Superposed

About Superposed

Every decision exists in superposition — multiple outcomes, all possible, until you choose. But how do you know which decision to make? Superposed applies quantum cognition — an emerging framework that uses quantum mechanics principles to explain how humans make decisions — to history's most consequential choices. Learn from this deeper perspective on how political, business, and scientific leaders have made the decisions that effect our everyday lives to gain a sharper mental model for the decisions you face today.

Publisher

Aidan Lewis

Category

science

Language

en

Explicit

No

First episode

23 Jun 2026

Latest episode

10 Nov 2026

Latest episodes

26 episodes in the feed.

1. 

   10 Nov 2026

   E25: Has Fear Beaten Hope? – The 2026 Midterms' Anti-Trump Wave Seen Through Quantum Cognition

   On election night 2026, Democrats took both chambers of Congress and won in states that hadn't gone blue in decades, all while polling as the less popular party. The data points to one driver: voters weren't voting for Democrats so much as against President Trump. So which force moves a decision more, what you hope to gain or what you're trying to escape? ================================= Links: 📖Substack: https://superposeddecisions.substack.com/ (https://superposeddecisions.substack.com/) 📺YouTube: @Superposed_Decisions (https://youtube.com/@superposed_decisions?si=7O1iZuyiG1p4C-jk) 🤝LinkedIn: https://www.linkedin.com/in/aidan-m-lewis/ (https://www.linkedin.com/in/aidan-m-lewis/) ================================= Going into the midterms, 43% of voters said their ballot was meant to oppose the president, up from 38% in 2018, while support-driven votes fell from 26% to 16%. Democrats trailed the GOP in favorability as late as March, yet voters who disliked both parties broke Democratic by 31 points. The result was a Senate majority, a House flip reaching deep into Trump-won districts, a slate of historic firsts, and a repeat of a pattern seen in all but three midterms since 1878: voters checking the party in power. We trace how negative partisanship grew from 2000, when most Gore and Bush voters said they were voting for their candidate, into an era where voting against is the default. ================================= We run the 2026 electorate's decision through the four pillars of quantum cognition. Superposition: every voter holds the beliefs of both parties at once, which is how a faith-forward candidate like James Talarico could carry Texas. Interference: fear of the other side and hope for your own act as competing forces, and since 2016 fear has been winning. Contextuality: the Iran war, inflation, and cost of living framed every ballot. Stacked across national, state, and local levels, these forces explain why a 30-year incumbent like Susan Collins lost to a challenger who campaigned for under three months, and why opposition can win an election but can't govern for you. ================================= What you'll take away: Why voting against someone has overtaken voting for someone since 2000, and what that asymmetry does to election outcomes How fear and hope act as interfering forces that stack across national, state, and local levels of a single decision A pre-decision exercise for any big choice: name what you hope to gain and what you're trying to avoid before you commit This is not a debate about Trump or either party. It's a decision-science breakdown of why opposition has become a stronger voting motive than support. ================================= Primary Sources: Kernell https://ideas.repec.org/a/cup/apsrev/v71y1977i01p44-66_25.html (https://ideas.repec.org/a/cup/apsrev/v71y1977i01p44-66_25.html) Abramowitz & Webster https://doi.org/10.1016/j.electstud.2015.11.001 (https://doi.org/10.1016/j.electstud.2015.11.001) Bankert https://doi.org/10.1007/s11109-020-09599-1 (https://doi.org/10.1007/s11109-020-09599-1) Siev, Rovenpor & Petty https://doi.org/10.1016/j.jesp.2023.104538 (https://doi.org/10.1016/j.jesp.2023.104538) Soroka & McAdams https://doi.org/10.1080/10584609.2014.881942 (https://doi.org/10.1080/10584609.2014.881942) Bafumi, Erikson & Wlezien https://doi.org/10.1017/S0022381610000113 (https://doi.org/10.1017/S0022381610000113) Weber https://doi.org/10.1017/S1537592721001171 (https://doi.org/10.1017/S1537592721001171) ================================= Secondary Sources: Pew Research Center — partisan antipathy / reasons for party affiliation (2018) (http://url) Pew Research Center — "vote for" vs. "vote against" candidate, 2000–2016 (http://url) CNN/SSRS poll — midterm vote as opposition to/support for Trump (http://url) NBC News poll — September 2026 (http://url) Gallup — party favorability, March 2026 (http://url) CNBC — 2026 midterm results / spending (http://url) Fox News — 2026 midterm results / voter analysis (http://url) NPR — 2026 midterm results (http://url) Al Jazeera — House seat projections (http://url) NYT – Election Spending (https://www.nytimes.com/2026/11/04/us/republican-party-fundraising-midterms.html)

2. 

