Fact Verification System

26:30 Brings up progress traps of this new technology

26:48

question How do we shift our (human being's) relationship with the rest of nature

27:00

metaphor - interspecies communications - AI can be compared to a new scientific instrument that extends our ability to see - We may discover that humanity is not the center of the universe

32:54

Question - Dr Doolittle question - Will we be able to talk to the animals? - Wittgenstein said no - Human Umwelt is different from others - but it may very well happen

34:54

species have culture - Marine mammals enact behavior similar to humans

• Unknown unknowns will likely move to known unknowns and to some known knowns

36:29

citizen science bioacoustic projects - audio moth - sound invisible to humans - ultrasonic sound - intrasonic sound - example - Amazonian river turtles have been found to have hundreds of unique vocalizations to call their baby turtles to safety out in the ocean

41:56

ocean habitat for whales - they can communicate across the entire ocean of the earth - They tell of a story of a whale in Bermuda can communicate with a whale in Ireland

43:00

progress trap - AI for interspecies communications - examples - examples - poachers or eco tourism can misuse

44:08

progress trap - AI for interspecies communications - policy

45:16

whale protection technology - Kim Davies - University of New Brunswick - aquatic drones - drones triangulate whales - ships must not get near 1,000 km of whales to avoid collision - Canadian government fines are up to 250,000 dollars for violating

50:35

environmental regulation - overhaul for the next century - instead of - treatment, we now have the data tools for - prevention

56:40 - ecological relationship - pollinators and plants have co-evolved

1:00:26

AI for interspecies communication - example - human cultural evolution controlling evolution of life on earth

for - Coscientist AI - Science AI - AI lab partner

Question: how does this notion of hypothesis space relate to causal inference and reasoning?

Wang et. al. "Scientific discovery in the age of artificial intelligence", Nature, 2023.

A paper about the current state of using AI/ML for scientific discovery, connected with the AI4Science workshops at major conferences.

(NOTE: since Springer/Nature don't allow public pdfs to be linked without a paywall, we can't use hypothesis directly on the pdf of the paper, this link is to the website version of it which is what we'll use to guide discussion during the reading group.)

[Nam, NeurIPS, 2022]. "Reinforcement Learning with State ObservationCosts in Action-Contingent Noiselessly Observable Markov Decision Processes"

Hoffman, R., Mueller, S., Klein, G., & Litman, J. (2021). Measuring Trust in the XAI Context. PsyArXiv. https://doi.org/10.31234/osf.io/e3kv9

ReconfigBehSci. (2020, November 9). Session 2: The policy interface followed with a really helpful presentation by Lindsey Pike, from Bristol, and then panel discussion with Mirjam Jenny (Robert Koch Insitute), Paulina Lang (UK Cabinet Office), Rachel McCloy (Reading Uni.), and Rene van Bavel (European Commission) [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1325795286065815552

AI and control of Covid-19 coronavirus. (n.d.). Artificial Intelligence. Retrieved October 15, 2020, from https://www.coe.int/en/web/artificial-intelligence/ai-and-control-of-covid-19-coronavirus

Yang, Scott Cheng-Hsin, Chirag Rank, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto. ‘Unifying Recommendation and Active Learning for Information Filtering and Recommender Systems’. Preprint. PsyArXiv, 25 August 2020. https://doi.org/10.31234/osf.io/jqa83.

Yang Yang: The Replicability of Scientific Findings Using Human and Machine Intelligence (Video). Metascience 2019 Symposium. https://www.metascience2019.org/presentations/yang-yang/

Yang, Y., Youyou, W., & Uzzi, B. (2020). Estimating the deep replicability of scientific findings using human and artificial intelligence. Proceedings of the National Academy of Sciences, 117(20), 10762–10768. https://doi.org/10.1073/pnas.1909046117

Hope, T., Borchardt, J., Portenoy, J., Vasan, K., & West, J. (2020, May 6). Exploring the COVID-19 network of scientific research with SciSight. Medium. https://medium.com/ai2-blog/exploring-the-covid-19-network-of-scientific-research-with-scisight-f75373320a8c

Sense Collective's Climate Tagger API and Pool Party Semantic Web plug-in are perfectly suited to support The Wilson Center's metadata schema project. Creating a common metadata schema that is used across multiple organizations working within the same domain, with similar (and overlapping) data and data types, is an essential step towards realizing collective intelligence. There is significant redundancy that consumes limited resources as organizations often perform the same type of data structuring. Interoperability issues between organizations, their metadata semantics and serialization methods, prevent cumulative progress as a community. Sense Collective's MetaGrant program is working to provide a shared infastructure for NGO's and social impact investment funds and social impact bond programs to help rapidly improve the problems that are being solved by this awesome project of The Wilson Center. Now let's extend the coordinated metadata semantics to 1000 more organizations and incentivize the citizen science volunteers who make this possible, with a closer connection to the local benefits they produce through their efforts. With integration into Social impact Bond programs and public/private partnerships, we are able to incentivize collective action in ways that match the scope and scale of the problems we face.

Astrology proven by artificial intelligence.

http://psychsciencenotes.blogspot.com/p/about-us.html<br> Psychologists Andrew Wilson and Sabrina Golonka