Ever try a restaurant based on a recommendation? A hotel? A new car? There’s a phrase for this you’ve probably heard – you made your choice based on word of mouth, or another human’s belief that the experience would be worth your time.
But what about the word-of-machine effect?
The word-of-machine effect is a term that’s been coined to describe times when, in today’s ever-advancing society, humans choose to believe artificial intelligence over the word of other humans.
In particular, innovation in the realm of AI has opened up new doors for corporate enterprises and governments to leverage it at scale – but do and should we really trust it?
In this episode of Diving into Data, host TC Riley explores the word-of-machine effect and the impact on the way we view data. A study in the Harvard Business Review found that there was a difference in what humans trusted depending on if they were asked to take a recommendation based on utilitarian or hedonistic (more human, experiential and sensory) aspects.
So, what implications does this effect have for data and analytics? More than anything, Riley said, it means that analysts should be acutely aware of this inherent bias and work to actively combat it. By forcing consumers to consider alternative viewpoints, you can help them recognize bias in their decision-making – and, likewise, you can work to ensure your organization balances the influence of analytics and intuition or experience.
Listen to past episodes of Diving into Data, here.