   3 Nov 2026

   E24: Science & Philosophy United – Dr. Peter Bruza on Quantum Cognition, and Reaching Your Potential

   In the early 2000s, Dr. Peter Bruza was near the top of his field in information retrieval when he noticed the math behind search engines looked a lot like quantum mechanics. A colleague pulled him aside on a conference bus to tell him he was trashing his career. Two decades later, a grant reviewer still wrote, "I simply do not believe in the existence of these indeterminate cognitive states." Dr. Bruza built a field on exactly that belief. ================================= Links: 📖Substack: https://superposeddecisions.substack.com/ (https://superposeddecisions.substack.com/) 📺YouTube: @Superposed_Decisions (https://youtube.com/@superposed_decisions?si=7O1iZuyiG1p4C-jk) 🤝LinkedIn: https://www.linkedin.com/in/aidan-m-lewis/ (https://www.linkedin.com/in/aidan-m-lewis/) ================================= Dr. Peter Bruza recently retired from the Queensland University of Technology, where he co-authored the field's foundational textbook, Quantum Models of Cognition and Decision, with Jerome Busemeyer (2012; second edition 2024). His first quantum cognition grant nearly died on a single reviewer's verdict that the idea "can't possibly be true" before an expert panel overrode it. Later, with funding from the US Air Force Office of Scientific Research, his team asked people to judge whether faces were real or AI-generated alongside a simulated AI, then rate their trust in it from 0 to 100. Trust swung up and down far more than expected, and a quantum model predicted those swings better than a classical Markov model. His work now pushes toward the experiencing mind: consciousness, qualia, and what Zen Buddhism and Bohr's physics share about a reality we can't fully represent. ================================= What you'll take away: Why "you haven't decided yet" can be a real state of mind, not just missing information, and why that changes how we model jurors, voters, and ourselves How trust in AI behaves less like a dial and more like a wave, and why predicting its decline matters before human–machine teams face a real crisis Why Bruza tells young researchers to follow passion over citation counts, and what a career built on an unpopular bet looks like from retirement ================================= Primary Sources: Busemeyer, J. R., & Bruza, P. D. (2024). Quantum Models of Cognition and Decision: Principles and Applications (2nd ed.). Cambridge University Press. https://www.cambridge.org/core/books/quantum-models-of-cognition-and-decision/9EEF7415DEA574E82F695AB7D0E13713 (https://www.cambridge.org/core/books/quantum-models-of-cognition-and-decision/9EEF7415DEA574E82F695AB7D0E13713) Tsuchiya, N., Bruza, P., Yamada, M., Saigo, H., & Pothos, E. M. (2025). Quantum-like Qualia hypothesis: From quantum cognition to quantum perception. Frontiers in Psychology, 15, 1406459. https://doi.org/10.3389/fpsyg.2024.1406459 (https://doi.org/10.3389/fpsyg.2024.1406459) Bruza, P. (2025). Bridging Quantum Physics and Human Cognition with Nishida's Logic of Basho. Philosophy East and West, 75(3), 528–543. https://doi.org/10.1353/pew.2025.a965460 (https://doi.org/10.1353/pew.2025.a965460) Roeder, L., Hoyte, P., van der Meer, J., Fell, L., Johnston, P., Kerr, G., & Bruza, P. (2023). A Quantum Model of Trust Calibration in Human–AI Interactions. Entropy, 25(9), 1362. https://doi.org/10.3390/e25091362 (https://doi.org/10.3390/e25091362) van der Meer, J., Hoyte, P., Roeder, L., & Bruza, P. (2025). Modeling the quantum-like dynamics of human reliability ratings in Human-AI interactions by interaction dependent Hamiltonians. arXiv:2504.13918. https://arxiv.org/abs/2504.13918 (https://arxiv.org/abs/2504.13918) ================================= Secondary Sources: Dr. Peter Bruza – QUT research profile (https://research.qut.edu.au/qutcds/?p=2887) Models of Consciousness Conference -- Dr. Bruza's talk (https://www.youtube.com/watch?v=JSIDft5xgpU) Dr. Peter Bruza on LinkedIn (https://www.linkedin.com/in/peter-bruza-1809b11/)

3. 

