1. Introduction2. Theoretical framework2.1. Introduction2.2. Definitions2.3. The history of artificial intelligence2.4 People VS Robots – a collision of the 21st century 2.4.1. The reasons of replacement2.4.2. Fields of application of artificial intelligence 2.4.3. Sub-conclusion2.5. The influence of artificial intelligence on labor market2.5.1 . Introduction2.5.2. Complimentary of workers2.5.3. Shift in demand on the labor market2.5.5. Social inequality2.5.6. Sub-conclusion2.6. Conclusion for Theoretical framework 3. Policy/Advice3.1. Introduction3.2. Public regulation of implementation AI3.2.1. Firing rate3.2.2. Tax policy3.2.3. Retraining programs 3.2.4. Unemployment benefits3.3. Conclusion policy4. Reflection 5. Bibliography 2 THEORETICAL FRAMEWORK2.1 IntroductionArtificial intelligence and economics are closely linked, complementary and in the nearest indivisible future. (Wisskirchen, Biacabe & Brauchitsch, 2017) Modern information technologies and the emergence of machines powered by artificial intelligence have already strongly influenced the labor market in the 21st century. (Wisskirchen, Biacabe & Brauchitsch, 2017) Computers, algorithms and software make everyday tasks much easier, and now it is difficult to imagine how things could be handled without them. (Wisskirchen, Biacabe & Brauchitsch, 2017)Even before the end of this century, 70% of modern professions will be automated. (DeCanio, 2016) The penetration of robots into all areas of human life is inevitable, and the replacement of people by them is only a matter of time. (DeCanio, 2016) Artificial intelligence (AI) was initially created as an attempt to imitate human intelligence, but nowadays it has become a socio-economic force, a form of high technology with all the appropriate social relations. (Decker,Fischer & Ott, 2017). A wide-spread process of automation will affect all types of employment: from physical to intellectual labor. (DeCanio, 2016)2.2 Definitions2.3 The history of artificial intelligence2.4 People VS Robots – a collision of the 21st century 2.4.1. The reasons of replacementAccording to a capital-skill complementarity theory (Decker,Fischer & Ott, 2017), firstly jobs that connected with repetitive, monotonous, heavy and dangerous handling operations will be replaced. Such jobs could be easily carried out by AI, mimicking human behaviour.But nowadays human behavior imitation is no longer sufficient: artificial intelligence can exceed human intelligence and generate another one. (DeCanio, 2016) Modern robots can replace not only unskilled work, but also perform tasks that extend beyond human capabilities. For instance, robots, in comparison to people, can easily cope with a flight to Mars or immersion in the Mariana Trench. (Decker,Fischer & Ott, 2017) Some tasks robots are able to perform with greater accuracy and better quality. In these areas, the process of implementing AI has been going on for a long time, and every year it only accelerates. (Decker,Fischer & Ott, 2017) However, not all operational processes can be fully automated. (DeCanio, 2016) In such cases, the division of a complete task into a series of small replaced tasks, can become the key to the significant quality improvements of the final product. (Decker,Fischer & Ott, 2017) As a result, a production process was created, in which automated work sequences were executed by machines, and non-automated tasks continued to be performed by people. (Decker,Fischer & Ott, 2017)2.4.2. Fields of application of artificial intelligence Artificial intelligence has been used in a variety of areas including medical diagnosis, stock trading, robot control, law, remote sensing and scientific discovery. (Pannu, Tech, 2015) Artificial Intelligence in MedicineArtificial intelligence has the capacity of being applied in almost every field of medicine. As a rule, AI is used for diagnostic sciences in biomedical image classification. (Shubhendu, Vijay 2013) Intellectual analysis based on different models and decision-support tools are important in diagnosis determination and its evaluation. AI technologies may help a radiologist who uses the output from an automated analysis of medical images in detecting pathologies, assessing scope of disease, and improving the accuracy and consistency of radiological diagnosis to reduce the rate of false negative cases. (Shubhendu, Vijay 2013) Artificial Intelligence in Accounting DatabasesFurthermore, artificial intelligence may be considered as the foundation of eliminating accounting databases weaknesses. People are met with difficulties in analysing large volumes of data, however integrating AI in accounting databases can abolish these problems. (Shubhendu, Vijay 2013) Without human participation such models help the users to sort through huge amounts of information. Thus, the systems based on AI can analyze the data and assist the users understanding or interpreting transactions to determine what journal entries are reflected by the system.( Shubhendu, Vijay 2013)Artificial intelligence for public safety and securityMany countries have already begun to use AI technologies for public safety and security. By 2030, the typical North American city will extensively apply them. (Grosz, Altman & Mitchell, 2016) For instance, cameras for monitoring that can detect anomalies pointing to a possible crime or violation.(Grosz, Altman & Mitchell , 2016) Also like most issues there are benefits and risks. Gaining public trust is crucial. While there are valid concerns that policing that considers AI may become authoritative or uniquious in some contexts, the opposite is also possible.