Artificial intelligence is part of the process of imperialism, its offshoot, which is commonly called information imperialism. Humankind has known about artificial intelligence since the middle of the last century, but at present, the technology is reaching its peak of popularity due to the improvement of data storage algorithms and process optimization. Artificial intelligence has appeared in many areas of life, helping science, society, and corporations achieve what was impossible even a decade ago (Marr, 2019). While affecting other areas, AI has also touched the realm of culture; it completes tasks and gradually learns using information gathered over time. As a result, artificial intelligence and its accompanying innovations are necessary for the dynamics of all spheres of human activity within a civilization. However, along with many advantages, the ubiquity of AI has many risks. The main research question considers the challenges of introducing artificial intelligence and ways to overcome them.
Information Imperialism
The term information imperialism is not new; it has been actively used to characterize the policy of monopoly capital that dominates the mass media of large capitalist states. Thus, it is the ideological expansion of the West into the countries of non-Western civilization. In other words, information imperialism is one of the forms of neo-colonialism, along with economics, aimed at continuing the exploitation of underdeveloped peoples by developed peoples of Western civilization (Kwet, 2019). Cultural information products are known to most effectively advertise and inculcate Western values, standards, and lifestyles, which contributes to the growing dependence of the developing countries of the third world on the developed countries of the West. Information imperialism is seen as an integral part of cultural imperialism, a more general concept, with the help of which people began to designate the principles of production and global dissemination of mass culture around the world.
Artificial Intelligence as a Part of Information Imperialism
Artificial intelligence is part of information imperialism, as countries with a developed AI system will dominate and dictate the terms. The actively ongoing process of information globalization leads to fundamental changes in the usual spectrum of areas of struggle for leadership in the modern world. In the conditions of the information society, a new information neo-colonialism is emerging, the main task of which is to put the information and communication industry of underdeveloped states under the control of the world’s leading information powers. Gradually, it is the development of information technology that becomes one of the factors determining the influence of a state on the world stage.
The widespread introduction of AI equal to, and even superior to, human capabilities will be a revolutionary breakthrough in technology. The spread of this technology will provide countries that have begun the integration process with dominance in the global information sector for a long time. In addition, the existence of information imperialism is impossible without the information dependence of some countries on others. Advanced AI technology will be in high demand; world leaders will benefit from helping other countries implement this technology. The economic gap reaches its maximum value in the era of active globalization. The negative consequences of imperialism can be considered one of the risks of the ubiquitous spread of artificial intelligence.
The Need to Consider Difficulties
Artificial intelligence will inevitably become an integral part of the life of modern society in the nearest future, as mobile phones once were. The technology is revolutionary, investment-attractive and a proven successful business tool. A Series of innovations and breakthroughs have shown the power and effectiveness of AI in various fields, including medicine, commerce, finance, media, and the fight against crime (Leslie, 2019). However, the rapid development of AI has highlighted that while helping people solve their problems, machines will also create new problems that can affect society’s economic, legal, and ethical foundations.
Main Problems of Artificial Intelligence Implementation
Automation has been cutting manufacturing jobs for decades, and the pace of artificial intelligence has accelerated the process. Moreover, job cuts have spread to those areas of human life that should have remained the monopoly of human intelligence for quite a long time. However, the technological revolution and the widespread adoption of AI will also create many new jobs in research, machine learning, engineering, and information technology. These areas will still require human resources to develop and maintain the systems and software involved in the operation of AI algorithms. The main problem is that, for the most part, people who lose their jobs do not have the appropriate skills needed to fill these new vacancies. Thus, on the one hand, humanity has an expanding personnel vacuum in technological areas, and on the other hand, a growing flow of unemployed and dissatisfied people. In the long term, governments and corporations need to consider introducing universal basic income — unconditional monthly or annual payments to all citizens, as humans move closer to the day when robots do all the work.
Tendentiousness
Artificial intelligence can be just as, if not more, biased than a human. A popular branch of AI is machine learning, which is widely used and studied. Depending on the training and given algorithms, the technology makes life easier for many people, from setting up contextual advertising to face recognition technology. The main problem is that if the information fed into the algorithms is unbalanced, the result can be both implicit and explicit bias based on that information. Racist and sexist judgments associated with the predominance of white males in the results of AI work can be considered an example of such bias.
