We're doomed we're saved #7

Show notes

GERMAN EPISODE Künstliche Intelligenz könnte dabei helfen, Krankheiten zu erkennen und zu heilen, Ärzten eine schnellere oder genauere Diagnose ermöglichen, und den Prozess der Arzneimittelentwicklung effizienter, kostengünstiger und erfolgreicher machen. Gleichzeitig wirft die Verwendung von Künstlicher Intelligenz im medizinischen Bereich schwierige ethische Fragen auf. Algorithmen, die Parameter wie elektronische Patientenakten, genetische Analysen oder Marker psychiatrischer Erkrankungen zur Vorhersage menschlicher Gesundheit nutzen könnten inhärente Bias kodieren und für unethische Fragestellungen verwendet werden. In Folge 7 von We’re doomed, we’re saved besprechen Louise von Stechow und Andreas Horchler die positiven und negativen Aspekte von Künstlicher Intelligenz im Bereich der Medizin und Pharmazeutischen Industrie.

Content and Editing: Louise von Stechow and Andreas Horchler

Disclaimer: Louise von Stechow, Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast.

Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow

Image: Merrit Thomas Via Unsplash

References: AI history

1. https://www.dataversity.net/brief-history-deep-learning/#
2. https://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/
3. https://www.livescience.com/47544-history-of-a-i-artificial-intelligence-infographic.html
4. https://sitn.hms.harvard.edu/special-edition-artificial-intelligence/
5. https://www.technologyreview.com/2016/11/10/156141/the-future-of-artificial-intelligence-and-cybernetics/
6. https://news.cornell.edu/stories/2019/09/professors-perceptron-paved-way-ai-60-years-too-soon Image recognition algorithms
7. https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30160-6/fulltext
8. https://www.bmj.com/company/newsroom/concerns-over-exaggerated-study-claims-of-ai-outperforming-doctors/
9. https://www.nature.com/articles/s41746-020-00324-0
10. https://www.sentisight.ai/the-use-of-ai-image-recognition-in-medicine/ Genomic analyses
11. https://www.genome.gov/human-genome-project/Timeline-of-Events
12. https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-019-0689-8 The electronic doctor
13. https://www.nytimes.com/2021/07/16/technology/what-happened-ibm-watson.html
14. https://erp.today/ai-in-healthcare-what-now-after-watson/
15. https://erp.today/cloud-healthcare-and-the-data-state-of-play/ Drug development
16. https://www.genengnews.com/artificial-intelligence/the-future-of-biotech-in-an-artificially-intelligent-world/
17. https://pharmaintelligence.informa.com/resources/product-content/2021-clinical-development-success-rates
18. https://www2.deloitte.com/content/dam/insights/us/articles/32961_intelligent-drug-discovery/DI_Intelligent-Drug-Discovery.pdf
19. https://www.globaldata.com/pharmaceutical-industry-continues-bet-big-ai/
20. https://www.europeanpharmaceuticalreview.com/news/112044/dsp-1181-drug-created-using-ai-enters-clinical-trials/
21. https://www.nature.com/articles/d41586-019-02871-3#ref-CR5
22. https://www.unlearn.ai/post/generating-digital-twins-with-multiple-sclerosis-using-probabilistic-neural-networks
23. https://themedicinemaker.com/discovery-development/intelligent-repurposing

Ethics of AI

1. http://www.bbc.com/future/story/20170307-the-ethical-challenge-facing-artificial-intelligence
2. https://intelligence.org/files/EthicsofAI.pdf
3. https://www.theatlantic.com/health/archive/2018/08/machine-learning-dermatology-skin-color/567619/