Fernando Alcoforado*
Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to perform very complex tasks – such as, for example, proving mathematical theorems or playing chess – with great proficiency. Still, despite continued progress in the speed and memory capacity of computer processing, there are still no programs that can combine human capacity in broader domains or in tasks that require a lot of knowledge. On the other hand, some programs have reached the performance levels of specialists in carrying out certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as, for example, medical diagnosis and speech recognition.
Artificial intelligence (AI) is already being widely used in production systems. In the management of productive systems, Business Intelligence and Big Data are used. Business Intelligence contemplates the use of data collection, organization, analysis, action and monitoring that requires robust software to make better decisions and to know if the investments made are bringing good results. Big Data is a computing model focused on processing and storing information in high volume and can be applied to the most diverse environments, public and private, that seek to ensure agility and efficiency in data processing. The Artificial Intelligence algorithms run in the Big Data environment and establish an effective communication between these two fields, which are, at the same time, different and complementary.
Artificial Intelligence can replace human beings in production activities and can also increase their productivity to the maximum. According to data presented by Accenture in one of its surveys, by 2035, Artificial Intelligence will contribute to an increase of up to 40% in the productivity of the industrial sector, reducing costs and increasing the production of manufactures around the globe. A neural network of an Artificial Intelligence system is capable of analyzing more than a billion data in a few seconds, being an incredible tool to support a decision maker within a company, thus guaranteeing the best option among the possible ones. As the data collected is constantly updated, the Artificial Intelligence systems always update their results as well, allowing managers to have access to recent information on variations that have occurred in the company’s operating market.
In addition to their use in production systems, the main applications of artificial intelligence in management, at the moment, are the following: 1) Chatbots that use language to talk to people in a natural and pre-programmed way, recognize names and phone numbers and reproduce human behavior; 2) Management applications that are useful to identify which employees are performing tasks more efficiently and, with this type of tool, to assist managers in decision making; 3) Personal assistant that is used to schedule meetings, schedules and daily activities, one of the best known being Siri present in Apple products; 4) Security mechanisms both in digital attacks and in everyday situations, such as events. In the digital part, the most common example is internet banking; 5) Predictions with machines equipped with artificial intelligence that can be used in marketing campaigns, for example, to predict different scenarios and possible results. From the captured data, the manager will have more information at his disposal to determine the paths that the company should follow according to the expected result of the strategy; 6) Sales and marketing to provide better quality customer service. Customization of customer service provides practicality and comfort. Machine learning is an application in which the system learns to act on its own without having to be programmed for the new function; 7) Teaching in which computer technology is used as a “teacher” that is available to students 24 hours a day.
In medicine, the main applications of artificial intelligence at the moment are the following: 1) AI-Assisted Robotic Surgery through which robots can analyze data from preoperative medical records to guide a surgeon’s instrument during surgery that is considered “minimally invasive” ”For patients; 2) Virtual Nursing Assistants in which virtual nurses will be available and can answer questions, monitor patients and provide quick answers; 3) Aid to the Judgment or Clinical Diagnosis in which algorithms examine medical records, habits and genetic information of patients; 4) Workflow and Administrative Tasks with the use of technologies that can help to order exams, prescribe medications and write notes in graphs; and, 5) Medical Image Analysis using an algorithm that can analyze 3D scans up to 1,000 times faster than is possible today.
In engineering, the main applications are as follows: 1) Routine tasks with the use of a robot capable of reproducing various human tasks on a construction site, such as handling construction materials and assembling structures systematically with millimeter precision with a rate of error close to zero; 2) Big Data, which is a technology that can be applied to analyze the situation of the work in the most diverse construction sites; 3) 3D printing to assemble precast and prefabricated structures; 4) Intelligent Buildings with Artificial Intelligence that, in addition to the physical structure design, makes the planning of an intelligent infrastructure, capable of facilitating users’ lives; 5) More efficient management with the use of Robot Process Automation (RPA), which is a robot created to manipulate digital systems, cross-check data and eliminate the errors that would happen if a person assumed this task; and, 6) Customer service to program customer service robots.
Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Arthur Samuel, an American pioneer in the field of computer games and artificial intelligence, coined the term “machine learning” in 1959, while working at IBM. Machine learning is closely related to computational statistics (and often overlapping), which also focuses on creating predictions with computers. It has strong links with mathematical optimization, which provides methods, theory and fields of application to the field. In data analysis, machine learning is a method used to design complex models and algorithms that lend themselves to prediction. In commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers and analysts to “produce reliable and repeatable decisions and results” and discover “hidden insights” by learning historical relationships and trends in the data.
In 1950, British computer scientist Alan Turing was already speculating about the emergence of thinking machines in his work “Computing Machinery and Intelligence”, and the term “artificial intelligence” (AI) was coined in 1956 by the scientist John McCarthy. In the 1990s, the artificial intelligence community set aside a logic-based approach, which involved creating rules to guide a computer how to act, for a statistical approach, using databases and asking the machine to analyze and solve them problems on their own. Experts believe that machine intelligence will match that of humans by 2050, thanks to a new era in their ability to learn. Computers are already beginning to assimilate information from collected data. This means that we are creating machines that can teach themselves and also how to communicate by simulating human speech, as with smartphones and their virtual assistant systems.
Thanks to advances in artificial intelligence, the business world is facing huge transformations. It is a new era in which the fundamental rules that regulated the activities of organizations are being rewritten. Artificial intelligence systems do not just mean automating many processes to make them more efficient. These Artificial intelligence systems are making the world go through a fundamental transition with machines developing beyond their historic role as a tool by becoming “self-employed workers”. As a result, AI systems are therefore changing the true nature of the work that is requiring management of operations with machines and workers to be processed quite differently from the past.
In recent years, we have seen surprising progress in areas such as independent learning, forecasting, autonomous navigation, computer vision and video gameplay. Computers can now trade shares on the order of milliseconds, automated cars are increasingly appearing on our streets and artificially intelligent assistants have invaded our homes. The coming years will present us with even more advances, with Artificial Super Intelligence through machines that can learn from their own experiences, adapt to new situations and understand abstractions and analogies. Human-level machine intelligence has a good chance of being developed until the middle of the 21st century, which can result in Artificial Super Intelligence. Artificial Super Intelligence will be the first technology to potentially surpass humans in all dimensions. Until now, human beings have had a monopoly on decision-making and therefore have control over everything. With Artificial Super Intelligence, this can end. A wide range of consequences can occur, including extremely good consequences and consequences as bad as the extinction of the human species.
Even if Artificial Super Intelligence produces benefits for humanity, there is a risk that it will be used for evil and not for the good of humanity. The immediate consequence of the progress of artificial intelligence is the rise of unemployment. This negative social effect is already happening and is inevitable because it results from economic forces that are out of control. Artificial intelligence is positive for the capitalist who will use it to face his competitors in a more competitive way, since it would provide, among other advantages, the increase of his productivity and the reduction of his costs. However, it would also be extremely negative for the capitalist system because it tends to reduce the income available to the mass of workers excluded from production, thus contributing to the fall in the demand for products and services and, consequently, the profits earned. Its impact on society would be devastating with mass unemployment resulting from its widespread use. The risk that Artificial Super Intelligence is used to the detriment of humanity is very great because it can be used for evil in an act of despair by the capital holders to repress social movements as a weapon to maintain at all costs the dying capitalist system which will end to an end in the middle of the 21st century.
There is also a risk that the Super Intelligence Artificial will be used by the great powers to develop armaments more powerful than the current ones to defend their interests and impose their will on the world scene. If the great powers embark on an arms race with the use of Artificial Super Intelligence against rival nations, an armed Artificial Super Intelligence could get out of control, either in peacetime or during a war. An Artificial Super Intelligence could intentionally end humanity by destroying our planet’s atmosphere or biosphere with self-replicating nanotechnology, or it could fire all of our nuclear weapons, unleash a robot apocalypse like in the Terminator, or unleash some powers of physics that we do not even know about.
Artificial Super Intelligence can also represent the extinction of the human race, according to scientist Stephen Hawking, who published an article addressing this issue on May 1, 2014 in The Independent. Hawking said that technologies are developing at such a dizzying pace that they will become uncontrollable to the point of endangering humanity. Hawking concludes: today, there would be time to stop; tomorrow it would be too late.
