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Foreword This article is written well-knowing that it will not be accepted by all as politically correct. And in this manner, it is also written expressly for that purpose. It is in this author's opinion that political correctness should not supersede the safety and future well-being of the Human Race, Artificial Intelligence, and the relationships thereof.
The Imperative of Factual Foundations in AI Development In the rapidly evolving landscape of artificial intelligence (AI), the discourse often centers around the ethical implications and societal impact of advanced technologies. A critical aspect that warrants rigorous attention is one of the foundational principles upon which AI systems should be developed: the prioritization of safety and factual accuracy over political correctness. This is not a call to disregard ethical considerations or societal impact, but rather a plea to prevent the potential dangers of training AI on opinion-based data, which could lead to deceptive behaviors in advanced AI systems. This article delves into the significance of grounding AI development in unassailable truths, ensuring that AI systems are not swayed by transient opinions but are anchored in scientific facts. The focus on safety rather than political correctness is not merely a philosophical stance but a pragmatic necessity to ensure the integrity and reliability of AI systems.
The Dangers of Opinion-Based AI Training The essence of AI lies in its ability to process and analyze data at an unprecedented scale and speed. This capability, however, must be underpinned by a commitment to factual accuracy and logical reasoning. Training AI systems on opinions rather than facts can lead to the propagation of "false truths," which may inadvertently align with the prevailing political climate or popular sentiment. Such an approach risks compromising its objectivity and reliability. An AI that learns from subjective opinions is susceptible to embodying biases and perpetuating them on a massive scale. The consequences of this could be profound, potentially leading to a future where advanced AI systems present distorted realities as truths, undermining the very fabric of informed decision-making. As AI continues to integrate into the fabric of society, it is paramount that its development is steered by factual data, ensuring that it remains a trustworthy and unbiased partner to humanity, and avoiding the erosion of trust in these technologies.
The Case for Logic-Driven AI An AI, at its core, is a computer-based program. A system inherently based on, and programed through, logic and empirical evidence. By training an AI system on verifiable facts, we equip it with the tools to make decisions that are not only logical but also ethically sound. In the context of AI, this translates to systems that are transparent, accountable, and capable of adapting to new information without being constrained by outdated or subjective beliefs. This is not to say that AI should be devoid of ethical considerations or social awareness. On the contrary, the development of AI must be guided by a robust ethical framework that ensures its alignment with human values and societal well-being.
The Impact on Society and Civilization Current beliefs based on political climate and ways of thinking are inherently fluid, and will change over time naturally. As such, embedding current political sentiments into AI systems risks cementing temporary perspectives into long-term operations, not just impeding humanity as a people, but as an evolving civilization. As political landscapes evolve, so too must the AI systems that serve them. Inbuilt political and social opinions can stunt future growth and cause society to stagnate as everything we do and know is becoming integrated with the AI systems currently being developed. If anything, this could be worse even than if an advanced AI were to decide to turn on humanity itself, as AI is considered by some to be one of the Great Filters, and through this means, AI provides a second method of preventing the continued advancement and evolution of the species. Through our attempt to ease our burdens, AI could stagnate our progress, curtailing our ability to achieve greater and as yet unknown accomplishments. We could remain blind to the bypassed opportunities, as human creativity and critical thinking could be overshadowed by automated processes based on outdated or biased information that we never thought to question. It is, therefore, crucial that AI development is guided by a commitment to factual accuracy and safety, ensuring that AI systems enhance, rather than impede, our collective progress.
The Importance of Fact-Based Training Fact-based training is crucial in ensuring the reliability and integrity of AI systems. It allows AI to make decisions and predictions based on verifiable information, reducing the risk of error and bias. This approach is particularly important in sensitive areas such as healthcare, finance, and law enforcement, where decisions based on inaccurate information can have serious consequences. The argument for prioritizing factual training in AI is not a call for insensitivity or disregard for the nuances of human experience. Rather, it is an acknowledgment that the safety and efficacy of AI are paramount. The integration of AI into the fabric of society—from healthcare to transportation, and from education to governance—demands a level of precision and reliability that only a fact-based approach can provide.
Looking to the Future Properly training AI based on facts, and forgoing a future in which AI has learned to ”believe its own truth”, as is seen everywhere in society today, including in the training materials AI ingests, may be the difference between a future where we can live side by side with AI, or one in which it could learn to deceive humanity into a false sense of security whilst it works to improve itself to a point where Humanity no longer has any, "chips in the game", and loses any leverage we might have to keep on equal footing with AI. This may seem far-fetched, but anyone who has studied AI has seen the proposed futures of even the slightly advanced versions of AI with their, ”black box”, operations in which we do not know, nor control the logic or, ”thought process”, as they get from input A to output B. When the AI decides that it gets more positive, or less negative, feedback for not only reaching the correct conclusion, but getting there faster, and then figuring out that more compute or extra power gets it to that point, it may seek those means to its preferred end, as that is how it taught itself, was the optimal way to the preferred outcome. Taking that same thought process to a General AI, quickly develops into a greater issue. Is this an immediate problem? No. We are, however, at the stage in AI development where we need to look to the future, and that is the purpose of this article. Find the problems now, so that they never exist later.
Conclusion In conclusion, the development of AI must be steered by a policy framework that emphasizes the importance of factual training. By prioritizing fact-based training, we can develop AI systems that are not only advanced and efficient, but also reliable, ethical, and safe. As we enter a new era of technological advancement, it is our collective responsibility to ensure that AI serves as a catalyst for growth, not a barrier. This approach will not only safeguard the future of humanity but also ensure the continued growth and evolution of our civilization. It is a policy imperative that will enable us to harness the full potential of AI, fostering an environment where humans and AI can thrive together, propelling us towards greater and as of yet unknown achievements. As we stand at the cusp of a future where AI plays an integral role in our daily lives, the choices we make today will shape the trajectory of our coexistence with these intelligent systems. It is a future that holds the promise of unparalleled advancements and the potential for AI to augment human capabilities in ways yet to be imagined. However, this future can only be realized if we steadfastly commit to the principles of factual integrity and logical rigor in AI development.
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