What is the impact of Artificial intelligence on academic integrity?

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Malik Stalbert

Artificial intelligence (AI) has the potential to impact academic integrity in several ways, both positively and negatively.

Positive impacts:

Detection of plagiarism: AI-powered plagiarism detection tools can scan large volumes of academic content and identify instances of plagiarism more efficiently than manual checks. This can help maintain academic integrity by preventing plagiarism and ensuring that original work is properly credited.

Enhanced security: AI can also improve the security of academic records by providing more robust authentication and encryption measures. This can help prevent fraud and protect sensitive data, ensuring academic integrity is maintained.

Automated grading: AI can automate grading, reducing the risk of human error and ensuring that grading is consistent and fair. This can help maintain academic integrity by ensuring that students are assessed based on their work rather than factors such as personal bias or inconsistent grading practices.

Negative impacts:

Creation of fake content: AI can also be used to create fake academic content, such as fake research papers or articles, which can undermine academic integrity. This can be particularly problematic if such content is used to advance fraudulent or unethical agendas.

Gaming the system: AI can be used to manipulate metrics and rankings, creating an unfair advantage for certain individuals or institutions. This can undermine academic integrity by skewing the perception of academic achievements and eroding trust in the system.

Data privacy concerns: AI relies on large amounts of data, and there are concerns around data privacy and security. Unauthorized access to academic records or data breaches can lead to academic misconduct and undermine academic integrity.

Overall, AI has the potential to both enhance and challenge academic integrity. It is important to monitor these impacts closely and ensure that AI is used in ways that promote academic integrity, rather than undermine it. This requires a combination of technological solutions, policy frameworks, and ethical guidelines to ensure that AI is deployed in a responsible and ethical manner.

Olusegun Lijofi

The relevance of AI in academic integrity is limited to intellectual properties profiling or plagiarism detection.