Maybe your use of artificial intelligence is limited to having ChatGPT rewrite the occasional proposal or business plan. Or perhaps you’ve instituted chatbots to answer common customer inquiries, or you’ve deployed AI solutions to streamline accounting or bookkeeping.
Many businesses are just beginning to discover the potential of AI, while others are jumping in with both feet. And some are learning that while AI can be an invaluable tool, it also presents a variety of new security risks.
On the cybersecurity front, organizations and solutions providers alike try to stay one step ahead of potential hackers with AI-powered solutions like threat detection or automated response systems. The problem, of course, is that the bad guys are using it also, creating a sort of never-ending arms race. All the tricks that hackers already use, from phishing to deepfakes to malware, gain new superpowers when propelled by AI.
The potential business fallout from AI, however, goes far beyond cyber breaches. There are risks that accompany many common uses of machine learning. Let’s look at a few:
Access in excess. Like that overly aggressive salesperson, AI doesn’t always know when to stop. For example, the chatbot mentioned above might need access to certain customer information in order to effectively answer questions. That access risks divulging information that should remain private, opening the door to a host of potential problems including identity theft and financial loss.
The solution is to apply the so-called principle of least privilege, which simply means that AI systems should be granted access to the bare minimum of data required to perform their tasks. Role-Based Access Control (RBAC) and Zero Trust security frameworks are often among the solutions here.
Employee misuse. Just as data access for AI must be limited, employee access to AI systems also needs some guardrails. A disgruntled or malicious employee, or an employee using systems for unauthorized purposes, can create huge exposures for a business.
Add AI use – and misuse – to the regular cyber-threat training your team members receive, and monitor internal use of AI at all times.
The human factor. Artificial intelligence carries with it a large range of very human, ethical concerns. An employee who fears that they’ll be “replaced by a computer,” or who is being surveilled by AI on the job, is more likely to be disgruntled at best, and a security risk at worst.
The use of AI in your organization should begin with an ethics framework that ensures that systems will be fair, transparent and accountable, with a goal of augmenting rather than replacing humans wherever possible. Many organizations establish an AI oversight team to craft this framework, conduct regular audits, and stay on top of evolving regulations.
AI makes mistakes. It’s probably more accurate to say that people make mistakes in deploying AI models, but the biggest names in tech have experienced AI disasters ranging from reputational damage (Amazon, Google, Microsoft) to multiple lawsuits (Tesla, IBM) to a direct loss of $500 million (Zillow). All resulted from training data that was flawed in some way.
Careful attention must be paid to the data used in deploying AI, especially in assessing for any kind of unintentional bias in the results. All systems should be thoroughly tested before deployment, and must be continually monitored to make sure they account for changing trends and data adjustments.
In the end, artificial intelligence illustrates the proverb that says, “With great power comes great responsibility.” The power of AI is undeniable, but the responsibilities – and the risks – are substantial as well. Proceed with care.
Questions about technology for your business? Contact Hill Tech Solutions.
