Into AI Safety

Andres Sepulveda Morales joins me to discuss his journey from three tech layoffs to founding Red Mage Creative and leading the Fort Collins chapter of the Rocky Mountain AI Interest Group (RMAIIG). We explore the current tech job market, AI anxiety in nonprofits, dark patterns in AI systems, and building inclusive tech communities that welcome diverse perspectives.Reach out to Andres on his LinkedIn, or check out the Red Mage Creative website!For any listeners in Colorado, consider attending an RMAIIG event: Boulder; Fort Collins(00:00) - Intro (01:04) - Andres' Journey (05:15) - Tech Layoff Cycle (26:12) - Why AI? (30:58) - What is Red Mage? (36:12) - AI as a Tool (41:55) - AInxiety (47:26) - Dark Patterns and Critical Perspectives (01:01:35) - RMAIIG (01:10:09) - Inclusive Tech Education (01:18:05) - Colorado AI Governance (01:23:46) - Building Your Own Tech Community LinksTech Job MarketLayoff tracker websiteThe Big Newsletter article - Why Are We Pretending AI Is Going to Take All the Jobs?METR preprint - Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer ProductivityAI Business blogpost - https://aibusiness.com/responsible-ai/debunking-the-ai-job-crisisCrunchbase article - Data: Tech Layoffs Remain Stubbornly High, With Big Tech Leading The WayComputerworld article - Tech layoffs surge even as US unemployment remains stableApollo Technical blogpost - Ghost jobs in tech: Why companies are posting roles they don’t plan to fillThe HR Digest article - The Rise of Ghost Jobs Is Leaving Job Seekers Frustrated and DisappointedA Life After Layoff video - The Tech Job Market Is Hot Trash Right NowEconomy Media video - Will The Tech Job Market Ever Recover?Soleyman Shahir video - Tech CEO Explains: The Real Reason Behind AI LayoffsDark PatternsDeceptive Design websiteJournal of Legal Analysis article - Shining a Light on Dark PatternsICLR paper - DarkBench: Benchmarking Dark Patterns in Large Language ModelsComputing Within Limits paper - Imposing AI: Deceptive design patterns against sustainabilityCommunications of the ACM blogpost - Dark Patterns[Preprint] - A Comprehensive Study on Dark PatternsColorado AI RegulationSenate Bill 24-205 (Colorado AI Act) bill and webpageNAAG article - A Deep Dive into Colorado’s Artificial Intelligence ActColorado Sun article - Why Colorado’s artificial intelligence law is a big deal for the whole countryCFO Dive blogpost - ‘Heavy lift’: Colorado AI law sets high bar, analysts sayDenver 7 article - Colorado could lose federal funding as Trump administration targets AI regulationsAmerica's AI Action Plan documentOther SourcesConcordia Framework report and repo80,000 Hours websiteAI Incident Database website

