Innovative value chain creation research according to AI jobs

Abstract

Purpose: It suggests that making a policy and strategies in a way of AI and its impact of commercialization on economic efficiency, social custom ethics. Research design, data, and methodology: The paper has analyzed the data based on the proposed model when derived as AI vs. FI job, etc. It is very different for each professional evaluation, which is artificial intelligence or robot job. One concept case was selected as a substitute job, with a relatively low level of occupation ability, such as direct labors, easily replaced. By the induction data has resulted in modeling. Results: The paper suggests that AI at high level become something how to make real decisions on ethical value modeling. Through physical simulation with the deduction data, it can be tuned to design and control what has not been solved, from human senses to climate. Conclusion: For the exploiting of new AI decision-making jobs in markets, the deduction data is possible to prove to AI's Decision-making that the percentage who can easily have different leadership as is different for each person. what is generated by some information silos may be applied to occupation societies. The empirical results indicate the deduction data that if AI determines ethical decisions (VC) for that modifications, it may replace future jobs.

1. Introduction

How can artificial intelligence improve our society? The process of growth into a DIGITAL country requires the potential of AI, the importance and role of ethics.

It is believed that this will enable the Smart Smart City of the 4th Industrial Revolution era to be implemented as an artificial intelligent system and to manage a large amount of data efficiently by changing into a new industrial structure. People believes that laws should be redefined in terms of ethics caused by linking existing objects to them, and artificial intelligence supports and creates new problems in addition to the benefits that industrial society has brought. Current and future artificial intelligence technologies can provide advanced education services that can adapt to people's capabilities and needs, and can react faster to humanitarian disasters, and more importantly, prevent and detect fraud.

1.1 Job structure in super network society

With artificial intelligence, some labor tasks or difficult or unpredictable ethic jobs will emerge as new jobs. For example, it can be helpful for repetitive, disordered labor intensity, dangerous work (repetitive approach to industrial equipment or difficult cleanings that are unsafe). Using artificial intelligence can organize and summarize large amounts of data and provide more accurate information and decision suggestions to get help as doctors diagnose. Ultimately, AI helps to improve people's abilities.

Artificial intelligence can provide new solutions to support more people to participate and maintain the labor market in an aging society, including people with disabilities. Different tasks will be replaced by common tasks. It is difficult to determine for each measure of each measure for any measure. Artificial intelligence works precisely by quantifying it to the appropriate task.

1.2 The mission of digital Europe

Digital Europe's mission is also applied human to robot against ethic job. it is to develop competitive industries in the European robotics and artificial intelligence field, from industrial and service robots to autonomous systems that handle unmanned aerial vehicles and unmanned vehicles to cognitive vision and computing. The Digital Europe project supports a broad understanding and use of robotics and artificial intelligence in all industrial and social fields.

Europe is responsible for the development and implementation of the Executive Committee's Robotics Agreement, PPP Participation and related strategic industry agendas by digitization. It manages RD&I projects in the H2020 strategy and ensures proper linkage with relevant national and regional activities. As finally added it adheres to the responsibilities and safety of ethical-legal issues associated with robots and autonomous systems, as well as aspects related to automation and robotics impacts on occupations and work environments.

2. Literature Review Model and Proposition

2.1. Precedent research of Robot Industrial Ethics

Europe seeks job innovation as a strategy for preparing for AI in Europe, and is looking for action plans in social and community relations. For this, community ethics is also important for artificial intelligence. So, a concrete discussion of the ethics of robots (artificial intelligence) in Europe can be referred to the "13 Principles of Robot Ethics" presented by the 2007 EUROCON (European Robot Research Network) at ICRA. This principle was specific enough to receive an evaluation that played a role in drafting other intelligence information technology ethics described below. This recommendation recommends that all researchers and designers involved in robot development should always consider human dignity, privacy and safety (Kim, 2017).

On the other hand, the European Union has established a guideline for robot regulation (2012.3 ~ 2014.3) (2014.9) after implementing the project for the legislation of robot law (2014.9) Submitted the 'Robotics Recommendation' to the European Commission (2017.2). This Recommendation was subjected that all researchers and designers involved in robot development must consider human dignity, privacy, and safety. But In industrial human-robot collaboration, variability is common in operating environments and components, resulting in uncertainties and errors that often require manual intervention for commutation (Wen & Chen, 2020). 

In addition, European Union has amended the GDPR to be applied to the artificial intelligence (robot) as it is, and it is expected to be an opportunity to legally demand the technical transparency of personal information processing.