Responsibility
Before the widespread study of AI, it was fairly easy to figure out who was to blame for a software failure: the user, the developer, or the manufacturer. However, in the era of AI, deciding who is to blame for a hardware failure is difficult. Machine learning algorithms decide on their own how to respond to a particular event. With the expansion of the scope of use, AI algorithms begin to make more important decisions, which can be difficult to predict. For example, an AI-equipped car must decide how best to mitigate the collision and whom to endanger in an imminent accident. When the boundaries of responsibility between the user, developer, and data entry operator become unclear, each side will try to shift the blame to the other. Therefore, it is necessary to develop and introduce new rules to be able to prevent possible conflicts and resolve legal issues that will surround AI soon.
Confidentiality
The concept of confidentiality implies that the information entrusted to storage will be reliably protected. AI consumes huge amounts of data, and companies whose business is built on these technologies will increase user data collection to make their services more efficient. There is also a problem with the malicious use of artificial intelligence and machine learning by government and non-government organizations. A reasonably effective facial recognition app could be a potential tool for despotic regimes seeking to identify and suppress dissidents and protesters.
Artificial intelligence is used to search for and track people; anyone can easily track the movement of any person around the city with the help of a special program. Artificial intelligence algorithms are increasingly used to authenticate users: biometric authentication by voice, fingerprint, and face scan. All of these methods compromise a person’s anonymity in a public place. Artificial intelligence can use machine learning to predict the course of events based on available data. So, based on a person’s behavioral patterns, one can predict his reaction and emotional state. In addition, modern programs can determine a person’s gender, age, race, and political views by voice or text notes.
Possible Solutions
Artificial intelligence has great potential, but it is necessary to level some of its implementation risks. First of all, it is necessary to create an explicable artificial intelligence for successful integration. This model will provide clarity and transparency to the process according to which AI makes a decision. Explainable artificial intelligence can provide general information about how the program makes a decision, and reveals the strengths and weaknesses of the program and decision criteria. Four principles for assessing the explainability of AI are proposed: providing evidence and justification for each result, providing user-friendly explanations, the correctness of systemic explanations, and the operation of the system only in the conditions for which it was designed (Christian, 2020). The introduction of this system will reduce the risks of ethical problems and the uncontrollability of AI actions. To reduce the risk of data leaks, strict controls are required. The success of artificial intelligence implementation depends largely on responsible data management, strict management standards, and ensuring a plurality of opinions on AI models. Quality management and communication mechanism are extremely important to the successful integration.
For many people, the ubiquity of AI may be morally unacceptable. However, public opinion often has nothing to do with how well AI works. Artificial intelligence is likely to change many organizational roles in the coming years, and society needs to prepare for this. Work with communications and marketing teams is needed to ensure that employees and customers understand and see the value of using AI. In addition, it is important to anticipate and quickly adapt business processes to emerging regulatory and legal innovations.
Conclusion
Thus, artificial intelligence is part of information imperialism, widening countries’ economic and social gaps. The widespread use of AI comes with various benefits for people, but this integration comes with several serious risks. Risks include ethical dilemmas, data security breaches, lack of accountability, and unemployment. The main problem of AI implementation has more to do with ethical issues. A version of AI is needed to overcome these risks that can explain its own actions. It will also require competent management, control, and work with the community. Society is changing rapidly, and the introduction of AI in all areas of life seems inevitable. Government agencies need to prepare for this: think about changes in legislation, provide jobs and conduct educational work with the community members.
References
Christian, B. (2020). The alignment problem: How can machines learn human values? Atlantic Books.
Kwet, M. (2019). Digital colonialism: US empire and the new imperialism in the Global South. Race & Class, 60(4), 3-26.
Leslie, D. (2019). Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector. The Alan Turing Institute.
Marr, B. (2019). Artificial intelligence in practice: How 50 successful companies used AI and machine learning to solve problems. John Wiley & Sons.