“To prevent succumbing to disappointment, never lose sight of knowledge and hope.” –Greg Williams, The Master Negotiator & Body Language Expert (click to Tweet)
“Artificial Intelligence – How To Avoid Disappointment In A Negotiation”
People don’t realize they’re always negotiating.
In every negotiation, savvy negotiators plan the strategies and tactics they’ll use before entering into a negotiation. That allows them to be more adaptive to rebuttals, offers, and counteroffers posed by their counterpart. It can also give them an advantage in the negotiation by not thinking of what they’ll implement. Instead, they execute, having considered the responses that might come from their actions. But artificial intelligence (AI) changes the equation of how negotiators interact with one another. That can lead human negotiators into disappointment.
Unlike bots (short for robots), humans can’t think as fast or with the depth in which bots can think in AI environments. As such, human negotiators may not accurately anticipate a bot’s reactions when negotiating in the realm of artificial intelligence. But a bot’s degree of functionality is within its programming. And they’re various degrees of latitude within those frameworks, based on the type of bot created. To avoid disappointment, consider the following before negotiating in environments containing artificial intelligence.
Types of Bots
Generally speaking, there are two types of bots – machine learning and rules-based. The main difference between them lies in their functionality. To that end, machine learning bots, while encompassing aspects of rules-based logic, tend to be more sophisticated than rules-based bots.
Machine Learning Bots
Machine learning bots accumulate data continuously. The more substantial the gathered data that goes into their make-up, the more rigorous the bot’s performance will be. It’s worth noting that these bots’ sophistication stems from how it enhances its knowledge base based on what it encounters. Thus, depending on where you are in its evolution, you can be up against a more formidable negotiation opponent than at other times in its development.
Rules-based bots’ foundation lies within specific scenarios the bot intends to address. Accordingly, it possesses a more simplified operational mandate. To that end, it may employ “what if” (e.g., what if a response is this, then I’ll do that) procedures to direct an individual down a particular path. Thus, rules-based bots tend to be less sophisticated than machine learning bots.
Negotiation Planning Against Bots
As is the case in any negotiation, if you’re not ready to engage, you shouldn’t. That’s truer when you know you’ll be negotiating against a bot. In some cases, people have made significant concessions to bots. That would not have been the case if they were dealing with a human negotiator. For one, some people are unsure of how to engage a bot. If the bot offers two options, non-savvy negotiators might accept one of them, never considering the possibility of a third option.
In some situations, timing components may control a bot’s actions. Those components function on the amount of time it takes the human counterpart to respond. That’s one way a human negotiator can alter the path of its bot companion. But the human negotiator has to know that to do that. And that leads to the main point in planning an artificial intelligence negotiation environment. If the negotiation is essential, understand the functionality of the bot you’ll be negotiating against, machine or rules-based. Based on that information, a bot will perform in one manner versus another.
Your negotiation world has changed. And artificial intelligence is at the heart of it. That’s why you must become smart about negotiating against bots. They can outthink humans. But the following are thoughts to consider to decrease the advantage they have.
1. The Delay Game
Sometimes a negotiator can delay a response to a bot, and the bot will issue a question. It may be something as abstract as, are you still there? To which you can even delay your response longer. The point of the ‘delay game’ is to observe how the bot responds. The more insight you gather, the more excellent the opportunity you’ll have to manipulate the bot to your advantage.
In a best-case scenario, you gain enough understanding to offset the bot’s advantage. Worst case, the bot begins to negotiate against itself by extending offers. And that can become a best-case scenario too.
2. Playing Hard To Get
In a human-to-human negotiation, I’ve used the takeaway strategy. It consisted of telling the other negotiator that we were close to concluding a deal but not quite there. This tactic is best employed when the negotiators have invested a reasonable amount of time in the negotiation. When my opponent wouldn’t make a key concession, and he thought the deal was close to completion, I told him I’d reached the end of my offers. As I exited, I suggested he call me if his situation changes.
When negotiating online to purchase products, if you place an item in the cart and don’t complete the purchase, you’ll usually receive a follow-up reminder indicating it’s still in the cart. If you withdraw it, sometimes you’ll get an offer to purchase the item at a discounted price. That’s one way you can beat a bot – play hard to get.
Negotiations against bots can be challenging. When considering artificial intelligence, bots can outthink humans. But that doesn’t mean a human negotiator has to feel downtrodden in a negotiation. Once a negotiator has planned for the non-human competitor he’ll be engaging, he can decrease the possibility of having his efforts met by disappointment. To do that, he’ll have to know the strategy the bot intends to employ and how to thwart its efforts. And everything will be right with the world.
Remember, you’re always negotiating!
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After reading this article, what are you thinking? I’d like to know. Reach me at Greg@TheMasterNegotiator.com
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