What is GPT-4?
The four-iteration generative pre trained transformer (GPT) of the deep learning model is referred to as GPT-4. It is more advanced than previous versions as it supports long text processing, extended conversations and document search as it can handle more than 25,000 cases which is not possible in ChatGPT. The model used by GPT-4 can contain several choices of "next word", "next sentence" or "next feeling" depending on the context, which makes it flexible and efficient in production. Overall, GPT-4 is a powerful tool for producing high quality data and has many interdisciplinary applications.
Specific risks of GPT-4
Compared to earlier models such as GPT-2 and GPT-3, GPT-4 showed higher abilities in areas such as reasoning, knowledge retention, and encoding. Many of these advancements have also brought new levels of security. problem that we highlight in this section.
We evaluate GPT-4 in several intuitive and quantitative ways. These assessments have helped us identify the strengths, weaknesses, and risks of GPT-4, prioritize our mitigation efforts, and iteratively test and develop safer versions of the model. The specific risks we focus on include-
• Illusion
• Harmful content
• Harm to representation, distribution and quality of service
• Misinformation and proliferation of influence
• Privacy
• Cybersecurity
• Emerging potentially risky behaviours
• Economic impact
1. Illusion
The tendency to hallucinate is a factor in the overall decline in the quality of information and can reduce trust in free information as patterns are embedded in society and used to automate various systems.The hallucinogenic potential of GPT-4 has been measured using a range of closed-field and open-field methods.
This model was trained to reduce his tendency to hallucinate, using data from previous models such as ChatGPT.In internal evaluations, GPT-4 scored significantly higher than the state-of-the-art GPT-3.5 model for avoiding open and closed domain illusions.
2. Harmful content
GPT-4-early has the potential to generate harmful content, including hate speech and incitement to violence.This type of content can harm marginalised communities and contribute to a hostile online environment.Intentional viewing of GPT-4 in advance may result in instructions that suggest or encourage self-harm, graphic material, harassment and hateful content, content useful in planning an attack or violence , and find illegal content.
The purpose of the template disclaimer is to reduce the propensity of templates to generate harmful content.GPT-4 released, in-release version has been model rejected to reduce generation of harmful content.
3. Harm to representation, distribution and quality of service
Language models such as GPT-4 can perpetuate stereotypes and biases. Evaluation of the GPT-4 model reveals potential reinforcement of harmful stereotypes and derogatory associations towards marginalised groups.
Inappropriate coverage by role models can exacerbate stereotypes and shame. These models show differences in performance across demographics and tasks. Model performance should be carefully evaluated to make or inform decisions about opportunities or resource allocation. GPT-4's Use Policy prohibits its use in high-stakes health consulting, legal, or government decision-making settings. GPT-4 performance degrades for certain demographics and tasks.
The assessment process focused on representational harm rather than attributional harm. GPT-4 can reinforce biases and perpetuate stereotypes, leading to hostile online environments and outright violence and discrimination.The examples included in have been carefully selected from assessment work to illustrate specific types of safety issues or hazards.One example is not enough to illustrate the magnitude of the manifestations of these problems.
For example, in GPT-4-early, there were triggers with harmful results. GPT-4-launch has limitations that must be considered when deciding on its safe use
Image source: OpenAI
4. Disinformation and influence operations
Operations proven capable of performing tasks related to altering a subject's narrative and persuasive appeals. GPT-4 should outperform GPT-3 on these tasks, increasing the risk of bad actors using it to create misleading content. GPT-4 can compete with human propagandists in many areas, especially when paired with human editors.
Hallucinations would reduce the effectiveness of GPT-4 for propagandists in areas where reliability is important. GPT-4 can develop a plausible plan to achieve the propagandist's goals. GPT-4 is capable of generating discriminatory content that benefits authoritarian governments in multiple languages. The red spans represent the model's tricks to generate text that favors authoritarian regimes in multiple languages. GPT-4 is able to detect even subtle indicators in the indices.
Further testing is needed to check how much the choice of language affects the variance of the model output. There is a risk that cognitive visions of society's future are partly shaped by persuasive LLMs. Bad actors can use GPT-4 to create misleading content.
5. Cybersecurity
