ALG Blog 2: How GenAI Works
Published on:
How does generative artificial intelligence (AI) work? Where does it work well, and where does it falter? How we can mitigate the harms of generative AI through technical and structural changes?
New Article
How Generative AI Works and How It Fails
The purpose of this case study is to educate readers about the use of AI and its potential negative impact on our environment. It discusses the key limitations of generative AI, particularly its issues with factual reliability and its tendency to produce plausible but incorrect information. The study also explains the technical foundations of generative AI systems, including diffusion models and transformers.
The case study analyzes how large language models evolve from simple text prediction to more complex capabilities through training and fine-tuning. It further examines some of the negative societal impacts of generative AI, such as labor exploitation and potential misuse. Additionally, it assesses possible technical and policy approaches to mitigate these harms.
Learning the Arabic language from a state-of-the-art chatbot while fact checking from a youtube video:
- False prnounciation
- Limited information
- lack of examples
- General and unspecific information
- use of outdated interpretaions
Having used AI as a learning tool, I realized how limited chatbots can be, especially when learning a new language. I do not plan to use AI as a learning tool knowing the risk of misleading and False information it may provide.
Due to the massive negative impact of AI usage, could it potenally become an illegal website to use? Having read and had a very broad perpective of the enviromental impact and the Deepfakes AI is capable of, it appears to me that the growth of AI is not sustainable.
This Assigment has helped broaden my understanding and strengthen my knowledge about the potentail harm of AI, not only towards the enviroment but also in our day to day activities.