What is ShadowAI?
Shadow AIrefers to artificial intelligence tools that employees or teams use without the knowledge or approval of an organization's information technology (IT) department. This term Shadow IT It is derived from the concept of and draws attention to the risks that uncontrolled, unmonitored technologies can create. This situation is becoming more important, especially with the increasing data security and privacy concerns today.
Risks of Shadow AI
Shadow AI One of the most important negative effects of its use is data security risks. Artificial intelligence platforms used without official approval can cause sensitive information to leak. For example, when employees upload personal or company data to these platforms, there is uncertainty about how this data will be used and who will access it. In addition, such platforms can create compliance issues and produce incorrect outputs. This can negatively affect companies' decision-making processes.
Artificial Intelligence and Data Security
Kaspersky Türkiye General Manager İlkem Özar, states that despite the speed and efficiency advantages provided by AI-based solutions, they pose serious risks in terms of data security and impartiality. It emphasizes that employees should be careful and avoid sharing sensitive information when using AI applications. At this point, it is of great importance to choose platforms with reliable and ethical values. The idea that the relevant data will remain only with the user can be misleading; because these systems are usually cloud-based and the uploaded information can be processed and returned.
Unbiasedness of AI Models
Artificial intelligence The impartiality of models is a controversial issue. Özar says, “When you ask the same question to different AI models, you can get completely different answers depending on the data they were trained on.” This raises big questions about how AI can be used as a source of information. For example, a China-based AI model and a Western-based model can approach the same subject from different perspectives. Therefore, when using AI systems, care should be taken to determine which data is being used as a reference.
Artificial Intelligence Trained with Wrong Data
Artificial intelligence, works based on the data sets it is fed. The quality of the data used in the training process is very important. Some artificial intelligence models are trained with data sets that are publicly available on the internet and accessible globally. However, this situation also brings some risks. There may be unverified or misleading information on the internet, especially in open data sources. This may cause the artificial intelligence to produce incorrect or biased results.
Precautions to be taken against Shadow AI Risk
Shadow AI The precautions that need to be taken against the risk show that classic security solutions alone are no longer sufficient. Özar states that traditional antivirus solutions may be insufficient. Because these systems can detect threats that have been encountered before. However, when new threats emerge, the antivirus may not be able to know them in advance. Therefore, advanced security solutions based on artificial intelligence should come into play.
Update of Cyber Security Policy
Companies cyber security policies They need to be updated continuously. It is important to use systems that can respond faster and more effectively to AI-based threats. In this context, companies and institutions that want to use AI technologies in their business processes risk assessment It is necessary to do so. It is necessary to consider which processes in the daily work routine can be automated with AI tools and how this can be achieved without creating additional risks. It should also be taken into account whether the data processed is confidential or subject to local laws.
Control and Traceability
Control and traceability, yapay zeka is critical to the effective use of their systems. Once relevant scenarios are identified, businesses can move away from the sporadic use of AI language model (LLM) services and towards a centralized approach via a corporate account via a cloud provider. During this process, the necessary security mechanisms and auditing (e.g., logging) should be implemented to monitor potential personal data in messages.
Based on understanding what data can be processed and the service provider’s policies, businesses should educate their employees on the acceptable use of AI tools and the access methods determined by the company, ensuring control and accountability.
