Massive Online Meetings (MOMs) have many new advantages but also many new tracking possibilities. Participants can potentially be tracked constantly through the whole duration of the event.
By Ferenc Borondics & Jesse McCrosky
The COVID-19 pandemic and our collective response has driven global change. Air and road traffic decreased, leading to a reduction in greenhouse gas emission to levels long lost in the records. Spain began a basic income trial intended to persist after the pandemic passes. Many office workers began to work from home, leading to a surge in online meetings. While many events, trade shows, and conferences were canceled or postponed, some organizations reacted with a new model inspired by the Massive Open Online Course (MOOC) approach, and took their events online. As a result, Massive Online Meetings, MOMs, were born. Now that the lockdown is ending, some things will return to the pre-COVID normal, while other changes will remain. Event organizers will consider the value of MOMs as they can save on expenses and, potentially capitalize on user data. As with many technologies, the innovation may outpace our ability to effectively regulate it, and the gap may lead to exploitation.
In a live meeting, the organizers’ ability to track participants is limited to registration data and perhaps scanning badges in some events. With online meetings, there are many new possibilities. Participants can potentially be tracked constantly though the entirety of the event. As well as the set of sessions that a participant chooses to view and perhaps the questions that participant asks, providers can potentially record and analyze the participants face through the webcam, monitoring attention, inferring emotion, and tracking gaze. Zoom, for example, has demonstrated the ability of attention span monitoring. Users were not happy about it and upon the uproar of their customer base they quickly disabled it. But there are many concerned about providers collecting and potentially exploiting this type of data. One example is from the book of Yuval Noah Harari, who picked Amazon’s Kindle as an example and wrote:
“If Kindle is upgraded with face recognition and biometric sensors, it can know what made you laugh, what made you sad and what made you angry. Soon, books will read you while you are reading them.” in his book Homo Deus: A Brief History of Tomorrow.
Online meetings involve cameras, microphones, and user interface interaction. These sources provide extremely rich sources of information for data mining. Collected data might be used for targeted advertising, sold to data exchanges, analyzed for competitive intelligence (are the employees of a particular company exceptionally interested in a particular development?), or other purposes.
Solved With A Click
MOMs can also bring benefits. Scientific conferences can be overwhelmingly large. In such a crowd it is hard to organize small meetings with the few people one would like to talk to, especially the stars of science. It is impossible to attend parallel sessions although overlapping talks might be interesting. Nothing is exactly on schedule, which adds more complexity to organize attendance. In MOMs this is all solved with a click. There is no running from one auditorium to another and waiting outside for the end of a talk to enter. Two parallel talks are no problem either. Everything is recorded and can be watched over and over again! This can also improve comprehension and retention for the audience. Speakers can enhance their presentation skills by rewatching their talks. Additionally, preventing travel for an event can have significant ecological benefits. Nature published a recent analysis of these.
A recent example of such a MOM is the CLEO 2020 conference that featured almost 20 000 registered people from 75 countries. This year online attendance was free, which is a generous offer for having access to more than 550 hours of high quality scientific content. For such a conference one must normally pay a pricey registration fee, airfare, and accommodation costs that quickly adds up to a small fortune. This is an especially important factor for countries or fields in which science is not well funded.
Cart Blanche to Your Data
The CLEO privacy policy does not appear to have been updated to explicitly tackle the complexities of online events. The policy allows them to “provide information to you about other relevant OSA programs and services based on your interests”, allowing targeted advertising of their own products and services as well as use data to “improve your online experience”, which is a sort of carte blanche – showing more useful third party ads could be considered to “improve your online experience”. They also state that they can “respond to a competent law enforcement body, regulatory, government agency, court or other third party where we believe disclosure is legally required; to exercise, establish or defend our legal rights; or to protect your vital interests or those of any person.” meaning that they can use a participant’s data against them in legal procedures!
Whether live or in the online space, collaboration is essential to scientific discovery and interaction is an absolute must in modern science. Conferences may return to physical spaces after the threat of COVID-19 has passed, but likely with an online component, which will enhance the experience and usability of scientific conference materials. The benefits and potential privacy threats of online meetings are likely to be something we will continue to explore and develop for a long time to come.
Also read this guide to ethical tools for online meetings
About the authors
Ferenc Borondics is a scientist with a PhD in Chemistry. He has been heading synchrotron infrared beamlines in the last decade in Canada and France. Previously, he was a postdoctoral fellow in the Lawrence Berkeley National Laboratory in CA, USA. Although his research focus is high-resolution infrared microscopy and materials science, recently he became interested in data science and machine learning in the natural sciences. He is one of the founders of Quasar (https://quasar.codes/) an open-source software for spectroscopy data analysis with ML tools.
Jesse McCrosky has been working in Data Science for over 10 years. Currently at Mozilla, he previously worked with Google, Statistics Canada, and a number of academic and government researchers as an independent statistical consultant. Inspired by his experience in the industry, Jesse’s research focuses on the ethical questions raised by new technologies and understanding the social consequences of their adoption. You can read more of his work at https://wrongbutuseful.com/ or follow him on Twitter.
Jesse and Ferenc have been collaborating on publications about the ethical use and potential issues of machine learning in a variety of aspects.
