Erilaiset organisaatiot miettiv\u00e4t omaa suhtautumistaan teko\u00e4lyyn ja miten sit\u00e4 otetaan k\u00e4ytt\u00f6\u00f6n. \n P\u00e4\u00e4asiassa k\u00e4sittelen opetuksen ja koulutuksen\nalaa. Asian k\u00e4sittelyss\u00e4 on ainakin syyt\u00e4 \nhuomioida ja tiedostaa seuraavia seikkoja.<\/p>\n\n\n\n
Usein puhutaan teko\u00e4lyst\u00e4 ja tarkoitetaan\n\nesimerkiksi suuria kielimalleja ja niiden pohjalle tuotettuja palveluita. Teko\u00e4ly on ns. yl\u00e4k\u00e4site ja se jakautuu moneksi erilaiseksi teknologiaksi, tunnetuimpia ovat:<\/p>\n\n\n\n
Kielimallit ovat kehittyneet viimeisten vuosien aikana ja\n\novat useimmille tuttuja. Tunnettuja kielimalleja ovat mm. Claude, Open\n\nAI:n Chat GPT ja Co-pilot, Krock, Gemini, Mistral, Deep seek ja lukuisia muita.\n\nSuuria kielimalleja on arvosteltu, ett\u00e4 ne hallusinoivat eli\n\nniiden tuottamat ratkaisut eiv\u00e4t ole luotettavia tai sis\u00e4lt\u00f6 on sinnep\u00e4in eik\u00e4 riitt\u00e4v\u00e4n\n\nk\u00e4ytt\u00f6kelpoista. Teko\u00e4lyn tuottaman prosessin l\u00e4pin\u00e4kym\u00e4tt\u00f6myytt\u00e4 on pidetty\n\nmy\u00f6s ongelmana.\n\nArvioitaessa teko\u00e4ly\u00e4 on huomioitava, ett\u00e4 uusissa\n\ninnovaatioissa on aina alkuvaiheessa puutteita ja ne v\u00e4henev\u00e4t ajansaatossa.\n\nToiseksi harva j\u00e4rjestelm\u00e4 on erehtym\u00e4t\u00f6n. Eli odotukset ja arviot kannattaa\n\nsuhteuttaa saatavaan hy\u00f6tyyn ja pyrki\u00e4 minimoimaan haitat.<\/p>\n\n\n\n
Opetuksen ja koulutuksen alalla on monia erilaisia kohtia, joissa voidaan hy\u00f6dynt\u00e4\u00e4 teko\u00e4ly\u00e4. \n\nEr\u00e4s vaikeimpia osa-alueita on kuitenkin tekstien ja kirjoitelmien tarkastus ja arviointi. Arvioinnilla voi olla \nopiskeljan opintomenestykseen ja jatkosuunnitelmiin keskeinen vaikutus. Ehk\u00e4\nkriittisin tilanne on opiskelijoiden luokittelussa vastausten mukaan ja\n\nvalintatilanteissa jatko-opiskeluun (p\u00e4\u00e4sykokeet) tai esimerkiksi ty\u00f6nhakuun\n\nliittyviss\u00e4 tilanteissa.<\/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>","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\/fi\/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\/fi\/wp-json\/wp\/v2\/posts\/1663","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/comments?post=1663"}],"version-history":[{"count":1,"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/posts\/1663\/revisions"}],"predecessor-version":[{"id":1666,"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/posts\/1663\/revisions\/1666"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/media\/1279"}],"wp:attachment":[{"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/media?parent=1663"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aicheq.com\/fi\/wp-json\/wp\/v2\/categories?post=1663"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aicheq.com\/fi\/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
\n