Will Petillo, onboarding team lead at PauseAI, joins me to discuss the grassroots movement advocating for a pause on frontier AI model development. We explore PauseAI's strategy, talk about common misconceptions Will hears, and dig into how diverse perspectives still converge on the need to slow down AI development.Will's LinksPersonal blog on AIHis mindmap of the AI x-risk debateGame demosAI focused YouTube channel(00:00) - Intro (03:36) - What is PauseAI (10:10) - Will Petillo's journey into AI safety advocacy (21:13) - Understanding PauseAI (31:35) - Pursuing a pause (40:06) - Balancing advocacy in a complex world (45:54) - Why a pause on frontier models? (54:48) - Diverse perspectives within PauseAI (59:55) - PauseAI misconceptions (01:16:40) - Ongoing AI governance efforts (SB1047) (01:28:52) - The role of incremental progress (01:35:16) - Safety-washing and corporate responsibility (01:37:23) - Lessons from environmentalism (01:41:59) - Will's superlatives LinksPauseAIPauseAI-USRelated Kairos.fm EpisodesInto AI Safety episode with Dr. Igor KrawczukmuckrAIkers episode on SB1047Exclusionary TendenciesJacobin article - Elite Universities Gave Us Effective Altruism, the Dumbest Idea of the CenturySSIR article - The Elitist Philanthropy of So-Called Effective AltruismPersuasion blogpost - The Problem with Effective AltruismDark Markets blogpost - What's So Bad About Rationalism?FEE blogpost - What’s Wrong With the Rationality Community?AI in WarfareMaster's Thesis - The Evolution of Artificial Intelligence and Expert Computer Systems in the ArmyInternational Journal of Intelligent Systems article - Artificial Intelligence in the Military: An Overview of the Capabilities, Applications, and ChallengesPreprint - Basic Research, Lethal Effects: Military AI Research Funding as EnlistmentAOAV Article - ‘Military Age Males’ in US Drone StrikesThe Conversation article - Gaza war: Israel using AI to identify human targets raising fears that innocents are being caught in the net972 article - ‘Lavender’: The AI machine directing Israel’s bombing spree in GazaIDF press release - The IDF's Use of Data Technologies in Intelligence ProcessingLieber Institute West Point article - Israel–Hamas 2024 SymposiumVerfassungsblog article - Gaza, Artificial Intelligence, and Kill ListsRAND research report - Dr. Li Bicheng, or How China Learned to Stop Worrying and Love Social Media ManipulationThe Intercept article collection - The Drone PapersAFIT faculty publication - On Large Language Models in National Security ApplicationsNature article - Death by Metadata: The Bioinformationalisation of Life and the Transliteration of Algorithms to FleshLegislationLegiScan page on SB1047NY State Senate page on the RAISE ActCongress page on the TAKE IT DOWN ActThe GavernorFastCompany article - Big Tech may be focusing its lobbying push on the California AI safety bill’s last stop: Gavin NewsomPOLITICO article - How California politics killed a nationally important AI billNewsom's veto messageAdditional relevant lobbying documentation - [1], [2]Jacobin article - With Newsom’s Veto, Big Tech Beats DemocracyMisc. LinksFLI Open Letter on an AI pauseWikipedia article - Overton windowDaniel Smachtenburger YouTube video - An Introduction to the MetacrisisVAISU website (looks broken as of 2025.06.19)AI Impacts report - Why Did Environmentalism Become Partisan?

I am joined by Tristan Williams and Felix de Simone to discuss their work on the potential of constituent communication, specifically in the context of AI legislation. These two worked as part of an AI Safety Camp team to understand whether or not it would be useful for more people to be sharing their experiences, concerns, and opinions with their government representative (hint, it is).Check out the blogpost on their findings, "Talking to Congress: Can constituents contacting their legislator influence policy?" and the tool they created!(01:53) - Introductions (04:04) - Starting the project (13:30) - Project overview (16:36) - Understanding constituent communication (28:50) - Literature review (35:52) - Phase 2 (43:26) - Creating a tool for citizen engagement (50:16) - Crafting your message (59:40) - The game of advocacy (01:15:19) - Difficulties on the project (01:22:33) - Call to action (01:32:30) - Outro LinksLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.AI Safety CampPause AIBlueDot ImpactTIME article - There’s an AI Lobbying Frenzy in Washington. Big Tech Is DominatingCongressional Management Foundation study - Communicating with Congress: Perceptions of Citizen Advocacy on Capitol HillCongressional Management Foundation study - The Future of Citizen Engagement: Rebuilding the Democratic DialogueTristan and Felix's blogpost - Talking to Congress: Can constituents contacting their legislator influence policy?Wired article - What It Takes to Make Congress Actually ListenAmerican Journal of Polical Science article - Congressional Representation: Accountability from the Constituent’s PerspectivePolitical Behavior article - Call Your Legislator: A Field Experimental Study of the Impact of a Constituency Mobilization Campaign on Legislative VotingGuided Track websiteThe ToolHolistic AI global regulatory trackerWhite & Case global regulatory trackerSteptoe US AI legislation trackerManatt US AIxHealth legislation trackerIssue One article - Big Tech Cozies Up to New Administration After Spending Record Sums on Lobbying Last YearVerfassungsblog article - BigTech’s Efforts to Derail the AI ActMIT Technology Review article - OpenAI has upped its lobbying efforts nearly sevenfoldOpen Secrets webpage - Issue Profile: Science & TechnologyStatista data - Leading lobbying spenders in the United States in 2024Global Justice Now report - Democracy at risk in Davos: new report exposes big tech lobbying and political interferenceIpsos article - Where Americans stand on AIAP-NORC report - There Is Bipartisan Concern About the Use of AI in the 2024 ElectionsAI Action Summit report - International AI Safety ReportYouGov article - Do Americans think AI will have a positive or negative impact on society?

