Beth Morling is my friend and fellow author at W.W. Norton & Co. Recently, we thought of each other when a news story came out about the repatriation of the remains of 19 Black New Orleanians whose skulls were used for racist phrenology research in Germany in the 1880s. It made us think about the various forms that self-correction can take in science, as well as the importance of adhering to the scientific method.  Check it out here .

I know it is January 2025, but I want to write about something that happened during the Spring of 2024. I think it is a story about how it is never too late to do the right thing, making it great thing to think about here at the New Year. Data can't undo the past, but the way we manage it moving forward can provide the opportunity for some measure of equity. Back in May, professional baseball decided to include Negro League (NL), which existed from 2910 to 1948, baseball stats as part of Major League Baseball (MLB) stats. This is was done to allow for proper recognition of talented ML players. This changed some storied records for the league: https://www.mlb.com/news/stats-leaderboard-changes-negro-leagues-mlb This was a lot more than merging a couple of spreadsheets. As such, this story also serves as a lesson in data management and making desperate datasets the same. One that is a lot more moving than your typical story of data-cleaning. The following screenshots are from:  ...

"(Algorithms) are used so heavily, they don't just predict the future, they are the future." -Cathy O'Neil ^This quote from this NPR story made me punch the air in my little Subaru after dropping my kid off to school. What a great sentence. There are many great one-liners in this little five-minute review of algorithms. This NPR story by Dina Temple-Raston is a great primer for All The Ethical Issues Related To Algorithms, accessible to non- or novice-statisticians. It clocks in at just under five minutes, perfect as a discussion prompt or quick introduction to the topic. How to use in class: They talk about regression without ever saying "regression": "Algorithms use past patterns of success to predict the future." So, regression, right? Fancy regression, but that one line can take this fancy talk of algorithms and make it more applicable to your students. Sometimes, I feel like I'm just waving my hands when I try to explain thi...

So, this is a story of data mining and Mechanical Turk and data privacy and political campaigns. Lots of good stuff for class discussion about data privacy, applied use of data, etc..  It won't exactly teach your students how to ANOVA, but it is a good and timely discussion piece. Short version of the story: Ted Cruz's campaign hired a consulting firm (Strategic Communications Laboratories, SCL) to gather information about potential voters. They did so by using Amazon's Mechanical Turk to recruit participants. Participants were asked to complete a survey that would give SCL access to your Facebook account. SCL would then download all visible user information from you. And then they would download the same information FROM ALL OF YOUR FRIENDS who did not consent to be involved in the study. Some mTurk users claim this was a violation of Amazon's Terms of Service. This data was then used to create psychological profiles for campaigning purposes. Discussion pieces: ...

Alright. This teaching idea is pretty involved. It is bigger than any one instructor and requires interdepartmental effort as well as support from The Powers that Be at your university. The U.S. Holocaust Museum hosts a number of  traveling exhibits . One in particular, " Deadly Medicine: Creating the Master Race ", provides a great opportunity for the discussions of research ethics, the protection and treatment of human research subjects, and how science can be used to justify really horrible things. I am extraordinarily fortunate that Gannon University's Department of History (with assistance from our Honors program as well as College of the Humanities, Education, and Social Sciences) has worked hard to get this exhibit to our institution during the Fall 2015 semester. It is housed in our library through the end of October. How I used it in my class: My Honors Psychological Statistics class visited the exhibit prior to a discussion day about research ethics. In...

This obituary for Dr. Frances Oldham Kelsey that tells an important story about research ethics, pharmaceutical industries, and the importance of government oversight in the drug creation process ( .pdf here ). Dr. Kelsey, receiving the President's Award for Distinguished Federal Civilian Service (highest honor given to federal employees) Dr.  Kelsey was one of the first officials in the United States to notice (via data!) and raise concerns about thalidomide , the now infamous anti-nausea drug that causes terrible birth defects when administered to pregnant women. The drug was already being widely used throughout Europe, Canada, and the Middle East to treat morning sickness, but Dr. Kelsey refused to approve the drug for widespread use in the US (despite persistent efforts of Big Pharm to push the drug into the US market). Time proved Dr. Oldham Kelsey correct (clinical trials in the US went very poorly), and her persistence, data analysis, and ethics helped to limit the ...

Back in the day, I remember having to complete an online research ethics course in order to serve as an undergraduate research assistant at Penn State. I think that such training could be used as an exercise/assessment in a research methods class or an advanced statistics class. NOTE: These examples are sponsored by the American agencies and, thus, teach participants about American laws and rules. If you have information about similar training in other countries (or other free options for American researchers), please email me and I will add the link. Online Research Ethics Course from the U.S. Health and Human Service's Office of Research Integrity. Features: Six different learning modules, each with a quiz and certificate of completion. These sections include separate quizzes on the treatment of human and animal test subjects. Other portions also address ethical relationships between PIs and RAs and broader issues of professional responsibility when reporting results. ...

Pew Research went around the globe and asked folks in 40 different countries if a variety of different behaviors qualified as "Unacceptable", "Acceptable", or "Not a moral issue". See below for a broad summary of the findings. Summary of international morality data from Pew The data on this website is highly interactive...you can break down the data by specific behavior, by country, and also look at different regions of the world. This data is a good demonstration of why graphs are useful and engaging when presenting data to an audience. Here is a summary of the data from Pew.  It nicely describes global trends (extramarital affairs are largely viewed as unacceptable, and contraception is widely viewed as acceptable). How you could use this in class. 1) Comparison of different countries and beliefs about what is right, and what is wrong. Good for discussions about multiculturalism, social norms, normative behaviors, the influence of religion ...

This story describes a 1966 journal article that argues that signing an informed consent isn't the same as truly giving informed consent. I think this is a good example for the ethics section of a research methods class as it demonstrates some deeply unethical situations in which participants weren't able to give informed consent (prisoners, non-English speakers, etc.). Indeed, the context within which the informed consent is provided is very important. It also provides a historical context regarding the creation of Institutional Review Boards. The original 1966 article is here .