The most surprising bit of information I learned from this interview was that scientists would never ask patients who had their genes studied if they'd want to know their polygenic scores. Not only do these scientists take "refuge" (as De Vivo states) under the fact that they are just researchers, their abstinence from letting patients know raises some extremely interesting ethical questions that I've also studied in other neuroethics questions. For example, in GWAS testing there is polygenic score that predicts for how risky a person may be. Thus, should we base credit scores, which have historically disadvantaged communites without proper financial education throughout generations, off polygenic risk scores rather than our current faulty system? Of course, not everyone with a high polygenic risk score would go on to commit crime or have a low credit score, but the probability of it is higher than if you had just taken a random person out of the population. I would have pressed De Vivo and Kraft on their personal views on whether this information (polygenic risk scores, certain heightened traits) should be distributed or not. Their work is critical to these genes becoming a weapon for legitimate policymaking that can have massive implications on the real world so I believe they should at least address why they believe doing their work is overall worth researching. Perhaps the absence of knowledge in gene studies is consequentially better for our society. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612115/#:~:text=We%20define%20polygenic%20risk%20scores,from%20summary%20statistic%20GWAS%20data.

The most surprising piece of information I learned in the interview with Dan Kammen is that a number of oil companies, such as ExxonMobil, had been paying scientists to research on climate change only if the results had come out the way they wanted it to. I always knew the science on climate change had been heavily politicized but this specific example of companies distributing select information to “influence science” was especially alarming. Furthermore, I was also interested in how the costs of climate change have different effects on different geographic areas, and how that slows down progress on climate change. For example, coastal areas and already developed countries have more of an incentive to invest in carbon neutral technologies; thus, other countries and areas can free-ride these technologies and have less incentive to contribute as much. If given the opportunity to conduct the interview, I would have asked Dan Kammen is how we can make predictions, like simulations/models on climate change, less politicized. While I like how Ms. Goodman asked many questions that are practical rather than just scientific — like the psychology of climate change and how climate has to be more emphasized in the humanities as well — I would love to know Dan’s thoughts on how the accuracy of our models interplay with policymaking and the psychology of politics.