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Cultural Worldviews about the Surrounding Environment and Their Implications for the Design and Societal Impact of Smart Technology

With Xiao Ge and Hazel Markus


Smart technology broadly refers to information and communication technologies that gather and process information on its operating environment or history to draw intelligent inferences from it and to act on these inferences by changing its characteristics in an advantageous manner (Goddard, Kemp & Lahne, 1997)

In this paper, we aim to take crucial initial steps to chart the cultural assumptions underlying the invention and use of smart technology. We situate our discussion of smart technology in the context of people's general relationships with essential tools they invented throughout history. Smart technology, we posit, is another example of a versatile and consequential tool that people have invented. Even though its current forms (e.g., deep learning neural networks, virtual reality, or the internet of things) are recent developments, the idea of creating intelligent tools that can perform human tasks has been attempted by people in various societies and can be traced back to ancient times. We thereby see the current and future development of smart technology in the context of people's continuous invention of tools and their relationships with these tools in different groups and societies. From this viewpoint, we will describe cultural assumptions underlying the design of smart technology based on people's worldviews about the surrounding environment (e.g., physical objects in daily life and natural beings) in different societies. We argue that this worldview affects the kinds of tendencies and states of existence that people imbue smart technology with, the level of agency that people impart to smart technology, and the level of relatability that people perceive smart technology to have, as well as preferences for non-mimetic versus mimetic designs of technology. After that, we will discuss cultural blindspots for smart technology in different societies.

Explore the Affordances of Smart Technology for Improving Equitable Social Interactions

With Xiao Ge, Cinoo Lee, Daigo Misaki, and Hazel Markus

Artificial Intelligence (AI) has been shown to maintain and exacerbate social inequity and social exclusion. Most current forecasts suggest that this will only intensify as AI is employed in many more domains. We propose that it is possible to leverage AI to purposely recognize and redress inequity. The focus of this project is on how to use AI to augment equity in teamwork. Here equity is concerned with recognition of diversity, support for diversity and fair or just treatment in teamwork. 


We argue that popular perceptions of AI are based on a narrow exploration of AI's technological affordances. As an ever-evolving technology, AI affords abundant possibilities for serving different purposes. Yet, there is a huge imbalance among the kinds of purposes that AI products currently serve. While products that aim to create economic gains (i.e., efficiency-serving AI) are taking the lion's share of all AI categories, products that promote an equitable and inclusive society (i.e., equity-serving AI) have yet to be conceptualized. Partially because of the dominance of efficiency-serving AI, current discourse surrounding AI ethics tends to focus on preventing harm. But given the historically accumulated high amount of inequity, merely creating efficiency-serving AI that does not add inequity would not drive society to a more equitable future. We instead posit that it is equally important to explore how AI can lend itself to facilitate social equity. The potential of developing purposeful AI to improve equity is immense, yet minimal research to date has been done about it.

We propose that AI offers a unique opportunity to enhance equitable team interactions. There is considerable malleability around how people perceive AI, which provides ample space for AI to take on novel roles in teamwork. For example, because AI is perceived as objective and non-judgmental, AI-based products are well positioned to uphold equity while potentially circumventing social backlash. Overall, we aim to explore the desirability and feasibility of equity-serving AI in light of its potential social impact and related ethical considerations. Our goal is to potentially galvanize the creation of a new category of AI applications that could directly contribute to equity in teamwork.

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