Do People Believe in Artificial Intelligence? | Technology
It sounds like science fiction, and often creates images of machines that become smarter if not smarter than humans. To describe it more practically (and accurately), AI refers to the use of computers and data to solve problems and in some cases to make decisions.
A range of industries use AI for a number of purposes, including healthcare and the automotive industry. For example, artificial intelligence has been invented as a way to help doctors make better diagnosis and treatment decisions; Using data about patients, artificial intelligence can predict which medication may be more effective for a given treatment. AI has also become increasingly popular and common in our daily lives: just think of how Alex and Siri are at the forefront of our daily activities.
Given how popular AI is becoming in our world, an important ethical question arises: Do we trust AI to do what we need to do? A new study published in International Journal of Human-Computer Interaction Attempted to give a quantitative answer to this question.
Researchers at the University of Tokyo developed an “octagon measure” to measure people’s perceptions of AI, which was used to rate people’s perceptions of AI in a number of categories, such as fairness, privacy, liability and responsibility. The researchers then sent respondents four scenarios to judge and analyze based on these eight categories: AI-generated art, customer service AI, autonomous weapons and AI in crime prediction.
In addition to gathering demographic information, the researchers found that the risks posed by these various scenarios are viewed more negatively by women, older individuals, and those with knowledge of AI content, which is consistent with previous work. That is, AI had less favorable views on this demographic. The researchers also noted that there is much more concern and hesitation about the use of AI in weapons, a discovery that was not unexpected.
The study team hopes that their assessment scale could be used to better measure public perceptions about AI technology in the future and help bridge the gap in understanding what is true as opposed to what people think about AI.