The impact of using artificial intelligence techniques with incorrect inputs On financial management work by application to financial institutions and colleges in the Gulf DOI: 10.5281/zenodo.10676662

Abstract

This study aims to highlight the risks associated with manipulating inputs in artificial intelligence applications in financial management and their role in producing erroneous results. The extensive use of artificial intelligence makes it nearly impossible to distinguish between "true" and "false," despite the significant positive aspects of artificial intelligence in this field, as in other areas. The study concludes with several results, including. The correlation between implementing artificial intelligence techniques and the significant enhancement and increased efficiency in financial management activities is noteworthy. Moreover, the data and information housed in databases powered by artificial intelligence, if flawed, have the potential to yield inaccurate results.
Introduction: The world has witnessed rapid economic and financial developments in recent years, driven by technological advancements and globalization. These factors have propelled the world at an accelerated pace towards the applications of artificial intelligence (AI). AI has emerged as a contemporary topic in the realms of finance and business, attracting the attention of numerous researcher’s eager to study and unravel its nature and its relationship with various variables. This has led to the emergence of various theories and opinions in this field, explaining its dimensions and structure, and highlighting its use in streamlining ideas and behaviors in professional life. In the era of widespread use of information networks, the ubiquitous presence of social media platforms, and the widespread adoption of electronic devices, the volume, quantity, and diversity of information have increased significantly. The information users have multiplied, presenting us with a massive amount of data and information that must be processed, stored, and presented to users for decision-making in the realms of finance and business. Accompanying this wealth of information are numerous risks and challenges that may impact the reliability and dependability of this information, as well as the trust of users and decision-makers. If the inputs stored in databases and information systems are unfair or incorrect, the same inputs will be utilized by artificial intelligence. Additionally, companies aspire to obtain financial information that matches the advancements in information technology associated with providing such information. Therefore, it became necessary to explore the latest smart systems and technologies that can restore credibility to this information, enabling it to be relied upon and used in problem-solving and financial decision-making in various financial domains such as finance and investment with integrity and credibility, avoiding many risks that may arise.
Jeffrey Heinton warns of misleading information associated with artificial intelligence, highlighting that the scientific enthusiasm and intensive use of artificial intelligence will make it almost impossible to distinguish "what is true from what is false." He even speaks of an "nonsense generator," referring to the ability of artificial intelligence to produce persuasive phrases that appear reasonable without being true." (Raqi، 2017) Therefore, it is essential to have a method or system for detecting erroneous biases in artificial intelligence to ensure the accuracy of results and the reliability of decisions.