Leaderboard

Thinking back on what I would've benefited from the most while growing up in an underserved community, neuroscience outreach workshops and lab tours would've been the most helpful. I believe hands-on experiences are the best at demystifying neuroscience in the younger population and sparking curiosity in the older population as well. The workshops could be, for example, visiting a classroom or community center, guiding the participants through brain dissections and explaining the different structures along with their function. Lab tours are also beneficial as they help students envision what an academic career in neuroscience would be like, and allow for the older population to get a better understanding of how experiments are done. As Hugo rightly pointed out, accessibility is key. Explaining concepts without overwhelming jargon is essential for maintaining the attention of non-scientists and maximizing understanding of the concepts being explained. By making neuroscience easy to understand and relatable, we can further its dissemination.

Neuroglionanobots… a pretty cool name, right? In the past, I considered myself a huge fan of IA, however, I didn’t consider how much AI could impact our work as scientists. I didn’t consider how many human activities can be affected by this new way of getting, organizing, and managing information. However, there are dark paths in which we need to be careful. The other day I saw a Facebook post in which a young fella showed how to do a Facebook place to get money. This guy showed how the AI was capable of choosing the best topic (health and self-care in this example), and the AI was capable of creating evidence that supports the contents of the page and creating smart quotes or highlights to get attention. At the end, this guy looks at the camera, so proud of his “work” and says that all this work was done in minutes thanks to the AI. So many problems in that post, in the first instance, one guy without any kind of preparation in health, medicine, pharmacy, etc. can do a place to advise on self-care and nutrition; secondly, nobody can corroborate the information because there is no clear how the IA took the information from the web; in third place, where is the ethics of doing in that way?; I can continue, but I believe that my point is out there. The IA feeds itself from the entrances that we do regularly, in the form of papers, books, blogs, comments, etc. but if we continuously use it to produce the products used for their feedback, then what??? Did you see the problem??? In the long term, the IA could be fed in a loop without entrance from the exterior… I know that I may be Im overreacting, but the truth is that we need laws to regulate the use of AI; we need to incorporate ethics in this discussion and we need to show to the new generations the implications of the misuse of AI. Long Live and Prosper humans

This is a great question to consider and discuss, because AI has the potential to exacerbate the existing rigor and reproducibility crisis, or to ameliorate it. As a contractor doing Program Development at NIA, I work on the Alzheimer's Preclinical Efficacy Database, or AlzPED (https://alzped.nia.nih.gov/) and analysis of publications in the field of testing Alzheimer's therapeutics in animal models shows the trends of poor rigor and reporting practices that are not getting better over time (atleast not fast enough). A crucial aspect of AI/ML models is that junk-in means junk-out - that is, the integrity of the data that models are trained on will dictate the utility and validity of these models. In considering how AI may intersect with rigor and reproducibility - it does come down to how scientists may use any other tool. Researchers, journals, non-profits, and funding agencies need to work to improve the rigor and reproducibility crisis, and as suggested previously, develop best practices, standards, and accountability measures for AI in parallel.