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8. Different Models of Political Reactions in:

Henry Alexander Wittke

Artificial Intelligence, page 64 - 69

An Approach to Assess the Impact on the Information Economy

1. Edition 2020, ISBN print: 978-3-8288-4459-9, ISBN online: 978-3-8288-7480-0, https://doi.org/10.5771/9783828874800-64

Tectum, Baden-Baden
Bibliographic information
ity be muted while preserving its ability to allocate resources efficiently and reward initiative and effort? What do fulfilling lives and healthy communities look like when they no longer center on industrial-era con ceptions of work?” (Makridakis 2017: 20f.). Yet, before turning to these questions, the analysis throughout of the current paper suggests the need to create political strategies to avoid scenarios of increasing mass unemployment or social inequality. 8. Different Models of Political Reactions The outlined AI revolution and emerging trends in IT will unfold over the coming decades with enormous opportunities, challenges, and impli cations for the information society. “To harness these benefits, countries will need to create conditions that support the deployment o f next-generation networks and ser vice infrastructures. In order to track the growth and impact o f these emerging ICT trends, new global indicators will need to be put in place.“ (International Telecommunication Union 2017). Thus, policy makers need to invent ways to make sure that everyone in society benefits because they have a responsibility to support the positive future development of their respective countries. Questions raised on a political macro-level are for example: How do regulators make these new patterns in AI and humanity symbiotic? How do politicians interact with emerging tech and new opportunities offered by AI? Regulators, politicians, and policy makers are called upon to create con ditions facilitating entrepreneurial experiments and innovation, and to find out how a human-machine integration can work most efficiently. Policies will also have to mitigate challenges to employment, rising ine quality but also information security and privacy issues (cf. Rotman 2017; International Telecommunication Union 2017). All in all, many political questions are coming up and should be answered before it is too late, and the pessimistic scenario outlined in chapter eight comes true. Politicians should support and invest in re search about all relevant topics such as privacy, ethical and social issues as well as new concepts for the future world of work. International ef forts are getting more important to work on these global topics caused by AI. Establishing a cross-cultural dialogue about specific AI issues and 64 building a learning network for investigating approaches to address these issues within and across domestic and global contexts, are an important outcome (cf. Berkman Klein Center 2017), as exemplified by the first US-China AI summit in June 2018 in California, Monterey. The most important goal should be that the negative consequences should be mitigated or made compatible with society. In the following, approaches to possible policy reactions are discussed in response to both scenarios developed in chapter eight. 8.1. Retraining, Focus on Education and Prepare a New Workforce As already discussed in chapter seven, scholars believe that AI will bring innovations that will change the way people work and the skills demand ed by the labor market. However, the technological upheaval will cause disruption. For example, a recent survey commissioned by Northeastern University in Massachusetts and conducted by Gallup finds that most of the American workers believe they are ill-prepared to deal with A I’s ex pected impact on the global digital economy (cf. Northeastern News 2018). Policy makers have to make sure that people will get enough edu cation, training, and support to even prepare for newly created jobs be cause of the technological upheaval. Because of this, funding in educa tion and retraining programs focused on developing fusion skills for the age of AI can be one of the most important steps in the face of an in creasing human-machine integration (cf. Dugherty/ Wilson 2018; Wachtel 2018). IT professor Acemoglu announced recently at MIT Technology Review’s EmTech Next conference the central message: “Societies must invest in education and welfare services in order to realize the full benefits o f robotics and AI. It’s not anyone’s re sponsibility by themselves; it’s our collective responsibility.“ (Ac emoglu MIT 2018). A commitment to preparing citizens to adapt to continuous and rapid technological change, and the beginning of strong AI, requires pursuing policy changes that would significantly expand the availability of highqualityjob training to meet the scale of need. In addition, regulators have to navigate job transitions of the people more successfully. Another key action towards preparing individuals for the economy of the future is providing quality education and specific training opportunities for all. By 65 that, it also gets increasingly important that governments make key in vestments in school education for children from all income backgrounds off to the right start (cf. U.S. Government 2016). One conclusion of the first analysis of the information economy says that AI will aid humans to make better decisions in almost every industry. But to harness