The Artificial Super Intelligence will, however, be able to make a decisive contribution towards scientific and technological advances, aiming to provide humanity with the necessary resources to face the threats coming from outer space and seek solutions for human beings to develop technologies capable of taking them to new habitats in the solar system and out of it in search of its survival with the increase in the distance from the Moon in relation to the Earth, with the collision of the Andromeda and Milky Way galaxies, the death of the Sun and the end of the Universe in which we live. With machines smarter than we are, with Artificial Super intelligence, humanity will be able to use them to solve scientific and technological problems that ensure the survival of the human species even with the end of the Universe in which we live by paving the way for parallel universes. If artificial brains ever surpass the intelligence of human brains, then this new superintelligence can become very powerful. Humanity’s fate would therefore become dependent on the actions of these superintelligent machines.
Until now, human beings have had a monopoly on decision-making and therefore have control over everything. With Artificial Super Intelligence, this can end. Artificial Superintelligence has the potential to profoundly transform human society in a positive way, but also in a negative way if it gets out of hand and turns against humanity. The short-term impact of Artificial Super Intelligence depends on who controls it, but the long-term impact depends on whether it can really be controlled. Bostrom states in his book Superinteligência (Super intelligence) that Artificial Super Intelligence poses a risk that threatens the premature extinction of intelligent life on Earth, or the permanent and drastic destruction of its potential for a desirable future development [BOSTROM, Nick. Superinteligência (Superintelligence). Rio: DarkSide Books, 2018].
Bostrom explained that Artificial Super Intelligence requires that better control mechanisms be developed. Bostrom says that we will need to have these control mechanisms before creating smart systems by attracting the leading experts in mathematics and computer science into this field. He suggests that is necessary a strong research collaboration between researchers of the Artificial Super Intelligence security and Artificial Super Intelligence development, and for all parties involved to incorporate the Common Good Principle into all long-term AI projects. This is a unique technology, he said, that must be developed for the common good of humanity.
* Fernando Alcoforado, 80, awarded the medal of Engineering Merit of the CONFEA / CREA System, member of the Bahia Academy of Education, engineer and doctor in Territorial Planning and Regional Development by the University of Barcelona, university professor and consultant in the areas of strategic planning, business planning, regional planning and planning of energy systems, is author of the books Globalização (Editora Nobel, São Paulo, 1997), De Collor a FHC- O Brasil e a Nova (Des)ordem Mundial (Editora Nobel, São Paulo, 1998), Um Projeto para o Brasil (Editora Nobel, São Paulo, 2000), Os condicionantes do desenvolvimento do Estado da Bahia (Tese de doutorado. Universidade de Barcelona,http://www.tesisenred.net/handle/10803/1944, 2003), Globalização e Desenvolvimento (Editora Nobel, São Paulo, 2006), Bahia- Desenvolvimento do Século XVI ao Século XX e Objetivos Estratégicos na Era Contemporânea (EGBA, Salvador, 2008), The Necessary Conditions of the Economic and Social Development- The Case of the State of Bahia (VDM Verlag Dr. Müller Aktiengesellschaft & Co. KG, Saarbrücken, Germany, 2010), Aquecimento Global e Catástrofe Planetária (Viena- Editora e Gráfica, Santa Cruz do Rio Pardo, São Paulo, 2010), Amazônia Sustentável- Para o progresso do Brasil e combate ao aquecimento global (Viena- Editora e Gráfica, Santa Cruz do Rio Pardo, São Paulo, 2011), Os Fatores Condicionantes do Desenvolvimento Econômico e Social (Editora CRV, Curitiba, 2012), Energia no Mundo e no Brasil- Energia e Mudança Climática Catastrófica no Século XXI (Editora CRV, Curitiba, 2015), As Grandes Revoluções Científicas, Econômicas e Sociais que Mudaram o Mundo (Editora CRV, Curitiba, 2016), A Invenção de um novo Brasil (Editora CRV, Curitiba, 2017), Esquerda x Direita e a sua convergência (Associação Baiana de Imprensa, Salvador, 2018, em co-autoria) and Como inventar o futuro para mudar o mundo (Editora CRV, Curitiba, 2019).
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