   27 Oct 2026

   E23: How Logical is the Law? – Dr. Bartosz Wojciechowski on Quantum Cognition in the Courtroom

   Same case file. Same evidence. Change only the order it's presented in, and the estimated probability that a suspect is guilty moves by about 10%. The legal system assumes a judge can read the truth out of the facts like an instrument reads a dial. Forensic psychologist and attorney Dr. Bartosz Wojciechowski has spent a decade showing that the act of judging changes what's being judged. ================================= Links: 📖Substack: https://superposeddecisions.substack.com/ (https://superposeddecisions.substack.com/) 📺YouTube: @Superposed_Decisions (https://youtube.com/@superposed_decisions?si=7O1iZuyiG1p4C-jk) 🤝LinkedIn: https://www.linkedin.com/in/aidan-m-lewis/ (https://www.linkedin.com/in/aidan-m-lewis/) ================================= Dr. Wojciechowski’s path into quantum cognition started with a puzzle. Trained forensic psychologists rating witness statements for truthfulness, item by item, ended up exactly where they started: the scoring criteria didn't determine the verdict, and the tools carried error rates of 35–40%. Searching for a model that could explain this led him to Busemeyer and Wang's work on quantum probability. Since then he has tested judges, prosecutors, attorneys, and laypeople on real Polish criminal case files, and recently tested GPT models on the same cases. ================================= We run the courtroom's core fallacies through quantum cognition. Superposition explains why raters don't read out a pre-existing judgment of veracity; the judgment is formed at the moment of decision. The quantum Zeno effect shows up in pretrial detention: when judges re-decide the same case every three months, each repetition makes them less likely to change their mind. Non-commutative order effects mean guilt-then-innocence evidence produces a different verdict than innocence-then-guilt, with recency winning. ================================= What you'll take away: Why the order of evidence, not just its content, can shift a guilt judgment by roughly 10%, and why the last word in court carries outsized weight How repeated review turns a provisional detention decision into a locked-in one, and why changing the decision-maker may matter more than reviewing more often Why laypeople fall for the conjunction fallacy on multiple charges while trained lawyers don't, and why AI trained on human text inherits the same procedural biases ================================= Primary Sources: Wojciechowski, White, Allefeld & Pothos (2025). “Order Effects and the Evaluation Bias in Legal Decision Making.” Decision 12(3), 246–267. DOI (https://doi.org/10.1037/dec0000263) · Open-access version (https://openaccess.city.ac.uk/id/eprint/35182/) Wojciechowski (2023/2024). Quantum Probability Theory, Psychology and Law: Modelling Legal Decision Making with Quantum Principles. Routledge. Taylor & Francis page (eBook DOI) (https://doi.org/10.4324/9781003402480) · Chapter list (https://www.tomlinsons-online.com/p-38853938-quantum-probability-theory-psychology-and-law.aspx). The DOI resolves to the T&F book page, but the site blocked my check of its content. Wojciechowski & Pothos (2018). “Is There a Conjunction Fallacy in Legal Probabilistic Decision Making?” Frontiers in Psychology 9:391. DOI (https://doi.org/10.3389/fpsyg.2018.00391) · Open access (https://openaccess.city.ac.uk/19580) Wojciechowski, Gräns & Lidén (2018). “A true denial or a false confession? Assessing veracity of suspects’ statements using MASAM and SVA.” PLOS ONE 13(6). Open access (https://doi.org/10.1371/journal.pone.0198211) Wojciechowski (2014). “Psychologiczna analiza treści zeznań” [Psychological content analysis of testimony]. Acta Universitatis Lodziensis. Folia Psychologica 18. DOI (https://doi.org/10.18778/1427-969X.18.05) Wojciechowski (2014). “Content analysis algorithms: an innovative and accurate approach to statement veracity assessment.” European Polygraph 8(3). No link verified. Wojciechowski et al. (2021/2022). “Constructive biases in clinical judgment.” Topics in Cognitive Science. DOI (https://doi.org/10.1111/tops.12547) Waddup, Błasiak, Yearsley, Wojciechowski & Pothos (2021). “Sensitivity to context in human interactions.” Mathematics 9. DOI (https://doi.org/10.3390/math9212784) Gallus, Pothos, Błasiak, Yearsley & Wojciechowski (2023). “Bell correlations outside physics.” Scientific Reports 13, 4394. DOI (https://doi.org/10.1038/s41598-023-31441-x) ================================= Secondary Sources: Jagiellonian University staff page: (https://ips.uj.edu.pl/instytut2/pracownicy/bartosz-wojciechowski)dr Bartosz Wojciechowski, Institute of Applied Psychology (https://ips.uj.edu.pl/pracownicy/sklad-osobowy/bartosz-wojciechowski) Dr. Wojciechowski’s legal practice: ip.land (https://ip.land/en/homepage/)

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