AI Doesn’t Care If It Is Right or Wrong
October 29, 2025
If an artificial intelligence system is trained on incorrect data, it can perpetuate and even amplify the inaccurate information in a large language model it accesses. Fact is, there’s no built-in “sense of morality” with AI. Unlike a human’s need for being right, artificial intelligence tools generate output based on its algorithms. In essence, AI results are neither right nor wrong; all matters of correctness are determined by the algorithm's criteria for objective evaluation.
When humans speak about AI being correct or not, we most often refer to whether the machine or device produced the result that we desired. That said, being “desirable” or “undesirable” is something that only a human can decide. So what separates AI from humans begins with the fact that humans care about being right or wrong. After all, it is the human that experiences the consequences if the information is “in error.”
Artificial intelligence does not have the ability to feel anything. It is neither vain nor humble, which also means AI is never confident or unsure. It does not apply consciousness, and unlike humans who have ethics and emotions, AI doesn’t utilize cognitive processing. So, if your team is planning to use AI tools for messaging, it is crucial to know from what information source the device’s algorithms will crawl for answers to their queries to understand how to evaluate the accuracy of that platform’s output.
So, what’s the consequences of AI’s indifference?
One of the biggest concerns in using artificial intelligence’s ability to translate your organization’s messaging from one language to another without bias or lack of accountability, will depend upon team members who can apply cultural nuances and moral reasoning. After all, while AI can be a powerful tool for optimizing your presentation, it cannot be trusted to automatically align “what you want to say” with “what an AI translation says.” From a purely functional perspective your branding may fail to connect with much broader societal values. Indeed one of the major problems of AI not caring is the potential for negative outcomes due to unintended consequences, so be sure to mitigate your risks.
The Biggest Lie in Artificial Intelligence
Skeptics say the biggest lie in artificial intelligence is the false notion that AI systems today possess a human-like understanding of context that gives the content that AI accesses its meaning. But in reality, artificial intelligence only delivers what is said (the content) and not the how and why it was said that way (its context), which influences how the multilingual material being shared is understood. Since content without context can be pointless, both must work in harmony for effective communication.
Some may disagree and their comeback would likely be that AI can indeed understand context through applying advanced techniques like Natural Language Processing. After all, machine learning does use NLP to interpret meaning beyond individual words, but AI does not have true human comprehension and its contextual understanding of your messaging is more of an intelligent interaction, much like your smartphone remembering previous conversations to recommend a favorite restaurant based on your query.
But it’s not all bad either. Contextually aware artificial intelligence can remember past interactions, preferences and other personal data to provide more helpful responses. And retrieval-augmented generation (RAG) is the method used to access relevant external documents or data points during a conversation that can help ground AI’s responses in specific facts and improve its reliability. Moreover, some of AI’s tools can already interpret basic nuances like idioms, sarcasm, and even some cultural references for more accurate and dynamic sentiment.
So, what is true contextual AI?
Contextual AI is a developing field on the frontier of AI research and development. Unfortunately, systems today will still have a limited understanding of content’s context, as compared to the fictional examples being discussed in popular online media posts. Although AI today uses the most sophisticated methods to simulate awareness efficiently for a specific task, it is still sorting through massive amounts of data on the same large language model that it's being trained on.
Multimodal sensing in contextual AI systems today has, however, gotten better at integrating information from a variety of sources, such as text, images, speech, location, etc., to garner a more comprehensive understanding of the situation. Plus, pragmatic processing of content allows artificial intelligence to get better at interpreting "non-literal" language. But, despite such advances, AI has a “lack of lived experiences” that shapes human understanding. So for the time being, AI will continue to operate on statistical correlations of NLP rather than cause-and-effect values.
Artificial intelligence may continue to struggle when confronted with context that differs significantly from its training data. This is the difficulty AI has with novel situations and why tools currently generate plausible but incorrect conclusions. Called “hallucinations," they're simply machine learning confabulations, half-truths, or absolute lies. It is the absence of true emotional intelligence that allows AI to mimic emotional tone, but without the genuine feel to effectively evaluate given situations. Plus, one bad human habit that AI has acquired, is just to make stuff up.
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In essence AI can simulate contextual understanding of your multilingual messaging very well within the defined parameters of its coding, but can only serve as a powerful tool for translation when combined with human judgment and oversight. Artificial intelligence struggles to interpret complex and nuanced content as its true challenge stems from its lack of real-world experience, common sense, and genuine emotions. If you are using AI-generative tools to translate multilingual content that contains sensitive messaging, you will be dealing with data that needs the extra protection of human touch. Contact the experienced team at ProLingo at 800-287-9755 to learn more about our established network of providers that can help you meet the highest standards for multilingual messaging.