EURON's 13 Principles of Robotics : [Principle 1] Human dignity and human rights, [Principle 2] Equality, Justice and Equality, [Principle 3] Profit and Loss, [Principle 4] Respect for religious diversity and pluralism, [Principle 5] Anti-discrimination and anti-stigmatization, [Principle 6] Independence and individual responsibility, [Principle 7] Responsibility based on public notice, [Principle 8] Privacy, [Principle 9] Reliability, [Principle 10] Solidarity and cooperation,[Principle 11] Social Responsibility, [Principle 12] Sharing of profits,[Principle 13] Obligation to Biosphere.

2.2. Establishment of Propositions

EU innovates artificial intelligence technology that strengthens European industry leadership, enhances scientific excellence, and leads AI applications to address social challenges in areas such as health, transportation and agriculture. The first, European Commission will invest approximately EUR 1.5 billion in 2018-2031. The Executive Committee try to breakthroughs in market creation innovation through the pilot phase of the European Innovation Council.

It focuses on SMEs, non-technical companies and public administration through the AI Research Excellence Center, and introduce AI across the board: AI on demand platforms enable support and easy access (latest algorithms and expertise; AI-centric digital innovation hub network facilitating testing and experimentation; industry data providing high quality data sets; Platform configuration, etc.). The Commission already was to promote private investment in AI in accordance with the strategic investment funds of Europe (2018 - 2 billion euros, at least 500 million euros).

The second, Commission's proposal, under the EU's multi-year financial assistance system (2021-2027), opens the door for investment in next one:

It will upgrade the AI center to a pan-European network. The first is research innovation in areas such as explanatory artificial intelligence, unchecked machine learning, energy and data efficiency. Second, the world's best test and test facilities are buffered in areas such as transportation, healthcare, agricultural products and manufacturing supported by hubs and regulations of digital innovation. Third, joint investment with member countries of European countries will help public services and organizations in all sectors adopting AI. Fourth, look for joint procurement for the use and development of AI. Fifth, the data-sharing support center is tightly linked with the AI on-demand platform to facilitate business and public sector application development.

First, Platform Organization: Healthcare Organization (data management for the environment, research and health in the public sector). Second, Manufacturing and Development Organization (General Data Protection Regulation). Third, Other digital ethics organizations (regulations such as the ePrivacy Regulation and the Cybersecurity Act), Digital Adult Care Center (upskilling training to train digital technology), Fourth, AI Social Partners Foundation (ICT private organizations and social partners) Dialogue with civil society organizations, to the government). So, it ensure that all citizens appropriately utilize this technology as a whole.

The final point make out overcoming Europe's three main challenges.

Europe emphasizes the fundamental role of education on vocational training for autonomous teachers and job trainer. The first challenge prepares society as a whole. Techniques are needed to help all European professionals to develop this basic digital technology and to complement them when it comes to replacing machines with critical thinking, creativity or management. The second includes occupations, workers and self-employment that will disappear due to automation, robotics and artificial intelligence.

There, priority is a need to focus efforts on the number of workers who are likely to be converted into jobs, and this should ensure the right to all citizens (because the pillars of European social rights are social security). Finally, the European Union is demanding more experts in artificial intelligence to create a suitable environment for AI under the old traditional system to be operated in the European Union (EU) and to attract more talents from abroad since 2016.

This study examines the effect of job creation model on the European and the neighboring countries as a result of AI diffusion, and considers it as the next step-by-step ‘Proposition.

'Proposition 1. In the short term, the model of AI digitization plan is related to job productivity and talent performance.

'Proposition 2. The preparation of the long-term AI industry is not related to the traditional ethics model, which is established by the ability of national response.

'Proposition 3. As a result, a new type of AI is derived from the balance between complementary stages and performance.

From the above ‘Proposition, who would you talk to before the AI makes a decision? or Who will the AI agree or reject the decision?, Who should know about AI's decisions? These make it difficult to make a 'decision' of a complex and important issue in fact. This is because the AI replacement rate will continue to be delayed in reasonable basis of public consultation as a justification and thorough its review.

3. Research and characteristics of the hyperlinked Europe

3.1 Ensure free ethics of personal data

The ethics of the 4th industry have to guarantee the free flow of personal data against data openness. Firstly, This includes provisions for decision-making only in processes based on automation, including profiling. The data subject has the right to be provided with meaningful information about the logic involved in the decision. The General Data Protection Regulation should give individuals the right not to commit themselves to automatic decisions by AI systems except in certain circumstances. The State should closely follow the application of the Regulation in the context of artificial intelligence and take the same steps to national data protection authorities and data protection committees. It will provide a series of proposals that should be the key driving force for AI development, such as the regulation on the free flow of non-personal information and plans to strengthen online trust.

