Humans, ChatGPT and Generative AI

Some Quotable Quotes from Industry Leaders

“ChatGPT and other Generative AI platforms will have huge implications for business productivity.”

“In a world where ChatGPT and other AI apps can do many things humans once needed to do themselves or needed to hire other humans to do, the question of ‘how will I add value?’ becomes more relevant than ever.”

“How will you add value in the era of generative AI? If you aren’t attempting to answer this question now by choice, it will ultimately be answered for you by force.”

“In an era of generative AI, trust will accrue greater value in the marketplace. People will elevate trust on their list of prerequisites to purchase and prerequisites to engage with content. Furthermore, there will be a redistribution of income and assets from companies and people who are less trusted to those companies and people who are more trusted.”

“In the age of generative AI, trust brokers will become increasingly necessary and increasingly valuable in the marketplace.”

― Hendrith Vanlon Smith Jr, CEO of Mayflower-Plymouth, Business Essentials 

Infographic on How Marketers are Moving with Generative AI

Generative AI is one of the most groundbreaking advancements in recent years, a cutting-edge technology revolutionizing how marketers engage with their audiences.

As Humans, What Should Be Your Concern about Large Language Models?

“On generative AI, LLMs, etc.

Humans acquire language and communication skills from a diverse range of sources, including raw, unfiltered, and unstructured content. However, when it comes to relying on knowledge, humans tend to rely on transparent, trusted, and structured sources.

In contrast, ChatGPT and other large language models (LLMs) use a vast array of opaque, unattested sources of raw, unfiltered, and unstructured content as their means of language and communication training and as the source of information used in their responses.

While this approach has proven to be effective in generating natural language, it has also been inconsistent and, at times, significantly lacking in integrity in its responses. While it may provide information, it does not necessarily provide knowledge.

To be truly useful, generative AI must be able to separate language and communication training from the acquisition of knowledge to be used in its responses. This will allow LLMs to not only generate coherent and fluent language but also to provide accurate and reliable information to users. However, in a culture that values self-proclaimed influencers where transparency and accuracy is secondary, it has become increasingly challenging to separate reliable information from misinformation and knowledge from ignorance. This poses a significant obstacle for AI algorithms that strive to provide accurate and trustworthy responses.”


“The danger of generative AI is that it lacks the ability to understand misinformation, leading to incorrectly equating correlation with causation based on incomplete/inaccurate data or lack of contextual awareness required to understand sensitive dependencies between data sets. The unintended consequence is technology shaping societal views on politics, culture and science.”

― Tom Golway