The Smart way to ask AI
How to ask questions to receive optimal results when extracting information from documents with AI | Article
Solving the Art of Inquiry: Mastering the Dance of Questions and Answers with AI
In the bustling heart of Canary Wharf, London, where the pulse of global finance beats incessantly, a team of bright minds congregates within the sleek confines of a Hedge Fund office. Among them, Emma, a diligent analyst with a penchant for unravelling financial intricacies, finds herself engrossed in a quest for optimal information extraction from voluminous documents, aided by the ever-evolving power of Artificial Intelligence (AI).
‘Optimal Results Begin with Precise Questions, Questions that Lead to Optimal Results’
Dialogue: How to solve this Challenge?
The team, comprising Emma, James, Sophia, Liam, and the seasoned Brian, grapples with a persistent challenge: extracting precise insights from vast swathes of financial data. Despite their collective experience, they often find themselves at an impasse, unable to fully harness AI’s potential. Emma laments in a heated exchange one afternoon, “AI seems incapable of discerning the nuances we seek in our financial reports. It’s frustratingly limited!”
Brian, the sage of the group, interjects with a wry smile, “Perhaps the fault lies not with the AI, but with the simplicity of our questions. We must delve deeper, my friends, and illuminate the shadows of ambiguity.”
… and the story unwinds
Thus begins a journey of enlightenment for the team, guided by Brian’s wisdom. They embark on a quest to refine their questioning technique, understanding that the potency of AI lies not in its mere existence but in the precision with which it is wielded. Through spirited debates and collaborative brainstorming sessions, they hone their craft, crafting questions akin to finely sharpened arrows aimed at the heart of complexity.
In the hallowed halls of their office, dialogue flows freely, each member contributing their unique perspective. Sophia, with her keen eye for detail, advocates for specificity, “We mustn’t ask broad strokes questions, but rather, pinpoint the exact metrics we seek to uncover.”
James, ever the pragmatist, adds, “Let us not forget the context in which our inquiries arise. The finance landscape is ever-shifting, and our questions must adapt accordingly.”
The penny has dropped
With newfound clarity, the team sets out to dissect their approach to questioning. They delve into the anatomy of an effective query, understanding that it is not merely a string of words but a conduit for extracting actionable insights. Each question becomes a beacon of illumination, guiding their journey through the labyrinthine corridors of financial data.
They learn to ask multi-tiered questions, each layer peeling back the veil of ambiguity to reveal more profound truths. No longer satisfied with surface-level answers, they probe the depths of complexity, solving the tangled web of financial intricacies with surgical precision.
Emma, infused with newfound confidence, declares, “Our questions are no longer shackles restraining the potential of AI, but keys unlocking the treasure trove of knowledge buried within our documents.”
Three good, extended, multi-tier questions to extract information from a 100-page quarterly financial report for an energy company. This is the example that the team came up with:
Good Question 1:
What were the energy company’s primary sources of revenue during the quarter? Can you break down the revenue streams by segment (e.g., renewable energy, fossil fuels)? What were each segment’s key contributing factors to revenue growth or decline? Were there any notable changes in market demand or pricing dynamics that influenced revenue performance?
Good Question 2:
How did operating expenses fluctuate compared to the previous quarter? Can you provide insights into the major drivers behind any significant changes? Were there any cost-saving initiatives implemented during the quarter, and if so, what impact did they have? Did the company incur unexpected expenses or one-time charges that affected its financial performance?
Good Question 3:
What was the company’s cash flow position during the quarter? Can you elaborate on the sources and uses of cash, including any significant investments or divestments? Were there any notable changes in working capital metrics, such as accounts receivable or inventory turnover? How did the company’s cash flow performance align with its strategic objectives and financial targets for the quarter?
Three examples of short, wrong questions:
How did the company perform financially last quarter?
Bad Question 2:
What were the expenses?
Bad Question 3:
Did the company make any money?
The same logic and structure will apply to formulating questions in many different domains such as legal, manufacturing, pharmaceutical, aviation, automotive, healthcare, etc. The core point is to precisely describe the objective that you want to achieve and what information you seek. AI cannot read your mind, and doesn’t know the history on what you are working. It needs constructive insight in the form of the question to read, analyse the text and deliver the answer you await.
‘Ask Questions, Questions that Uncover: Master AI’s Potential’
Conclusion:
In the crucible of inquiry, the team emerges transformed, armed with a newfound understanding of the symbiotic relationship between questions and answers. Through the crucible of conflict, they have forged a path towards mastery, harnessing the full potential of AI to navigate the labyrinthine corridors of financial data with confidence and clarity.
As they gaze out over the glittering skyline of Canary Wharf, they know that their journey has only just begun. With each question asked, each answer unearthed, they inch ever closer to the elusive pinnacle of understanding. And in this dance of questions and answers, they find not just information but wisdom – the true currency of the modern age.
‘Precision in Inquiry Leads to Insight, Insight Unlocks Potential with AI’
‘The quality of our questions determines the quality of our answers, and ultimately, the depth of our understanding.’
— Brian Tracy
What are the top three aspects of this article?
— How to ask questions so AI can understand our goal and deliver expected results
— Short vs Extended questions: which method delivers optimal results
— AI cannot read our minds; it can leverage billions of algorithms to comprehend extended and precise question
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— v500 Systems | AI for the Minds, this is an example from our AI Document Processing SaaS Solution, asking a long-winded, multi-tier question. Please notice the comprehensive answer AI was able to deliver from a 77-page Financial Report (click on the image to enlarge) — https://myAI.v500.com
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Disclaimer: The names and locations mentioned in this story have been changed to protect the confidentiality of our clients. We take privacy and confidentiality seriously and never disclose sensitive information about our clients. The narrative presented here is used solely to illustrate how AI functions within large business environments
