Don’t believe it all, AI can help you fill in your application form:
With the release of college entrance examination results, volunteer application has become a hot topic recently. In the context of the full outbreak of big models, using AI to apply for admission has become the choice of many candidates and parents.
As long as you input information such as the college entrance examination region, test scores, regional ranking, and interests, you can generate a college entrance examination application form with recommended universities, majors, and admission probabilities. However, is it really reliable to use AI to help fill in applications?
An AI software answers the question "How to fill in the college entrance examination application form? What are the things to pay attention to?"
It should be noted that whether seeking help from a volunteer application consultant or seeking help from AI, it is essentially due to information anxiety. The difficulty of filling out college entrance examination applications is that ordinary candidates cannot exhaust all the information about colleges, majors and employment prospects. Professionals who specialize in this "knowledge" or AI application software that uses large language models for data analysis can largely eliminate this information gap. Compared with their own "blank sheet of paper", professional analysis with more information advantages is naturally very attractive.
In 2024, the number of applicants for the national college entrance examination is 13.42 million, an increase of 510,000 over last year, breaking the 13 million mark for the first time. However, the number of undergraduate enrollment places is expected to be only about 4.5 million, and the undergraduate admission rate is about 33%. At the same time, the cautious expectations for the future employment situation also make candidates dare not be careless in their choice of majors. Even under the psychological factor of "30% test and 70% application" as some people say, filling in the college entrance examination application is more important than the test results and must be taken seriously.
Objectively speaking, AI is more trustworthy than AI writing articles. This is because AI is essentially a kind of machine learning, which analyzes the input data and draws conclusions. Literary creation itself is a process of interpretation. In addition to arranging and combining bytes, it also requires imagination, emotions and values. At present, AI cannot match these capabilities.
An AI software answers the question "What are the admission scores for the 985 universities' journalism and communication, economics, and engineering experimental classes in Zhejiang in the past two years?"
Volunteer application is much simpler. As long as the data sample size in the model is large enough and the algorithm is accurate enough, it is not difficult to draw a common conclusion. This is essentially a mechanical process. In these aspects, machines have replaced manual labor in enough scenarios to be verified.
Therefore, candidates do not have to be conservative about AI application, and do not reject it as a scourge. They can refer to it if necessary. Of course, the premise is to choose a high-quality platform. There are a lot of large model tools on the market now, and it is not ruled out that some companies behind the software are just trying to make money. In this process, parents with the ability should also be more careful and help candidates keep a close eye on it.
However, the choice of university and volunteering is a personalized choice event, which needs to incorporate the candidate's strengths, interests, and future life plans. Those "cold" analyses and answers cannot cover these hidden factors. Therefore, candidates cannot entrust their future entirely to AI for decision-making. Refer to it but don't believe it completely, this is the correct attitude towards AI volunteering.
Of course, the hidden security and privacy risks of the AI volunteer application software itself cannot be ignored. The core logic that enables such tools to operate is data feeding, training and output, which is accompanied by a large amount of data collection, storage and use. The personal scores, provinces, volunteer preferences and other data entered by candidates are themselves "feeding" for the big model. Once stolen or illegally used by criminals, it may cause security risks. Candidates and parents should fully understand and predict risks.
In fact, in addition to the large model software for reference, the "Sunshine Volunteer" information service system, which is open to the public for free by the Ministry of Education, is also a platform for filling out applications. This system brings together authoritative and detailed professional databases, school databases, employment prospects and other data to provide multiple reference information for filling out applications. At the same time, it also helps candidates better understand their majors and career inclinations from four dimensions: interests, values, personality, and subject preferences. With official endorsement and comprehensive and humane evaluation dimensions, "Sunshine Volunteer" is a good helper for candidates to make scientific decisions.
In the final analysis, volunteering is a complex process of analysis, calculation and selection. Many times, no matter how you choose, it will not be perfect and there will be regrets. What candidates need to do is to make full use of the tools in front of them, collect enough information, and combine various factors to choose the major that suits them best. Try to have no regrets in your heart, that's enough.
