AGI: Artificial General Intelligence for Education
- URL: http://arxiv.org/abs/2304.12479v5
- Date: Wed, 13 Mar 2024 16:47:04 GMT
- Title: AGI: Artificial General Intelligence for Education
- Authors: Ehsan Latif, Gengchen Mai, Matthew Nyaaba, Xuansheng Wu, Ninghao Liu,
Guoyu Lu, Sheng Li, Tianming Liu, and Xiaoming Zhai
- Abstract summary: This position paper reviews artificial general intelligence (AGI)'s key concepts, capabilities, scope, and potential within future education.
It highlights that AGI can significantly improve intelligent tutoring systems, educational assessment, and evaluation procedures.
The paper emphasizes that AGI's capabilities extend to understanding human emotions and social interactions.
- Score: 41.45039606933712
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Artificial general intelligence (AGI) has gained global recognition as a
future technology due to the emergence of breakthrough large language models
and chatbots such as GPT-4 and ChatGPT, respectively. Compared to conventional
AI models, typically designed for a limited range of tasks, demand significant
amounts of domain-specific data for training and may not always consider
intricate interpersonal dynamics in education. AGI, driven by the recent large
pre-trained models, represents a significant leap in the capability of machines
to perform tasks that require human-level intelligence, such as reasoning,
problem-solving, decision-making, and even understanding human emotions and
social interactions. This position paper reviews AGI's key concepts,
capabilities, scope, and potential within future education, including achieving
future educational goals, designing pedagogy and curriculum, and performing
assessments. It highlights that AGI can significantly improve intelligent
tutoring systems, educational assessment, and evaluation procedures. AGI
systems can adapt to individual student needs, offering tailored learning
experiences. They can also provide comprehensive feedback on student
performance and dynamically adjust teaching methods based on student progress.
The paper emphasizes that AGI's capabilities extend to understanding human
emotions and social interactions, which are critical in educational settings.
The paper discusses that ethical issues in education with AGI include data
bias, fairness, and privacy and emphasizes the need for codes of conduct to
ensure responsible AGI use in academic settings like homework, teaching, and
recruitment. We also conclude that the development of AGI necessitates
interdisciplinary collaborations between educators and AI engineers to advance
research and application efforts.
Related papers
- Human-Centric eXplainable AI in Education [0.0]
This paper explores Human-Centric eXplainable AI (HCXAI) in the educational landscape.
It emphasizes its role in enhancing learning outcomes, fostering trust among users, and ensuring transparency in AI-driven tools.
It outlines comprehensive frameworks for developing HCXAI systems that prioritize user understanding and engagement.
arXiv Detail & Related papers (2024-10-18T14:02:47Z) - Generative AI and Its Impact on Personalized Intelligent Tutoring Systems [0.0]
Generative AI enables personalized education through dynamic content generation, real-time feedback, and adaptive learning pathways.
Report explores key applications such as automated question generation, customized feedback mechanisms, and interactive dialogue systems.
Future directions highlight the potential advancements in multimodal AI integration, emotional intelligence in tutoring systems, and the ethical implications of AI-driven education.
arXiv Detail & Related papers (2024-10-14T16:01:01Z) - How Far Are We From AGI [15.705756259264932]
The evolution of artificial intelligence (AI) has profoundly impacted human society, driving significant advancements in multiple sectors.
Yet, the escalating demands on AI have highlighted the limitations of AI's current offerings, catalyzing a movement towards Artificial General Intelligence (AGI)
AGI, distinguished by its ability to execute diverse real-world tasks with efficiency and effectiveness comparable to human intelligence, reflects a paramount milestone in AI evolution.
This paper delves into the pivotal questions of our proximity to AGI and the strategies necessary for its realization through extensive surveys, discussions, and original perspectives.
arXiv Detail & Related papers (2024-05-16T17:59:02Z) - Levels of AGI for Operationalizing Progress on the Path to AGI [64.59151650272477]
We propose a framework for classifying the capabilities and behavior of Artificial General Intelligence (AGI) models and their precursors.
This framework introduces levels of AGI performance, generality, and autonomy, providing a common language to compare models, assess risks, and measure progress along the path to AGI.
arXiv Detail & Related papers (2023-11-04T17:44:58Z) - Transformation vs Tradition: Artificial General Intelligence (AGI) for
Arts and Humanities [40.80626345766025]
This paper provides a comprehensive analysis of the applications and implications of AGI for text, graphics, audio, and video pertaining to arts and humanities.
We outline substantial concerns pertaining to factuality, toxicity, biases, and public safety in AGI systems.
The paper argues for multi-stakeholder collaboration to ensure AGI promotes creativity, knowledge, and cultural values without undermining truth or human dignity.
arXiv Detail & Related papers (2023-10-30T15:19:15Z) - What Students Can Learn About Artificial Intelligence -- Recommendations
for K-12 Computing Education [0.0]
Technological advances in the context of digital transformation are the basis for rapid developments in the field of artificial intelligence (AI)
An increasing number of computer science curricula are being extended to include the topic of AI.
This paper presents a curriculum of learning objectives that addresses digital literacy and the societal perspective in particular.
arXiv Detail & Related papers (2023-05-10T20:39:43Z) - World Models and Predictive Coding for Cognitive and Developmental
Robotics: Frontiers and Challenges [51.92834011423463]
We focus on the two concepts of world models and predictive coding.
In neuroscience, predictive coding proposes that the brain continuously predicts its inputs and adapts to model its own dynamics and control behavior in its environment.
arXiv Detail & Related papers (2023-01-14T06:38:14Z) - Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society.
A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests.
This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
arXiv Detail & Related papers (2021-06-25T22:31:55Z) - Personalized Education in the AI Era: What to Expect Next? [76.37000521334585]
The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to meet her desired goal.
In recent years, the boost of artificial intelligence (AI) and machine learning (ML) has unfolded novel perspectives to enhance personalized education.
arXiv Detail & Related papers (2021-01-19T12:23:32Z) - Future Trends for Human-AI Collaboration: A Comprehensive Taxonomy of
AI/AGI Using Multiple Intelligences and Learning Styles [95.58955174499371]
We describe various aspects of multiple human intelligences and learning styles, which may impact on a variety of AI problem domains.
Future AI systems will be able not only to communicate with human users and each other, but also to efficiently exchange knowledge and wisdom.
arXiv Detail & Related papers (2020-08-07T21:00:13Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.