Enhancing Human-Machine Cooperation through the Integration of Empathetic AI into Corporate Cybersecurity and Forensic Operations
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Le résumé fourni par la source
In order to strengthen the cooperation between humans and machines, empathic artificial intelligence is increasingly emerging as a key player. This cooperation is particularly evident in corporate cybersecurity and digital forensics. Today, thanks to the inclusion of emotional awareness in artificial intelligence systems, many organizations can more easily monitor the cognitive load of their analysts during critical security situations. Empathic artificial intelligence in corporate cybersecurity is a new force for proactive threat detection, compliance and risk management. It helps analysts to respond to constant cyber threats more effec-tively, and in forensic investigations it offers great support in emotional and behavioral analysis. In this way, in cybercrime inves-tigations, through the observation of anomalies and their patterns, decisions are made with a higher degree of accuracy. How-ever, this technology still faces numerous challenges, such as accurately reading emotional cues, protecting sensitive data, and ensuring ethical management. In any case, well-defined frameworks that promote cooperation between artificial intelligence and humans are the necessity of the present, in order to remove these barriers. It is undeniable that empathic artificial intelligence has the potential to create security ecosystems that are more adequate, reliable and above all focused on human needs. Therefore, in the near future, it will revolutionize the field of corporate cybersecurity operations and digital forensics, but only if it is smartly implemented.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Enhancing Human-Machine Cooperation through the Integration of Empathetic AI into Corporate Cybersecurity and Forensic Operations
- Date Crossref
- 31/08/2026
- Éditeur
- FSFEI HE Don State Technical University
- Type
- journal-article
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