Background
God Made Work Good
“God blessed [the humans] and said to them, “Be fruitful and increase in number; fill the earth and subdue it. Rule over the fish in the sea and the birds in the sky and over every living creature that moves on the ground.”” (Genesis 1:28 NIV)
…
“The Lord God took the man and put him in the Garden of Eden to work it and take care of it” (Genesis 2:15 NIV)
Additional reading on theology of work:
Brief History of Automation
Since the Industrial Revolution in the 1800s there has been the fear of machines taking over human labor. Admittedly, in the short-term, these fears have been realized. However, in the long-term, automation has evolved fields like manufacture (factories), construction (bulldozers, cranes and excavators) and even research (search engines). Moreover, human roles in these evolved fields have remained, albeit changed and maybe more specialized.
What is AI-Human Collaboration?
AI-Human Collaboration is the idea that this trend can continue with the rise of AI in the workforce. Instead of outright replacement and banishment in a certain field, humans can take on more specialized roles. However, that isn’t to say that there aren’t concerns for both the short and long-term.
Uses
AI and humans taking complementary roles in the workforce. AI/robots carry out the more menial tasks, humans fulfill roles that require them to expect the unexpected.
Proper implementation of AI, like other instances of automation, could see the expansion of human roles.
Ironies of Automation
“We draw on this extensive research alongside recent GenAI user studies to outline four key reasons for productivity loss with GenAI systems: a shift in users’ roles from production to evaluation, unhelpful restructuring of workflows, interruptions, and a tendency for automation to make easy tasks easier and hard tasks harder.”
The irony is not new; see, for example, this 1983 article arguing that automation doesn’t necessarily remove the difficulties in human work.
Who
- Construction companies
- Factories
- Medical and biological research
- Software development ("The End of Programming"?)
Potential Concerns
- Jobs will still be lost.
- Possible mid-career re-training/re-education
- Still a transition period with a new technology
- Over-prescription of underdeveloped technology
- AI could be less efficient, less effective or more expensive than a human workforce.
- AI + moving parts = potential safety hazard
Provocative Questions
Pick one of the following areas to explore in your discussion post. You may address the questions listed here or come up with your own.
Historical
- In what ways is the rise of AI in the workforce similar to the Industrial Revolution? Is it as impactful? What’s different this time? What other historical changes can we compare it to? Is the development of AI just another step in the development of interconnected digital technology?
- Consider the short-term and long-term consequences of the Industrial Revolution or other past technological changes. How might the difference between short and long term impacts shape how we understand the impact of AI in the workforce now?
Theological
- Think about how God created work before the Fall. How might AI help bring out the good aspects of work? How might it hinder those?
- Envision specific AI systems, current or future, that might exemplify both the helpfulness and hindrance aspects of the relationship of AI and work.
Social Impact
- What principles should guide the design of AI systems that collaborate with humans rather than replace them? Give specific examples.
- Consider a specific job, perhaps some job that intersects with your life (service industry? health? design/manufacturing? …). What tasks in that job can be automated? What tasks shouldn’t be automated?
- How should we handle work displacement and re-training?
- What occupations are more likely to lose their value when we take away the element of human-to-human interaction?
Dispositions
- How might AI change the career field you’re considering? What dispositions and skills will become more important?
Further Reading
- Historical review of the industrial revolutions by Brittanica
- Why Copilot is Making Programmers Worse at Programming · The Angry Dev
- Building machines that learn and think with people | Nature Human Behaviour
- GitHub Copilot AI pair programmer: Asset or Liability? | Abstract
- “Impact of AI in The Workforce” by Artificial Solutions
- The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems
Acknowledgments
This page was originally written by Calvin CS 344 student Caleb Vredevoogd in Spring 2022. It was revised by Ken Arnold in Spring 2025.