Why will the inability to manage "agreement" do more harm in this AI age?

It is easy to be overwhelmed with the rapid pace with which companies such as Open AI and Google are launching revolutionary improvements to the AI ecosystem. Entire industries are always waiting with bated breath so that they can “follow fast” with initiatives and announcements to stay relevant and ahead of the competition.

And we have come to agree that the time to act is NOW, and if you do not then only oblivion and irrelevance awaits you.

Join now or be left behind?!

So, the message we are emitting is — nod your head in agreement — start planning for the AI race on the individual and organisational level.

But, in all this rushed madness of our blinded agreements regarding action for AI, our inability to manage this “agreement” — more than our inability to manage conflict — will be the most pressing issue of our times.

Reminds me of the Abilene Paradox for reasons I mention as follows.

The Abilene Paradox

The Abilene Paradox, a concept introduced by Jerry B. Harvey in 1974, warns of the dangers of groupthink and the tendency for individuals to conform to perceived consensus, even if it contradicts their personal preferences.

This paradox is a concept in group dynamics that describes a situation where a group of people collectively decide on a course of action that contradicts the preferences of the individual members. This occurs because each member believes that their own preferences are counter to the group's and thus goes along with what they think is the consensus to avoid conflict or discomfort.

The paradox highlights how group decisions can lead to outcomes that none of the participants truly desire.

This paradox also warns against decisions based on assumptions about what others in the group want, and a similar dynamic is emerging right now in the AI landscape.

Organizations are being frequently bombarded with success stories, promising advancements, and industry-wide adoption. This pervasive narrative can create a sense of urgency, prompting organisations to jump on the AI bandwagon without thorough scrutiny.

Consider the scenario where a company, under pressure to embrace AI for enhanced productivity, invests in a sophisticated AI-driven system without fully understanding its applicability to their specific business needs.

In the rush to implement AI, organizations might assume a consensus on the perceived benefits of AI without conducting a comprehensive analysis of their internal capabilities and challenges. This can lead to misaligned strategies, where the chosen AI solutions do not address the actual needs of the organisation.

Furthermore, the hype surrounding AI can foster a culture where dissenting opinions or concerns about the ethical implications of AI are stifled. For instance, if employees have reservations about the potential bias in AI algorithms or the ethical use of AI in decision-making, there might be a reluctance to voice these concerns openly.

This silence can result in a decision-making process that neglects critical ethical considerations, reminiscent of the Abilene Paradox, where individuals avoid expressing dissent to maintain an illusion of unanimity.

The Abilene Paradox is harmful because it results in:

• poor decision-making,
• wasted resources, and
• unnecessary stress.

Also, it can lead to outcomes that do not satisfy anyone involved, eroding trust and morale within the group. Additionally, it stifles honest communication and innovation, as individuals suppress their true opinions and ideas to conform to perceived group norms.

Let us consider a few examples:

1. Customer Service: Let us consider the case of a retail company rushing to deploy AI-driven customer service chatbots to keep up with competitors. Despite the initial excitement about embracing cutting-edge technology, employees might harbour concerns about job displacement and the impact on customer relationships. If these concerns are not addressed openly and transparently, the organisation risks implementing a solution that creates internal and customer dissatisfaction.
2. Recruitment: Organisations eager to streamline recruitment procedures might turn to AI algorithms to screen resumes and conduct initial candidate assessments. However, if the potential biases in the training data used to develop these algorithms are not thoroughly examined and addressed, the organisation may unwittingly perpetuate existing biases, leading to unintended consequences. Decisions made without considering individual perspectives can result in unforeseen negative outcomes.

The way forward

My advice is to navigate the excitement surrounding AI technologies by fostering

• an open dialogue,
• considering diverse perspectives, and
• critically evaluating the specific needs and challenges unique to your context.

Secondly, the short-term goal of every organisation should be to have a clear data strategy to support —

• data discovery,
• data design,
• data development, and
• data delivery.

And remember....

NOW is not just the best time to REINVENT — but also a good chance to REASSESS!

#organization #ideas #technology #culture

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*Disclaimer: Nothing in this article constitutes as financial advice. Always do your own research.