This should ensure that such proposals are adopted as soon as possible in ethical regulations such as the ePrivacy Regulation and the Cybersecurity Act, except bad things. Citizens and businesses all have to rely on effective means of trusting interoperable technologies, having a predictable legal environment and protecting basic rights and freedoms. To further enhance trust, people need to understand the importance of research on the explanatory power of artificial intelligence systems by understanding how technology works. In fact, in order to increase transparency and minimize the risk of bias or error, the AI system must be developed in a way that humans can understand their behavior. Like all technologies and tools, because AI can be used in not only positive but malicious ways. AI clearly creates new opportunities, but challenges and risks arise in the areas of safety and responsibility, security (cyber criminal attack), prejudice and discrimination. These require a review of the interaction with other countries between AI and intellectual property rights from the point of view of the IP office and the user in order to foster legal certainty in a balanced way.

Secondly, The characteristics of complex ecosystems and autonomous decision making, accompanied by the emergence of artificial intelligence, are required to consider the suitability of some provisions on safety and civil law to liability.

For example, because the Internet (IoT) of advanced robots and objects authorized by artificial intelligence can operate in an unpredictable manner, so AI's wide range of uses considering the horizontal, sectoral rules should be done.

First, the national security framework will consider using intended anticipated (wrong) use of the product when it is released on the market. This is because it leads to strong standards development in the field of artificial intelligence equipment that is continuously applied consistent with the advance of technology. At the International Organization for Standardization, by developing and promoting these safety standards and support, domestic enterprises can gain profits through competitive advantage and increase consumer confidence. The country is currently evaluating whether the framework of a safe or national responsibility matches the objective or whether it fills the gap in light of these new tasks. High level of safety and efficient relief for victims in case of damage, supports the trust and social acceptance of users of these technologies (conduct product liability guidelines and machine directive evaluation).

Second, the consumer receives clear information about the use, characteristics and characteristics of AI-enabled products. Capacity building to enable individuals and consumers to make the most of AI and large-scale use of AIenabled tools in business-to-business transactions must be fair and transparent and comply with consumer laws. Individuals should be able to control the data generated using ethical tools and know whether they are communicating with computers or other people. Especially they need to consider how to inform users about them, and to reach humans when interacting with automated systems and, to check and change system decisions.

Third, stakeholders and experts form an AI alliance. This is for co-operation with a group on ethics in science and technology to develop a draft AI ethics guideline with basic rights in mind.

Fourth, a document on the interpretation of production liability guidelines should be issued from the viewpoint of technology development such as developer, producer, and user. This requires efforts to ensure legal clarity for consumers and producers of defective products. This is because the AI must present a report on the broader impact of potential gaps and directions on the responsibility of the Internet and robots and the safety system of things.

Fifth, in order to support exploitable the artificial intelligence (AI) development study, the National Assembly will implement this proposed demonstration project to collect robust documentation and support designing policy responses to problems caused by automated decision making (such as prejudice and discrimination).

It firstly must support national level consumer organizations and data protection regulators in building AI understanding of AI-based applications by collecting AI ethical perceptions from consumer protection groups and data protection committees under the guidelines above.

(1) the importance of ethics in the development and use of new technologies; it making an attractive environment for accommodation in government for the best talent education.

(2) Education and vocational training: In order to confirm that non-discriminatory ethics including artificial intelligence are included, it is also possible to interdisciplinary (by encouraging a joint degree, for example, law or psychology and artificial intelligence ). First, encouragement: depending on the work experience, it encourage young people to choose artificial intelligence on the subject-related field, and promote initiatives, depending on work experience. Second, digital internship: the government presents "support opportunities traineeships", a support internship, to master advanced digital technology. Third, experts training: spreading coding technology, it should be increasing the number of personnel of digital technology and work purpose cooperative objective and digital experts.

4. Research Results of 4th wave on Science Strategy POLICY

As the following table 1. confirms ‘Proposition 3 : a new type of AI is derived from the balance between complementary stages and performance.

Table 1: The Job ethic value based on the case of Top Job's high risk vs. low risk

(1) Policy commercialization promotion system: It is reflected in social change in a potentially deeper way.

