Framing Use: Managing technological symbolism
Emerging technologies carry multiple meanings - but early adopters can help others interpret their use.
I have answered about 150 variations of “What is your dissertation about?” over the past two years as I applied to jobs, bumped into colleagues, and attempted to explain to old friends why, yes, I was still in school. When I told people I study AI scheduling technologies, I’ve noticed people always have something to say. Some people want to share how excited they are for the innovation of AI and the new possibilities that it ushers. Others tell me about the futility of replacing any human judgement with AI (often accompanied by their story of Siri’s latest misinterpretation). And some times people share their concerns for how AI will shape privacy, justice, and labor.
I call people’s willingness to talk about AI the “AI Bump”- which means instead of people getting bored talking to me about my research after 30 seconds, they get bored talking to me about my research after 45 seconds. 150% increase, baby.
My interviews with users of scheduling technologies equipped with artificial intelligence (who are by far more interesting conversational partners than a stressed grad student) confirmed my “AI bump” theory. I learned that artificial intelligence means a lot of different things to different people - not only in terms of a classification of computational processes, but as a cultural symbol.
The users I interviewed certainly saw AI scheduling technologies in terms of what they could do, often citing these tools’ capabilities to “save time” and “help me get the administrative tasks done so I can focus on my real work” as huge draws. But users also talked about what their use of AI could symbolize to others, such as a “willingness to experiment with new technologies,” “technological savviness,” and “being on the cutting edge.” Users in my research often described themselves as the people who have always been willing to try a new tool and usually found themselves the first in their networks to adopt and embrace creative technological solutions. And a lot of the times, doing so reaped them big rewards, like the ability to grab the attention of top innovators and secure new tech-forward clients.
But users also talked about an important problem - not everyone with whom they worked shared the same meaning of these technologies. Users talked about how people often interpreted their use of any technology for scheduling as rude or impersonal and that their use of AI technologies in particular offended people like executive assistants when they perceived that their jobs were threatened by automation. And when I interviewed people who worked with users of AI scheduling technologies, I confirmed that not everyone shares technological optimism - people can interpret someone’s use of AI scheduling tools as an attempt to create distance or as a signal that the meeting isn’t all important to them.
The good news? Users said that they found ways to change others’ interpretations. Over and over again, users said that a best practice of using emerging technologies for scheduling was framing what the tool meant for others. Users talked about some different ways they did this. Here are a few of the most common:
Framing technology as mutually beneficial: Users said that explaining to their communication partners that the tool would help both of them find a good time to meet helped them use it more successfully.
Example: “We’re both really busy - why don’t we give this new tool a try so it can help us find a time that works for both of us?”
Offering a choice: Users said that explaining that experimenting with AI could be a fun experience and that they could always find an alternative to an AI scheduling tool also helped.
Example: “I’d love for you to try out this new scheduling tool and tell me what you think. But if it doesn’t work as you’d like it, let me know and I’m happy to step in and get this meeting scheduled myself.”
Affirming professional value: Users said that explaining that their use of the tool did not negate the value of others professionals (administrative and executive assistants or coordinators) could also be useful.
Example: “I really appreciate the work that executive assistants do for scheduling. If I was a bigger business and could afford to hire one, I would! But as a new freelancer, I tend to rely on tools like this to help me out.”
Through these framing practices, users could help assuage fears about emerging technologies and avoid being negatively judged for using them. So even though AI can mean a lot to different people, users can help steer their contacts’ interpretation through how they frame its meaning. And maybe some better framing will help this newly-minted PhD be a little more fun at parties too.
Are there other framing practices you’ve found helpful in deploying AI scheduling technologies? Has it ever gone awry? Tell us about it in the comments!