On May 31, OpenAI announced its efforts to improve ChatGPT’s mathematical problem-solving capabilities, with the goal of reducing artificial intelligence (AI) models.
OpenAI emphasizes reducing bias as a critical step to develop adaptive AI. In March, the introduction of the latest version of ChatGPT – ChatGPT-4 – threw another AI into the mainstream. However, generative AI chatbots have been struggling for accuracy, sometimes producing false information, often called “hallucinations”.
Publicize efforts to stop these AI demonstrations by posting on the OpenAI website. AI phenomena refer to instances where artificial intelligence systems generate inaccurate, misleading, or unsupported data from real-world data.
These biases can manifest in different ways, such as creating false information, creating non-existent events or people, or providing incorrect information about certain topics. OpenAI has conducted research to evaluate the effectiveness of two types of feedback: “results monitoring” and “process monitoring”.
Outcome monitoring involves feedback based on final results, while process monitoring provides information for each step in the conceptual process.
OpenAI evaluated these models using mathematical problems, generating multiple solutions and choosing the best solution based on each type of response. After careful analysis, the research team found that system management is highly effective because it encourages the model to follow human-approved processes.
On the other hand, the evaluation of the results showed that it is difficult to analyze in a consistent way. OpenAI recognizes that process analysis will go beyond mathematics, and further research is needed to understand its impact in different domains. He expressed the possibility that if the results are found to hold in a large context, system monitoring can provide a better combination of efficiency and structure over monitoring results. To make research easier, the company has made the public to review the complete series dataset, calling for research and studies in this area.
Although OpenAI did not provide a clear example that inspired its research of visualization, two recent events have shown the problem in real-life situations.
In a recent incident, attorney Steven Schwartz in the case Mata v. Avianca Airlines admits to relying on chatbot as a research tool. However, the information provided by ChatGPT turns out to be completely fabricated, making the issue clear.
OpenAI’s ChatGPT is not the only example of an AI system encountering pitfalls. During a demonstration of its chatbot technology in March, Microsoft’s Bing AI chatbot turned to financial reports and produced incorrect numbers for companies such as Gap and Lululemon.
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