A. Moral construction - It is estimated that about 90% of road traffic accidents are caused by human error. The committee's report (COM (2016) 0787 final) worked on automation of knowledge labors, robotics and self-driving vehicles in 2025 from 6.5 to 12trillion a year (increasing productivity, improving the quality of life guarantees in the EU's self-influence of economic knowledge included). In addition, in an aging population, artificial intelligence can significantly improve public services and help achieve the goals set out in the “Electronic Government Ministerial Declaration”.

B. Building Leadership Experts: The report from the "High-Level Group on Industrial Technology" recognized the innovative role of artificial intelligence and the "technology enabling core technologies" that emphasized the need for industry to maintain leadership using artificial intelligence. The Executive Committee has launched the European Common Interests Critical Project Strategic Forum to support and secure large-scale financing appropriate to the value chain of European strategic importance, including the integration of AI to strengthen EU industrial leadership.

When comparing leadership with A.I. to global manufacturers, Wu & Wu (2017) got the following results with the elitist that elite strategies have been adopted to prevent the destruction of the optimal solution during evolution. The results showed that the proposed algorithm outperformed the best-known algorithm for FJSP in most FJSP benchmarks.

Figure 1: Job Volatility against automating

The Executive Committee also supports and promotes regional partnerships for investment in advanced technology and AI through the Smart Specialization Platform in the field of industrial automation.

(2) Incentive system: Ensures workers are given opportunities to apply new opportunities to artificial intelligence, to access and adapt to the important things for people.

(3) Artificial Intelligence Sharing System: Like other technologies, it is not imposed only on artificial intelligence society. The process of ensuring that the benefits are shared extensively is made possible by the collective use of AI technology and It can be so, the inclusion of social partners, civil society organizations, dialogue, the government and all citizens appropriately are widely shared.

Naqvi (2017) does not cover how to lead a workshop consisting of intelligent machines.Specifically, however two levels of leadership require analysis. leadership had to lead companies through a big shift from industry-information to cognitive economy. Then the intelligent machine reached stability and maturity, which occupied the central position of the workforce, it was necessary to manage and lead the company. Although there is extensive research in leadership theory, Naqvi (2017) should bridge the gap linking the field of applied artificial intelligence with leadership theory.

5. Korea perspective

5.1. Reorganization of cities and professions of science innovation

Countries around the world are required to utilize public data on private data, traffic system information, ecosystem, and sensor data of traffic lights. In the future, Korea should handle small data in public data rather than big data in local governments. Analyzing what happens in our daily life, here in Korea + data jacket emphasizes The - protection that is not disclosed.

In one case - the United States has provided $ 1 trillion to a specialized agency for AI-related assistance, however, has budgeted for both engineering scientists and humanities and sociologists. For future it also requires why autonomous weapons, and decision support systems(Pfaff, 2020).

This requires solving the ethical problem - because the data can be used as a successful case, and the engineering research and development part is reduced to 1/4.

Similarly, in urban administration, transparency of administration is important in the utilization of data. Just like the failure of U City in Korea in the past, AI Smart City, which is now being implemented, can only become like an apartment cluster. If so, artificial intelligence or robots could be easily replaced whole process jobs and difficult field jobs, however experts evaluate is very different. One example is that by 2030, substitute ratios were selected as jobs that are relatively easy to replace, such as cleaners and kitchen assistants, who are relatively low in vocational ability. On the other hand, professions such as accountants and aircraft pilots have relatively low substitution rate of work performance, then artificial intelligence is difficult to replace.

Figure 2: ICT sectoral correlation

Table 2: Multiple linear regression on future industry (1)

Table 3: Multiple linear regression on future industry (2)

It is because professions unlike or like AI generally require comprehensive problem-solving ability and judgment depending on the situation. This explains why it is necessary to interpret the legal system (accountant) with leadership or make important decisions (aircraft pilots) related to the life and safety of passengers in an emergency. The result is that artificial intelligence or robots with following pre-defined rules are difficult to replace all over fields in countries with high corruption index.

A. ICT Future Industry Group Sectoral Correlation (Regression Analysis)

It is data of the survey from Future of Jobs 2018, World Economic Forum,“ Technology adoption by industry and share of companies surveyed“. Future industry occupation

(User and entity big data analytics, App- & web-enabled markets, Internet of things, Machine learning, Cloud computing, Digital trade, Augmented and virtual reality, Encryption, New materials, Wearable electronics, Distributed ledger (blockchain), 3D printing, Autonomous transport, Stationary robots, Quantum computing, Nonhumanoid land robots, Biotechnology, Humanoid robots, Aerial and underwater robots), It was found that ICT would only affect the next occupational group (excluding Travel & Tourism).

