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Article written by Carlos Dangelo and Philippe Ciampossin

As a professional in today's data-driven business landscape, adopting generative AI is becoming essential to stay competitive. While these technologies hold great promise, it's wise to approach them with open eyes regarding potential pitfalls.

We are entering an era of unprecedented human-machine collaboration. The symbiotic brain relationship with technology really began with smartphones (who can remember days before mobiles) and is expanding as AI tools are further woven into daily life through the technology. Now we are at a stage where it does really start to complement us in acquisition of knowledge and our reasoning abilities.

Generative AI can accelerate acquiring new insights and magnify thinking by interacting with a system that occasionally seems eerily human.  However, fully realizing the potential of generative AI requires recognizing these technologies as aids for collaboration, not as oracles. The core mechanism aggregates information and knowledge in a way so that business professionals avoid needing to ingest the entire corpus of data, instead allowing targeted querying and iterative content refinement through added context.

To maximize the potential of generative AI, we must use it in a closed-loop fashion with human oversight – the AI tools may never be ready for autonomous thinking or worse, making decisions without human oversight.  While generative AI provides intriguing information and insights, you must refine, fact-check, and validate that the output makes sense for your specific problem. The key is to augment your reasoning capabilities.

Experts recommend professionals to explore hands-on testing to determine how best to integrate generative AI into day-to-day work. If you haven't already opened a dialogue with management about these tools, those conversations will likely come sooner than later.

This blog is an overview of AI’s Generative Models concerns reflecting personal views on the technology and eco systems.

( Philippe Ciampossin & Carlos Dangelo & Dan Maslowski - Nov 2023. All rights reserved)

The notion of a catastrophe scenario based on a rogue AI has been a fundamental trope for legions of books and movies. Wintermute, the William Gibson protagonistic in Neuromancer or Arnold Schwarzenegger’s depiction of a sentient robot in The Terminator evoke the quintessential fear of the take over of the human condition. Isaac Asimov in his foundational Robot series talks about the three laws of Robotics and they nicely articulate the fear and doubt that many of us feel when we look at Generative AI.

Setting aside theater and science fiction, do you find yourself worrying about releasing your offering around GenAI and keeping it under control? GenAI is a long way from the Hal9000, but as the owner of a GenAI initiative in your company are you afraid that one day you may hear “I am sorry (insert your name), I can’t do that” when you ask it to open the pod bay doors? The reality is that AI can get away from the intended consequences and as such we should discuss that.