Ethical Implications of AI in Accounting

The evolution of artificial intelligence (AI) has significantly influenced all aspects of human life, such as business, education, law, accounting and many more. AI technology has enabled individuals and organizations to handle huge chunks of data within the shortest time, computerize repetitive and tedious tasks and hasten the decision-making approach.

These are among the benefits that accounting firms derive from the technology. Many accounting organizations are using AI in their daily operations. Even though AI presents multiple benefits in accounting and has been widely adopted, there are various ethical implications attached to its use, including the likelihood of bias, data privacy and security concerns, and transparency and accountability issues.

Bias and fairness concerns

Accounting firms that use AI will likely experience bias and fairness concerns. AI has been designed to learn and interpret information based on the targeted task. To achieve this, it uses dataset algorithms, often based on expert knowledge or the organizations' past reports and data to execute the desired functions. The information has human involvement, and there are possibilities that the data presented to the system might be subjective or biased. The consequences include distorted outputs, which might mislead the organization and result in undesired results. In response, firms should strive to ensure fairness in training datasets and the decision-making process to help eliminate bias.

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Data privacy and security uncertainties

Another ethical implication of AI use in accounting is uncertainties in data privacy and security. Accounting entails handling sensitive data that is often highly confidential. When using AI, accounting professionals must provide key datasets that might contain sensitive information. Most databases are prone to hacking and unauthorized access, or users may interfere with confidential financial information. For example, the Equifax data breach exposed the confidential information of close to 147 million clients. When security concerns arise, the organization or institution may experience adverse consequences, such as lawsuits, a distorted reputation and losing important information and clients. As a result, institutions or people who use AI should critically safeguard their privacy and security, using methods such as installing encryptions, access controls and strong data protection policies and regulations.

Transparency and accountability issues

Moreover, accounting firms may encounter transparency and accountability issues when using AI in their operations. Accounting requires accuracy, openness and clarity regarding how the system derives conclusions and decisions. However, there might be instances when institutions use black-box AI, making it challenging for the other end users to follow the decision-making process. As a result, the users may question the fairness and validity of the financial or auditing results generated by AI.

Besides this, there are cases where the algorithm datasets used in accounting are complex, such as when various data sources and variables are used. As a result, it would require the users to have specialized knowledge to analyze and interpret the output, which some stakeholders might not have. Therefore, AI use in accounting raises various ethical concerns regarding transparency and accountability.

In conclusion, despite AI presenting various benefits in accounting, there are ethical implications related to its use. The major ethical implications discussed here include bias, privacy concerns and transparency and accountability issues. There are times when the datasets may be biased and provide inaccurate outcomes. Institutions must also provide sensitive information to the AI databases for quality output, risking hijacking or unauthorized access. Accounting institutions should consider these ethical implications to derive maximum benefits from AI and limit the likelihood of negative outcomes.

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