5 Failings of ChatGPT and Generative AI (and How to Fix Them)
Generative AI, particularly ChatGPT, has been a topic of debate lately. While some view it as a revolutionary breakthrough, others view it as a threat that could bring the end of the world closer. However, what is missing from the discussion is a realistic assessment of generative AI's shortcomings. Here are five failings of ChatGPT and generative AI that need attention:
1. Lack of Understanding
ChatGPT and other Large Language Models (LLMs) work by using a vast amount of human-generated text to generate an answer to a question, using a neural network model. It excels in pattern recognition and data-mining, but it doesn't really understand what it's talking about. This limits its ability to explain why things happen, come up with theories and laws to explain phenomena, and make creative leaps that have never been seen before.
2. The Hallucination Challenge
Since ChatGPT and other LLMs rely heavily on pattern recognition and plagiarism, they do well in standardised tests. However, this makes them wrong yet extremely convincing, creating a hallucination challenge for LLM models.
3. The Explosion of Fake Content
Generative AI can create websites, write content, and create images with ease, which leads to an increase in fake websites, emails, and fake people. This explosion of fake content can easily defraud the unsuspecting user.
4. Security Issues
Chained GPT-4 models such as Auto-GPT or BabyAGI, in particular, can take ChatGPT to another level by acting like autonomous agents. While this means that you can ask it to do something, and it will self-generate prompts until the task is done, it poses security issues. For instance, the AutoGPT agent will need access to the internet, permission to impersonate you on the site, access to your PC to get your personal information, and permission to make payments. Someone could modify the code in the autonomous agent model to give them backdoor access to Auto-GPT and take over your life.
5. Lack of Imagination
The development of ChatGPT use cases currently lacks imagination, which limits the potential revolutionary tools that could be created. ChatGPT is being used for existing tasks, but more efficiently. The truly revolutionary tools have yet to come out.
Generative AI has the potential to change the world for the better, but it also poses significant risks. Developers and users must be aware of these shortcomings and work to address them to avoid being the first casualty.
