Dedicated to liberation in all its forms, Deconstructing Yourself is passionate about fearlessly investigating, attempting, and questioning all things to do with awakening, meditation, mindfulness, brain hacking, consciousness, neurofeedback, and more. more
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Host Michael Taft talks with teacher Shinzen Young about Shinzen's decades-long dream of computer-based meditation instruction, his current creation of a rule-based, expert system based on Artificial Intelligence, the upcoming major upheavals in scie... more
Host Michael Taft speaks with author and professor Jeffrey Kripal about his early aspiration to be a Benedictine monk, the prophetic dimensions of the humanities, the sudden conversion, or "flip," into a weirder worldview experienced by some material... more
Host Michael Taft speaks with author and journalist Erik Davis about the power of partaking in the forbidden and the loss when formerly forbidden things become normalized, particularly in the case of psychedelics; Tantric and Christian modes of trans... more
I really enjoy this podcast because it covers one of the most fascinating aspects of the human experience (Buddhist meditation) in exquisite depth and from a place of obviously real personal experience, but it does so without any unnecessary obscurantism, mystifying religiosity, or new age hippie nonsense.
I’ve listened to every episode and sometimes revisit them. An intellectual and heart-felt experience.
Michael's experience, hosting style, and guests have taught me so much about consciousness, the human mind, and spiritual practice. I love Michael's selection of topics and also the depth of the discussions. Wonderful pod!
The mind predicts itself to predict the world. Mind Blown!
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Deconstructing Yourself launched 7 years ago and published 91 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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You can view podcasts similar to Deconstructing Yourself by exploring Rephonic's 3D interactive graph. This tool uses the data displayed on the 'Listeners Also Subscribed To' section of Apple Podcasts to visualise connections between shows.