FINESSE: Can AI Help Reduce Noise in Business Presentations?
Communication is the exchange of information or ideas from one person to another. It has three elements: a communicator (or sender), a message to transmit information or ideas, and a receiver. Balancing words, people, and data is one way to reduce noise in business presentations and reports. Software applications that use artificial intelligence (AI) can help the communicator check for balance, but the tools need an overarching communication approach like FINESSE to be truly useful.
Effective communication occurs only if the receiver understands the exact information or idea the sender intends to transmit.
Successful communication is analogous to the signal-to-noise ratio (SNR) in electronics. The breakdown between the signal generator and the receiver occurs during message delivery. In electrical and communications engineering, noise is unwanted energy degrading signals and data quality. A signal breakdown, including too much noise, is not the receiver's fault. It is the fault, and the responsibility, of the sender.
A Balanced Approach
One way to look at potential noise is by considering that information is either communicated perceptively or interpretively.
The general public communicates perceptively — visually, audible, olfactory (smell), tactile (touch), and taste. Technical professionals like engineers and scientists communicate interpretive-symbolic (using mathematics and diagrams). Other technically trained professionals, such as lawyers and policymakers, communicate interpretive-conceptual conceptual (or narratively).
Too much on any one form creates noise for the other two. The balance is in letting the data speak for itself and presenting it in a balanced and ethical manner regardless of the immediate audience to which you are trying to appeal,
Experience and Word Searches
Experience has taught me to look at every document through the lens of words, numbers, and people. Even in the most scientific papers and presentations, the word choices and the mention of people must still be included and with relative balance. The conclusions and recommendations should also have good internal consistency with the balance of numbers, words, and people.
I worked with Dr. Diane Lauritsen to develop a paper titled "Communicating Complex Changes While Dodging Sacred Cows" for the 2022 Joint Aquatic Sciences Meeting (JASM). The paper and Dr. Lauritsen's presentation discuss challenges to effective communication with stakeholders related to complex, large-scale changes that can contribute to lake ecosystem changes in hydrology, chemistry, and productivity.
Overcoming multiple sacred cows (business as usual) provides the biggest challenge in helping communities avoid killing the golden goose (their lake). The case example is a multi-year journey of a shallow lake in eastern North Carolina, White Lake.
These were a few of my comments after reviewing the draft:
Ammonia is mentioned only four times, but its reduction is the first recommendation. Ammonia is mentioned only one time in the text. There is insufficient supporting data and no mention of how it creates social impact in the main body.
Poultry is mentioned once in the text but appears high in the list of agriculture reform measures that are needed in the region. There is not enough supporting data and no mention of social impact.
The commercial boating issue is a recurring theme. Boating, boaters, boat, and watercraft are used 29 times, plus a highlighted 1955 letter is all about the commercial boating issue. The document is wide-ranging, but boating drowns out the other issues. And the boating issue is near the bottom of the recommendation.
Re-working of the paper and presentation followed. Other issues like stormwater, groundwater, development, and other recreation received good, balanced attention in the main document, but that was not the reader's feeling.
AI-Assisted Noise Reduction
There are several dozen AI-assisted tools on the market. Searches for text analysis, text mining, and text analytics can be used to find applications for different forms of text documents. I have two favorites to supplement my normal editing and grammar tools.
Wordtune Read simplifies complex documents, articles, and blogs into bite-sized summaries to help focus on the most critical information. Wordtune Read is a very effective tool if you are researching and have to analyze or prioritize documents. As a noise reduction tool, Wordtune Read quickly provides an evaluation of what the text means versus what someone thinks it means.
For shorter documents on the order of 1000 words, Wordtune Read will provide three to five summary points. The tool will provide 3 to 5 summary points per page for longer documents, reports, and papers. Because the tool pulls the actual key points for the text on the page (and highlights them), it is always interesting to see what the application indicates what the key sentences and words are.
Wordtune Read is a good supplement to my experience and some of the other primary editing and grammar tools I use. I use it sporadically when collaborating with a co-author or needing reinforcement in a debate.
Google’s Natural Language API
Natural Language API allows users to apply natural language understanding (NLU). The tool includes entity analysis, sentiment analysis, syntax analysis, and content classification.
I like using this tool using the entities and categories features. Entities classify keywords in items like people, organizations, numbers, locations, and consumer products, making it easy to get an overall count and balance indication. Categories give an overall assessment of how the trained program classified the text among hundreds of possibilities (this article has a 67% chance of being about Business & Industrial/Business Operations).
I am good at old-school word searches at this point in my career. Natural Language API occasionally provides a few surprises and is a good reinforcement tool when I need one in an editing debate.
Applying It with FINESSE
I have lain down some narrative concepts, mentioned a personal application, and dropped in some numbers, website links, and references to artificial intelligence. Hopefully, keeping all three in balance to minimize noise.
Minimizing noise takes discipline and practice. The burden of effective communication is on the sender, not the receiver. The good news for technically trained professionals is that some AI tools will now help you.
The AI tools, however, are effective only as part of a larger communication approach. After all, all AI tools have some underlying logic and approach to them as well. Once a communication approach like FINESSE is established, AI tools become important, supplemental aspects for making communication more effective.
The N in FINESSE stands for Noise reduction. Are you Communicating with FINESSE?
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