Critically Acclaimed After Effects 3
作品集 3
Artifacts for
SMART GOAL 3
智慧目標 3 的工件
I explore the future impact of AI on education, addressing teaching, learning, and ethical dimensions. A critical examination of AI applications includes assessing usability criteria such as functionality, flexibility, errors, learnability, accessibility, interactivity, and effectiveness.
我探討人工智慧對教育的未來影響，解決教學、學習和道德問題。對人工智慧應用的嚴格檢查將包括評估可用性標準，如功能、靈活性、錯誤、可學習性、可訪問性、交互性和有效性。
How do Artifacts 6-7 match SMART GOAL 3?
以下工件如何與智慧目標 3 匹配？
Artifact 6:
Personalized Education in the Future
未來的個人化教育
This course delves into diverse themes such as usability, artificial intelligence, algorithms, media convergence, global health, sustainability, digital labor, and attention. Exploring these topics equips students with a comprehensive understanding of the intricate interplay between technology, society, and the global landscape in the digital era.
本課程深入探討了各種主題，如可用性、人工智慧、演算法、媒體融合、全球健康、可持續性、數字勞動和注意力。探索這些主題使學生能夠全面瞭解數位時代技術、社會和全球格局之間錯綜複雜的相互作用。
This object visually conveyed my contemplative responses to the future implications of AI on education. I specifically focused on the pivotal concept of tailoring educational practices by incorporating artificial intelligence, emphasizing the significance of personalization. My reflections delved into the potential role of AI in crafting more individualized and efficient learning experiences for students. The artifact encapsulated my thoughtful considerations regarding the transformative impact of AI in shaping the educational landscape, particularly in terms of adapting to the unique needs and preferences of learners.
這個物體直觀地傳達了我對人工智慧對教育的未來影響的沉思回應。我特別關注了通過結合人工智慧來定製教育實踐的關鍵概念，強調了個人化的重要性。我的思考深入探討了人工智慧在為學生打造更個人化和更高效的學習體驗方面的潛在作用。這件作品概括了我對人工智慧在塑造教育格局方面的變革性影響的深思熟慮，特別是在適應學習者的獨特需求和偏好方面。
I reflect interesting ethical considerations of AI. Error detections, consciousness, and social norms are intertwined. Errors can be detected by human whose consciousness is shaped by social norms (Fridman, 2023). Proponents of controversial issues such as legalization of euthanasia validate their arguments with factual evidence that have been created and associated with collective ideas by the social norms; that is why how they believe that their arguments are valid to rebut opponents. What humans know shapes the concept of consciousness. How about areas that humans do not know or have not yet delved into? Fridman (2023) takes an analogy of AI with aliens whose mindsets may differentiate from humans’ consciousness. Indeed, a majority of human beings may not have full understandings of aliens, and such comprehension applies the same to AI. It could be multiple realms that humans have not been consciously investigated. In other words, referring to my question to the interviewees, AI could be possibly “consciously” generating information that alters users’ ways of thinking. The world of AI could be another “species” with their own mindset, and educators should unite and forge a future by educating the next generation to uphold values and manners that shape what human is.
我反映了人工智慧的有趣倫理考慮。錯誤檢測、意識和社會規範是交織在一起的。錯誤可以被意識受社會規範塑造的人發現（弗裡德曼，2023 年）。安樂死合法化等有爭議問題的支援者用社會規範創造並與集體思想相關的事實證據來驗證他們的論點;這就是為什麼他們相信他們的論點可以有效地反駁對手。人類所知道的塑造了意識的概念。人類不知道或尚未深入研究的領域呢？弗裡德曼（2023）將人工智慧與外星人進行了類比，外星人的思維方式可能與人類的意識不同。事實上，大多數人可能對外星人沒有充分的瞭解，這種理解同樣適用於人工智慧。這可能是人類沒有被有意識地調查的多個領域。換句話說，參考我向受訪者提出的問題，人工智慧可能“有意識地”生成改變用戶思維方式的資訊。人工智慧世界可能是另一個擁有自己思維方式的“物種”，教育工作者應該團結起來，通過教育下一代堅持塑造人類的價值觀和方式來創造未來。
Artifact 7:
Algorithmic bias
演算法偏差
在本課程中，我分析了媒體表現，研究了其當代政治、經濟、物質和文化意義。我探索教育、技術創新和社會變革之間的動態相互聯繫。此外，我還研究了課程如何塑造我對自我、社會和世界的看法，並探索了利用媒體在教學和學習中培養反壓迫框架的策略。
This artifact serves as a poignant reminder to me of the imperative role that cultural inclusivity plays in mitigating algorithmic bias. While advancements can be achieved in algorithmic refinement, the intrinsic challenge lies in the intricate nature of cultural contexts and the dynamic evolution of societal norms. Recognizing the perpetual need for improvement, I discern that sustained endeavors to augment diversity in both data collection and algorithmic development are pivotal. However, the complete eradication of bias emerges as an enduring pursuit.
Acknowledging these inherent limitations, I believe the implementation of transparent processes, routine audits, and continual adjustments becomes indispensable to minimize, rather than eliminate, algorithmic bias. This balanced approach underscores my perpetual quest for enhancement, cognizant of the intricate interplay of cultural inclusivity in algorithmic systems.
這個工件尖銳地提醒我，文化包容性在減輕演算法偏見方面發揮著至關重要的作用。雖然在演算法改進方面可以取得進步，但內在的挑戰在於文化背景的複雜性和社會規範的動態演變。認識到不斷需要改進，我發現持續努力增加數據收集和演算法開發的多樣性至關重要。然而，徹底消除偏見成為一項持久的追求。
認識到這些固有的局限性，我相信實施透明的流程、例行審計和持續調整對於最大限度地減少而不是消除演算法偏見是必不可少的。這種平衡的方法強調了我對增強的永恆追求，認識到演算法系統中文化包容性的錯綜複雜的相互作用。