The sophistication of AI to answer questions has changed the way we get information quickly. With high data speed and accuracy, AI technology is now capable of answering questions ranging from trivia to complex and in-depth analysis within seconds. AI platforms utilize Natural Language Processing (NLP) technology and massive databases to provide relevant and contextual responses.
However, with such convenience comes the question, does the reliance on AI technology in getting answers to questions erode one's ability to think critically and human creativity? While it offers efficiency in sifting through millions of data to generate answers to questions instantly, there is also a risk of bias.
In this article, we will discuss the use of AI as question answering. By understanding its uses and limitations, we can utilize AI wisely without losing the essence of creative learning.
The rapid advancement of AI technology has made obtaining information easier. Here is how the AI process answers questions:
AI uses Natural Language Processing (NLP) to understand the context, nuances, and intent behind human questions. Technologies like GPT-4 and BERT are able to analyze sentence structure, recognize idioms, and even distinguish between formal or informal tones. For example, when you ask, "What impact does inflation have on gold prices?", AI not only looks for keywords (inflation + gold), but also connects relevant economic concepts to provide a data-driven answer.
AI intelligence comes from training with billions of data-from scientific journals, to news, to discussion forums. Tools like Consensus scan 200+ million studies to provide evidence-based answers. Example: Medical questions like "Is vitamin D effective against depression?" will be answered by referring to the latest meta-analysis, complete with study quality indicators (sample size, methodology).
AI can also handle technical or specific questions. With machine learning, systems like IBM Watson can compare data from different domains (e.g., financial vs. geopolitical) to explain "Why does the price of gold rise during a crisis?" AI can also filter results based on certain criteria, such as clinical studies with randomized trials for health questions.
AI does not just provide raw data, but also summarizes and organizes information. Features like Copilot in Consensus can turn raw data into concise bullet points, tables, or ready-to-use reports. For example, the question "What are safe investments during a recession?" will be answered with a list of instruments (gold, treasury bonds) plus their risks in an easy-to-digest format.
AI is constantly improving its accuracy through user feedback and model updates. Systems like Google's MUM learn from previous interactions to adjust answers. If many users question the validity of a response, the AI will revise the source or add a disclaimer.
Compared to manual search, AI saves time by scanning thousands of sources in seconds. In addition, AI minimizes human errors such as interpretation bias or typos. Tools like Scite.ai can even check if a study has been replicated or refuted by other studies.
While AI has many advantages, it also has a number of limitations that make it unable to provide truly contextual and humanized answers. Here are some of the major drawbacks of AI in understanding and responding to questions in depth:
AI does not have human-like empathy or emotional understanding. While it can be trained to recognize emotional words (such as "sad" or "angry"), it doesn't really understand the feelings behind them. For example, when someone asks, "What should I do after a breakup?", AI might give logical advice based on data, but it cannot feel sadness or provide genuine emotional support. This makes the answer feel stilted and less human.
AI learns from a given dataset, and if the data contains bias, the AI's answers will also be biased. An example of this is Amazon's recruitment AI, which tends to discriminate against female candidates because it is trained on historical data that is male-dominated. In the context of questions, if the AI only relies on certain sources (e.g., news from one political viewpoint), its answers can be unobjective or even misleading.
AI excels at analyzing existing patterns, but cannot create new solutions like humans. For example, if asked, "How to reduce air pollution in Jakarta with an innovative approach?", AI might summarize common solutions (such as reducing vehicle emissions). However, AI cannot propose a completely new idea (e.g. generating energy from pollutant-absorbing moss) without prior data to support it.
AI also often fails to understand questions that are ambiguous or require cross-disciplinary understanding. Example: The question "Why did the price of Bitcoin rise during the war?" requires analysis of economics, geopolitics, and market psychology. AI may be able to provide separate answers for each aspect, but it is difficult to bring them together in a coherent and in-depth narrative like human analysts.
AI trained with formal data often struggles to understand slang, sarcasm, or cultural references. For example, the question "Why are you ghosting?" may not be recognized by AI as a romantic relationship issue because the word "ghosting" is informal. Also, AI can misinterpret jokes or satire because it doesn't have human-like common sense.
AI also requires regular data updates and retraining. Otherwise, the answers may become outdated or irrelevant. Example: AI trained on 2020 COVID-19 data will not be aware of the latest variant developments or cutting-edge health policies. Without updates, the AI could give dangerous or inaccurate advice.
So, after learning that question-answering AI, while it can be trained to give quick and efficient answers, it still lacks in understanding emotions, cultural context, and creativity. This shows that AI technology is yet to fully replace human intelligence.
AI is indeed a powerful tool, but users still need to be critical in assessing its responses. By understanding its advantages and disadvantages, we can use AI wisely and optimize its capabilities without neglecting the irreplaceable values of humanism.
