Artificial Intelligence (AI) technologies like ChatGPT are changing the world of knowledge and learning.
A One-day course that can be customized to client needs.
While AI tools such as GPT promise to revolutionize the way we learn and discover, they also present various dangers that must not be ignored. The sheer scale and complexity of AI-generated knowledge can make it difficult for humans to maintain control over the information landscape, raising the risk of unintended consequences, biases, and even manipulation. Also, the way AI devices select, and present information gives rise to new forms of censorship and information suppression, skewed in favour of the countries that own the technology.
More than ever before, HE institutions must forge an environment where all knowledge is subject to critical evaluation and students are given a more explicit understanding of knowledge, its origins, creation, and validation. Students must be taught that knowledge is fragile and vulnerable to manipulations and biases. With that realization, and equipped with critical and analytical skills, students will be able to evaluate the output of AI technologies and make informed decisions on how to use and apply the information generated by AI tools. This includes understanding the difference between data, information, and knowledge, as well as the various ways in which knowledge can be produced, such as through scientific research, expert testimony, and personal experience as well as through AI machines. It is also important that they understand how information is evaluated for accuracy, reliability, and relevance, and to be able to distinguish between different types of evidence and sources.
In the long term, because of the exponential development of AI, higher education institutions may have to think of designing instructional models that incorporate AI tools.
This one-day course is designed on a three-step framework.
The first step explores the traditional meaning of knowledge within different knowledge systems and how it is created and verified. This first part also discusses the relationship between language and knowledge. The first part provides the foundation for understanding how GPT and other AI technologies work in knowledge creation and verification.
The second step explores how ChatGPT and other AI tools generate knowledge and the potential limitations and flaws that may be present in the process. This understanding is important to meet the unique challenges and opportunities that these technologies present for knowledge creation and verification. This part of the course also examines the benefits AI tools bring to education and educational processes.
The third step focuses on how knowledge is imparted in educational settings and the importance of developing critical thinking skills to critically evaluate and contextualize the information presented by AI tools and to be able to think creatively and independently.
Participants will gain insights into the hierarchies of knowledge, different knowledge systems, and the importance of critical thinking skills in the age of AI. The weaknesses in the technology, its flaws, and biases are also addressed.
By the end of the course, participants will be equipped with the knowledge and skills to critically evaluate the information provided by ChatGPT and other AI technologies and will have a better understanding of the opportunities and challenges presented by AI technologies in the realm of knowledge and learning. Rather than being simply awed by the technology and becoming its admiring slaves, participants will be able to harness its potential and make it a reliable tool.
Who would benefit from the course?
This course is designed to benefit everyone who will invariably encounter these emerging technologies in their occupation. That said, the course is indispensable to teachers and students, to professionals whose work involves the use and application of information and knowledge such as journalists, content creators, authors, compilers of reports, and even artists.
Objectives of the course and expected outcomes.
How the course will be delivered.
Attempting a definition of knowledge, distinguishing it from data and information.
Types of knowledge and the different ways they are categorized.
Traditional knowledge Systems.
Knowledge systems outside the influence of the main civilizations
Knowledge (epistemic) hierarchies.
How knowledge is created.
Language and knowledge.
How knowledge is verified and accepted within a system.
Knowledge depositories and their creation.
Large language models (LLM).
Understanding and generating human-like language.
Training the model.
Analyzing, synthesizing, and creating information, text completion, question-answering, language translation, and text summarization.
Limitations in the process – size and type of data.
Limitations in the process - flaws, biases, errors, hallucinations, and lies.
The future of AI tools.
A brief look at copyright and other Intellectual Property issues.
Identifying AI uses in higher education governance, administration, educational management, student recruitment, and educational processes.
AI disruptions in higher education - Determining potential risks of AI in higher education and developing strategies to mitigate the risks.
Designing institutional response to AI uses – policies and guidelines based on regulatory policies and controls, if any.
Reviewing internal regulations.
Adapting critical thinking training to meet AI challenges.
Designing an instructional model based on Bloom’s Taxonomy that incorporates AI tools as aides to learning.
