The Top 9 AI Chatbot Myths Debunked – MUO – MakeUseOf

Concerned about AI chatbots? Your concerns might be rooted in myths that aren’t true. Here, we debunk some of the top AI chatbot myths.
It usually takes time for myths to perpetuate about any subject. It says much about generative AI chatbots that so many myths have arisen so quickly.
Almost in the blink of an eye, AI chatbots have become the most disruptive technology of the century. It is also a technology enveloped in controversy, and some of this is of genuine concern. But myths are at the heart of at least some of the controversy.
Let’s untangle fact and fiction as we explore the top AI chatbot myths.
Chatbots like ChatGPT and Bing Chat may be able to generate human-like responses, but they are far from sentient. This ability is mimicry and not sentience. These tools use huge databases of text and images to create responses that mimic human responses.
It is complex, it is clever, and to some extent, you could argue the presence of intelligence—but not sentience. Any “intelligence” present in these tools is created by training them on massive amounts of data. In this sense, they are more akin to an incredibly powerful and flexible database than a sentient being.
While chatbots can be considered as something of a technological Swiss army knife, there are distinct limitations as to what they can achieve. This is apparent when working with complex or highly-specialized topics. But even simple tasks can throw them.
For instance, the emerging field of generative AI chatbots would be a subject that you’d think such tools would know all about, but try asking ChatGPT a question about one of its rivals and the limitations are immediately apparent:
We asked it: "What large language model does Google Bard use?"
Now, just to be clear, there are known limitations to ChatGPT and the age of the data it can reference. That question was deliberately set up to expose this. However, we asked Bard the same question when comparing Google Bard vs. ChatGPT, and it got it wrong too:
Chatbots may be clever, but they aren’t capable of any type of task and will sometimes fail on the simplest of questions.
The problem here is that people are mixing up productivity tools with Robocop. Chatbots may pose a job threat to some people, and they may disrupt certain industries. But it would be an exaggeration to claim that they are a threat to humanity as a whole.
Ultimately, AI is an emerging technology that will need to be closely monitored to make sure it remains an ethical and safe technology. But chatbots are not about to rule supreme.
In this case, we couldn’t put it better than ChatGPT.
But it would say that. Wouldn't it?
Nothing could be further from the truth. As the tools themselves go to great pains to explain, they may generate incorrect information. The problem is that generative AI chatbots rely on huge databases called large language models (LLMs).
LLMs contain text from a vast range of sources, everything from literature to social media posts are included in LLMs. This is the repository that the chatbots reference to supply their answers. Any factual errors present in these can manifest themselves in the answers they provide.
AI hallucinations are a common form of error that all too often shows just how fallible these tools are.
The answer to this question can hark back to the section on sentience. Chatbots can mimic human responses and can certainly competently answer factual questions (mostly) and help in many ways. However, they cannot understand emotions, human experiences, and many of the nuances of conversation.
Human interaction is a complex and multileveled process that involves such elements as empathy, critical thinking, emotional understanding, and intuition. None of these attributes are present in generative AI chatbots.
This one has at least a ring of truth about it. However, advancements have been made in the field of AI generative chatbots to expand their capabilities beyond just text.
Recent developments have introduced multimodal chatbots that can handle not only text but also incorporate other interactions such as images, videos, and even voice commands.
The speed at which these tools are developing is part of the reason behind this myth. The boundaries of what this technology can do are being pushed at a rapid pace and the initial iterations that were primarily text-based are already considered old-fashioned.
Unfortunately, this is not the case. The potential for biased responses is always there with AI chatbots. The root of the problem can be traced back to the LLMs. The vast amount of data that chatbots reference does, inevitably, contain bias. These biases can include gender, race, nationality, and broader societal biases.
While developers do make efforts to minimize bias in chatbot responses, the task is incredibly challenging and biased responses do slip through the net. Inevitably, these “unbiasing” techniques will improve and the number of biased responses will decline.
However, for the moment at least, the potential for biased responses is an unresolved issue.
Perhaps the most ludicrous myth is that behind every AI chatbot is a real human. This one is treading a delicate line between conspiracy theory and myth, we won’t dwell on this one other than to say that it's nonsense.
Chatbots need to be trained and programmed to perform their tasks in much the same way as any piece of software needs to be programmed to perform specific functions.
While AI chatbots utilize machine learning techniques to improve their performance, they do not possess the ability to program themselves autonomously.
The training process could be likened to the testing process of non-AI software. Training involves predefining their objectives, designing their architecture, and teaching them to generate responses based on the data in the relevant LLM. This entire progress still requires human intervention and programming expertise.
The rapid uptake in the use of these tools has perpetuated a whole host of myths. Some of them are absolute nonsense, and some of them have a grain or two of truth. What is clear is that there is a lot of misinformation surrounding AI chatbots that needs to be clarified.
By examining the facts and dispelling the fiction, we can gain a better understanding of the true capabilities and limitations of these powerful tools. AI Chatbots are not alone in quickly perpetuating myths, there are plenty of other myths circulating about AI in general.
Bob is a professional writer who has been writing extensively on technology topics since 2020, with a focus on AI, software, hardware, SaaS, and networks. Prior to becoming a writer, he owned and operated an IT firm in Scotland for over twenty years.
He currently resides in Spain and continues to provide valuable insights and analysis on the latest developments in the tech industry.