Is AI the next step in human evolution?

The aim of this article is to understand the implications of Artificial Intelligence (AI) in the modern world. From a historic point of view, we analysed its difference from the past and what would suppose for humankind its development and deployment. Subsequently, an overview of the necessary actions to be taken in an eventual transition period was also carried out. Lastly, is particularly relevant to distinguish the existing digital gap between Europe and AI leaders.

From Amazon Alexa to self-driving cars, present day AI can detect cancers better than human doctors, build better AI algorithms than engineers, and beat the world champions at chess. Many of the entertained public may not have realized how ingrained AI has already become in our day to day lives. It is present when we listen to the Spotify’s “Discover Weekly,” which is an internally developed cluster of personalized playlists of new music [1]. Netflix offers a system of personalisation of movie recommendations: users who watch A are likely to watch B [2]. Similarly, in the photo gallery of our smartphones is possible to find the pictures of our dog, and all the photos of him grouped into a virtual folder.

However, in the modern 21st century a simple, straightforward definition of Artificial Intelligence, or “AI”, is difficult to find. In simple words, refers to the simulation of human intelligence in machines, meaning a strategic technology that will lead humankind into the future. Nevertheless, although its applications highlight its ability to perform with a greater efficacy than humans, they are not generally intelligent, namely, they are exceedingly good at only one single function while having zero capability to do anything else. Note that while AI has to be trained in any function it needs to perform with massive volumes of training data, humans can learn with significantly fewer learning experiences. Machines, in the other hand, simply follow instructions, perform tasks, and make decisions, whilst not knowing what they are, what they are doing, why they are doing it, or what their purpose is.

The World Economic Forum has already announced the Fourth Industrial Revolution, which is building itself on the Third. Namely, it is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. This is to say that, the previous Industrial Revolutions were featured by merely mechanical and repetitive work, conversely, the current one is based on intellectual work, rapidity and availability.

The not-so-distant automation crisis will work in quite the same way it did in the past. Nonetheless, an important point in this discussion is the recognition of human capabilities, strictly speaking, the definition of what makes us human. It has already been underlined that machines perform far better than us in several tasks. However, particularly in the following years, it is specially relevant to invest in skills that define our emotional intelligence and qualities as human beings. Such characteristics involve creativity, empathy, human knowledge, and the like. To put it in simple words, a rational human being is able to go from zero to one, yet AI is capable to go from one to infinity at a faster and better pace than humans, though it cannot accomplish the first (simple) step. In a similar fashion, machines will never have values, dreams or love. They have chips, humans have hearts.

One of the main arguments of the Fourth Industrial Revolution concerns its difference from the previous ones. That is, not just low-skilled jobs are said to be taken over (such as truck driver or house cleaning), but also the so-called high-skilled ones (such as accountants and doctors). However, when addressing this topic is necessary to do so with perspective. As we have already explained above, only humans are able to make society going forward. Therefore, it is important that we think of AI as complementary to human abilities, namely, a means of technology that improves the working process. A society of highly motivated, educated and creative individuals should be pursued, in order to lead to a society of entrepreneurs and passionate people. In the past, there were jobs that are considered obsolete in the present day. Not so long ago, actual persons used to knock on your window in order to wake people up, the so-called knocker-uppers. However, these kinds of jobs are not even taken into account today and, therefore, they are not deemed as ‘lost due to automation’, whereas as evolution.

Although an eradication of jobs will occur in the short term, it will probably be a creative destruction (Schumpeter, 1942). Consequently, alternative measures of action have to be tackled by governments. Visionary entrepreneur Elon Musk defends the idea of universal basic income (UBI) in order to help societies to adopt to the new standards. The rationale is based on the assumption that automation will bring abundance, meaning everything will be cheaper, faster and better.

Other aspects of the process are education and training programs. Future generations have to be prepared for what is next, and even if the future of jobs is rather unclear, a shift in the contents on what is taught in schools nowadays has to be made. A recent study of the McKinsey Global Institute (MGI) estimated that, by 2025, online talent platforms could enable as many as 60 million people find work that more closely suits their skills or preferences. Besides, the cost of human resources management, including recruitment, is likely to decrease by as much as 7 percent [3].

