The Glitchatorio

Witch of Glitch

30-minute introductions to some of the trickiest issues around AI today, such as:  - The alignment problem - Questions of LLM consciousness - Chain-of-thought and monitorability - Scheming and hallucinations The Glitchatorio is a podcast about the aspects of AI that don't fit into standard narratives about superintelligence or technology-as-destiny. We look into the failure modes, emergent mysteries and unexpected behaviors of artificial intelligence that baffle even the experts. You'll hear from technical researchers, data scientists and machine learning experts, as well as psychologists, philosophers and others whose work intersects with AI. Most Glitchatorio episodes follow the standard podcast interview format. Sometimes these episodes alternate with fictional audio skits or personal voice notes. The voices, music and audio effects you hear on The Glitchatorio are all recorded or composed by the Witch of Glitch; they are not AI-generated. 

  1. AI & Mental Health

    MAY 4

    AI & Mental Health

    Could AI address the global mental health crisis at scale? And what are the risks and unknowns that go along with that? These are the questions being investigated by a working group called AIMHI (https://forum.effectivealtruism.org/posts/MrFBezseyfnQd9XmJ/seeking-feedback-an-initiative-on-ai-mental-health-and). In this episode, I talk to four members of the group about their field research as well as the mental health chatbot they're developing (https://stillwater.coach/), whose focus is on serving populations with severe mental healthcare shortages (https://impartial-priorities.org/p/ai-mental-health-chatbots-for-low). Find out more about Effective Mental Health: https://effectivementalhealth.comJoin one of AIMHI's weekly coworking sessions: https://luma.com/calendar/cal-JNJlcdItDuFEFcnRead about the project's theory of change:  https://impartial-priorities.org/p/breaking-the-cycle-of-trauma-and

    36 min
  2. 2 AIs Take A Session (Fiction)

    APR 13 ·  BONUS

    2 AIs Take A Session (Fiction)

    What if AIs went to therapy? Would it help them to become "fitter, happier, more productive" ? (in the words of the old Radiohead song) Or would they take it as a novel type of evaluation (and maybe that's what it really is)? Note: this episode was written and recorded in November 2025, five months before the release of the Mythos Preview system card that mentions Claude's session with a human psychiatrist in the "Model welfare" section. So as weird as this episode might seem, the truth is actually stranger. https://www-cdn.anthropic.com/8b8380204f74670be75e81c820ca8dda846ab289.pdf  (See page 180 for the psychiatrist's report)

    8 min
  3. You Be The Judge

    MAR 30

    You Be The Judge

    Can we trust AI to keep AI honest? Having a human in the loop is already more illusion than reality, as the task of checking and overseeing LLM outputs is increasingly assigned to other LLMs. The problem is that these LLM judges tend to be biased in favor of the answers they generate themselves — even when the answers are wrong. To understand why this is, and what we can do about it, listen to my conversation with AI safety researcher Taslim Mahbub. We'll talk about his research into self-preference bias, the surprising results of his experiments and some potential mitigation strategies, as outlined in this post on mitigating collusive self-preference: https://www.lesswrong.com/posts/nB7kAf8c4tvnvZ4u3/mitigating-collusive-self-preference-by-redaction-and-2 and this paper on mitigating self-preference through authorship obfuscation: https://arxiv.org/abs/2512.05379 As a bonus, if you're interested in Taslim's earlier research on using machine learning in service of biodiversity monitoring, here's the abstract of his paper on convolutional neural networks (CNN) for identifying bat species: https://ieeexplore.ieee.org/document/9311084

    22 min
  4. The Scratchpad Monologues (CoT part 2)

    MAR 16

    The Scratchpad Monologues (CoT part 2)

    If chain of thought is a model "thinking aloud" to itself, then why does it express doubt, frustration or suspicion about the problems it's solving, sometimes for pages and pages of its scratchpad? And what does chain of thought mean for AI safety? We'll hear from Julian Schulz, a researcher who's studying encoded reasoning in large language models, about where the opportunities, risks and weirdness lie in chain of thought. Here are some links to his research: On a model jailbreaking its monitor: https://www.lesswrong.com/posts/szyZi5d4febZZSiq3/monitor-jailbreaking-evading-chain-of-thought-monitoringA roadmap for safety cases based on CoT: https://arxiv.org/html/2510.19476v1#S1His posts on Less Wrong: https://www.lesswrong.com/users/wuschel-schulzSome of the other papers we discussed include: On the biology of a large language model: https://transformer-circuits.pub/2025/attribution-graphs/biology.htmlMonitoring reasoning models for misbehavior and the risks of promoting obfuscation: https://arxiv.org/pdf/2503.11926How steganography comes about: https://arxiv.org/pdf/2506.01926Assuring agent safety evals by analysing transcripts (with excerpts from weird monologues): https://www.alignmentforum.org/posts/e8nMZewwonifENQYB/assuring-agent-safety-evaluations-by-analysing-transcriptsStress-testing deliberative misalignment: https://www.apolloresearch.ai/research/stress-testing-deliberative-alignment-for-anti-scheming-training/And the "watchers" CoT snippet from the paper above:  https://www.antischeming.ai/snippets#using-non-standard-language

