{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Crazy Wisdom","title":"Can AI predict the 3rd order effects of its own intervention? - DT","html":"","width":"100%","height":180,"duration":3189,"description":" Robert DT on twitter: @DeeperThrill Doctorate on biomedical engineering with a focus on AI Entrepreneur building biomedical systems with AI specifically; medical imaging The conversation centers on the role of artificial intelligence (AI) in medical imaging, with an emphasis on computer vision and the utilization of existing imaging algorithms. Transformers, a type of deep learning model, are discussed for their unique self-attention mechanism and applications in natural language processing and computer vision. The talk pivots to data cleaning, specifically anonymization and safeguarding personal identifiers in the context of healthcare. Questions arise about data storage in healthcare facilities and the process of transferring it to the cloud. The conversation broadens to encompass AI's predictive capabilities and inherent risks, including the possibility of AI predicting third-order effects of its own interventions and concerns about excessive trust in AI predictions. The potential of AI in genetic engineering surfaces, particularly regarding CRISPR technology and nanobots. The conversation explores the benefits and risks of such advancements, including the revival of extinct plants and emergence of new diseases. Finally, the conversation shifts to societal implications of AI, including job displacement, the emergence of an attention economy, and the prospects of decentralized AI. The importance of understanding the limits of AI is underscored.   Show notes We need to examine what's currently happening in the field of AI, particularly in relation to medical imaging. This involves an exploration of computer vision technologies and how pre-existing imaging algorithms are being applied. We should discuss the concept of a \"transformer\" in the context of artificial intelligence. A critical part of working with AI is data cleaning. This includes the process of anonymization, ensuring that we only use the person's image and not any identifiable data like...","thumbnail_url":"https://img.transistorcdn.com/UZbrDrlO5VTfDNcq188THwbv0T09vcmLyzx3BcPI9bs/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS81Y2Rj/OGFiMTYyMGFkNTM5/N2NjOWI2MWM5YzQ1/YTc2Ny5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}