The almost Dr. Igor Krawczuk joins me for what is the equivalent of 4 of my previous episodes. We get into all the classics: eugenics, capitalism, philosophical toads... Need I say more?If you're interested in connecting with Igor, head on over to his website, or check out placeholder for thesis (it isn't published yet).Because the full show notes have a whopping 115 additional links, I'll highlight some that I think are particularly worthwhile here:The best article you'll ever read on Open Source AIThe best article you'll ever read on emergence in MLKate Crawford's Atlas of AI (Wikipedia)On the Measure of IntelligenceThomas Piketty's Capital in the Twenty-First Century (Wikipedia)Yurii Nesterov's Introductory Lectures on Convex OptimizationChapters(02:32) - Introducing Igor (10:11) - Aside on EY, LW, EA, etc., a.k.a. lettersoup (18:30) - Igor on AI alignment (33:06) - "Open Source" in AI (41:20) - The story of infinite riches and suffering (59:11) - On AI threat models (01:09:25) - Representation in AI (01:15:00) - Hazard fishing (01:18:52) - Intelligence and eugenics (01:34:38) - Emergence (01:48:19) - Considering externalities (01:53:33) - The shape of an argument (02:01:39) - More eugenics (02:06:09) - I'm convinced, what now? (02:18:03) - AIxBio (round ??) (02:29:09) - On open release of models (02:40:28) - Data and copyright (02:44:09) - Scientific accessibility and bullshit (02:53:04) - Igor's point of view (02:57:20) - Outro LinksLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance. All references, including those only mentioned in the extended version of this episode, are included.Suspicious Machines Methodology, referred to as the "Rotterdam Lighthouse Report" in the episodeLIONS Lab at EPFLThe meme that Igor referencesOn the Hardness of Learning Under SymmetriesCourse on the concept of equivariant deep learningAside on EY/EA/etc.Sources on Eliezer YudkowskiScholarly Community EncyclopediaTIME100 AIYudkowski's personal websiteEY WikipediaA Very Literary Wiki -TIME article: Pausing AI Developments Isn’t Enough. We Need to Shut it All Down documenting EY's ruminations of bombing datacenters; this comes up later in the episode but is included here because it about EY.LessWrongLW WikipediaMIRICoverage on Nick Bostrom (being a racist)The Guardian article: ‘Eugenics on steroids’: the toxic and contested legacy of Oxford’s Future of Humanity InstituteThe Guardian article: Oxford shuts down institute run by Elon Musk-backed philosopherInvestigative piece on Émile TorresOn the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜NY Times article: We Teach A.I. Systems Everything, Including Our BiasesNY Times article: Google Researcher Says She Was Fired Over Paper Highlighting Bias in A.I.Timnit Gebru's WikipediaThe TESCREAL Bundle: Eugenics and the Promise of Utopia through Artificial General IntelligenceSources on the environmental impact of LLMsThe Environmental Impact of LLMsThe Cost of Inference: Running the ModelsEnergy and Policy Considerations for Deep Learning in NLPThe Carbon Impact of AI vs Search EnginesFilling Gaps in Trustworthy Development of AI (Igor is an author on this one)A Computational Turn in Policy Process Studies: Coevolving Network Dynamics of Policy ChangeThe Smoothed Possibility of Social Choice, an intro in social choice theory and how it overlaps with MLRelating to Dan HendrycksNatural Selection Favors AIs over Humans"One easy-to-digest source to highlight what he gets wrong [is] Social and Biopolitical Dimensions of Evolutionary Thinking" -IgorIntroduction to AI Safety, Ethics, and Society, recently published textbook"Source to the section [of this paper] that makes Dan one of my favs from that crowd." -IgorTwitter post referenced in the episode<...

