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The Machine Ethics podcast: Avoidable misery with Adam Braus

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19 January 2024



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Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology’s impact on society.

Avoidable misery with Adam Braus

This episode we’re chatting with Adam Braus about natural stupidity, natural intelligence, misericordianism and avoidable misery, the drowning child thought experiment, natural state of morality, Donald Trump bot, Asimov’s rules, human instincts, the positive outcomes of AI and more…

Listen to the episode here:

Adam Braus is a professor and polymath professional, author, and expert in the fields of ethics, education, and organizational management. He is a writer, speaker, teacher, podcaster, coach, and consultant. He lives in San Francisco, California. You can subscribe to his weekly podcast, find links to his books, or contact him via his website.


About The Machine Ethics podcast

This podcast was created and is run by Ben Byford and collaborators. The podcast, and other content was first created to extend Ben’s growing interest in both the AI domain and in the associated ethics. Over the last few years the podcast has grown into a place of discussion and dissemination of important ideas, not only in AI but in tech ethics generally. As the interviews unfold on they often veer into current affairs, the future of work, environmental issues, and more. Though the core is still AI and AI Ethics, we release content that is broader and therefore hopefully more useful to the general public and practitioners.

The hope for the podcast is for it to promote debate concerning technology and society, and to foster the production of technology (and in particular, decision making algorithms) that promote human ideals.

Join in the conversation by getting in touch via email here or following us on Twitter and Instagram.




The Machine Ethics Podcast




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