Background: The story begins! This poster was inspired by these 2012 remarks about medical jargon by the then University of Alberta Dean of Science Jonathan Schaeffer explaining how jargon influenced him to become a computing scientist rather than a physician. “I read the papers and they were all full of this jargon. I don’t want to offend anyone, but there is a lot of jargon in medicine. And it wasn’t fun for me".  Potentially now everyone with a large language model AI app on their cell phone has access to quality medical information, but there needs to be an effort to reduce medical jargon to make it useful. This common language will also have the effect of merging large medical challenges with large challenges of humanity in general. In all the individual great challenges of life it helps to know what the long range plan is and what model one is aiming for. In xenotransplantation - pig to human transplants - if one follows Einstein’s advice to keep things “as simple as possible, but not simpler” then one opts for the three gene edit pig in the human decedent model without bilateral nephrectomy. However, simplicity is best only for the overall design of the experiment. For analysis the opposite is true, the Tom Sawyer “as complicated as possible” deep phenotyping approach to the immune system is best to detect even the most subtle signs of rejection, so that immunosuppression can be optimized. In immunosuppression planning, artificial intelligence analysis can be employed and there again the more nuanced and multifaceted it is the better. iBox analysis (Loupy et al.) is similarly complex and benefits from that complexity.

 

Methods:  It is important to note that this whole plan can work without specialized medical AI models for the 24 individual challenges. The medical insights noted in the recent Eric Topol video are from the regular model of ChatGPT everyone is using. If one can attain agreement on these parameters for xenotransplantation, then this same general approach may be used for all the other 23 big challenges of humanity in the all inclusive list, a concept first suggested by computing scientist Marcus Hutter, described at the beginning of this recent video:  1. Human aggression, 2. Nuclear war, 3. Climate emergency, 4. Systemic racism, 5. Pandemics, 6. Neocolonialism, 7.  AI alignment, 8. Energy, 9. Avatars, 10. Water scarcity, 11. Asteroids, 12. Nanotechnology, 13. Biodiversity, 14. Environment, 15. Resource depletion, 16. Solar winds, 17. Behavioural biology, 18. Financial crisis, 19. Genetic engineering, 20. Ideology, 21. Complexity fragility, 22. Unknown unknowns, 23. Other. Overall one can imagine humanity solving many of these individual challenges and aiming toward an equitable near Star Trek world. Gene Roddenberry would be proud! 

 

Results: At the January 25-26, 2024 AST Controversies Conference on Ethics in Xenotransplantation, and the planning meetings before that, we came up with a six-month or longer "low risk time travel" plan for the conference, where we start writing a white paper document in January 2024 predicting the situation in July 2024 (or later) when we finish the white paper and make it public. It is "low risk time travel"! We think nothing has ever been written with a time travel plan like that and it adds very productive tension to the writing process, invigorating it, including the current moment. In the age of AI much more progress can be made in six months than usually happens in that time period, it is like having a very smart assistant, smarter than anyone you have worked with before. That AI speeding up effect is there even without a custom made AI component of the project. That is why the time traveling idea works, the amount of idea generation in six months is much greater than it used to be before AI. It is no longer "just six months." Now it is six months with two exclamation points: "six months!!" (Or longer!!) Please complete the five question survey on ethics of xenotransplantation we have constructed.

 

Conclusions: Successful models require the right mixture of simplicity and purposeful complexity. Time is kidney (Figure at top right) , and artificial intelligence alters time in many ways, speeds up progress and life itself. So it is natural that AI will positively impact kidney, transplant medicine, and xenotransplantation profoundly. Basic goodness of human beings (Figure at top left)  is something we have to work on, but can emerge more easily under the influence of AI, QR code for accessing hyperlinks and images.

 

Elimination of medical jargon and reaching out for opinions beyond the medical sphere results in input like this essay from Memorial University and Portage College Classicist Kevin Solez on Contemplating the Pig-Man: Intuitions of our Shared Nature

 

If you find this poster text persuasive, remember that ironically persuasion is one of the dangers of AI, that it can convince you to do bad things, but it can also persuade you to do good things, and that good will likely overwhelm the bad. This new video from late December 2023 talks about the risk of persuasion for AI at about minute 20. So that is another example of our poster being self referential. If our poster is convincing-persuasive then it is a kind of example of the risk of AI persuasion which is the most fascinating example of AI risk so far! And in our case more good than bad. 

 

OpenAI CEO Sam Altman's idea on how the benefits of AGI will be distributed to every person on earth: "One 8 billionth of the money from AGI, but also one 8 billionth ownership of the system, and one 8 billionth of the voting rights on how the AGi is used. The better the AGI gets the more your little one billionth ownership is worth to you." From AGI Before 2026? Sam Altman & Max Tegmark on Humanity's Greatest Challenge  

 

"Ideas ahead of their time" will likely become mainstream in 2024 and 2025. Five years ago Kim Solez applied for a high profile editorship. He was told that he was strongly supported by the young people on the board, and if he keeps applying for such positions he would eventually be successful as the older people rotate off the board. There is also this line from a recent reference letter: "The more junior members will enjoy Kim’s vision."

 

GPT5 and beyond can accurately predict the future and greatly stimulate innovation "ideas ahead of their time". One can imagine a New Banff Classification of Xenotransplant Pathology this decade, but also New Banff Classifications of Tissue Engineering Pathology and Bioengineered Organ Pathology in future decades, innovations that would not have been possible in our lifetime if we relied on human creativity alone, but that can easily be enabled in the future with humans and machines working together. Similar very impactful innovations will affect the other 23 big challenges of humanity making for a great future!

 

Abstract keywords: medical jargon, pig-to-human transplants, xenotransplantation, artificial intelligence, big challenges of humanity, accessible future, simplicity, complexity, self-referential song lyrics, Albert Einstein, Mark Twain, Gene Roddenberry, QR code, AST Controversies Conference, Ethics in Xenotransplantation, optimism about the future with AI, New Banff Classifications for the pathology of xenotransplants, stem cell generated organs, and bioartificial organs, Accurate predictions of the future