As always, the best things come in 3s: dimensions, musketeers, pyramids, and... 3 installments of my interview with Dr. Peter Park, an AI Existential Safety Post-doctoral Fellow working with Dr. Max Tegmark at MIT.As you may have ascertained from the previous two segments of the interview, Dr. Park cofounded StakeOut.AI along with Harry Luk and one other cofounder whose name has been removed due to requirements of her current position. The non-profit had a simple but important mission: make the adoption of AI technology go well, for humanity, but unfortunately, StakeOut.AI had to dissolve in late February of 2024 because no granter would fund them. Although it certainly is disappointing that the organization is no longer functioning, all three cofounders continue to contribute positively towards improving our world in their current roles.If you would like to investigate further into Dr. Park's work, view his website, Google Scholar, or follow him on Twitter00:00:54 ❙ Intro00:02:41 ❙ Rapid development00:08:25 ❙ Provable safety, safety factors, & CSAM00:18:50 ❙ Litigation00:23:06 ❙ Open/Closed Source00:38:52 ❙ AIxBio00:47:50 ❙ Scientific rigor in AI00:56:22 ❙ AI deception01:02:45 ❙ No takesies-backsies01:08:22 ❙ StakeOut.AI's start01:12:53 ❙ Sustainability & Agency01:18:21 ❙ "I'm sold, next steps?" -you01:23:53 ❙ Lessons from the amazing Spiderman01:33:15 ❙ "I'm ready to switch careers, next steps?" -you01:40:00 ❙ The most important question01:41:11 ❙ OutroLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.StakeOut.AIPause AIAI Governance Scorecard (go to Pg. 3)CIVITAIArticle on CIVITAI and CSAMSenate Hearing: Protecting Children OnlinePBS Newshour CoverageThe Times Sues OpenAI and Microsoft Over A.I. Use of Copyrighted WorkOpen Source/Weights/Release/InterpretationOpen Source InitiativeHistory of the OSIMeta’s LLaMa 2 license is not Open SourceIs Llama 2 open source? No – and perhaps we need a new definition of open…Apache License, Version 2.03Blue1Brown: Neural NetworksOpening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generatorsThe online tableSignalBloomz model on HuggingFaceMistral websiteNASA TragediesChallenger disaster on WikipediaColumbia disaster on WikipediaAIxBio RiskDual use of artificial-intelligence-powered drug discoveryCan large language models democratize access to dual-use biotechnology?Open-Sourcing Highly Capable Foundation Models (sadly, I can't rename the article...)Propaganda or Science: Open Source AI and Bioterrorism RiskExaggerating the risks (Part 15: Biorisk from LLMs)Will releasing the weights of future large language models grant widespread access to pandemic agents?On the Societal Impact of Open Foundation ModelsPolicy briefApart ResearchScienceCiceroHuman-level play in the game of Diplomacy by combining language models with strategic reasoningCicero webpageAI Deception: A Survey of Examples, Risks, and Potential SolutionsOpen Sourcing the AI Revolution: Framing the debate on open source, artificial intelligence and regulationAI Safety CampInto AI Safety Patreon

