Podcasts about spelke

In this episode, we chat about strength-based approaches in developmental cognitive neuroscience and the importance of identifying and building upon individuals' strength rather than solely focusing on deficits/weaknesses. We explore how strength-based perspectives highlight individuals' resilience and adaptivity in the face of structural inequities, and the ways we can incorporate strength-based approaches in our work. Gavkhar is joined by wonderful guests who have done and are continuing to do impactful work in advancing strength-based research in our field -- Drs. Divyangana Rakesh, Monica Ellwood-Lowe, and Meriah DeJoseph.For a full transcript, visit: bit.ly/S3E4-strength-based-in-dcnConnect with our guests:Dr. Monica Ellwood-Lowe: @mellwoodlowe.bsky.socialDr. Meriah DeJoseph: @meriahdejoseph.bsky.social Dr. Divyangana Rakesh: @divyangana.bsky.socialRelevant resources and discussed papers:Communicating and Expanding Research on Adversity Network  (https://cera-network.com/) Monica E. Ellwood-Lowe, Gabriel Reyes, Meriah L. DeJoseph, Willem E. Frankenhuis; Caring for Children in Lower-SES Contexts: Recognizing Parents' Agency, Adaptivity & Resourcefulness. Daedalus 2025; 154 (1): 52–69. doi: https://doi.org/10.1162/daed_a_02123DeJoseph, M. L., Ellwood-Lowe, M. E., Miller-Cotto, D., Silverman, D., Shannon, K. A., Reyes, G., Rakesh, D., & Frankenhuis, W. E. (2024). The promise and pitfalls of a strength-based approach to child poverty and neurocognitive development: Implications for policy. Developmental cognitive neuroscience, 66, 101375. https://doi.org/10.1016/j.dcn.2024.101375Rakesh, D., Sadikova, E., & McLaughlin, K. (2024). Beyond the income‐achievement gap: The role of individual, family, and environmental factors in cognitive resilience among low‐income youth. JCPP Advances, Article e12297. Advance online publication. https://doi.org/10.1002/jcv2.12297Ellwood-Lowe, M. E., Whitfield-Gabrieli, S., & Bunge, S. A. (2021). Brain network coupling associated with cognitive performance varies as a function of a child's environment in the ABCD study. Nature communications, 12(1), 7183. https://doi.org/10.1038/s41467-021-27336-yBanerjee, A. V., Bhattacharjee, S., Chattopadhyay, R., Duflo, E., Ganimian, A. J., Rajah, K., & Spelke, E. S. (2025). Children's arithmetic skills do not transfer between applied and academic mathematics. Nature, 1-9.Hoff, Karla and Pandey, Priyank, Belief Systems and Durable Inequalities: An Experimental Investigation of Indian Caste (June 25, 2004). Available at SSRN: https://ssrn.com/abstract=610395Taylor, E. K., Abdurokhmonova, G., & Romeo, R. R. (2023). Socioeconomic status and reading development: Moving from “deficit” to “adaptation” in neurobiological models of experience‐dependent learning. Mind, Brain, and Education, 17(4), 324–333. https://doi.org/10.1111/mbe.12351 Reach out to your host, Gavkhar Abdurokhmonova (ga2541@umd.edu | @gavkhar-a.bsky.social).Connect with us on social media! We are always looking for ideas for episode topics, co-hosts, or guests. 