these benefits, each algorithm needs to be tailored careful ly to existing data, and the objectives pursued, which requires considera ble human expertise in machine learning and large datasets to train these algorithms (cf. International Telecommunication Union 2017). For this goal even information worker needs to be educated enough as well, so retraining-programs and basic research seems more important than ever for today’s information societies. For example, based on the analysis of the information economy, within the education sector is an enormous potential for AI in the future. It is enabling teachers and students enor mous benefits (See Chapter 5.1). But implementing and deploying this technology at school requires government investment in education re sources. All in all, governments and regulators also play an essential role in advancing the AI field by investing in basic research and development. They need to retrain the worker within the society and educate a work force that develops AI, which includes researchers who drive fundamen tal advances in AI and related fields, a larger number of specialists who refine AI methods for specific applications, and a significant number of users who operate those applications in specific settings. These workers of the future will also need comprehensive training in ethics. It is fundamental for them to navigate a world in which the value of human beings can no longer be taken for granted. Even the fields of cyberdefense and fraud detection are getting more and more important regarding the safety of the information society. But fundamental ques tions have to be answered still, like, can robots and humans work togetherjust as smoothly? That is a current goal of researchers in the Tellex lab for example. They are trying to give both robots and humans the tools to understand each other a little better and work together more fluidly in real environments by understanding each other’s different strengths and using them together in the most efficient way (cf. Regalado 2018; U.S. Government 2016: 27ff.; Mahroum 2018). This increasing human and machine integration could lead to a much better output of almost every kind of task. These technological benefits are a huge chance to solve the most important problems in an increasingly complex information socie ty. 66 Against this background, education must be ensured and focused more than ever before. Especially based on the assumption that the demands on the jobs of the future will increase. Joseph E. Aoun, President of the Northeastern University in Massachusetts, recommends: “The answer to greater artificial intelligence is greater human intelligence.” (NortheasternNews 2018). In conclusion, these education and retraining programs are important strategies for the future of today's information societies, in which the human-machine symbiosis will be essential. For this, it is essential to determine how people can work together in an optimal relationship with robots and AI-driven applications. This suggests that both humans and machines should better understand the opposing part. All in all the syn thesis of tasks getting done by machines and others by people will be even smarter than just one side of the equation. 8.2. Discourse of a Basic Income Whether strong AI causes a scenario of mass unemployment and increas ing social inequality depends not only on the technology itself but also on the framework conditions of society, like institutions or policies, that are in place. On the basis of the literature dealing with the prevention of such future scenarios, some scholars believe the governments should in stitute a so-called basic income. Especially as described in chapter eight, tech titans like Elon Musk or Bill Gates and the academics around them are concerned that AI and robots they have built will rapidly displace humans in the work force, or at least push them into jobs with no room for growth (cf. Ito 2018; Freedman 2016; Amadeo 2018). In summer 2016, former American president Obama addressed the idea of a universal basic income in an interview with the Director of MIT's Media Lab, Joi Ito: "Whether a universal income is the right model — is it gonna be accepted by a broad base of people? — that's a debate that we'll be having over the next 10 or 20 years." (Clifford 2016). Against this backdrop, the basic-income concept has regained popularity. The idea is still mostly theoretical, but in the last years, there have been 67 intensified discussions, concrete plans, and a number of experiments re garding basic income around the globe. Most of the experiments offer basic income as a solution to automation, lack of disposable income, benefit traps, or a bloated bureaucracy (cf. Oxford University 2016; King 2016; Amadeo 2018; The Next Era 2017). But the idea of a basic income is actually not new. There were famous advocates in the last century. For example, Martin Luther King, Jr. (1967) said a guaranteed income would abolish poverty, which means reducing inequality as well. Economist Milton Friedman proposed a socalled “negative income tax”, which supports the poor by giving them a tax credit if their income fell below a minimum level (cf. Amadeo 2018; Bimbaum 2016). Over history, this exceedingly simple idea of a basic income has a surprisingly diverse pedigree. In the past it has been inde pendently thought up under a variety of names such as “territorial