Join me for round 2 with Dr. Peter Park, an AI Existential Safety Postdoctoral Fellow working with Dr. Max Tegmark at MIT. Dr. Park was a cofounder of StakeOut.AI, a non-profit focused on making AI go well for humans, along with Harry Luk and one other individual, whose name has been removed due to requirements of her current position.In addition to the normal links, I wanted to include the links to the petitions that Dr. Park mentions during the podcast. Note that the nonprofit which began these petitions, StakeOut.AI, has been dissolved.Right AI Laws, to Right Our Future: Support Artificial Intelligence Safety Regulations NowIs Deepfake Illegal? Not Yet! Ban Deepfakes to Protect Your Family & Demand Deepfake LawsBan Superintelligence: Stop AI-Driven Human Extinction Risk 00:00:54 - Intro00:02:34 - Battleground 1: Copyright00:06:28 - Battleground 2: Moral Critique of AI Collaborationists00:08:15 - Rich Sutton00:20:41 - OpenAI Drama00:34:28 - Battleground 3: Contract Negotiations for AI Ban Clauses00:37:57 - Tesla, Autopilot, and FSD00:40:02 - Recycling00:47:40 - Battleground 4: New Laws and Policies00:50:00 - Battleground 5: Whistleblower Protections00:53:07 - Whistleblowing on Microsoft00:54:43 - Andrej Karpathy & Exercises in Empathy01:05:57 - OutroLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.StakeOut.AIThe Times Sues OpenAI and Microsoft Over A.I. Use of Copyrighted WorkSusman Godfrey LLPRich SuttonReinforcement Learning: An Introduction (textbook)AI Succession (presentation by Rich Sutton)The Alberta Plan for AI ResearchMoore's LawThe Future of Integrated Electronics (original paper)Computer History Museum's entry on Moore's LawStochastic gradient descent (SGD) on WikipediaOpenAI DramaMax Read's Substack postZvi Mowshowitz's Substack series, in order of postingOpenAI: Facts from a WeekendOpenAI: The Battle of the BoardOpenAI: Altman ReturnsOpenAI: Leaks Confirm the Story ← best singular post in the seriesOpenAI: The Board ExpandsOfficial OpenAI announcementWGA on WikipediaSAG-AFTRA on WikipediaTesla's False AdvertisingTesla's response to the DMV's false-advertising allegations: What took so long?Tesla Tells California DMV that FSD Is Not Capable of Autonomous DrivingWhat to Call Full Self-Driving When It Isn't Full Self-Driving?Tesla fired an employee after he posted driverless tech reviews on YouTubeTesla's page on Autopilot and Full Self-DrivingRecyclingBoulder County Recycling Center Stockpiles Accurately Sorted Recyclable MaterialsOut of sight, out of mindBoulder Eco-Cycle Recycling GuidelinesDivide-and-Conquer Dynamics in AI-Driven DisempowermentMicrosoft WhistleblowerWhistleblowers call out AI's flawsShane's LinkedIn postLetters sent by JonesKarpathy announces departure from OpenAI

UPDATE: Contrary to what I say in this episode, I won't be removing any episodes that are already published from the podcast RSS feed.After getting some advice and reflecting more on my own personal goals, I have decided to shift the direction of the podcast towards accessible content regarding "AI" instead of the show's original focus. I will still be releasing what I am calling research ride-along content to my Patreon, but the show's feed will consist only of content that I aim to make as accessible as possible.00:35 - TL;DL01:12 - Advice from Pete03:10 - My personal goal05:39 - Reflection on refining my goal09:08 - Looking forward (logistics

Dr. Peter Park is an AI Existential Safety Postdoctoral Fellow working with Dr. Max Tegmark at MIT. In conjunction with Harry Luk and one other cofounder, he founded ⁠StakeOut.AI, a non-profit focused on making AI go well for humans.00:54 - Intro03:15 - Dr. Park, x-risk, and AGI08:55 - StakeOut.AI12:05 - Governance scorecard19:34 - Hollywood webinar22:02 - Regulations.gov comments23:48 - Open letters 26:15 - EU AI Act35:07 - Effective accelerationism40:50 - Divide and conquer dynamics45:40 - AI "art"53:09 - OutroLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.StakeOut.AIAI Governance Scorecard (go to Pg. 3)Pause AIRegulations.gov USCO StakeOut.AI Comment OMB StakeOut.AI Comment AI Treaty open letterTAISCAlpaca: A Strong, Replicable Instruction-Following ModelReferences on EU AI Act and Cedric O Tweet from Cedric O EU policymakers enter the last mile for Artificial Intelligence rulebook AI Act: EU Parliament’s legal office gives damning opinion on high-risk classification ‘filters’ EU’s AI Act negotiations hit the brakes over foundation models The EU AI Act needs Foundation Model Regulation BigTech’s Efforts to Derail the AI Act Open Sourcing the AI Revolution: Framing the debate on open source, artificial intelligence and regulationDivide-and-Conquer Dynamics in AI-Driven Disempowerment

