAL TRANSFORMATION OF THE ECONOMY TOWARDS GREEN ECONOMY AND CIRCULAR ECONOMY

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:

APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

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

I've recently released a software package that combines my research interests (history of science and statistics) and my day job (machine learning and statistical modelling) It is called timeline_ai (see https://github.com/coppeliaMLA/timeline_ai) It extracts and then visualises timelines from the text of pdfs. It works particularly well on history books and biographies. Here are two examples:

The extraction is done using a large language model so there are occasional inaccuracies and “hallucinations". To counter that I've made the output checkable. You can click on each event and it will take you the page the event was extracted from. So far it has performed very well. I would love some feedback on whether people think it would be useful for research and education.

In some countries, such as Japan, there have already been mass-produced robots for years that act as domestic helpers mainly for the elderly. Perhaps in the not too distant future, mass-produced autonomously functioning, programmable robots, including highly intelligent androids equipped with generative artificial intelligence technology, will also be on sale in many other countries. Such robots can act as domestic help, child or elderly caregivers. With the rapidly advancing technological progress being realized in the field of robotics, artificial intelligence and other technologies typical of the current fourth technological revolution, Industry 4.0/5.0 technologies will soon be mass-produced humanoid, highly intelligent, highly autonomous robots performing various household and other jobs. Such robots equipped with generative artificial intelligence technology can have a number of alternative algorithms built in to perform specific functions of their choice and can be programmable. Thus, after purchasing a kind of helper robot for household and/or other work, the robot owner will be able to determine the scope and types of functions for which he will give the robot authorization to perform them. The programming of the purchased robot will consist of selecting from the available options of various functions only those that will correspond to specific activities and tasks possible for the robot to perform. Also, the level of autonomy within a certain possible range from to will be able to be defined by the robot owner as part of the programming. In addition to typical household chores, providing assistance around the house involving, for example, cleaning, watering flowers, feeding pets, walking pets, such robots can act as controllers analyzing the operation of various household appliances and systems, including smart home systems, heating, ventilation, lighting, air conditioning, etc. Besides, the robots can act as a night watchman in the situation of the owner's departure from home, can act as a bodyguard for home assets, and can call for help in an unusual situation when the owner needs urgent assistance from public services, including the police, security company, health service, etc. Such intelligent robots can also have a permanent connection to the Internet and, according to the owner's command, can quickly search for something on the Internet, print it out or send it to a smartphone belonging to the owner of a particular robot.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

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

In order to reduce the growing scale of disinformation, including disinformation generated in social media through in the increasing scale of emerging fakenews, deepfakes, disinformation generated through the use of applications available on the Internet based on generative artificial intelligence technology, the just mentioned GAI technology can be used. Constantly improved, taught to carry out new types of activities, tasks and commands, intelligent chatbots and other applications based on generative artificial intelligence technology can be applied to identify instances of disinformation spread primarily in online social media. The aforementioned disinformation is particularly dangerous for children and adolescents, it can significantly affect the world view of the general public's awareness of certain issues, it can affect the formation of development trends of certain social processes, it can affect the results of parliamentary and presidential elections, it can also affect the level of sales of certain types of products and services, and so on. In the absence of a developed institutional system of media control institutions, including the new online media; lack of a developed system of control of the level of objectivity of content directed to citizens in advertising campaigns; lack of consideration of the issue of disinformation analysis by competition and consumer protection institutions; lack of or poorly functioning democracy protection institutions; lack of institutions that reliably take care of a high level of journalistic ethics and media independence, the scale of disinformation of citizens by various groups of influence, including public institutions and commercially operating business entities may be high and may generate high social costs. Accordingly, new technologies of Industry 4.0/5.0, including generative artificial intelligence (GAI) technologies, should be involved in order to reduce the scale of growing disinformation, including the generation of factoids, deepfakes, etc. in social media. The aforementioned GAI technologies can help identify fakenews pseudo-journalistic content, identify photos containing deepfakes, identify factually incorrect content contained in banners, spots and advertising videos published in various media as part of ongoing advertising and promotional campaigns aimed at activating sales of various products and services.

