Illustration created by DALL-E with the prompt “portrait of an computer built to run an artificial general intelligence (AGI) model, metallic armor, white black gold, mechanical features, baroque rococo, cinematic lighting, golden ratio, dynamic pose, sigil metallic armor, ritual, intricate gold, 3D ornate alter, highly detailed ornaments crystallized black gems, ambient occlusion, high key photography, bokeh 8K beautiful, detailed scenery, metal diamond design gold photorealistic, insanely detailed and intricate, hyper minimalist, elegant, ornate, hyper realistic, super detailed, 8K, aspect ratio 16:9”


Recent developments at OpenAI, marked by the abrupt departure of CEO Sam Altman, have stirred the AI community. Speculations suggest internal disagreements over the pace of AI development, particularly around commercialization, hinting at deeper issues within the field.

Generative AI: The Current Landscape

Generative AI, exemplified by models like ChatGPT, Google’s Bard, Anthropic’s Claude, and Inflection AI’s Pi represents the most consumer-engaging facet of AI today. These technologies, harnessing advanced algorithms, are adept at creating content – from text to images – based on learned data patterns. However, it’s vital to recognize that generative AI, while popular, is merely a part of the broader AI spectrum, mostly categorized under narrow or weak AI due to its specialized applications.

The Concept and Promise of AGI

While OpenAI is famous for ChatGPT (its generative AI product), the company’s stated goal is the creation of a model capable of Artificial General Intelligence (AGI) a model that would achieve a level of intelligence and cognitive ability parallel to human intellect. Such a model would be capable of understanding, learning, and applying knowledge across a diverse range of fields. The realization of AGI would not only be transformative but also revolutionary, potentially addressing complex global challenges in ways currently unimaginable.

Concerns and Fears Surrounding AGI

AGI’s transformative potential comes with profound concerns. Prominent figures like Ilya Sutskever (Chief Scientist at OpenAI) have voiced apprehensions about the rapid pace and unpredictability of AGI development. Concerns include unpredictability and Lack of Control. AGI, by definition, would have the ability to perform any intellectual task that a human can, and potentially more. Its decision-making process could become complex and opaque, making it difficult for humans to predict or control, raising concerns about unintended consequences.

But the fears go deeper ranging from existential risks, where misaligned AGI goals could lead to human or environmental harm, to ethical and moral dilemmas about its treatment, rights, and decision-making ethics. AGI also poses threats of social and economic disruption, potentially outperforming humans across tasks and exacerbating unemployment and inequality. Additionally, the potential misuse or weaponization of AGI by various actors raises significant security concerns.

The concept of a “singularity” further intensifies these fears, suggesting that AGI’s rapid self-improvement could lead to uncontrollable and irreversible technological growth. These challenges are compounded by deep philosophical questions about consciousness, identity, and the essence of intelligence, challenging our fundamental understanding of these concepts.

Market-Driven Optimism

Unsurprisingly, the fear of AGI is not universal. Some experts argue that market mechanisms and regulatory frameworks can effectively manage AGI’s development. They advocate for industry standards and ethical AI guidelines as tools to mitigate risks. This viewpoint underscores a belief in the power of collaborative innovation and regulation to steer AI towards beneficial outcomes. It is the system we have in place today – you can judge for yourself if it is working or if it needs work.

You Must Help Architect the Future

There’s a palpable concern about AGI’s unpredictable nature and its potential societal, ethical, and existential risks. Others believe in the efficacy of market dynamics and regulatory measures to mitigate these risks. How do you see the future of AI? Are you excited about having an AI assistant but scared that one day it may go too far? Can you be both thrilled and scared at the same time? The way I see it, if AI doesn’t thrill you and scare you in equal measure, you don’t understand it well enough.

If you want to learn more about the practical differences between Generative AI and AGI, please sign up for our free online course Generative AI for Execs. It will help you gain the knowledge and insights you need to become an architect of the future you want to live in.

Author’s note: This is not a sponsored post. I am the author of this article and it expresses my own opinions. I am not, nor is my company, receiving compensation for it. This work was created with the assistance of various generative AI models.

About Shelly Palmer

Shelly Palmer is the Professor of Advanced Media in Residence at Syracuse University’s S.I. Newhouse School of Public Communications and CEO of The Palmer Group, a consulting practice that helps Fortune 500 companies with technology, media and marketing. Named LinkedIn’s “Top Voice in Technology,” he covers tech and business for Good Day New York, is a regular commentator on CNN and writes a popular daily business blog. He's a bestselling author, and the creator of the popular, free online course, Generative AI for Execs. Follow @shellypalmer or visit


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