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Woods' new preprint on object permanence, published by Steven Byrnes on March 8, 2024 on LessWrong. Quick poorly-researched post, probably only of interest to neuroscientists. The experiment Justin Wood at University of Indiana has, over many years with great effort, developed a system for raising baby chicks such that all the light hitting their retina is experimentally controlled right from when they're an embryo - the chicks are incubated and hatched in darkness, then moved to a room with video screens, head-tracking and so on. For a much better description of how this works and how he got into this line of work, check out his recent appearance on the Brain Inspired podcast. He and collaborators posted a new paper last week: "Object permanence in newborn chicks is robust against opposing evidence" by Wood, Ullman, Wood, Spelke, and Wood. I just read it today. It's really cool! In their paper, they are using the system above to study "object permanence", the idea that things don't disappear when they go out of sight behind an occluder. The headline result is that baby chicks continue to act as if object permanence is true, even if they have seen thousands of examples where it is false and zero where it is true over the course of their short lives. They describe two main experiments. Experiment 1 is the warmup, and Experiment 2 is the headline result I just mentioned. In experiment 1, the chicks are raised in a VR visual world where they never see anything occlude anything, ever. They only see one virtual object move around an otherwise-empty virtual room. The chicks of course imprint on the object. This phase lasts 4 days. Then we move into the test phase. The test initializes when the chick moves towards the virtual object, which starts in the center of the room. Two virtual opaque screens appear on the sides of the room. In the easier variant of the test, the object moves behind one of the screens, and then nothing else happens for a few minutes. The experimenters measure which screen the chick looks at more. The result: all 8 chicks looked more-than-chance at the screen that the virtual object would be behind, than at the other screen, at least for the first 30 seconds or so after the object disappeared from view. In the harder variant, one of the screens moves to the object, occludes the object, then moves back to its starting point. Again, the experiments measure which screen the chick looks at more. Here, 7 of the 8 chicks looked more-than-chance towards the screen that the virtual object would be behind, at least for 15ish seconds. Moving on to experiment 2, the test phase was the same as the easier variant above - the object moved to behind one of the two opaque virtual screens on the sides. But the preceding 4-day training phase was different for these chicks: instead of never seeing any occlusion events, they witnessed thousands of occlusion events, where the object would go behind a virtual opaque screen, and then after a variable amount of time (0-20 seconds), the screens would lower to reveal that the object was where we might expect (for the "natural world" chicks), or had magically teleported to behind the "wrong" screen (the "unnatural world" chicks). (There was no randomization - each chick lived its whole training-phase in either the natural or unnatural world.) Remarkably, all four chicks in the "natural world" and all four chicks in the "unnatural world" spent more time looking at the screen that the object had disappeared behind, rather than the other one, more than chance, at least for the first 15-30 seconds. In fact, remarkably, there was no difference between the natural-world and unnatural-world chicks! How do we make sense of these results? It's always worth asking: maybe the experiment is garbage? I'm far from an expert, but the methodol...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Woods' new preprint on object permanence, published by Steven Byrnes on March 8, 2024 on LessWrong. Quick poorly-researched post, probably only of interest to neuroscientists. The experiment Justin Wood at University of Indiana has, over many years with great effort, developed a system for raising baby chicks such that all the light hitting their retina is experimentally controlled right from when they're an embryo - the chicks are incubated and hatched in darkness, then moved to a room with video screens, head-tracking and so on. For a much better description of how this works and how he got into this line of work, check out his recent appearance on the Brain Inspired podcast. He and collaborators posted a new paper last week: "Object permanence in newborn chicks is robust against opposing evidence" by Wood, Ullman, Wood, Spelke, and Wood. I just read it today. It's really cool! In their paper, they are using the system above to study "object permanence", the idea that things don't disappear when they go out of sight behind an occluder. The headline result is that baby chicks continue to act as if object permanence is true, even if they have seen thousands of examples where it is false and zero where it is true over the course of their short lives. They describe two main experiments. Experiment 1 is the warmup, and Experiment 2 is the headline result I just mentioned. In experiment 1, the chicks are raised in a VR visual world where they never see anything occlude anything, ever. They only see one virtual object move around an otherwise-empty virtual room. The chicks of course imprint on the object. This phase lasts 4 days. Then we move into the test phase. The test initializes when the chick moves towards the virtual object, which starts in the center of the room. Two virtual opaque screens appear on the sides of the room. In the easier variant of the test, the object moves behind one of the screens, and then nothing else happens for a few minutes. The experimenters measure which screen the chick looks at more. The result: all 8 chicks looked more-than-chance at the screen that the virtual object would be behind, than at the other screen, at least for the first 30 seconds or so after the object disappeared from view. In the harder variant, one of the screens moves to the object, occludes the object, then moves back to its starting point. Again, the experiments measure which screen the chick looks at more. Here, 7 of the 8 chicks looked more-than-chance towards the screen that the virtual object would be behind, at least for 15ish seconds. Moving on to experiment 2, the test phase was the same as the easier variant above - the object moved to behind one of the two opaque virtual screens on the sides. But the preceding 4-day training phase was different for these chicks: instead of never seeing any occlusion events, they witnessed thousands of occlusion events, where the object would go behind a virtual opaque screen, and then after a variable amount of time (0-20 seconds), the screens would lower to reveal that the object was where we might expect (for the "natural world" chicks), or had magically teleported to behind the "wrong" screen (the "unnatural world" chicks). (There was no randomization - each chick lived its whole training-phase in either the natural or unnatural world.) Remarkably, all four chicks in the "natural world" and all four chicks in the "unnatural world" spent more time looking at the screen that the object had disappeared behind, rather than the other one, more than chance, at least for the first 15-30 seconds. In fact, remarkably, there was no difference between the natural-world and unnatural-world chicks! How do we make sense of these results? It's always worth asking: maybe the experiment is garbage? I'm far from an expert, but the methodol...

