June 21, 2023
June 21, 2023
It seems like the ultimate time and money saver, and while it can be, it’s important to get the whole picture before going all in.
In an increasingly digital and automated world, you’re facing more pressure than ever to reduce costs and improve efficiency with the digital tools at your fingertips.
AI is very good at specific activities such as pattern recognition, bulk output, context-sensitive predictions, summarization, and translation. Combining these strengths enables AI to generate novel output that seems to hold limitless potential.
Still, it’s also important to acknowledge its limitations when considering how it can be applied and the impact it will have on your business.
Implemented appropriately and with a rigorous governance program, generative AI has immense potential to improve quality, streamline workflows, and help businesses run more effectively. Such low-hanging fruit includes:
While you might want to rush to sign up and access the benefits of generative AI right away, it’s important to know the risks and caveats associated with them. Regardless of the industry you’re in, consider these risks before jumping in.
Hallucinating chatbots can occur when an AI model has become convinced of incorrect facts and responds to questions with completely made-up answers. Such hallucinations are more likely to occur when prompts are overly vague or (intentionally or not) leading.
Generative AI programs use “temperature” parameters to determine the level of confidence in their predictions. Lower temperatures mean more creative responses while higher temperatures equate with greater confidence in the results. But higher temperatures don’t necessarily mean the results are more precise.
Chatbots absorb information from across the internet, and from myriad sources, some of which are reliable and trustworthy, and others that are not. It’s the sourcing of information, and input from humans, that can cause these programs to present incorrect, misleading, and biased information, or hallucinate.
False information can have significant real-world consequences and while these hallucinations can be addressed, privacy and security concerns must be considered when fine-tuning a model against sensitive or confidential data.
From a risk perspective, knowing how to spot when content was authored, either partly or entirely by AI, will dictate how much you can trust the results.
Look for sentences that lack complexity or contain words that are frequently repeated. When editing content, keep an eye out for scientific facts or citations that don’t match up with manual calculations or sources, seemingly correct code that looks out of date or place, and inaccurate or stale data.
Here are a few online tools that can be used to determine if copy has been AI-generated:
If you’re considering implementing the use of ChatGPT or other chatbot programs into your business, there are a few best practices to take when building a plan.
For more information and to learn how best to incorporate generative AI technologies into your business, contact Jason Lee.