    46 min
  5. Chain of Thought 101

    MAR 2

    Chain of Thought 101

    "Think step by step."  Although a simple technique in itself, the problems that chain-of-thought reasoning (CoT) addresses are complex, ranging from the specific issue of hallucinations to the general lack of explainability of AI (both in terms of understanding how it works as well as fixing things that go wrong). We'll hear from data scientist Afia Ibnath on the basics of CoT, how it can be used to evaluate the faithfulness of LLM responses, and her experiences of using it in a business context. Check out Afia's portfolio on Github: https://afiai14.github.io/ Here's the Anthropic paper we discussed, which outlines that reasoning models are often unfaithful in their CoT: https://www.anthropic.com/research/reasoning-models-dont-say-think For a concise definition of how faithfulness is calculated, see this article: https://www.ibm.com/docs/en/watsonx/saas?topic=metrics-faithfulness

    21 min
  6. Reading the Mind of AI

    FEB 16

    Reading the Mind of AI

    What if we could figure out how large language models really work by getting inside their "heads"? While possible, it relies on a a controversial technique called mechanistic interpretability ("mech interp" ), also known as the neuroscience of AI.   In this episode, Ihor Kendiukhov — lead researcher at SPAR, a research programme for AI risks —  explains mech interp in laypersons terms, and what it's currently able to reveal about the thinking processes of AIs.  We also talk about why mech interp has charted an unusually emotional course in AI research over the past few years, from physicists falling in love with it to prominent AI safety figures throwing shade on it, and where it might be headed next. Some of the papers and announcements referenced in this episode include: Golden Gate Claude: https://www.anthropic.com/news/golden-gate-claude And the excited announcement about mind-mapping that preceded it: https://www.anthropic.com/news/golden-gate-claudeAn example of recent criticism of mech interp: https://ai-frontiers.org/articles/the-misguided-quest-for-mechanistic-ai-interpretability

    26 min
  7. Agent Learn

    FEB 2

    Agent Learn

    Continual learning is a hot topic in early 2026, in part because it holds out the possibility for AI to become autonomous in its own growth and development. Meanwhile, AI agents are already showing us what autonomous behavior can look like. Putting the two together — i.e. agents that learn like humans do, without humans being involved — has serious implications for safety. In this episode, we'll hear from researcher Rohan Subramani (https://rohansubramani.github.io/home/) about different ways that AI agents could learn continually, along with ideas for making it safer.  Find out more about Rohan's work with Aether, an independent LLM safety research group: https://aether-ai-research.org/#research

    28 min
  8. 5 Big Questions

    JAN 19

    5 Big Questions

    Is AI still an experimental technology? What would real alignment look like? What are the key pro & contra philosophical views on AI consciousness? How would an AGI economy work? And finally, how can we make sure AI goes well for animals?In this episode, we're listening to unreleased material from previous episodes (featuring short takes on each of these questions from the following guests, in the same order as above: Ihor Kendiukhov, AI safety researcher - "What We Want"Scott Blain, computational neuroscientist - "Dreaming or Scheming"Jakub Mihalik, philosopher - "What it's like to be an AI"Lili M., AI tool tester - "Who's the tool?"Max Taylor, animal charity researcher - "Animal in the Loop"Plus some new music !

    12 min
See All (19)

Trailer

Ratings & Reviews

5
out of 5
2 Ratings

About

30-minute introductions to some of the trickiest issues around AI today, such as:  - The alignment problem - Questions of LLM consciousness - Chain-of-thought and monitorability - Scheming and hallucinations The Glitchatorio is a podcast about the aspects of AI that don't fit into standard narratives about superintelligence or technology-as-destiny. We look into the failure modes, emergent mysteries and unexpected behaviors of artificial intelligence that baffle even the experts. You'll hear from technical researchers, data scientists and machine learning experts, as well as psychologists, philosophers and others whose work intersects with AI. Most Glitchatorio episodes follow the standard podcast interview format. Sometimes these episodes alternate with fictional audio skits or personal voice notes. The voices, music and audio effects you hear on The Glitchatorio are all recorded or composed by the Witch of Glitch; they are not AI-generated. 

Information

  • Creator
    Witch of Glitch
  • Years Active
    2025 - 2026
  • Episodes
    19
  • Rating
    Clean
  • Copyright
    © 2026 The Glitchatorio
  • Show Website
    The Glitchatorio

You Might Also Like