Take a trip with me through the paper Large Language Models, A Survey, published on February 9th of 2024. All figures and tables mentioned throughout the episode can be found on the Into AI Safety podcast website.00:36 - Intro and authors01:50 - My takes and paper structure04:40 - Getting to LLMs07:27 - Defining LLMs & emergence12:12 - Overview of PLMs15:00 - How LLMs are built18:52 - Limitations if LLMs23:06 - Uses of LLMs25:16 - Evaluations and Benchmarks28:11 - Challenges and future directions29:21 - Recap & outroLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.Large Language Models, A SurveyMeysam's LinkedIn PostClaude E. ShannonA symbolic analysis of relay and switching circuits (Master's Thesis)Communication theory of secrecy systemsA mathematical theory of communicationPrediction and entropy of printed EnglishFuture ML Systems Will Be Qualitatively DifferentMore Is DifferentSleeper Agents: Training Deceptive LLMs that Persist Through Safety TrainingAre Emergent Abilities of Large Language Models a Mirage?Are Emergent Abilities of Large Language Models just In-Context Learning?Attention is all you needDirect Preference Optimization: Your Language Model is Secretly a Reward ModelKTO: Model Alignment as Prospect Theoretic OptimizationOptimization by Simulated AnnealingMemory and new controls for ChatGPTHallucinations and related concepts—their conceptual background

Esben reviews an application that I would soon submit for Open Philanthropy's Career Transitition Funding opportunity. Although I didn't end up receiving the funding, I do think that this episode can be a valuable resource for both others and myself when applying for funding in the future.Head over to Apart Research's website to check out their work, or the Alignment Jam website for information on upcoming hackathons.A doc-capsule of the application at the time of this recording can be found at this link.01:38 - Interview starts05:41 - Proposal11:00 - Personal statement14:00 - Budget21:12 - CV22:45 - Application questions34:06 - Funding questions44:25 - OutroLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.AI governance talent profiles we’d like to seeThe AI Governance Research SprintReasoning TransparencyPlaces to look for fundingOpen Philanthropy's Career development and transition fundingLong-Term Future FundManifund

Before I begin with the paper-distillation based minisodes, I figured we would go over best practices for reading research papers. I go through the anatomy of typical papers, and some generally applicable advice.00:56 - Anatomy of a paper02:38 - Most common advice05:24 - Reading sparsity and path07:30 - Notes and motivationLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.Ten simple rules for reading a scientific paperBest sources I foundLet's get critical: Reading academic articles#GradHacks: A guide to reading research papersHow to read a scientific paper (presentation)Some more sourcesHow to read a scientific articleHow to read a research paperReading a scientific article 

Join our hackathon group for the second episode in the Evals November 2023 Hackathon subseries. In this episode, we solidify our goals for the hackathon after some preliminary experimentation and ideation.Check out Stellaric's website, or follow them on Twitter.01:53 - Meeting starts05:05 - Pitch: extension of locked models23:23 - Pitch: retroactive holdout datasets34:04 - Preliminary results37:44 - Next steps42:55 - RecapLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.Evalugator libraryPassword Locked Model blogpostTruthfulQA: Measuring How Models Mimic Human FalsehoodsBLEU: a Method for Automatic Evaluation of Machine TranslationBoolQ: Exploring the Surprising Difficulty of Natural Yes/No QuestionsDetecting Pretraining Data from Large Language Models

I provide my thoughts and recommendations regarding personal professional portfolios.00:35 - Intro to portfolios01:42 - Modern portfolios02:27 - What to include04:38 - Importance of visual05:50 - The "About" page06:25 - Tools08:12 - Future of "Minisodes"Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.From Portafoglio to Eportfolio: The Evolution of Portfolio in Higher EducationGIMPAlternativeToJekyllGitHub PagesMinimal MistakesMy portfolio

Darryl and I discuss his background, how he became interested in machine learning, and a project we are currently working on investigating the penalization of polysemanticity during the training of neural networks.Check out a diagram of the decoder task used for our research!01:46 - Interview begins02:14 - Supernovae classification08:58 - Penalizing polysemanticity20:58 - Our "toy model"30:06 - Task description32:47 - Addressing hurdles39:20 - Lessons learnedLinks to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.ZooniverseBlueDot ImpactAI Safety SupportZoom In: An Introduction to CircuitsMNIST dataset on PapersWithCodeClusterability in Neural NetworksCIFAR-10 datasetEffective Altruism GlobalCLIP (blog post)Long Term Future FundEngineering Monosemanticity in Toy Models

