We are heading into a new technological era. It won’t look like what it looks like now with broad anthropomorphic artificial intelligence (AI) applications. Instead, we will become more capable through the development and adoption of new tools, platforms, and integrations appropriate for how we as a species adopt technology. I use capable rather than productive on purpose: plenty is being said about the ethical implications of AI on the job market and the development and costs of operating them. In this series, I suggest we enter the next phase of adoption of this technology, from early technical tooling to common-use applications and the integration of AI into our daily lives. If we do so with open eyes and a loud voice, we can better shape what it will look like.

Just as the advent of personal computing and the Internet brought about significant shifts in our interaction with information and each other, AI is poised to be the next major transformative force in our interaction with technology. To comprehend this transition, I will explore the psychological, technological, and ethical considerations that are top of mind for me as we explore how humans interact with and adopt new technologies.

Lessons from the Past

Technological advancements come in waves, each bringing a new paradigm. Two modern examples of these waves are personal computers and the internet. The introduction of personal computers in the 1980s democratized computing power, and the internet in the 1990s connected the world. Like those waves, AI will transform many sectors, from healthcare to finance, entertainment, and education. We can learn from how these other waves have gone to help direct this one.

The Personal Computing Revolution

Innovators and early adopters, people with exploratory cognitive styles, a high need for cognition, and the time to spend learning to adapt, were the first to take on personal computing. Their actions, driven by curiosity and a willingness to embrace unproven advancements, opened the door for societal transformation. Over time, computers became more user-friendly and their benefits apparent, leading to widespread adoption in workplaces and households worldwide.

Personal computing came into my life around 1987 when we got our first computer, an IBM PC. In 1988, we upgraded to an IBM PS2, on which I played Pool of Radiance, a game that opened the world of gaming to me and drove my interest in computers, gaming, and coding, leading me to the career I have today.

The Internet Boom

The internet faced a similar trajectory. Initially a tool for researchers and academics, it quickly became a global transformative power as its potential for communication, commerce, and information sharing became clear. Again, innovators and early adopters paved the way, and as connectivity and digital literacy improved, many more people eventually joined the digital world.

In the early days before the World Wide Web came along, we communicated through Bulletin Board Systems. Online, I could communicate with like-minded people who were thinking about what the Internet could be used for. Of course, we played games, but we also started learning early how to operate in remote teams using something like Slack to communicate.

AI: The Next Disruptive Innovation

We are now at the beginning of another wave: the AI age. As with previous technological waves, the early stages are marked by excitement, experimentation, and rapid innovation. We spend more time discussing how the systems work than what significant problems they will solve. While we also worry about the possible impact the technologies will have, we must learn how to ethically train them and sustainably use them without causing further harm to the global ecosystem. Fortunately, intelligent people are thinking about these problems; I won’t touch on them here. In this series, I want to focus on three influences for technology adoption: psychological factors, technology adoption theories, and ethical considerations of adoption and equitable deployment.

Psychological Factors

Understanding how people behave, react to, and seek change is crucial in predicting and facilitating technology adoption. Cognitive styles and emotional reactions significantly affect how individuals engage with AI. Those with an explorative cognitive style and a high need for cognition will likely be the early adopters, driven by curiosity and a desire to understand and master new technologies.

Technology Adoption Theories

Society's readiness to embrace AI is more than just a product of digital infrastructure, education, and economic conditions. It's also shaped by how new technologies are adopted through society. Rogers’ Diffusion of Innovations theory suggests that people who understand AI's potential and are willing to learn and adapt are at the forefront as innovators and early adopters (Rogers, 2003). The early majority waits for proof of effectiveness before adopting, followed by the late majority finally adopting the new wave. Just as the spread of the internet was accelerated by the proliferation of affordable personal computers and increasing digital literacy, AI adoption will be influenced by the availability of user-friendly AI tools and our understanding of AI's potential benefits.

Ethical Considerations

AI's integration into society raises critical ethical questions. Issues such as equitable access, privacy, autonomy, and the potential for bias in AI systems must be addressed to build public trust and ensure that AI technologies are developed and used responsibly. It's our collective responsibility to ensure that AI enhances, rather than detracts from, the human experience.

Moving Forward

In this series, I will examine the dynamics of AI adoption, exploring the psychological perspectives, technology adoption theories, and philosophical and ethical considerations that shape our interaction with AI. I envision a future where technology enhances, rather than detracts from, the human experience. My goal is to be a catalyst for reflection. What are your thoughts on this future? How do you see AI adoption evolving? How can we ensure the maximum number of people benefit most from this new technology wave?

Posts in the series

References

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

Reference Summary

Rogers, E. M. (2003). Diffusion of Innovations (5th ed.): This book by Everett Rogers is a foundational work on how new ideas and technologies spread through societies. Rogers presents a model for understanding how innovations are adopted, categorizing adopters into innovators, early adopters, early majority, late majority, and laggards. The book outlines critical factors influencing adoption rates, including relative advantage, compatibility, complexity, trialability, and observability. It provides valuable insights into the dynamics of technology adoption, which are highly relevant when discussing the current wave of AI integration.