Balancing Innovation And Data Security In The Workplace

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Balancing Innovation And Data Security In The Workplace

As CEO, Chris Schueler drives the overall vision and strategy for Cyderes – a global Cyber Defense and Response services provider.

In an era where artificial intelligence (AI) is rapidly transforming industries, many AI-powered cyber tools like ChatGPT promise automated workflows for employees and a way to ease the day’s workload.

It’s no secret that many are increasingly turning to AI to bolster their ability to get tasks done, recognizing AI’s astounding ability to analyze vast amounts of data, identify patterns and adapt to what users direct them to do. These tools are constantly learning and modifying, in what is being heralded as the pinnacle of human ingenuity and digital intelligence.

However, the risk of exposing sensitive information through unregulated AI usage remains clear to those who know what they’re looking for.

The Shadow AI Phenomenon And Its Risks

Employees across many industries are turning to publicly available AI tools like chatbots to assist with various work tasks throughout the day—often without the knowledge or approval of IT departments or management. The growth of these noncorporate AI actions in the workplace, often referred to as “shadow AI,” is becoming a significant security concern for organizations.

The consistent use of these tools and inputting of the information needed to use them leads to an alarming increase in the amount of an organization’s sensitive data—intellectual property, proprietary code and other confidential business information—being input into them. This trend poses substantial risks, including:

1. Privacy violations. Breaking data protection regulations for some confidential information could lead to serious reportable breaches for businesses.

2. Intellectual property exposure. Companies risk losing their competitive advantage if proprietary information is exposed through these AI interactions.

3. Lack of control. Organizations have limited control over how data is used, stored or protected once it’s input into public AI models. Most models will keep that data to “teach” the tool, making it unlikely to be removed.

4. Security vulnerabilities. Hackers can target public AI models, potentially compromising the security of data shared through these platforms.

5. Data poisoning. Open datasets that public AI models use are vulnerable to the malicious or unintentional introduction of false values, which can affect some AI outputs and give false or incorrect answers as a result.

6. Reidentification risks. AI’s pattern recognition capabilities make it possible to reidentify individuals from anonymized datasets who consistently use the tools, posing significant privacy concerns.

Addressing The Risks

Organizations should look to implement a multifaceted approach to combat the temptation employees might have to try to use these tools without permission.

Robust identity management can control access to sensitive data, preventing the unauthorized use of AI systems and protecting against data breaches. Data fabric architecture can provide a unified and integrated environment for managing data across various platforms and systems, including governance, consistent security policies and real-time processing capabilities for quicker threat detection and response.

Organizations should implement data tagging, conduct regular security audits and use tools like data cards for sensitive information. This can help manage and protect sensitive information in the context of AI usage.

Education programs for employees can raise awareness about the risks associated with using noncorporate AI accounts and public AI models in the workplace. Everyone in the organizations from the top down should understand that inputting sensitive information into these tools can lead to unintended data exposure and potential breaches.

Additionally, this education program should emphasize the importance of using only approved, corporate AI tools and provide clear guidelines on what types of data are safe to input. Real-time coaching and immediate feedback on risky behaviors, such as pasting source code into personal AI accounts, can be highly effective in reducing ongoing bad practices.

By implementing these strategies, organizations can create a more robust and adaptive cybersecurity posture that’s better equipped to handle the challenges AI-powered cyber tools and evolving data vulnerabilities pose.

Best Practices For Organizations

In addition to employee education and real-time coaching, organizations should also consider adopting additional measures for employees like enterprise mobility management (EMM) systems to further protect confidential data from possible human (or AI) error.

EMM solutions can enable IT departments to manage and secure mobile devices and applications. This ensures employees access corporate data only through approved channels, which can help mitigate the risks associated with shadow AI usage. This proactive approach not only protects sensitive information but also empowers employees to work securely across various devices and gives managers the freedom to know the information being accessed.

Another way to prevent employees’ unauthorized use of AI tools is to give access to approved and specific tools to ensure employees use only applications that meet established security standards. Regular security audits and vulnerability assessments should complement the approved programs, allowing organizations to identify potential weaknesses in their systems and processes.

Conclusion

The rapid adoption of these cyber tools presents a truly unique double-edged sword for the workplace. While these tools offer unprecedented capabilities in threat detection, response and automating select tasks for organizations, they also introduce new vulnerabilities that demand to be addressed.

The rise of shadow AI usage in the workplace has amplified these risks, potentially exposing sensitive data and intellectual property to unauthorized access. By tackling these issues head-on and offering solutions rather than ignoring the issue, employees can harness the power of these cyber tools in their daily work, and companies can take the steps needed to protect their information from public models—a win-win for everyone as we begin this exciting time of AI integration into businesses.


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