4. Disinformation
While LLMs may convincingly pretend to be smart, they don’t actually “understand” what they produce. Instead, their currency is probabilistic relationships between words. They can’t distinguish fact from fiction—some results may seem very plausible, but turn out to be confidently stated untruths. An example of this is ChatGPT, which falsifies quotes and even entire articles, as one Twitter user recently discovered .
The results of LLM tools should always be taken with a grain of salt. These tools can be incredibly useful in solving a huge number of problems, but humans must be involved in checking the accuracy, usefulness, and overall reasonableness of their answers. Otherwise, we will be disappointed.
When communicating online, it’s becoming increasingly bahrain mobile database to determine whether you’re speaking to a human or a machine, and some actors may be tempted to take advantage of this. For example, earlier this year, a mental health tech company admitted that some of its users seeking online counseling had unknowingly been communicating not with a human volunteer, but with a GPT3-powered bot. This has raised ethical concerns about the use of LLM in psychiatry and any other field that relies on interpreting human emotions.
There is currently little regulatory oversight to ensure that companies cannot use AI in this way, with or without the end user’s explicit consent. Moreover, malicious actors could use convincing AI bots for espionage, fraud, and other illegal activities.
AI does not have emotions, but its reactions may hurt people's feelings or even lead to more tragic consequences. It is irresponsible to assume that an AI solution can adequately interpret human emotional needs and respond to them responsibly and safely.