Namaste Yogis. Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, was submitted by Alfredo and he wants to know what is the AI divide and what can be done to bridge it?

Alfredo, you came to the right place. Alfredo if you believe history repeats itself you won’t be surprised by an AI divide. The adoption of new technology follows a well-established pattern, and it goes like this–people and societies with the most resources adopt new technologies first and the rest follow behind. Initial buyers of automobiles, televisions, telephones, and internet at home were people with resources and access. Adoption and use of AI is following a similar trajectory. Fortunately, at least one university president, Adela Dela Torre, of San Diego State University (SD State U) has noticed and demands action before the divide turns into a canyon. Let’s examine what DelaTorre wrote on April 4, on Inside Higher Ed.
She begins with a simple declarative sentence—leaders in higher education must take decisive actions to prevent AI from further exacerbating inequality. According to DeLaTorre, Amazon Web Services says that 73% of employers report prioritizing hiring talent with AI skills. Given the direction and obvious impact AI will have on the future workforce, why 27% would not prioritize AI skills is unexplainable! Holy head in the sand, Batman! Moreover, employers are willing to offer higher salaries (up to 50%) for graduates with AI skills. What do students say?
Students agree AI will impact their future careers. In a survey of 8,000 students, 71% expect using AI will be an essential part of their job. However, the survey revealed noticeable differences that are explainable by access to technology and socio-economic background.
For example, students with plenty of access to technology (measured by the quantities of smart devices owned) viewed AI positively, less intimidating, or complex. The same is not true for students from economically disadvantaged neighborhoods, first -generation, low-income, and those coming from under-represented communities. These students reported a lower use of AI tools, were significantly less comfortable using or understanding AI tools, and see AI less favorably. The result–an AI divide.
Will time solve the AI divide? According to DelaTorre the trend is not a friend. She says the trend is toward pricey commodification. DelaTorre correctly notes, many AI tools are free today–emphasis today. However, according to the U.K. non-profit, Jisc, access to a full suite of the most popular AI tools costs nearly $1,300 per year and that is beyond the financial reach of many on the wrong side of the AI divide.
DelaTorre concludes with a call to action by recommending greater partnerships for AI affordability and access between universities and AI companies. Her second recommendation calls for universities to embrace data-driven discussions and decision-making regarding AI. Her third point is to enhance training and responsible use of AI. She concludes with suggesting development of comprehensive AI strategies.
Given the history of technology adoption and the survey results, the AI divide is legitimate and Dela Torre’s recommendations are on target. As an AI community, we should acknowledge reality and support those working to bridge the AI, not dismiss their warnings.
Time to go, but first a proverb from the Dominican Republic, where they say: Don’t be like the shadow: a constant companion, yet not a comrade.
Until next time,
Yogi Nelson
