Many meeting planners are already aware of artificial intelligence’s presence in virtual events, where the technology can be used to transcribe speech into text, create summaries for the different topics addressed, and deliver next-step action items.
But in a recent Harvard Business Review article by Dash Bibhudatta, principal of Infinite Possibilities, a generative-A.I. developer for companies, he notes that “in the near future, [online] meetings will offer personalized content and promote active learning, while also serving as a guardian against bias.”
Bibhudatta says that some of the capabilities he envisions are already being tested, while others are common in other generative-A.I. systems and should be available for virtual-meeting use within several months to a few years.
For his prediction about content being personalized for each participant, Bibhudatta says that it should soon be possible for A.I. to create different narratives almost instantly for each content segment in a meeting. For instance, participants could be sent to breakout rooms they feel are most aligned with their learning styles: content presented as a causality tree for visual learners, as a set of hierarchical notes for read/write learners, or as an audio version for auditory learners. A.I. tools, he says, will also be able to detect and capture standout moments from audio and video feeds of meetings and make them available for distribution to the participants and other colleagues based on their specific interests.
When it comes to active learning, Bibhudatta predicts that generative A.I. will soon be able to provide real-time feedback on the effectiveness of an online session’s content and format by continuously analyzing its dialogue and scoring it on the basis of engagement and other factors. “These can be used to encourage meeting leaders to improve future sessions,” he says.
However, could such a feature alter how participants choose to exchange ideas and opinions, affecting the quality of interaction because they know their communication is being judged in real time?
There's More to Consider
If that question seems like a leap too far, consider this feature that Bibhudatta believes will become available before long: A.I. will analyze virtual-meeting interactions, including spoken words and observed behaviors, to identify for the human-resources team “potential hot spots where biases may be present.”
Further, A.I. will be able to “detect and address biases in real time; the software can be trained to respond based on the severity of the bias” by raising a warning in the chat window or, if necessary, by interrupting the meeting “in order to facilitate remediation strategies.” In fact, A.I will be able to “use direct quotes or video clips to illustrate specific instances.” Bibhudatta says that “the goal is not to shame or criticize, but to facilitate reflection and self-correction.”
On their face, such abilities seem beneficial. On the other hand, there is no way to predict the unintended consequences that could come from an automated H.R. representative—one that can monitor every participant at all times—being present in virtual meetings throughout an organization.
Further, it soon might not be too difficult to use A.I. to conduct the same activities during in-person events. As a result, each organization will have to make informed decisions on an ongoing basis regarding which new A.I. capabilities it will employ in both its virtual and in-person meetings.
