Just like any other technology, generative AI is not perfect. It also has its downsides too but they are rarely discussed which make people believe that the technology is flawless. The hype around generative AI creates a fear of missing out, which is why we are seeing more and more businesses jump on the generative AI bandwagon without properly evaluating the risks associated with the technology.
If you are interested in learning about those risks, you are at the right place. In this article, you will learn about six dangers of generative AI that IT leaders should be aware of.
6 Dangers of Generative AI IT Leaders Should Be Aware Of
Here are six dangers of generative AI that IT leaders must pay attention to before implementing the technology.
Hallucinations and Accuracy Issues
Generative AI models are notoriously famous for making stuff up and do so confidently enough that you end up believing the output is factual. In reality, that is not the case. If you end up making decisions based on that output, your business will suffer. That is why it is important to keep these issues in mind when using generative AI for making business decisions. Then there are factual errors. These models can be straight up wrong and if you believe what they are saying, you could end up in hot waters. That is why it is imperative to vet the output carefully before accepting it.
Due to hallucinations and accuracy issues, tech giants are little cautious when it comes to launching generative AI products. Even if they do, they always tell you about these issues and encourage businesses to use these tools as an assistant instead of a replacement.
The best example of this is Microsoft Co-pilot and Google Bard. Google took longer to release their chatbot to iron out those flaws while Microsoft used the word Co-Pilot instead of auto pilot to tell businesses how they should use these tools, which is in conjunction with humans not without them.
Excessive Reliance and Overuse
The flood of generative AI tools have made the technology more accessible to the masses. This democratization and ease of use have forced both individuals and businesses to rely solely on it and use it extensively for their day to day tasks. There is nothing wrong with that but the problem starts when they start overlooking its flaws. They start believing that it is perfect and depend on it for everything from simple to more sophisticated tasks.
Security Implications and Ethical Concerns
Data security frameworks, privacy, copyrights and ethical implications of generative AI are some of the biggest roadblocks in its wider adoption. The risk of your sensitive data getting leaked by these large language models is real while the copyright concerns are also something that creatives have been raising their voices about for quite some time now.
Then there are employees who are secretly using these tools to get their work done without letting IT departments and business managers know about it. This raises ethical questions as well as leaving you more exposed to cybersecurity attacks and data breaches. Since most of these tools are hosted on the cloud and not on the cheap dedicated server, IT departments don’t have the visibility into these tools, they can easily be targeted by hackers.
A small bug or loophole in that tool can give cyberattackers a foot in the door, which is what they really need to wreak havoc on your business. The worst part, your security team will not even know about the incident or may know about it when the damage has been done.
Considering It As a Solution To Every Problem
Generative AI is not the silver bullet that most businesses believe it to be. Technology is in its early stages of development and as the technology matures, we might see new generative AI use cases and applications emerge. It can perform admirably in some areas while struggling in others just like cheap dedicated server hosting. That is exactly what experts think. According to Saurabh Daga, who is the associate project manager at GlobalData, “Generative AI is typically not suited for contexts where empathy, moral judgment, and deep understanding of human nuances are crucial.”
Raising The Bar
Democratizing every technology has its upsides and downsides. The same holds true for generative AI. With a generative AI powered chatbot accessible to every business and individual, it has raised the bar for quality of output. Whether you are using it to generate content or create websites or applications, the flood of AI generated content, apps and websites already available in the market make it difficult for businesses to make their offerings stand out.
You have to think out of the box and come up with creative ideas or give it your unique spin to differentiate your products and services from what’s available in the market. This is not easy when you are up against millions of other blogs, websites and apps which are already competing for users’ attention. This is where your creativity, ability to innovate and expertise comes into play.
Reputation Damage
If you are heavily relying on generative AI and it messes up, you are the one that is going to bear the brunt. This happened with Micorosoft recently when their bing chat responses contained ads that pointed users to malware. Not only that, it told users to eat from a food bank in Ottawa as well as interesting a dubious poll in between a sensitive news article.
The poll was automatically generated and asked participants to speculate about the death of a woman. Microsoft came under fire for it as Guardian claimed that it tarnished their reputation. The worst part is that Microsoft Bing Chat has been found guilty of inserting such polls in sensitive news articles automatically on multiple occasions.
Which is the biggest danger of generative AI in your opinion? Share it with us in the comments section below.
