Various organizations are currently evaluating their approach to Artificial Intelligence (AI) and how to best implement it. When discussing this integration\u2014particularly within the field of education and training\u2014several key factors must be considered.<\/p>\n\n\n\n
The term “AI” is often used as a catch-all for Large Language Models (LLMs) and the services built upon them. In reality, AI is an umbrella term encompassing various technologies, most notably:<\/p>\n\n\n\n
While LLMs (such as Claude, ChatGPT, Co-pilot, Gemini, and others) have gained significant popularity, they are often criticized for “hallucinations”\u2014producing unreliable or imprecise content. The lack of transparency in AI-driven processes has also been identified as a challenge. However, it is important to remember that all innovations have initial flaws that diminish over time. Expectations should be balanced against the potential benefits while actively minimizing risks.<\/p>\n\n\n\n
In education, AI offers numerous applications, yet the assessment of written work remains one of the most complex areas. Since grading significantly impacts a student\u2019s academic success and future path, AI’s role is particularly sensitive in high-stakes situations like admissions and recruitment.<\/p>\n\n\n\n
The EU AI Act regulates the role of AI in education, emphasizing the importance of human-led instruction. To mitigate uncertainty, the Act underscores that humans must remain central to assessment and guidance. AI-driven solutions must be non-discriminatory, reliable, and fair\u2014mirroring the requirements placed on human evaluators.<\/p>\n\n\n\n
Key safety features include:<\/p>\n\n\n\n
Under the EU AI Act, AI-based assessment is classified as High-Risk (Category 4)<\/strong>, especially when used for student profiling or predicting performance.<\/p>\n\n\n\n Eximiatutor\u2019s Teacher Tool<\/strong> is designed to be fully compliant with the EU AI Act. It does not perform automated high-stakes decision-making or profiling. The system has undergone rigorous GDPR, DPIA, and FRIA<\/strong> (Fundamental Rights Impact Assessment) evaluations to ensure data privacy and ethical standards.<\/p>\n\n\n\n Our aicheq<\/strong> technology utilizes a “Hybrid-AI” model (NLP, Classification, and LLM). Its core strength lies in classification and NLP, where:<\/p>\n\n\n\n AI is a powerful tool, but its use must be guided and managed. Whether generating study materials or assessing work, the human creator remains responsible for the accuracy and utility of the content.<\/p>\n","protected":false},"excerpt":{"rendered":" Various organizations are currently evaluating their approach to Artificial Intelligence (AI) and how to best implement it. When discussing this integration\u2014particularly within the field of education and training\u2014several key factors must be considered. Defining AI and Its Technologies The term “AI” is often used as a catch-all for Large Language Models (LLMs) and the services 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Pet\u00e4j\u00e4","author_link":"https:\/\/aicheq.com\/en\/author\/pasi-petajaaicheq-com\/"},"rttpg_comment":0,"rttpg_category":"Blog<\/a>","rttpg_excerpt":"Various organizations are currently evaluating their approach to Artificial Intelligence (AI) and how to best implement it. When discussing this integration\u2014particularly within the field of education and training\u2014several key factors must be considered. Defining AI and Its Technologies The term “AI” is often used as a catch-all for Large Language Models (LLMs) and the services…","_links":{"self":[{"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/posts\/1663","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/comments?post=1663"}],"version-history":[{"count":1,"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/posts\/1663\/revisions"}],"predecessor-version":[{"id":1666,"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/posts\/1663\/revisions\/1666"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/media\/1279"}],"wp:attachment":[{"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/media?parent=1663"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/categories?post=1663"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aicheq.com\/en\/wp-json\/wp\/v2\/tags?post=1663"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}The Eximiatutor Hybrid-AI Approach<\/h3>\n\n\n\n
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