Introduction
Over the past couple of decades, there has been marked progress in exploring digital technologies and the opportunities they provide. The integration of Artificial Intelligence (AI) into a variety of contexts for automation has been one of the key trends in a number of industries in recent years (Hernandez-Boussard et al., 2013). However, many are struggling to answer one question: whether AI should be trusted with public concerns through the contexts of economics, politics, and sociocultural departments.
Good evidence has shown that AI gives society many advantages, but despite the described innovation, it may cause more harm than good due to the lack of control over the issues in question. Since humans create AI, the threat of biases is quite tangible; however, it increases exponentially in AI once it is deployed in a public context due to the lack of opportunity to introduce ethics into the AI framework. The possibilities of Artificial Intelligence are limitless, and it is necessary to consider both the advantages and the dangers of its use in addressing global issues.
Limitations of Integrating Artificial Intelligence
The problem of AI being biased in its assessment of certain information has been affecting the quality of data processing and the resulting functioning of the relevant systems and industries. For instance, studies by Akter et al. (21), DeCamp and Lindvall (2021), and Bouschery et al. (141) confirm that the problem of racial bias is quite tangible in AI-powered technologies. Similarly, the research by McLennan et al. (21) emphasizes that the effort to introduce AI to the notion of colorblindness leads to further enforcement of prejudice against racial and ethnic minorities. Therefore, additional efforts must be taken to examine the methods of minimizing racial biases in AI.
To reiterate, AI tools cannot instill ethical standards and principles; they are bound to integrate biases into their systems due to the imperfections of the people creating them. As a result, including AI-powered technologies for addressing public concerns and social issues does not seem to be a reasonable step to take. At the same time, the opportunities for automation that AI provides call for further examination of the problem and the search for an available solution.
AI-based automation may have other negative consequences. Although this process is unlikely to lead to mass unemployment in the near future, the displacement of human labor has many devastating consequences for society. Citizens with low attachment to labor may participate less in public and political life.
Nevertheless, more importantly, automation shifts the balance of power from labor to capital. IT can have far-reaching consequences for democratic institutions (Wynsberghe 214). In other words, to the extent that democratic politics depend on the distribution of power between labor and capital, automation can harm democracy because it levels the importance of labor in production.
Benefits of Applying AI to Global Goals
Despite the dangers, artificial intelligence is now the core of economic and societal transformation. Harnessing the potential of artificial intelligence will increase productivity and improve well-being. Moreover, it can help solve global problems such as climate change, resource scarcity, and health crises. High technology is an additional limitation and a new opportunity that can strongly respond to societal challenges.
Artificial intelligence is believed to accelerate the fulfillment of 80% of all targets of the UN Sustainable Development Goals (Wynsberghe 214). The effectiveness of AI applications is gradually increasing due to the constant increase in memory size and the strengthening of the internal connections of the neural network. Thus, it can be assumed that AI is rational and even useful for addressing global issues.
Seventeen sustainable goals can be roughly divided into three categories. Considering that fact, artificial intelligence helps to fulfill 93% of the tasks in the environment category, 82% in the society category, and 70% in the economy category (Wynsberghe 214). Moreover, it is increasingly used in other areas, such as transportation, which is no less important in societal issues.
For example, today, AI is increasingly important in developing smart city mobile solutions (Wynsberghe 216). AI-based technologies are changing how cities are managed and lived. As metropolises become smarter, AI is helping to provide more efficient, cost-effective, and sustainable urban mobility solutions.
Equally important in the field of AI applications is the increase in economic efficiency. It is estimated that by 2030, AI could add up to 11.78 trillion euros to total global production (Wynsberghe 216). It would increase the annual growth rate of global GDP by more than one percentage point. Research shows that AI will be most profitable if it focuses on innovative growth, especially if proactive management measures accompany it.
In particular, retraining workers gives them the skills to master the new work environment. As AI begins to accelerate GDP growth, social welfare may increase. It is estimated that artificial intelligence and related technologies could improve welfare by 0.5% -1% per year between 2020 and 2030 (Wynsberghe 216). This assessment is similar to the social impact of previous technological revolutions in the Internet and communications technology.
AI will likely improve numerous aspects of well-being, from job security and living standards to educational practices and environmental sustainability. Its most significant positive contribution to human well-being may be related to health and longevity issues. AI-based drug discovery is many times faster than traditional research. Moreover, AI-based traffic control can reduce the negative impact of air pollution by 3-15% (Wynsberghe 217).
AI technology, which is currently field-tested, includes disease detection systems, smuggler tracking systems, and technologies that help predict and assist in disaster relief efforts. Thus, its role is enormous and difficult to overstate. At the same time, any AI error in executing global objectives could become an enormous problem. The advantages undoubtedly exist, but using AI at the local level is much safer.
Conclusion
Artificial Intelligence is one of the fastest-growing fields in science and technology, and its impact on modern society is becoming increasingly apparent. It encompasses many technologies that allow machines and programs to perform tasks that normally require human intelligence. Today, AI penetrates all areas of life and is becoming an integral part of modern society. Artificial intelligence is a technology that can change the world, and its use will only increase. Nevertheless, as its role has grown, there has been a significant change in the scale of the dangers and difficulties associated with its application at the global level.
Despite the advantages of artificial intelligence, there are numerous risks. The effectiveness of the machine learning algorithms that underpin AI-based solutions depends heavily on the quality of the data they are powered by. Potential risks must be considered, and AI must be developed ethically and legally to ensure the safety and well-being of all people. All of the above guide to a straightforward deduction: the existing problems with AI are those of unregulated AI and ignoring its large-scale consequences for society. It would be naïve to anticipate unregulated markets to make the proper choice between the public good and profits from data monopolization.
Works Cited
Akter, Shahriar, et al. “Addressing Algorithmic Bias in AI-driven Customer Management.” Journal of Global Information Management (JGIM), vol. 29, no. 6, 2021, pp. 1-27. Web.
Bouschery, Sebastian G., Vera Blazevic, and Frank T. Piller. “Augmenting Human Innovation Teams with Artificial Intelligence: Exploring Transformer‐Based Language Models.” Journal of Product Innovation Management, vol. 40, no. 2, 2023, pp. 139-153.
DeCamp, Matthew, and Charlotta Lindvall. “Latent Bias and the Implementation of Artificial Intelligence in Medicine.” Journal of the American Medical Informatics Association, vol. 27, no. 12, 2020, pp. 2020-2023. Web.
Hernandez-Boussard, Tina, et al. “MINIMAR (MINimum Information for Medical AI Reporting): Developing Reporting Standards for Artificial Intelligence in Health Care.” Journal of the American Medical Informatics Association, vol. 27, no. 12, 2020, 2011-2015. Web.
McLennan, Stuart, et al. “AI Ethics Is Not a Panacea.” The American Journal of Bioethics, vol. 20, no. 11, 2020, pp. 20-22. Web.
Wynsberghe, Aimee. “Sustainable AI: AI for Sustainability and the Sustainability of AI.” AI and Ethics, vol. 1, no. 3, 2021, pp. 213-218. Web.