Künstliche Intelligenz – Der vorhersagbare Mensch

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.

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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


24. 
    

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/