AI technology is incredibly attractive to businesses and customers alike, but along with it comes a serious issue: AI hallucination.
Popular culture of the twentieth century envisioned the future of technology in the form of flying cars, robot housekeepers, and machines that could instantly replicate any kind of food or drink.
That's not quite our reality (at least, not yet). But we do have readily accessible AI in our phones, computers, and other devices, and while generative AI is a fantastic tool, AI errors can negatively affect the trust a customer has in a business or brand.
What Is An AI Hallucination?
An AI hallucination is a result that sound plausible but is factually wrong and sometimes completely fabricated. AI systems are quickly becoming permanent fixtures in daily life, but with this comes the willingness to trust technology that still makes mistakes.
Most people know that fact-checking an internet search is vital and are generally aware of how to tell if a source is credible. But by labeling any technology as "intelligent", people will have confidence in the accuracy of the technology whether or not that confidence is deserved.
If a customer uses a generative AI model to search for information about your business, it is possible for the AI to make a realistic-sounding mistake. If this happens, it damages the trust between your business and the customer. People have high expectations of AI, and it's important to take steps to avoid any instances of AI hallucination.
How Do AI Errors Happen?
As we all know, anyone can say or publish anything on the internet, no matter how accurate or true. AI is not always capable of discerning fact from fiction. Much like how search engines pull information from databases and filter with pre-set specifications, AI technology also relies on accurate design models and common patterns to provide answers.
Several ways AI errors can occur include:
- Insufficient databases
- Maliciously misleading input
- Flawed training models
- Design limitations
Mitigating AI Risks
One of the best ways to mitigate the risks of AI errors is human-in-the-loop AI testing, or HITL AI testing. This means that humans are included somewhere in the process to ensure AI accuracy and oversight.
It might seem counterintuitive to include humans in an AI process - after all, isn't AI meant to be able to function independently, or at least as independently as possible? This is true to an extent, but AI can't always predict all human error, as human nature is inherently unpredictable.
So what can businesses do to minimize AI errors? HITL AI testing is our recommended method, but other measures can be taken as well, including:
- AI governance tools
- Using high-quality training data
- Carefully choosing AI models
- Prompt engineering
Maintaining Customer Trust
Maintaining trust between a business and customer is crucially important to the success of the business. We have all experienced negative incidents with businesses and brands that have caused us to choose alternatives or competitors.
Businesses must learn how to use AI technology to their advantage and work to prevent AI errors, as the consequences of an AI hallucination can be devastating.
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