The rapid spread of artificial intelligence asked people: Who is most likely in their daily life? Many assume that it is the technically experienced-The ones who understand how AI works-who are the most on taking over it.
Surprisingly, our new research (published in the Journal of Marketing) finds the opposite. People with fewer knowledge of AI are actually more open to the use of technology. We call this difference in the tendency to adoption the connection “lower literacy high susceptibility”.
This link is displayed in different groups, settings and even countries. For example, our analysis of data from the market research company Ipsos, which includes 27 countries, that people in nations with lower average AI alphabetization are more susceptible to the introduction of AI than people in countries with higher literacy.
Similarly, our survey among US students finds that those with less understanding of AI are more likely to indicate that they are used for tasks such as academic tasks.
The reason for this link is how AI is now doing tasks that we once thought that only people could do it. When AI creates a work of art, writes a warm answer or plays a musical instrument, it can feel almost magically – as if it were going into the human area.
Of course, AI has no human properties. A chat bot could create a sensitive reaction, but it doesn't feel sensitive. People with more technical knowledge of AI understand this.
You know how algorithms (sentences of mathematical rules used by computers to execute certain tasks), training data (used to improve the functionality of a AI system) and arithmetic models. This makes the technology less mysterious.
On the other hand, those with less understanding can see AI than magical and impressive. We suggest that this feeling of magic makes you more open to use AI tools.
Our studies show that this recovery connection, which is prospective with lower literacy, is strongest for the use of AI tools in areas that associated people with human characteristics, e.g. B. emotional support or advice. When it comes to tasks that do not emerge the same feeling of human characteristics as the analysis of test results, the pattern flips. People with higher AI alphabetization are more susceptible to these uses because they focus more on the efficiency of AI than on “magical” properties.
It's not about skills, fear or ethics
Interestingly, this connection remains between lower literacy and greater sensitivity, although people with lower AI alphabetization look at the probability of less capable, less ethical and even a bit scary. Her openness to AI seems to be due to her feeling of amazement at what she can do, despite this perceived disadvantages.
This knowledge provides new insights into the question of why people react so differently to the technologies. Some studies suggest that consumers prefer new technology to a phenomenon called “Algorithm value estimation”, while others have skepticism or “algorithm difference”. Our research indicates the perception of AIS “magic” as a key factor that shapes these reactions.
These findings are a challenge for political decision -makers and educators. The efforts to increase the AI alphabetization could unintentionally dampen people's enthusiasm for the use of AI by making less magical. This creates a difficult balance between the support of people to understand AI and to keep them openly to their adoption.
In order to optimize AI's potential, companies, educators and political decision -makers have to increase this balance. If we understand how the perception of “magic” influences the openness of people for the AI, we can help to develop and use new products and services on AI-based AI that take into account the way people take into account , and help them to understand the advantages and risks of AI.
And ideally, this will happen without causing a loss of awe, which inspires many people to use this new technology.
Chiara Longoni, Associate Professor, Marketing and Social Science, Bocconi University; Gil Appel, Assistance Professor of Marketing, School of Business, George Washington University, and Stephanie Tully, Associate Professor of Marketing, USC Marshall School of Business, University of Southern California
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