(Grosz, Altman & Mitchell 2016) But assuming slow deployment, AI may also help remove some of the prejudice in human decision-making. (Grosz, Altman & Mitchell 2016)2.4.3. Sub-conclusion Today, it may be challenging to predict exactly which jobs will be immediately most affected by AI-driven automation. (Mannino, Althaus & Metzinger,2015) Because AI is not a single technology, but rather a collection of technologies that are applied to specific tasks, the effects of AI will be felt unevenly through the economy. Some work tasks will be more easily automated than others, and some jobs will be affected more than others(Mannino, Althaus & Metzinger,2015) Artificial intelligence gives the ability to the machines to think analytically, using concepts. It will continue to play an increasingly important role in the various fields and help solving difficult problems in diverse areas as science, engineering, finance, medicine, weather forecasting. Even nowadays the areas employing the technology of Artificial Intelligence have seen an increase in the quality and efficiency.(Mannino, Althaus & Metzinger,2015) 2.5 The influence of artificial intelligence on labor market2.5.1 IntroductionIn light of recent successes in the field of machine learning and robotics, it seems there is only a matter of time until even complicated jobs requiring high intelligence could be comprehensively taken over by machines. (Mannino, Althaus & Metzinger,2015) If machines become quicker, more reliable and cheaper than human workers in many areas of work, this would likely cause the labour market to be uprooted. (Mannino, Althaus & Metzinger,2015) AI has already begun to transform the international labor market, changing the types of jobs available and the skills that workers need to thrive. Artificial intelligence brings a seismic shift in the future of work – making some roles obsolete, enhancing others, while creating new jobs and even spawning new professions. (Mannino, Althaus & Metzinger, 2015)2.5.2 Complimentary of workers Given the ability of robots, they can serve as collaborators of human labor. Generally this means that robots do not only substitute human labor, but complement it and, in certain areas, make it even more effective. (Decker,Fischer & Ott, 2017) AI expands labor by complementing human capabilities, offering employees new tools to enhance their natural intelligence. (Decker,Fischer & Ott, 2017)For example, Praedicat, a company providing risk modeling services to property and casualty insurers, is improving underwriters’ risk-pricing abilities. (Purdy, Daugherty, 2016) Using machine learning and big data processing technologies, its AI platform reads more than 22 million peer reviewed scientific papers to identify serious emerging risks. As a result, underwriters can not only price risk more accurately, but also create new insurance products. (Purdy, Daugherty, 2016)2.5.3 Shift in demand on the labor market What types of jobs will AI create ?Those who will benefit the most from technological progress are the people and nations that understand how to make use of new technological opportunities and the corresponding flow of “big data”. (Mannino, Althaus & Metzinger,2015) One example of a newly created job is that of the data scientist. The task is to structure huge data volumes collected by big data analyses. This includes the research of both the data and their structure or origin, to supplement incomplete data sets and to create links between abstract data sets.(Purdy, Daugherty, 2016)A global study (Wilson, Daugherty,& Morini-Bianzino,2017) asserts that AI will create 3 representative roles of data professionals: TRAINERS : Trainers teach AI systems how they should perform, help natural-language processors and language translators make fewer errors. They teach AI algorithms how to mimic human behaviors. EXPLAINERS: Explainers bridge the gap between technologists and business leaders. They help provide clarity, which is becoming all the more important as AI systems’ occupancies increases. SUSTAINERS: Sustainers help ensure that AI systems are operating as designed and that unintended consequences are addressed with the appropriate urgency.TrainersCustomer-language tone and meaning trainerTeaches AI systems to look beyond the literal meaning of a communication by, for example, detecting sarcasmSmart-machine interaction modelerModels machine behavior after employee behavior so that, for example, an AI system can learn from an accountant’s actions how to automatically match payments to invoices.ExplainersContext designerDesigns smart decisions based on business context, process task, and individual, professional, and cultural factors.Transparency analystClassifies the different types of opacity (and corresponding effects on the business) of the AI algorithms used and maintains an inventory of that information.SustainersAutomation ethicistEvaluates the non-economic impact of smart machines, both the upside and downside.Automation economistEvaluates the cost of poor machine performance.Overall, employment in areas where humans engage with existing AI technologies, develop new AI technologies, supervise AI technologies in practice, and facilitate societal shifts that accompany new AI technologies will likely grow.(Wilson, Daugherty,& Morini-Bianzino,2017) Job obsolescence On the other hand, most of all lower-paid, lower-skilled, and less-educated workers will be threatened by automation. Routine-intensive occupations that focused on predictable, easily-programmable tasks—such as switchboard operators, filing clerks, travel agents, and assembly line workers— were particularly vulnerable to replacement by new technologies. Some occupations were virtually eliminated and demand for others reduced. (Purdy, Daugherty, 2016)This means that automation will continue to put downward pressure on demand for this group, putting downward pressure on wages and increase inequality. In the long-run, there may be different or larger effects.(Wilson, Daugherty,& Morini-Bianzino,2017) 2.5.5. Social inequalityThe critics assert that even if technological automation may not increase unemployment, it can destroy middle range jobs and increase those on the low and high ends, thus lead to social inequality.