Joseph and Ashley talk about how infants, toddlers and children think about social relationships, how they track who is connected and how they are connected, what we can learn about children from studying animal behavior, and how children in other cultures might think differently about social relationships.Dr. Ashley Thomas is a postdoctoral researcher in Brain and Cognitive Sciences at the Massachusetts Institute of technology (MIT). She is interested in what infants, toddlers and children think and feel about social relationships and social intimacy. She also investigates adults moral judgments and asks questions like where do moral norms come from and how do they change? Ashley is currently a postdoctoral fellow with the Center for Research on Open and Equitable Scholarship at MIT. The fantastic Science paper that was referenced: Thomas, A. J., Woo, B., Nettle, D., Spelke, E., & Saxe, R. (2022). Early concepts of intimacy: young humans use saliva sharing to infer close relationships. Science, 375(6578), 311-315To learn more about Ashley's research please visit her personal website and her lab's website. Her twitter handle is @AshleyJ_Thomas--We are currently conducting a survey to get to know our listeners better and to collect any feedback and suggestions so we could improve our shows. If you have 1 minute or so, please click the link here to submit your response: https://forms.gle/dzHqnWTptW8pSVwMA. All responses will be anonymous!

Why do logic and mathematics work so well in the world? Why do they seem to describe reality? Why do they they enable us to design circuit boards, build airplanes, and listen remotely to handsome and charming podcast hosts who rarely go off topic? To answer these questions, we dive into Chapter 9 of Conjectures and Refutations: Why are the Calculi of Logic and Arithmetic Applicable to Reality?. But before we get to that, we touch on some of the good stuff: evolutionary psychology, cunnilingus, and why Robin is better than Batman. References: Ben on Do Explain with Christofer Lovgren (https://www.doexplain.org/episodes/311-nonuniversal-explainers-with-ben-chugg) Debate (https://www.youtube.com/watch?v=-Hb3oe7-PJ8&ab_channel=HarvardUniversity) between Spelke and Pinker Very Bad Wizards discussing the paper "Oral Sex as Infidelity detection" (episode (https://www.verybadwizards.com/216), paper (https://www.toddkshackelford.com/downloads/Pham-Shackelford-PAID-2013.pdf)). [Sturgeon's Law](https://en.wikipedia.org/wiki/Sturgeon%27s_law#:~:text=Sturgeon's%20law%20(or%20Sturgeon's%20revelation,science%20fiction%20author%20and%20critic.) Eugene Wigner's paper (https://www.maths.ed.ac.uk/~v1ranick/papers/wigner.pdf) The Unreasonable Effective of Mathematics in the Natural Sciences. Stoic versus Aristotilian logic. Here (https://www.uvm.edu/~jbailly/courses/196Stoicism/notes/StoicLogic.html) is a nice discussion of the differences between the two. Rob Wiblin's tweet (https://twitter.com/robertwiblin/status/1345800502093766657) that all probabilities are subjective probabilities (in an otherwise very good thread). Buhler's three functions of language: (i) Expressive, (ii) Signaling, and (iii) Descriptive. See the "Organon Model" (https://en.wikipedia.org/wiki/Organon_model#:~:text=B%C3%BChler's%20work%20influenced%20Roman%20Jakobson,the%20representation%20function%20(Darstellungsfunktion)). Piece (https://www.skeptic.org.uk/2021/06/youre-probably-not-galileo-scientific-advance-rarely-comes-from-lone-contrarian-outsiders/) on Brett Weinstein and Ivermectin. Quotes: _“The indescribable world I have in mind is, of course, the world I have ‘in my mind'—the world which most psychologists (except the behaviourists) attempt to describe, somewhat unsuccessfully, with the help of what is nothing but a host of metaphors taken from the languages of physics, of biology, and of social life.” _ _“In so far as a calculus is applied to reality, it loses the character of a logical calculus and becomes a descriptive theory which may be empirically refutable; and in so far as it is treated as irrefutable, i.e. as a system of logically true formulae, rather than a descriptive scientific theory, it is not applied to reality.” _ Send us the most bizarre use of evolutionary psychology you've seen at incrementspodcast@gmail.com.

