One thing I love about conversations (real, honest-to-goodness conversations between real, actual people) is that they don’t ever end — not even when one or both parties stop talking.
When people talk with one another, when we share and discuss ideas, there is a transfer of energy that takes place — whether the people involved in that conversation intend for it to happen or not. Energy from the conversation doesn’t disappear or go back where it came from once the conversation stops. The energy — coming from the actual words we speak, our intention and our tone, and the impact we have on one another — is in motion.
A little while ago, I was speaking with a professional in a university setting, and they were lamenting about how their small department has been having an increasingly hard time reaching a consensus when it comes to making critical office decisions, sticking to various protocols, and that there seem to be new intradepartmental conflicts popping up every day while older conflicts remain unresolved.
When the topic of our conversation shifted to AI, this person shared that they are generally cautious about using AI but use some AI tools at work. They stated that they use AI tools to “clean up” or “polish” their emails or “adjust the tone” in their communication with coworkers. The believed that AI was useful and making them a more effective communicator.
(You see it, right??)
I then asked this person if they knew whether any of their department colleagues might be using similar AI tools to communicate as well. They weren’t sure, but said they thought it was possible.
(And then, they began to see it as well.)
Instead of these coworkers communicating authentically in ways that genuinely expressed what they really think and feel and want to accomplish (even if the communication might contain an error or two) they are sending “cleaned up” and “neatly-wrapped” versions of their ideas, ones that have been “adjusted for tone.” We then discussed how these AI-modified (or perhaps entirely AI-generated?) messages simply aren’t landing the same way their original message would and are diluting some of the essential matter from the original messages, which means they are not being responded to as urgently, and may or may not be taken as seriously at all, and so on. After our conversation, this person said they would rethink how they are using AI in future communications with their team.
Around the same time, I had another conversation with a school administrator about students using generative AI. I had asked this person — from a place of genuine curiosity — about the policy they were creating for using generative AI with students and why they thought such young students should be using generative AI and/or be exposed to AI-generated materials. I was especially curious, because large school districts (like New York City and Los Angeles) had recently put a pause or ban on students using AI at all. I was curious to learn why this particular administrator was determined to go in a different direction.
The administrator quickly compared generative AI to many other technology tools that have been introduced for use in schools over the years, like Google Docs and speech-to-text applications, and declared that as educators they believed we should educate.
Right. OK. Me too.
As an educator, I also believe we should question the resources we use with our students, what exactly they will be learning as a result of using them, and if there are any negative effects that may arise as a result of using them.
I found myself trying to explain the differences between Google Docs as they were first introduced and the generative AI we have today and then trying to help this person understand why I was asking my question in the first place; I was hopeful they would see that I, too, believe in progressive educational practices and that we were likely and ultimately sitting on the same side of that particular table — but generative AI is different.
I then shared a personal anecdote about receiving AI generated material from professional adults and how it raises some red flags of concern for me, thinking that as a professional educator they, too, may have had similar experiences, however, the person quickly and dismissively retorted, “Well, that’s you.”
This school administrator didn’t want to hear what the red flags were for me or why I felt that way; they only wanted to defend their point of view. So, while I knew this particular conversation wasn’t going to go any further, I also knew the energy from this conversation was now very much in motion.
I kept wondering, is it just me?
Could I be the only person who isn’t using AI to “clean up” emails?
Could I be the only person who questions the professionalism, the intentions, the abilities and capabilities, the knowledge, or how trustworthy someone is when they attempt to pass off AI generated content as their own?
Did the rest of the world all jump ahead to a place in time where professionals don’t need to think for themselves at work anymore, where we will no longer expect students to think anymore, where we blindly generate and accept AI-created content without needing to know anything about the source, the creator, the purpose, or the validity?
Are we all just supposed to assume and accept that everything we see and read is AI generated now — and are we supposed to be OK with that?
Thankfully, no.
There are plenty of other people who are currently questioning and cautioning others about the impact generative AI is having in various industries.
It’s not just me.
I came across the article, I banned my employees from using AI — they think it makes them look clever, by MaryLou Costa, and in it, James Cobb, CEO of Crowd Connected, is quoted as telling his employees, “I don’t want to end up with my AI agent talking to someone else’s AI agent. If I want an update on what’s happening, I want to hear from you. I don’t want to hear AI.” After noticing that his employees were still using AI for their internal communications, even after imposing the ban, he said, “If you allow AI to write something and then think you’re going to use that as a starting point and human‑edit it, it never ends up that way, because AI’s fingerprints are always there.”
(This idea of one AI agent talking to another AI agent immediately reminded me of that university employee’s dilemma from the beginning of this post — so, I made sure to go back and share the article with them.)
Costa goes on to explain two terms: “botsitting” and “botshitting,” and I am grateful to have these new (to me) vocabulary words for future conversations about the impact that generative AI has on us.
“Botsitting” is defined as “the time workers are increasingly spending making AI generated content usable.”
“Botshitting” is defined as “when workers distribute AI generated work without checking they actually understand it themselves – the next evolution of AI slop.”
Basically, if you are using generative AI you are likely spending your time doing one or the other — or both. Is “excellent botsitter” something that we want to put on our CVs and resumes? Is botsitting and botshitting really what we want our children to be spending their time on in school?
I’ve already shared the article with some family and close friends. If you haven’t read it yet, please do.
More observations, more studies, more articles, more conversations to come…