(Wisskirchen, Biacabe & Brauchitsch, 2017) The increasing demand for data, computer professionals resulted in raising their salaries simultaneously while eliminating necessity in clerical positions. Shifting demand towards more qualified labor increased the relative pay of this group, contributing to rising inequality. (Wisskirchen, Biacabe & Brauchitsch, 2017)It would be wrong, however, to believe that inequality is purely a function of technology. Relative wages do depend in part on the demand for labor, which is partially a function of technology. However, they also depend on the supply of different levels of skill—in other words, the distribution of educational attainment (Goldin and Katz 2008)—and also on institutional arrangements that affect wage setting, such as collective bargaining (Western and Rosenfeld 2011).2.5.6. Sub-conclusionFor economic reasons, numerous jobs will be carried out by intelligent software or machines rather than by humans in the future. Both blue-collar and white-collar sectors will be affected. It must be noted that no jobs will be lost abruptly.(Mannino, Althaus & Metzinger,2015)Instead, a gradual transition will take place, which has already commenced and differs from industry to industry and from company to company. One of the biggest fears around robots and AI in the workplace is that many jobs will be replaced and income inequality could rise. (Mannino, Althaus & Metzinger,2015)3. POLICY/ ADVICE3.1. IntroductionResponding to the economic effects of AI-driven automation will be a significant policy challenge for the governments and its successors. In this section, the advice and policy regarding influence of Artificial Intelligence on labor market will be considered. They will allow to solve the following management problem: “How can the government influence unemployment, caused by implementation of AI?”3.2. Public regulation of implementation A3.2.1 Tax policy Tax policy plays a critical role in combating inequality, including income disparity that may be exacerbated by changes in employment from AI-based automation. A progressive tax system helps ensure that the benefits of economic growth are broadly shared, pushing back against increased inequality in pre-tax income. (M. West, 2015) Progressive taxation is critical for raising adequate revenue to fund national security and domestic priorities, including supporting and retraining workers who may be harmed by increased automation. (M. West, 2015)One of the ways to modernize the tax policy is implementation of “tax on robots”. It proposes either directly tax automated machinery or, more commonly, the capital gains accrued by corporations from the use of automated machinery that has a labor-displacing effect. Moreover, it will lead to transferring capital from automated fields to ones that can not be AI-assisted. (M. West, 2015)3.2.3. Retraining programs AI changes the nature of work and the skills demanded by the labor market, workers will need to be prepared with the education and training that can help them continue to succeed. Delivering this education and training will require significant investments. (Mannino, Althaus & Metzinger,2015)This starts with providing all children with access to high-quality early education so that all families can prepare their students for continued education, as well as investing in graduating all students from high school college- and career ready. Assisting U.S. workers in successfully navigating job transitions will also become increasingly important; this includes expanding the availability of job-driven training and opportunities for lifelong learning, as well as providing workers with improved guidance to navigate job transitions.(Mannino, Althaus & Metzinger,2015)3.2.4. Basic income guaranteeWith jobs disappearing to robotics and worker wages stagnating, governments should provide “a payment that would give the chance to live reasonably”. This proposal must be structured in a way that balances payments with work encouragement. Otherwise, people may stop working and do little to contribute to community goals. Yet evidence from abroad shows that giving people basic money does not create dependency. (M. West, 2015)According to Charles Kenny of the Center for Global Development, providing a social safety net “may help lift people up and out of poverty. Give poor people cash without conditions attached, and it turns out they use it to buy goods and services that improve their lives and increase their future earnings potential”. (M. West, 2015)Another tool of social policy is revamping the earned income tax credit (EITC). The goal of this proposal is to encourage people to work but make sure they have basic support for very low incomes. Income transfers take place only once a year, at the time of tax filing and refunds. If large numbers of people have no jobs and little income, the EITC would need to be configured and applied to broader groups of people.(M. West, 2015)3.3. Sub-conclusionEconomic incentives and public policy can play a significant role in shaping the direction and effects of technological change. Given appropriate attention and the right policy and institutional responses, advanced automation can be compatible with productivity, high levels of employment, and more broadly shared prosperity. The policies described above may be implemented by governments in order to take care of citizens and, therefore, solve the management problem: “How can the government influence unemployment, caused by implementation of AI?”4. ReflectionThe aim of this report was to make an attempt to solve the management problem: “How can the government influence unemployment, caused by implementation of AI?”It must be stressed out that recommended policy referred to the government perspective, because most companies would unequivocally prefer replacement of employees by AI based on cost-savings principles. During the research process, it turned out that a policy could not be applicable for all countries. One of the limitations is the stage of country’s high technology development. Obviously, implementation of defined measures is pointless in countries with low technology progress, because the last have other reasons for unemployment. Another limitation is that predicting future job growth is extremely difficult, as it depends on technologies that do not exist today and the multiple ways they may complement or substitute for existing human skills and jobs.