divi dend” or “state bonus,” for example; also “demogrant,” “citizen’s wage,” “universal benefit” or “basic income.” These concepts could primarily help the people who will not be able to find work and protect them from falling under the poverty line in a future with AI-driven automation. Ad vocates argue that it leads to greater economic security among vulnera ble citizens. By that, it could be useful to keep negative side-effects such as depredations away from everyday life. In this way, it would prepare for a world with increasing divisions and social conflicts between elites and unemployed masses as described in chapter eight (cf. Maney 2017; Van Parijs Basic Income 2004; Dahlbom 2017; Makridakis 2017:19ff.; King 2016; Ito 2018). The general idea of a basic income has many different faces, so the devil will be in the details, as it is said because concepts already dif fer on who receives the income (cf. De Wispelaere et al 2004: If.). Fo cussing on details of a basic income and what type of guaranteed income suits each country best are beyond the scope of this chapter. The following part of the chapter will look at the most discussed type of a basic income and its general advantages and disadvantages for society. Based on most parts of the definitions in the literature, it supports all cit izens with modest, yet unconditional, income paid by a political commu nity. “Basic income is a periodic cash payment unconditionally deliv ered to all on an individual basis, without means test or work re quirement/1 (Birnbaum 2016). 68 Notably, this definition of the Basic Income Earth Network is the most common in the literature. It includes five common characteristics based. Firstly, it is periodic, and it is paid at regular intervals, not as a one-off grant. Secondly, it is a cash payment, which allows those who receive it to decide what they spend it on (so it is not, therefore, paid rather in vouchers dedicated to a specific use). Thirdly, it is paid on an individual basis, not, for instance, to households. Fourthly, it is universal and paid to all, without a specific test or requirements. Fifthly, it has an uncondi tional character, so it has to be paid without a requirement to work or to demonstrate willingness-to-work (cf. Bien 2018; Bimbaum 2016). The next part of the chapter will discuss the advantages and dis advantages of a basic income. Advocates suggest a basic income could stand to alleviate poverty on a global scale, especially regarding tech and automation. Wages have remained largely stagnant for a long time so that despite technological leaps forward, many employees have not felt as many tangible benefits as might be expected. But services or even products do not just need to be assembled. They need to be bought. For this, a guaranteed income could be a solution for solving upcoming chal lenges. It would enable workers to wait for a better or more suitable job or negotiate better wages. With a basic income, individuals could also improve their marketability by going back to school and taking some time off in case of illness. Apart from the high cost of such social sup port, the simplicity of the program means it would also cost governments less, also by cutting down on bureaucracy. In terms of disadvantages, if everyone in the society suddenly received a basic income, it could lead to inflation and many people would immedi ately spend the money, which drives up demand. In consequence, retail ers would have to order more goods, and manufacturers would try to produce more. But if manufacturers were not able to increase the supply, they would raise prices. In consequence higher prices would make the basics unaffordable for lower-income people, so in the long run, a guar anteed income would not meet its main goal to increase living standards, abolish poverty, or reduce social inequality. Furthermore, there might be different challenges for how to finance it, because the whole payments would be extremely expensive for the governments. Another aspect may be the risk that it could remove the incentive to work hard. Recipients might prefer a life with a free income rather than applying for an availa ble job. The last aspect is that especially poor countries could get left behind because they could not afford a basic income for their societies. Therefore it could be seen as a utopian ideal of developed countries only. 69

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Abstract

The ongoing and seemingly unstoppable digital transformation brings forth new options, opportunities but also challenges to individuals, organizations, companies and societies alike. Governments are alarmed, realizing the potential consequences on the workforce, while also being apparently helpless against uncontrollable and powerful digital players such as Google or Facebook. As Henry Wittke shows, recent breakthroughs in the field of machine learning increase the potential of Artificial Intelligence to disrupt the world’s largest industries. Wittke attempts to provide a basic framework of what constitutes AI as well as to assess its impact on the Information Economy. What happens in case of rising mass unemployment or social inequality? What will be the effect on labor as a value system for today’s societies? Could the entire notion of capitalism be questioned in the wake of AI? The book aims to draw conclusions and give recommendations to policymakers.