IMHER.net (“International Menstrual Hygiene Entrepreneurship Roundup) was created in a different time, in 2018: a time when information was much harder to find. As a result, many social entrepreneurs doing the work of menstrual hygiene management ended up reinventing wheels, and getting lost in questionable information. Some were even forced into paying predatory consultants “introduction fees” just to connect with other people like themselves doing similar work in their respective regions.
IMHER worked to minimize those information gathering costs for the many small-scale social good entrepreneurs around the world that it worked to serve. We leveraged the hard-charging intellect of Dartmouth undergraduates to do that work so that the people running menstrual hygiene organizations on the ground could more efficiently engage in their core mission of helping girls and women in their communities.
During the intervening years, however, artificial intelligence has eliminated most of that long-standing information gap. In the case of menstrual hygiene management, this is a very good development!
Because of this, as of early 2026, we stopped updating the core IMHER databases, and eventually, we will disable the site. In the meantime, we are leaving it up for people to us, with the caveat that users should do further searches to make sure they are drawing on the most recent information available.
Why was this decision made?
For one thing, A.I. has already taken the data that IMHER compiled. This happens to be the rare case where that unauthorized taking of intellectual property is an unequivocally positive outcome, given that the whole goal of IMHER was to make that information as widely available as possible. But still, having A.I. repackage our work, often without attribution, does not seem like a good use of volunteered human hours.
More generally, A.I. can do the work in minutes that amazing undergraduate research assistants took days or even weeks to compile, and a professor a good deal of time to manage beyond that. Again, while that dynamic of replacing human labor with computer labor may pose problems for individuals, the environment, and labor economics moving forward, this is also happens to be a case where this is a positive outcome for global understanding of menstrual hygiene work and options.
Finally, this has been a laborious undertaking. It increased the knowledge and management skills of numerous Dartmouth undergraduates, many of whom have gone on to impressive research and social-good careers of their own. It was a truly incredibly successful experiment in student/faculty learning partnerships. But there are also many other ways to teach research skills to undergraduates, and the reality is that this is no longer the best way to add value to the work of MHM in such an information-rich era.
What does this mean for users?
While not everyone has access to top-level chatbots, everyone does at least have access to basic search engines that rely on A.I. In our tests, IMHER data permeates both search-engine searches and chatbox searches about global menstrual health and hygiene. Sometimes IMHER is explicitly acknowledged, and sometimes it is only discernable because we know our data and can find the original source of it. Either way, it is our understanding that because IMHER data will always be available in internet archives, our data will continue to appear in searches that draw on A.I. even long after we eventually disable the site entirely.
The key for users is in structuring search requests to be successful.
- Push for double checks and sources for information (and then check those original sources when possible). That is how we compiled IMHER, and it is the essence of any good research, including A.I.-driven research.
- Demand clarity. If responses don’t seem to make sense, push for explanations that do make sense. Sometimes lack of clarity means that you need to refine your search, and sometimes it means that A.I.. is steering you in the wrong direction. Push until you get clarity to figure out what is going on.
- Make sure the information you get has been fully updated. Remember that most IMHER data was only updated through early 2026 (and some was discontinued before that, including the research database and the calendar), so cover your bases and explicitly request additional information from all of the most recent years when it says it is using IMHER data.
- More generally, “triangulate” your requests: prompt it to go back in and check it against data from other available sources regardless of where the original data was front. This is key for any research task, whether conducted using A.I. or “Old School” methods like those we used to create IMHER. Information that has multiple reliable sources saying the same thing is far more reliable than any information that comes just from one source.
Best of luck to you with your work, and we hope this information proves to continue to be useful to you in some way – The IMHER Team