Do we really know what implicit bias is, and whether we have it? This is the second episode on our two-part series on implicit bias; the first part was an https://yourparentingmojo.com/captivate-podcast/implicitbias/ (interview with Dr. Mahzarin Banaji), former Dean of the Department of Psychology at Harvard University, and co-creator of the Implicit Association Test. But the body of research on this topic is large and quite complicated, and I couldn't possibly do it justice in one episode. There are a number of criticisms of the test which are worth examining, so we can get a better sense for whether implicit bias is really something we should be spending our time thinking about - or if our problems with explicit bias are big enough that we would do better to focus there first. [accordion] [accordion-item title="Click here to read the full transcript"] References: Banaji, M.R., & Greenwald, A.G. (2002). Blindspot: Hidden biases of good people. New York: Delacorte. Blanton, H., & Jaccard, J. (2008). Unconscious racism: A concept in pursuit of a measure? Annual Review of Sociology 34, 277-297. Blanton, H., Jaccard, J., Strauts, E., Mitchell, G., & Tetlock, P.E. (2015). Toward a meaningful metric of implicit prejudice. Journal of Applied Psychology 100(5), 1468-1481. Brown, E.L., Vesely, C.K., & Dallman, L. (2016). Unpacking biases: Developing cultural humility in early childhood and elementary teacher candidates. Teacher Educators’ Journal 9, 75-96. Cao, J., Kleiman-Weiner, M., & Banaji, M.R. (2017). Statistically inaccurate and morally unfair judgements via base rate intrusion. Nature Human Behavior 1(1), 738-742. Carlsson, R. & Agerstrom, J. (2016). A closer look at the discrimination outcomes on the IAT Literature. Scandanavian Journal of Psychology 57, 278-287. Charlesworth, T.E.S., Kurdi, B., & Banaji, M.R. (2019). Children’s implicit attitude acquisition: Evaluative statements succeed, repeated pairings fail. Developmental Science 23(3), e12911. Charlesworth, T.E.S., Hudson, S.T.J., Cogsdill, E.J., Spelke, E.S., & Banaji, M.R. (2019). Children use targets’ facial appearance to guide and predict social behavior. Developmental Psychology 55(7), 1400. Charlesworth, T.E.S., & Banaji, M. (2019). Patterns of implicit and explicit attitudes: I. Long-term change and stability from 2007-2016. Psychological Science 30(2), 174-192. Chugh, D. (2004). Societal and managerial implications of implicit social cognition: Why milliseconds matter. Social Justice Research 17(2), 203-222. Cvencek, D., Meltzoff, A. N., Maddox, C. D., Nosek, B. A., Rudman, L. A., Devos, T. Dunham, Y., Baron, A. S., Steffens, M. C., Lane, K., Horcajo, J., Ashburn-Nardo, L., Quinby, A., Srivastava, S. B., Schmidt, K., Aidman, E., Tang, E., Farnham, S., Mellott, D. S., Banaji, M. R., & Greenwald, A. G. (in press). Meta-analytic use of Balanced Identity Theory to validate the Implicit Association Test. Personality and Social Psychology Bulletin. Forscher, P.S., Lai, C.K., Axt, J.R., Ebersole, C.R., Herman, M., Devine, P.G., & Nosek, B.A. (2019). A meta-analysis of procedures to change implicit measures. Gawronski, B., & Bodenhausen, G.V. (2017). Beyond persons and situations: An interactionist approach to understanding implicit bias. Psychological Inquiry 28(4), 268-272. Goode, E. (1998). A computer diagnosis of prejudice. The New York Times. Retrieved from https://www.nytimes.com/1998/10/13/health/a-computer-diagnosis-of-prejudice.html Greenwald, A.G., & Lai, C.K. (2020). Implicit social cognition. Annual Review of Psychology 71, 419-445. Greenwald, A.G., & Lai, C.K. (2020). Implicit social cognition. Annual Review of Psychology 71, 419-445. Greenwald, A.G., Banaji, M.R., & Nosek, B.A. (2015). Statistically small effects of the Implicit Association Test can have societally large effects. Journal of Personality and Social Psychology 108, 553-561. Greenwald, A.G., Poehlman,...