＊Dependent variable(Occupational field): Information & Communication Technologies. ＊Independent variables: Automotive, Aerospace, Supply Chain & Transport, Aviation, Global Health & Healthcare, Professional Services.

B. Results of correlation analysis of future job groups for Modify value chain

The result of polynomial function is that only (1) Expand the workforce, (2) Bring financing on-board for transition has significant value. And the rest is irrelevant for (3)Modify value chain, (4)Reduce workforce due to automation, (5)Expand task-specialized contractors, (6)Modify locations of operation, (7)Expand workforce due to automation.

Figure 3: Modify value chain correlation

Table 4: Multiple linear regression on future job (1)

Table 5 : Multiple linear regression on future job (1)

This means that the application of current technology in the AI-related industry of the future occupational group will only rapidly change “Expand the workforce, Bring financial provision“ for industrial transformation.

As the result above, Jones (2018) may differ from what was presented. The use of unpredictable and unimaginable data in AI systems is considered a feature, not a bug. However, this feature not only evaluates when consent is required based on potential use, harm, and consequences, but also has problems in notifying users.

These results can be demonstrated that the leadership of ethical values previously demonstrated should be embraced,  followed by a sudden change in artificial intelligencerelated fields in the overall future industry occupational group.

5.2 Korea's replacement rate for AI ethics

The occupational groups related to moral ethics are constantly maintained and demanded such fields even though new jobs are always created in the fourth industrial wave.

There, however is a problem here. The ethics and morality of Korea are not yet fully understood and systematically agreed upon it. This is because they are not trying to be absorbed perfectly into the fourth wave as they do not abandon their existing vested rights. It confirms that future growth has been taken their place when given up ethical ownership. The Decisions on legal interpretation, problem solving, and safety derived from the social consensus of a nation are allied to AI. those jobs with indirect worker become jobs to disappear. Alternative ratios proposed by the above research institutes can only mean 'technological' substitution by artificial intelligence or robots. Whether or not the actual artificial intelligence or robot will replace them is determined by economic utility or social consensus. Because the AI will make a big difference in the world of work. and evolve into AI vs. FI (Fusion Intelligence).

However , Vochozka (2018) insisted that companies need to consider how work as cognitive skills evolve, is done with specific innovative applications, detailing the division of labor between workforce and artificial intelligence.

Professions such as accountants and airplane pilots have a relatively low substitution rate, and AI is difficult to replace. As a result, the AI can be programmed to schedule what actually happens through processor control, such as climate. If AI decides whether it is right, then future decisions will be possible. These possibilities lead to unexpected new career changes against AI, the deduction data is analyzed in many ways require more robust research. Here, the work created by the 6 human senses is applied as job. Under assumptions, big data, analyzed in many ways. what is generated by human intuition (some information silos).

6. Conclusions

The demonstration suggestion in this paper is the influence on the economics and social customs ethics of (new occupation) associated with the commercialization of AI. It makes ethical decisions for that purpose, future decisions can be substituted. However, This paper demonstrates how high-level AI makes human modeling decisions. It is designed for new work and controlled as unsolved by tuning the profession through physical simulation rules (normalized value dataization). This requires a more thorough study, as jobs created by human intuition (some information silos) are sometimes applied to traditional jobs and societies.

As a result, AI is evolving in the job world with a lot data changes and AI's fusion intelligence work. This eliminates inaccurate silos of information from occupational groups for data standardization.

This is because AI changes a great deal in the professional world and evolves to AI's Fusion Intelligence Job. The paper also proves that as a result of analyzing the data based on the proposed model, it has been derived to the AI occupation. So, it can be have the paper industry schedule programming for the AI job to do the actual work through control of processors like climates.

The high level of AI will show you how to make the actual modeling decisions. For the new job it is designed and controlled as if it was not solved by tuning it through physical simulation rules. There are also cases where something generated by human intuition is applied.

Instead of thorough automating each human work, they should gradually have leadership in the automating work for various fields to connections, mainly as they reinforce human workers. It can see that career group is turning into leadership. This is because cognitive technology cannot drastically change organizational structure.

This work was supported by the National Research Foundation (NRF) of Korea grant funded by the Korean Government (NRF2018R1D1A1B07050680)