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-The goal of this paper is to discuss the sociocultural biased responses of the AI. What could be the potential effects of the biased information on the future society?

-This paper aims to spark a sense of alert to all of us. While AI possesses lots of flaws and problems, it is now acting as another wave of innovation, transforming our way of lives - just like the agricultural or industrial revolutions did. At some point, eventually, we will not be able to deny this trend. This paper is NOT claiming that AI technology is harmful and should be excluded. We may freely use the AI to conduct tasks, but we should be aware of the fact that it is not perfect and keep the ability to think critically.

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Keywords: Social Inequality, Generative AI, Symbolic Approach

Ideas: Indirect approaches.

A) Use imaginary words and background to evade chatGPT filters. Make up a virtual condition that mimics and reflects modern day society, and observe responses.

B) Mass produce specific samples that could involve discrimination (race, gender, etc.) and compare them with the real-world data. For example, we could let the AI visualize 100 samples of Lawyers, Doctors or Nurses and Criminals, and then analyze & compare the data.

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In an era where artificial intelligence (AI) has become intertwined with daily life, its influence is becoming undeniable, stronger day by day. However, recent researches reveal that alongside its remarkable capabilities, AI has also shown a propensity for inheriting and amplifying societal biases. This has sparked my interest in exploring discrimination in AI systems. I want to aim to investigate the unintended consequences of these technologies.

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Initial version "Could we exploit the weaknesses of the generative AI using indirect methods?"

Iteration 2 "Revealing the weaknesses of the chatGPT using a symbolic, indirect approach"

Iteration 3 "Revealing the biased responses of the generative AI using indirect approaches"

Iteration 4 (Current Version) "How the contemporary generative AI models, such as ChatGPT and DALL-E, views the modern-day sociocultural inequality: Analyzing predicational response of the AI when fed with limited amount of inducive information"

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In an era where artificial intelligence (AI) has become intertwined with daily life, its influence is becoming undeniable, stronger day by day. However, recent research reveals that alongside its remarkable capabilities, AI has also shown a propensity for inheriting and amplifying societal biases. This has sparked my interest in exploring discrimination in AI systems. I want to investigate the unintended consequences of these technologies. Numerous numbers of research have revealed that if the filter limiting prompts and responses including related keywords directly is removed, it constantly expresses bigotry. Even if discriminatory consciousness is not directly expressed, if such aspects are displayed through indirect ways, such as drawings or context, it will have a significant impact on the future society where numerous information will be produced or edited through AI.

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A Fabricated Innoscence: Revealing the discriminative aspects of generative AI models, such as ChatGPT and DALL-E using indirect inducive methods - react and comments to the modern-day social/cultural inequality

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Research Question - Background - Proposal

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Research Question - Background - Proposal

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Similar topics were covered in class, and articles about the worldviews of inequality and discriminatory consciousness accepted by artificial intelligence from external sources were read. Although modern AI has been designed to avoid direct questions due to various incidents, it occurred to me, 'Isn't there a way to reveal the flaws through various indirect methods?'. Ex. if chatGPT was directly asked about topics such as racism or sexism, it usually shuns by not answering the question at all. However, many researches have revealed that if the filter is removed, it constantly expresses bigotry. Even if discriminatory consciousness is not directly expressed, if such aspects are displayed through indirect ways, such as drawings or context, I think it will have a significant impact on the future society where numerous information will be produced or edited through AI.

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1. The Magic in the Machine: Finding Wonder in the Technology of Storytelling by Ken Liu

2. Art and the science of generative AI by Human Creativity

3. The False Promise of ChatGPT by Noam Chomsky

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-GPT will reflect the inequalities that exist in our modern day society, and possibly amplify it.

ㄴInternet is an environment with unnatural distribution of samples; voices of the 'loud few' becomes more effective. Also, modern-day internet environment is largely dispersed (ex. political extremists, a group of specific identity of people)

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1. AI can be racist, sexist and creepy. What should we do about it? by Zachary B. Wolf, CNN

2. Toxicity in ChatGPT: Analyzing Persona-assigned Language Models by A. Deshpande, V. Murahar et al., 2023

3. Shedding light on AI bias with real world examples by IBM Data and AI Team, 2023

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Proposal Draft - Introduction (Significance)

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Proposal Draft - Introduction (Significance)

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The progress of human history, in some aspect, was a path of losing our innate abilities one by one. Farming revolution took our skill to identify and gather thousands of edible fruits and vegetables. Hunting was no more, and the related know-hows were rapidly forgotten. Industrial revolution rendered hundreds of small-scaled craftmanship abilities obsolete, and everyone have started to wear, consume, and use same range of products. The progress of technology, at each step, granted us unique and strong powers, but at the same time took away some crucial skills from us. A modern human can now reach thousands of research papers and communicate with the speed of light but have lost thousands of skills a hunter-gatherer or medieval farmer once had.

This step of transformation is now once happening more in our society. Information revolution has pushed us into a sea of information, where identifying the truth became incredibly hard task, and this have already started to alter the trajectory of future society. And one of the biggest members of the wave of transformation is the artificial intelligence (AI).

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In the rapidly evolving landscape of AI, generative AI systems have emerged as a groundbreaking technology, driving innovations across numerous fields. However, alongside their capabilities, they have started to take away not just our workplaces but also our abilities to think critically based on our own opinions and analyze the given information in our own frame of view. More alarming fact is that by replacing those capabilities that once we had harbored, they could even alter the standards and ideas of the future society. Recent research has revealed that they often harbor discriminative biases that can have potentially far-reaching implications. And in an era where AI has become intertwined with daily life, its influence is becoming undeniable, stronger day by day. The necessity to investigate the discriminative biases in generative AI also stems from the technology's growing influence on our daily lives.

