Can Artificial Intelligence Get Sick?

Artificial intelligence is all the rage these days. In fact, most businesses are using it for a multitude of things. With everyone all-aboard the AI train, it’s easy to confuse the computational power and speed AI offers to be infallible. Unfortunately, AI can get things going sideways if you aren’t careful. When it does go wrong, the consequences can be more than just an inconvenience.

Here’s a look at some of the most critical ways AI can go wrong:

The Problem of AI Bias and Discrimination

This is perhaps the most well-known danger. AI systems learn from the data they are fed, and if that data reflects societal prejudices, the AI will not only learn those biases, but because of the amount they are used, end up amplifying them.

AI has been shown to unfairly deny loans to people based on their zip code, exhibit higher error rates in facial recognition for darker-skinned individuals, and create racially biased predictive policing or healthcare models. This can be used to significantly deepen social and economic inequality.

Do you remember the case of an Amazon recruiting algorithm that reportedly discriminated against women? Since the system was trained on historical data, which mostly came from male engineers, it learned to penalize resumes that included the suggestion of the female gender, ultimately screening out qualified applicants.

Public exposure of a biased system can lead to severe reputational harm and a loss of customer trust that is difficult to repair. This is largely because complex AI and deep learning models operate as black boxes and their decision-making process is so opaque that even the engineers who built them can’t fully explain how or why a particular conclusion was reached.

If an AI system recommends a medical treatment, plays a role in the wrongful conviction of a defendant, or denies a claim, and no one can explain the reasoning, trust in that system—and the institutions using it—collapses.

LLMs can confidently generate completely false information, sometimes called hallucinations. Remember that lawyer who recently faced a court sanction for submitting a brief that cited non-existent legal cases fabricated by an AI chatbot, and then doubled down with an AI-fueled apology? Imagine that error applied to medical advice or financial planning.

For businesses, it can be an accountability nightmare. In the event of an AI-driven failure (e.g., an autonomous vehicle accident or a system-wide financial error), determining liability becomes a tangled legal mess without transparency into the system’s decision-making.

Businesses relying on an unexplainable model for supply chain or demand prediction are operating on blind faith. If the decision is wrong, there’s no way to debug the logic and prevent it from happening again.

Automation through AI is often lauded for boosting efficiency, but it carries a very real risk of eliminating jobs, particularly in roles involving repetitive tasks. While AI may create new, highly-skilled jobs, those who lose their current roles may not have the skills or resources to transition. This can lead to increased socioeconomic inequality.

The power of AI is also a double-edged sword. As it becomes easier to use, it also becomes a powerful tool in the hands of bad actors and can dramatically accelerate the number of successful cyberattacks, creating more convincing phishing scams and finding vulnerabilities in a system much faster than a human.

Responsibility is Key Moving Forward 

The risks posed by AI are not reasons to halt innovation, but rather a powerful call for responsible development and deployment. For AI to be a net positive for society, businesses and developers must prioritize a strategy of testing AI models on diverse datasets to proactively identify and correct discriminatory outcomes. Also, businesses need to establish clear, thoughtful regulations that assign responsibility when AI systems cause harm and ensure ethical standards are met. AI is a reflection of the data and values we feed into it. It is up to us to ensure that reflection is one of fairness, safety, and accountability.

For more information about AI integration and more innovative technologies, give the IT experts at White Mountain IT Services a call today at (603) 889-0800.

Related Posts

Big Data Initiatives Can Give You a Better Idea on the Best Ways to Run Your Business

Big data is now a crucial resource for businesses of all sizes, including small enterprises. Today, businesses have unprecedented access to vast amounts of data, enabling them to make more informed decisions and operate more efficiently. This month’s newsletter explores how small businesses harness big data's power. Customer Insights and Personalization Understanding customer behavior is vital...

Tip of the Week: Three Steps to Policing Your IT Policies

Small businesses are presented with the challenging prospect of monitoring and policing various IT-related policies that you might have for your network infrastructure and workplace technology use. The difficulty of this notion does little to lessen its importance, however. You need to take action to protect your assets, data, and reputation from the countless threats out there, and ensuring that ...

3 IT Metrics to Pay Attention To

Any business can benefit from data and use it to improve its operations. This is especially the case where information technology is involved. By collecting the right metrics, you can better evaluate your business IT’s performance and identify areas for improvement. Let’s review what some of these metrics should be. What are Metrics, and Why Should You Track Them? There’s a difference between...

Proactive IT Management Requires a Thorough Monitoring Strategy

Technology doesn’t just support modern businesses, it drives them. Whether it's handling customer transactions, storing data, or running day-to-day operations, companies depend on their IT systems to work reliably. But what if you could spot problems before they actually cause trouble? That’s exactly what IT monitoring is designed to do. Let’s take a look at IT monitoring and why it's an import...