Understanding Risks Of Generative AI: Legal, Ethical, And Security Implications

Generative AI – Which would you prefer: Increased productivity or security?

As a business, you do not have a choice between the two. Both are required for a company to thrive.

A recent study, by the National Bureau of Economic Research, suggests that “The use of generative AI for less-skilled workers increases productivity by 14%.”

Nonetheless, the Adversaries it brings are well-known. New and complicated cyber-attacks, advanced phishing tactics, and undetectable spam are all instances of increased security threats generated by AI.

Since banning AI usage for the sake of security is not a wise option, CISOs now have to find a way to skillfully manage the risks and threats associated with using AI.

Significant Risks Associated With Generative AI

The major risks associated with AI can be recognized as legal and compliance, ethics, and security.

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Legal And Compliance Risks

It arises due to the nascent legal and regulatory landscape around generative AI, which may result in companies being unaware of the essential standards.

Intellectual property rights, data privacy, and liability issues are part of the concerns too.

Ethical Risks

Ethical risks pertain to the potential misuse of generative AI in harmful ways. Issues such as the creation of manipulated content like deep fakes raise concerns about misrepresentation and harm to individuals.

Microsoft’s President, Brad Smith has mentioned that his biggest worry about AI is “Deepfake.”

Security Risks

The use of large language models like ChatGPT can inadvertently lead to sensitive data leakage.

Although no direct public disclosure may occur, the data could be used by AI creators to train future models, potentially indirectly disclosing sensitive information.

Another risk is Generative AI’s ability to ]scan source code for vulnerabilities, it allows developers to quickly identify and fix issues.

However, this capability also poses a risk, as malicious actors can exploit vulnerabilities before defenders have a chance to address them.

With the advancement of AI, phishing is another major risk that has now become easier to automate, leading to higher response rates.

Mitigating Risks Of Generative AI

To mitigate these risks while using AI, the following measures should be taken:

  • using self-hosted or cloud-based models of these technologies with matching privacy policies
  • enforcing limits on data input
  • keeping systems patched and up-to-date
  • deploying anti-phishing software
  • educating employees on identifying and reporting suspicious emails.

Implementing proper safeguards and countermeasures is essential to mitigate the associated risks and ensure the safe and secure use of generative AI.

This is not an exhaustive list as the threat landscape is huge and thus requires consistent efforts in keeping your organization secure.

For more news and updates on Cybersecurity, visit The Cybersecurity Club.

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