A summary and reflections on the path I have taken to get this podcast started, including some resources recommendations for others who want to do something similar.Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.LessWrongSpotify for PodcastersInto AI Safety podcast websiteEffective Altruism GlobalOpen Broadcaster Software (OBS)CraigRiverside

This episode kicks off our first subseries, which will consist of recordings taken during my team's meetings for the AlignmentJams Evals Hackathon in November of 2023. Our team won first place, so you'll be listening to the process which, at the end of the day, turned out to be pretty good.Check out Apart Research, the group that runs the AlignmentJamz Hackathons.Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.Generalization Analogies: A Testbed for Generalizing AI Oversight to Hard-To-Measure DomainsNew paper shows truthfulness & instruction-following don't generalize by defaultGeneralization Analogies WebsiteDiscovering Language Model Behaviors with Model-Written EvaluationsModel-Written Evals WebsiteOpenAI Evals GitHubMETR (previously ARC Evals)Goodharting on WikipediaFrom Instructions to Intrinsic Human Values, a Survey of Alignment Goals for Big ModelsFine Tuning Aligned Language Models Compromises Safety Even When Users Do Not IntendShadow Alignment: The Ease of Subverting Safely Aligned Language ModelsWill Releasing the Weights of Future Large Language Models Grant Widespread Access to Pandemic Agents?Building Less Flawed Metrics, Understanding and Creating Better Measurement and Incentive SystemseLeutherAI's Model Evaluation HarnessEvalugator Library

In this minisode I give some tips for staying up-to-date in the everchanging landscape of AI. I would like to point out that I am constantly iterating on these strategies, tools, and sources, so it is likely that I will make an update episode in the future.Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.ToolsFeedlyarXiv Sanity LiteZoteroAlternativeToMy "Distilled AI" FolderAI Explained YouTube channelAI Safety newsletterData Machina newsletterImport AIMidwit AlignmentHonourable MentionsAI Alignment ForumLessWrongBounded Regret (Jacob Steinhart's blog)Cold Takes (Holden Karnofsky's blog)Chris Olah's blogTim Dettmers blogEpoch blogApollo Research blog

Alice Rigg, a mechanistic interpretability researcher from Ottawa, Canada, joins me to discuss their path and the applications process for research/mentorship programs.Join the Mech Interp Discord server and attend reading groups at 11:00am on Wednesdays (Mountain Time)!Check out Alice's website.Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance. EleutherAI Join the public EleutherAI discord server DistillEffective Altruism (EA)MATS Retrospective Summer 2023 postAmbitious Mechanistic Interpretability AISC research plan by Alice RiggSPARStability AI During their most recent fundraising round, Stability AI had a valuation of $4B (Bloomberg) Mech Interp Discord Server

We're back after a month-long hiatus with a podcast refactor and advice on the applications process for research/mentorship programs.Check out the About page on the Into AI Safety website for a summary of the logistics updates.Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance. MATSASTRA FellowshipARENAAI Safety CampBlueDot ImpactTech with TimFast.AI's Practical Deep Learning for CodersKaggleAlignmentJamsLessWrongAI Alignment Forum

This episode is a brief overview of the major takeaways I had from attending EAG Boston 2023, and an update on my plans for the podcast moving forward.TL;DLStarting in early December (2023), I will be uploading episodes on a biweekly basis (day TBD).I won't be releasing another episode until then, so that I can build a cache of episodes up.During this month (November 2023), I'll also try to get the podcast up on more platforms, set up comments on more platforms, and create an anonymous feedback form.Links Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance. How to generate research proposalsKarolina Sarek: How to do research that mattersWill releasing the weights of future large language models grant widespread access to pandemic agents?Like the show? Think it could be improved? Fill out this anonymous feedback form to let me know!Please email all inquiries to intoaisafety@gmail.com.