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Generative AI Will Make Work More Efficient But Less Human. What Kind of Work Will Be Worth Doing?

In the mid-90s, a new research and information-sharing tool became available to the general public. This interconnected network of computers – dubbed the Internet for short – was faster and more efficient than the book, telephone, or handwritten mail. This marked the beginning of a digital revolution that has reshaped every aspect of the way people live, work, and build relationships in the 21st century. Over the next two decades came social media, the smartphone, digital apps, microblogging, chat forums, and streaming audiovisual content. New industries and ways of connecting with people were made possible by the Internet, but it also exacerbated issues of mental health, exploitation, loneliness, misinformation, political division, privacy rights, and more. The Internet and personal computing devices advanced very quickly in a short span of time, and people have barely figured out how to live well with it. In 2023, we are on the cusp of what may be an even greater technological revolution with Artificial Intelligence.

Thanks to pop culture, AI may draw up images of robots gaining sentience and trying to kill or enslave humanity. These fears are not very grounded in reality, but there are some very legitimate concerns about its consequences. This article will focus on how AI will transform workplaces, how people work together, and the meaning of work itself.

AI, Machine Learning, and Deep Learning

To understand how recent breakthroughs in AI will change work, it is important to first brush up on what AI technology is. In brief, AI is a field of computer science that uses machine learning and deep learning to process large quantities of data. Machine learning is a subfield of AI research into developing computer systems that can learn and improve each time they are used to process data, and with minimal human guidance. Deep learning is a type of machine learning that gets trained to process information in a way that mimics human thinking. These computer models are used to develop AI algorithms that can perform analytical and predictive tasks. AI is an advanced form of computer technology that is very effective at generating solutions and new insights from existing data in a short timeframe.

Generative AI has passed the threshold of convincingly simulating human thinking

This year, AI research hit a breakthrough in the field of generative AI. Before now, AI technologies were very effective at data processing, but they had not achieved a convincing level of verisimilitude in humanlike speech and behaviour. Generative AI systems like Chat GPT have changed that. AI has passed a threshold where not only can it produce high quality text that is near indistinguishable from something written by a human – and even hold a conversation – but it can also create new images and video with a high degree of accuracy and artistry. Type in a prompt worded for the system to understand, and it will spit out images or a piece of text in less than a minute. For this reason, tech developers boldly describe Generative AI as a “disruptor” technology that will transform every area of society and culture. They are right.

What is AI’s vision of work and the worker?

In a 48-page document designed to help business incorporate generative AI into their organization, Google describes a new team structure based around human-AI collaboration. These teams are made of at least three members that manage a different aspect of the AI bot. Roles in these teams include building and maintaining the AI, creating prompts, and fine-tuning the results. Once a workplace figures out how to implement these human-AI teams in one part of their organization, such as customer service, they can expand this team structure to more areas.

Google’s proposed AI team is not just a way of using AI. In this new system, AI is not just a tool, but another member of the team. The human worker is reimagined as a manager of an AI, rather than a skilled worker with a particular knowledge application. The result will be people spending less time interacting with other people, and more time with an AI assistant or chatbot. As more workplaces start to implement similar AI-based team structures, it is likely that we will see a deepening of the modern loneliness crisis. A deep-learning algorithm can provide answers and even mimic human behaviour, but it cannot meaningfully encourage people or challenge them to grow. This way of working might create more efficient workplaces, but it will not help people thrive.

As more workplaces start to implement AI-based team structures, it is likely that we will see a deepening of the modern loneliness crisis.

What makes work meaningful?

In his book The Unsettling of America, Wendell Berry identifies two kinds of workers: exploiters and nurturers. He writes:

“The exploiter wishes to earn as much as possible by as little work as possible; the nurturer expects, certainly, to have a decent living from his work, but his characteristic wish is to work as well as possible. The competence of the exploiter is in organization; that of the nurturer is in order – a human order, that is, that accommodates itself both to other order and to mystery.”

Berry’s categorization of workers as exploiter and nurturer reveals that generative AI may have a stronger tendency toward exploitation. AI’s intended function is ultimately to reduce effort and increase productivity, which reflects the exploiter’s desire to “earn as much as possible by as little work as possible”. In contrast, the nurturer wants good work done well that will provide enough to live by. The tendency of the exploiter is not even to know they are exploiting others, but to believe that they are helping people achieve a better way of living by eliminating hard work.

In a recent discussion with Carey Nieuwhof about the promise of AI to make life effortless, Dr. John Wyatt asked the rhetorical question, “Is it possible for human beings to grow in a world that is completely frictionless?” Those developing AI and the institutions beginning to use it are not asking this question, but it is the most important question to ask. It is through facing challenges that people learn how to persevere and overcome difficulty, which leads to maturity. People also naturally enjoy thinking about how to solve a problem, both individually and as part of a team. There may be wisdom in giving AI the most repetitive parts of a job to do, but we should also ask why we gave ourselves such work in the first place. Workplaces should not eagerly hand off the challenging parts of thinking to machines. It is by encountering friction in their work that people learn resilience and gain skills in creative thinking. Leaders should be asking what kinds of work people thrive in, and how they can better enable people to do that work.

Workplaces should not eagerly hand off the challenging parts of thinking to AI. It is by encountering friction in their work that people learn resilience and gain skills in creative thinking.

Contrary to the vision of tech industrialists, people find the activity of thinking about how to solve problems intellectually satisfying. AI systems promise to help people think better and liberate them from burdensome mental tasks, when human cognition is not in need of a better thinking apparatus. It is the industrialization of work that has impeded human thinking. The efficient organization forces the human mind to fit all its ideas into a linear, step-by-step mode, and increasingly does away with any space for the free flow of ideas or immersive work. It does not matter who you are, or how you get work done. We are all working under a systematization of thought that is shallow, fast, repetitive, and productive, but not one that is morally or intellectually satisfying. For work to be meaningful, it has to allow space within organizational structures for people to engage in unimpeded, free-flowing, immersive thinking about how to solve a problem.

Good work will allow people to thrive and find meaning in what they do. People need to feel like they are contributing a tangible good to society, but they also need to encounter challenges in their work that push them to think creatively. The use of AI will make it easy to go through life without giving deep thought to anything. Growth, improved skill, and maturity cannot happen without some form of adversity and mystery. Human-AI collaboration will make workplaces more organized and efficient, but at the cost of the kinds of work that people find most fulfilling and formative.

Photo by Cash Macanaya on Unsplash.