ChatGPT: Are you a Resister, Ignorer, Experimenter or a Reflector?
A Taxonomy of Responses to Generative AI
Categorizing Responses to Generative AI
I have been giving numerous talks to academics and business people on the impact of ChatGPT and other generative AI, explaining what it is, what it can do, its potential upside and downside, how it will change work & organizations and how to take advantage of it, either personally or organizationally. At the beginning I ask how many people use it daily, 2-3 times a week, have tried it at least once or have never tried it. Those that answer affirmatively with either of the first two responses I think of as frequent users and that runs in the ~20% range of the audience. Those that have tried it at least once tend to come in at ~50% and those that have never tried it are ~30%.
One thing that is interesting to me is that, while there is a higher usage response by younger people - e.g., university students - the majority of them don’t seem to be adopting it quickly either. This seems consistent with these data from YouGov here.
With the above in mind, it was interesting to watch a talk by Professor Christopher Capozzola from MIT on the impact of ChatGPT. In his speech he classifies professors into one of four groups;
those that resist the use of generative AI in their classrooms,
those that ignore its existence,
those that are experimenting with it and
those that are considering what is crucial for students to learn from an assignment and how generative AI should or should not be used to help them learn that subject.
I think the above taxonomy is also a useful way to think not just about professors but also about businesspeople and organizations, as I believe the same four categories can be applied with a little tweaking to these domains.
One can plot these groups as shown below, with generative AI usage on the X axis and consideration of its impact on the Y axis.
Ignorers, whether they are professors, knowledge workers or organizations, pretend nothing has changed. They don’t want to think about generative AI nor bother to use it, hoping it will either go away or not affect them.
Resistors at least have thought about how it might affect their classroom, profession or institution and have made a principled or logical decision to not use it. Professors might decide that students using Gen AI will keep them from gaining a deep understanding of a subject. Artists might feel that using Gen AI pollutes or devalues their craft. Organizational leaders might decide that the security or legal risks of Gen AI at this early stage outweigh the potential upside.
Experimenters are those that are playing with Gen AI to see how it can make them more impactful, enabling them to be more productive, creative, and knowledgeable. They understand that Gen AI gives them new abilities to create text, code, music, audio, video and ideas quickly and with ever improving quality.
Reflectors seek to explore how people, organizations and society may change over time as generative AI becomes more pervasive and powerful. They offer others glimpses into what the future might hold for us, both the positive and the negative. The size of this group is very small but their influence is outsized, as they shine a light on a path that other Reflectors and Experimenters can follow.
To have this insight, Reflectors also need to be Experimenters as well as being constantly engaging with other Reflectors to further develop their ideas about what lays ahead. Ethan Mollick and Nathan Labenz are both great examples of Reflectors.
How it might play out…
The likelihood of success that the “Ignore” strategy will work over the long term is obviously pretty low. While there is a small chance generative AI will go away or its impact very limited due to legal issues or costs, it’s foolish to bet the farm that that will happen. You’re really risking your job and not doing right by those that depend on you, whether it’s your students, your employer or your employees.
According to this new IBM study, “AI won’t replace people—but people who use AI will replace people who don’t.” This is something I and many others have been saying for months.
Resistance may work in the short term but over the long term it is not likely to be a feasible strategy. Professors who refuse to allow it in class will have to be constantly policing for it while other professors encourage their students to use it and prospective employers tell students they need to have Gen AI skills to get hired. Longer term, students entering college will have grown up with AI tutors like Khanmigo, the new tool for K-12 kids from Khan Academy. Eventually, these professors may have to acknowledge reality and give in.
The same is true for professionals and businesses. Google and Microsoft are putting Gen AI capabilities into software we use every day so it will be ubiquitous and also be secure. Those that use these tools will have significant productivity and creative advantages over those that don’t. In the end, Resistors will understand that they must follow the adage of, “if you can’t beat ‘em, join ‘em.”
Those individuals best positioned to thrive in the new world of generative AI are (big surprise) the Experimenters and the Reflectors. Both need to be supported leadership and will be key to moving their organizations through the experimentation and adoption of these tools. For organizations, individuals will be crucial in the following arenas;
Finding use cases for generative AI for themselves and the organization.
Educating others in how to use generative AI tools.
Developing a sound philosophy and policy for Gen AI use.
Participating in the creation of the organization’s Gen AI strategy and investment plan.
Organizationally, leaders who want their institution to gain competitive advantage must at a minimum find Experimenters and support them while encouraging as many others as possible to also to be Experimenters. Ethan Mollick, in his Substack piece, Detecting the Secret Cyborgs offers these three means of doing so.
Recognize that those experimenting and using generative AI may be anywhere in the organization. They could be in the upper echelons, middle management or lower level individual contributors. Encourage them to come forward and give them the training and tools they need to build their skills.
In addition to offering positive incentives to Experimenters, leaders must also reduce the risk and fear knowledge workers have that that their use of generative AI to be more productive will not create layoffs. Leaders can allay those concerns by encouraging workers to use Gen AI to eliminate boring tasks and also telling them there will be no layoffs are a result of Gen AI for a certain time period.
Finally, use the Experimenters to bring others along with them on the generative AI journey as well as recognizing and rewarding Experimenters for finding new use cases that make the firm more competitive.
Which are you?
Given you’re reading this I’m guessing you are either an Experimenter or a Reflector. That’s great. However, if you find yourself falling into either the Resistor or Ignorer category, now might be the time to rethink your strategy.