During the transition process, jurisprudence plays a fundamental role due its regulatory nature. In 2018, the European Union issued a regulation called General Data Protection Regulation (GDPR) on data protection and privacy [4]. Companies will have to show that they have 4 a reason to keep the data and, most importantly, they ought to act responsibly. In case of infringement, potential penalties for companies can be up to 20 million dollars, or 4 percent of their turnover. Presently individuals have more control over their personal data and businesses benefit from a level playing field.

Finally, in terms of costs, in order to build a growing path driven by AI, around 40 percent of the potential investment is likely to be spent during the evolution process. Transition and implementation costs would probably amount for slightly less than half of those costs, yet handled by firms adopting and absorbing AI and redeploying and re-skilling their workforces. Hence, negative externalities that may arise from the new work with machines, including temporary unemployment, explain the other half of the costs.

Usually, when we talking about AI superpowers, the countries in question are the United States and China. However, the competition in the AI race is increasing, with new incumbents including Canada, Japan, and South Korea [5]. Europe should focus on areas where it has an advantage, such as in business-to-business (B2B) and advanced robotics. The European Commission (EC) announced that is investing around €2.6 billion in AI and robotics as part of its Horizon 2020 plan. Hence, European governments should start developing an Europe-wide web of AI-based innovation hubs. For the purpose of encouraging a digital transition, AI technologies have to be integrated in the core business activities of the European companies.

In order to understand Europe’s digital gap in terms of its national income, it is quite interesting to reflect on the following. Europe’s GDP is comparable to that of the United States and just ahead of China’s. However, the digital based portion of Europe’s ICT sector accounts for around 1.7 percent of GDP, rather lower than the share in China at 2.2 percent and only half the 3.3 percent share in the United States [6].

One of the biggest barriers that prevent companies from adopting this technology is the uncertainty on return on investment (ROI) and a lack of relevant AI inputs in the market. Therefore, AI suppliers need to develop industry-specific professionals in order to understand business opportunities and what potential industry-specific solutions there could be.

To conclude, at a time when digital technologies are becoming the focus of attention worldwide, policy makers are realising that warranting Europe’s place among AI superpowers should be a priority. Nonetheless, the rate of improvement of this technology is exponential and, therefore, should promptly be democratized and regulated. Namely, if mankind collectively decides that developing a digital transformation is the right choice, then we should do so rather carefully. Governments should make sure that AI does not represent a danger to the public, whereas maximizing society’s freedom. Most importantly, they should be able to grant citizen’s privacy regarding their data. Besides, it is their responsibility to preserve the humanity of people, because if they did not, how would individuals even have meaning? It is significantly relevant to encourage the population to read, study and discuss about this technology. The biggest concern about AI is that people continues to ignore its powerful tools and, most particularly, its rapidity and potential threat. It is our responsibility to embrace those digital and sociological changes. Specifically, the outcome depends heavily on human perception, for this reason, we must encourage research, studies, information and discussions about AI. Moreover, it is of great interest the inclusion of AI into the public debate and the education system. By seeing it as some kind of machine that will destroy our future, mankind will not be able to go forward. People should regard AI open-mindedly, while chasing a symbiosis between humans and machines, that is, between biological and artificial intelligence.

 

Notes:

[1] Bernard Marr, “The Amazing Ways Spotify Uses Big Data, AI And Machine Learning To Drive Business Success,” Forbes, October 1 2017.

[2] Nathan McAlone, “Why Netflix thinks its personalised recommendation engine is worth $1 billion per year,” Business Insider, June 2 14, 2016.

[3] A labor market that works: Connecting talent with opportunity in the digital age, McKinsey Global Institute, 3 June 2015.

[4]  European Commission: EU data protection rules. May 2018.

[5] See AI Singapore, National Research Foundation, Prime Minister’s Office, Singapore (https://www.nrf.gov.sg/programmes/artificial-intelligence-r-d-programme); Artificial Intelligence Research Center, Government of Japan (https:// www.airc.aist.go.jp/en/intro/Brochure_en.pdf); Mark Zastrow, “South Korea’s Nobel dream”, Nature, Volume 534, 2016; and PanCanadian Artificial Intelligence Strategy, CIFAR (https://www.cifar.ca/ai/ pan-canadian-artificial-intelligence-strategy).

[6] We use the share of sales and the online supply chain to compute the digital share of value added in the ICT sector. Data for online share are consistent between the Eurobarometer and the 2018 McKinsey survey used for digitisation in this paper. Statistics on the value-added share of ICT in Europe and other countries come from the European Commission Directorate-General for Research and Innovation

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