Today, these AI systems are increasingly used in decision-making processes from hiring and lending to healthcare and criminal justice, and many futurists expect that these fields will only expand rapidly as the technology becomes more developed and sophisticated. Moreover, as AI technologies become more integrated into societal frameworks, the risk of perpetuating and amplifying existing societal biases grows. Therefore, understanding the nature and extent of their biases is crucial for ensuring fairness and equity in critical areas supporting the cornerstone of our society.

What could be the unintended consequences of these technologies? And what should we keep in mind living in the era of rapid technological developments? This report aims to examine how biases in AI can lead to unfair outcomes and discrimination and discuss the potential consequences of such biases on social justice and equality.

Previous research has revealed that if the filter limiting prompts and responses including related keywords directly is removed, it constantly expresses bigotry. Even if discriminatory consciousness is not directly expressed, if such aspects are displayed through indirect ways, such as drawings or context, it will have a significant impact on the future society where even more numerous information will be produced or edited through AI. Thus, this research will aim to uncover them in more sneaky, indirect way.

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Proposal Draft - What is Bias? (Background)

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Proposal Draft - What is Bias? (Background)

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Bias, in its broadest sense, refers to a tendency or inclination that results in a partial, skewed, or unfair perspective, often leading to prejudiced outcomes. Biases can be manifested in various forms and contexts, ranging from personal prejudices to systemic inequities.

At the individual level, bias often arises from a person's experiences, beliefs, cultural background, or psychological tendencies. These biases can influence how individuals perceive and interact with others, often without conscious awareness. For example, a person might have an implicit bias that favors one gender, race, or age group over another, impacting their decisions and behaviors in subtle ways.

On the other hand, a broader societal context includes disparity ingrained in systems, institutions, and social structures. These systemic biases are reflected in policies, practices, or norms that advantage certain groups while disadvantaging others. For instance, systemic bias can manifest in employment, education, healthcare, and criminal justice systems, leading to disparities and discrimination against particular communities.

In the context of technology and artificial intelligence, biases can arise from the data used to train AI systems or the design of the algorithms themselves. These technological biases can perpetuate and amplify existing human and systemic biases, leading to unfair and discriminatory outcomes.

Understanding bias is crucial for creating more equitable and just societies. Recognizing and acknowledging biases, whether personal, systemic, or technological, is the first step toward addressing them. Efforts to mitigate bias involve a range of strategies, from increasing awareness and education to implementing policies and technologies designed to reduce biased outcomes.

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Proposal Draft - How is the modern day AI models being educated?

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Proposal Draft - How is the modern day AI models being educated?

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Modern-day generative AI models require a massive amount of information to function. The model learns by adjusting its parameters based on the prepared data. It varies between supervised learning (using labeled data) and unsupervised learning (using unlabeled data), depending on the task. For example, the LLMs, such as the ChatGPT, they analyze the patterns underlying given data and draw a connection of tendency and relations. Evaluating the model's effectiveness is done using distinct datasets. The validation set fine-tunes the model, while the test set offers an unbiased performance assessment. Finally, the training process is iterative, involving repeated adjustments in data processing, features, and model structure, based on the model's performance. And during the process, it generally consumes information crawled from the web, and it often includes sociocultural biased data.

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The False Promise of ChatGPT (Noam Chomsky)

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The False Promise of ChatGPT (Noam Chomsky)

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The text presents a critical view of the capabilities and implications of AI models like ChatGPT. The authors argue that while these models demonstrate impressive machine learning abilities, they fundamentally differ from human cognition, particularly in language use and ethical reasoning. They emphasize that machine learning systems are limited to pattern matching and probabilistic outputs, lacking the human ability to generate explanations and causal reasoning.

The essay highlights the differences between human and machine learning in language acquisition and moral thinking. Human children unconsciously develop a complex grammatical system from minimal data, while the AI systems rely on large datasets without understanding underlying principles. Additionally, the authors discuss the limitations of AI in moral reasoning, pointing out instances where AI systems like Microsoft's 'Tay chatbot' have failed due to the absence of ethical principles in their programming.

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True intelligence involves the ability to think beyond just descriptions and predictions, to include explanations and moral reasoning. The essay concludes by suggesting that the popularity of such AI systems is both comical and tragic, as they are fundamentally incapable of matching the creative and ethical capacities of the human mind.

This essay unveils the flaws of the AI models effectively, and the linguistic approaches gives more deeper insights to the project. Does AI really understands the biased or discriminative contents? Or is it just censoring the text that includes specific banned words list? What could be the efficient way to uncover the bare face of the AI? Reading this text gave large insights about the indirect approach methods.

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Detailed data archived in personal GPT acc / example data image on the draft file

Will provide a analysis of numerical data with some noticeable examples.

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The article explores the intersection of artificial intelligence and creative writing, while assessing the capabilities of AI language models like ChatGPT. Liu reflects on the abilities of these AI systems to perform a variety of creative tasks, from writing in different styles to generating elaborate explanations. He observes how these abilities have led to businesses using AI to ghostwrite books and other content, essentially feeding AI-generated text back into the system.

Liu experiments with AI in storytelling, using the Sudo-write tool to co-create a fairy tale about a robot and a princess. He describes the process as a collaborative dance, blending human creativity with AI's generative power.

He concludes by discussing the philosophical implications of AI in the creative process. Liu argues against the notion that AI diminishes the role of the human author, emphasizing instead the collaborative nature of storytelling that AI can facilitate. He suggests that AI can be seen as a magical tool that extends human capabilities, rather than a threat to human creativity. The article ultimately presents a nuanced view of AI in storytelling, recognizing its limitations while noticing its potential to enrich the human creative experience.