New technologies usually follow the technology adoption life cycle. Innovators and early adopters rush to embrace new technologies, while laggards and skeptics jump in much later.
At first glance, it looks like artificial intelligence is following the same pattern, but a new crop of studies suggests that AI might follow a different course – one with significant implications for business, education and society.
This general phenomenon has often been described as “AI hesitancy” or “AI reluctance.” The typical adoption curve assumes a person who is hesitant or reluctant to embrace a technology will eventually do so anyway. This pattern has repeated over and over – why would AI be any different?
Emerging research on the reasons behind AI hesitancy, however, suggests there are different dynamics at play that might alter the traditional adoption cycle. For example, a recent study found that while some causes of this hesitation closely mirror those regarding previous technologies, others are unique to AI.
In many ways, as someone who closely watches the spread of AI, there may be a better analogy: veganism.
AI veganism
The idea of an AI vegan is someone who abstains from using AI, the same way a vegan is someone who abstains from eating products derived from animals. Generally, the reasons people choose veganism do not fade automatically over time. They might be reasons that can be addressed, but they’re not just about getting more comfortable eating animals and animal products. That’s why the analogy in the case of AI is appealing.
Unlike many other technologies, it’s important not to assume that skeptics and laggards will eventually become adopters. Many of those refusing to embrace AI actually fit the traditional archetype of an early adopter. The study on AI hesitation focused on college students who are often among the first demographics to adopt new technologies.
There is some historical precedent for this analogy. Under the hood, AI is just a set of algorithms. Algorithmic aversion is a well-known phenomenon where humans are biased against algorithmic decision-making – even if it is shown to be more effective. For example, people prefer dating advice from humans over advice from algorithms, even when the algorithms perform better.
But the analogy to veganism applies in other ways, providing insights into what to expect in the future. In fact, studies show that three of the main reasons people choose veganism each have a parallel in AI avoidance.
Ethical concerns
One motivation for veganism is concern over the ethical sourcing of animal by-products. Similarly, studies have found that when users are aware that many content creators did not knowingly opt into letting their work be used to train AI, they are more likely to avoid using AI.
