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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.

I'd like to raise 2 points for consideration and discussion of this topic. 1) I've learned a lot about neuroscience communication since the publication of my book, Baby Senses. I've been trying to learn from the artist and children's fiction writers communities how to make science more engaging. I often find that non-fiction can come across as dry and boring while fiction - even while being factual - can come across as enchanting and interesting. I've myself been using principles of story telling, art, and narrative creative non-fiction to get a lay audience interested in science, and have, for BAW 2024, used puppets to engage very young audiences in sensory neuroscience (in a collaborative project). 2) While communicating to communities traditionally under-represented in STEM and neuroscience, it is important to go in with a nuanced and considered approach. Once, when I was TAing a summer high school biology/histology class for first nations students during my Masters, I came out of the class thinking I had been incomprehensible. I kept attempting to make the session interactive and waiting for their response without understanding that culturally it is unusual for first nation communities to participate in interactions without "electing" a representative to speak for the group. This was very eye opening for me - when I read the teacher evaluations, the students still rated my class as one of the best they'd been to, which was completely contrary to my impressions. All this to say, when I approach neuroscience communication, I try to meet people where they are at and use a nuanced approach since minorities in science can feel easily discouraged from neuroscientific careers and a one-size-fits-all approach doesn't work.

I think there are 2 main ways to do this. The first is to create opportunities, from elementary school to the final years of graduation, integrating neuroscience into their lives and conveying the concept that neuroscience is not restricted to the laboratory or operating room. Neuroscience is all around us, it explains what we are! I think it should be taught like mathematics, geography, etc. I believe that also creating jobs and opportunities for employment, for studying at universities, is also a great idea, bringing the community together to take up positions, be interested in science, whether through extension courses. Regarding underserved communities, I think that outreach programs are vital. It is important that leaders in neuroscience, in the health area, educators, etc., get closer to vulnerable populations, going to these places, talking to people, understanding what they need, their desires, carrying out educational programs. Involving the leaders of these communities is a great strategy, and the experiences that can be shared are always rewarding. Many people need is just a chance for someone to believe in them, and if we have the chance to be this someone is just amazing

I think the general principle of scientific research must always be ethics, and the neuroscientist must keep this in mind. So, I cannot conceive of a world where neuroscience is not linked to ethics, even though I know that this is not always true. I believe that the full use of ChatGPT without it being only instrumental for ideas (or helping with creativity blocks - who hasn't never had them?) is wrong and it goes against the ethical principles of intellectual property or creativity, of expression of science as a whole. ChatGPT does not obey the rules of academia, and still does not obey the rules of science. That said, the reality is that ChatGTP , Leonardo and others are here to stay. And if so, we should see it naturally and as a sign of the cultural revolution and the passage of time. And better than anything else, Neuroscience aways had thrived in challenge times. We have all the tools to adapt, so neuroscience and neuroscientists will adapt to this new cultural and intellectual transformation.But we need to have rules and establish standards of conduct about the instrumental , not protagonist, use of artificial intelligence .We need to stablish good practices and make use of verification tools (like AI detector programs).There are already good artificial intelligence detectors and I believe that they may be useful for scientific websites and accontable neuroscience journals . ChatGTP is a cultural , intelectual and social transformation . And like everything in humankind history, we must learn to adapt in a good and ethical way. Neuroscientists can play an important role in this adaptation and ajust ChatGTP to this new world of us.