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in an article of my co-authorship:

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

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 regards,

Dariusz Prokopowicz

Perhaps in the future - as a result of the rapid technological advances currently taking place and the rivalry of leading technology companies developing AI technologies - a general artificial intelligence (AGI) will emerge. At present, there are unresolved deliberations on the question of new opportunities and threats that may occur as a result of the construction and development of general artificial intelligence in the future. The rapid technological progress currently taking place in the field of generative artificial intelligence in connection with the already high level of competition among technology companies developing these technologies may lead to the emergence of a super artificial intelligence, a strong general artificial intelligence that can achieve the capabilities of self-development, self-improvement and perhaps also autonomy, independence from humans. This kind of scenario may lead to a situation where this kind of strong, super AI or general artificial intelligence is out of human control. Perhaps this kind of strong, super, general artificial intelligence will be able, as a result of self-improvement, to reach a state that can be called artificial consciousness. On the one hand, new possibilities can be associated with the emergence of this kind of strong, super, general artificial intelligence, including perhaps new possibilities for solving the key problems of the development of human civilization. However, on the other hand, one should not forget about the potential dangers if this kind of strong, super, general artificial intelligence in its autonomous development and self-improvement independent of man were to get completely out of the control of man. Probably, whether this will involve mainly new opportunities or rather new dangers for mankind will mainly be determined by how man will direct this development of AI technology while he still has control over this development.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

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 regards,

Dariusz Prokopowicz

The growing volume of data that is processed in companies and enterprises determines the need to involve specialized software and information systems, thanks to which both the analysis of data will be carried out effectively and the results of the analytics carried out will enable the use of the resulting knowledge to support the management processes of the business entity. The issue of the scope of large amounts of data acquired from various sources, their storage and processing is related to Big Data Analytics technology. However, in order to significantly increase the efficiency of processing large sets of data and information with the use of this type of analytics to support the management process of the business entity, computerized, multi-module business intelligence applications are particularly helpful in this regard. The combination of database technologies and analytical platforms of Big Data Analytics and Business Intelligence type applications makes it possible, on the basis of large data sets containing not fully structured and organized data, to generate useful information for a specific entity, as well as concretized and sublimated substantive knowledge used to support the management process of an organization, institution, business entity, etc. In terms of the key objectives of the application of knowledge generated in this way, it is distinguished to improve the quality of business decisions, reduce the risk of making errors during the processes of managing the organization, improve risk management systems, increase the effectiveness of early warning systems of new threats and development opportunities, etc. Analytics conducted on large data sets and implemented using Big Data Analytics and Business Intelligence applications can help in the processes of carrying out restructuring, developing a new strategy, investment project, marketing plan, business remodeling, etc. Analytics based on Business Intelligence applications can be helpful in the processes of supporting the management of various spheres of business activity of companies and enterprises and thus supporting the operation of various departments, including procurement, production, distribution, sales, marketing communication with customers, relations with business contractors, financial or public institutions. Multi-module business intelligence information systems can operate as integrated information systems or can be one of the key elements of such information systems digitally integrating many different aspects of companies, enterprises or other types of entities. Besides, multi-module complex Business Intelligence information systems can be dedicated to handle and support the implementation of specific business processes at different levels of an organization's organizational structure, i.e. they can consist of modules dedicated to handling for operational employees, departmental managers, managers, but also the board of directors and the company's president. Besides, in connection with the development of deep learning technologies carried out using artificial neural networks and generative artificial intelligence technologies, there are opportunities to increase the scale of automation of analytical processes through the use of the aforementioned technologies. The application of artificial intelligence technologies to analytics carried out using Big Data Analytics and artificial intelligence can significantly increase the efficiency of analytical processes and in terms of supporting organizational management processes, can speed up decision-making processes and reduce the risk of errors. A particularly important attribute of such solutions is the ability to perform predictive analysis and forecasting, so that an entrepreneur can spot certain business and economic patterns in good time and forecast future financial performance and development trends more accurately. Thanks to the use of generative artificial intelligence technology, the functionality and usefulness of analytics based on Big Data Analytics and Business Intelligence class systems is significantly increasing.

In view of the rapid development of applications of generative artificial intelligence technology and its implementation into applications and information systems supporting business management processes, I addressed the Research Gate community of Researchers, Scientists, Friends with the above question.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:

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