Ex Machina

Robin Wigglesworth highlights the effect of Artificial Intelligence on executive communications in an article in the Weekend FT (subscription required). A new form of “robo-surveillance” by trading algorithms is spurring executives to place a deeper focus on the spoken word.

Executives are coached to avoid saying certain phrases, such as “but” which could trigger stock sales by natural language processing (NLP) machines taught the intricacies of human speech. Using NLP, investment funds instantaneously scrape speeches, social media chatter and corporate earnings calls for clues.

Cat and mouse

The result is a cat and mouse game, where CEOs try to outwit the machines that can pick up a verbal clue that a human might not even realize is relevant.

A recent academic paper — How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI — points out that companies are keen to show off their business in the best possible light.

…firms with high expected machine downloads manage textual sentiment and audio emotion in ways catered to machine and AI readers, such as by differentially avoiding words that are perceived as negative by computational algorithms as compared to those by human readers, and by exhibiting speech emotion favored by machine learning software processors.

The paper found that companies have tweaked the language of annual reports and how executives speak in public to avoid words that might trigger red flags for machines listening in.

These changes extend to the tone of voice executives use, in addition to the words they use. The paper notes:

Managers of firms with higher expected machine readership exhibit more positivity and excitement in their vocal tones, justifying the anecdotal evidence that managers increasingly seek professional coaching to improve their vocal performances along the quantifiable metrics.

Some companies’ investor relations departments are even running multiple draft versions of press releases and speeches through such algorithmic systems to see which scores the best.

In return, NLP powered algorithms are also continuously adjusted to reflect the increasing obfuscation of corporate executives, so it ends up being a never-ending game of fruitless linguistic acrobatics.

In this game, the machines have the upper hand. The algorithms can immediately adjust for a chief executive’s idiosyncratic styles.

A certain CEO might routinely use the word “challenging” and its absence would be more telling while one that never uses the word would be sending as powerful signal by doing so.

Body language

Machines are still unable to pick up non-verbal cues, such as a physical twitch ahead of an answer, but experts predict it’s only a matter of time before they can do this as well.

Where this will all end, and the impact it will have on speechwriters, presentation coaches, investor relations, and PR professionals is open to speculation.

Usually when machine and men collide, it’s the machines that have the upper hand.

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