很多时候，不用数，一眼看过去，我们往往就能知道前面有几个人、几辆车。在数量很小的情况下，譬如只有1到4个人，我们往往一下就能知道精确的人数。而数量在5及以上的时候，我们虽然也能很快得出一个数量，但这个数量往往是一个粗略的估计，并不精确。识别数量的能力不只是成年人才有，不会说话的小婴儿和小动物也能区分数量的不同，这说明我们感知数量的能力并不来自于语言和数数。那么，我们的认知系统是怎样加工数量信息的呢？我们在识别1、2、3这样小的数量和更大的数量时有什么不同？小数量和大数量的识别来自于不同的数量感知系统还是同一个数量感知系统？在这一期节目中，我们和嘉宾Jenny Wang老师一起聊聊人的数量感知和这方面的有趣研究。 【核心文献】 Cheyette, S. J., & Piantadosi, S. T. (2020). A unified account of numerosity perception. Nature Human Behaviour, 4(12), 1265-1272. Feigenson, L., Dehaene, S., & Spelke, E. (2004). Core systems of number. Trends in cognitive sciences, 8(7), 307-314. 【嘉宾】 Jinjing(Jenny) Wang，Rutgers大学New Brunswick校区心理学系助理教授 【支持我们】 欢迎大家在Patreon和爱发电上支持我们的节目。 Patreon: https://www.patreon.com/jzyd 爱发电: https://afdian.net/@jzyd-cn 【关注我们】 大家可以在mindabit.chat看到我们的最新消息、文献链接和相关资料，也可以关注我们的微信公众号《午后的笛卡尔》。我们的节目目前可以在Apple Podcasts, Google Podcasts, Spotify, Castbox, Pocket Casts, AnchorFM等平台收听到。相关平台的登录页面也可以在我们的网站首页的链接找到。大家也可以加入我们的电报频道和电报群（在telegram中搜索 @mindabit和@mindabitchat ），获得最新更新消息并和我们交流。 --- Support this podcast: https://anchor.fm/jzyd/support

Problembaserat lärande (PBL) är en populär undervisningsform som utgår från att eleverna, med mer eller mindre hjälp, själva ska lösa ett problem. Men hur bra fungerar det egentligen? Vad behöver man tänka på för att det ska fungera bättre? I detta avsnitt hamnar vi även i en flippad diskussion om det så kallade flippade klassrummet – och vad detta betyder för PBL. De som var med idag är: Betty Tärning, forskare i Educational Technology Group vid Lunds universitet, och doktor i kognitionsvetenskap, med specialisering inom digitala läromedel. Björn Sjödén, lektor i utbildningsvetenskap vid Högskolan i Halmstad och doktor i kognitionsvetenskap. Han undervisar på lärarutbildningen och forskar om digitalt lärande. Kalle Palm, gymnasielärare i fysik, filosofi och matematik samt kognitionsvetare. Tekniker och producent var Trond A. Tjøstheim. Varje avsnitt är granskat av Agneta Gulz, professor i kognitionsvetenskap vid Lunds och Linköpings universitet. Tillsammans bidrar vi med vetenskapliga referenser till varje avsnitt, för den som vill veta mer. Referenser Arena, D. & Schwartz, D. (2013). Experience and explanation: Using videogames to prepare students for formal instruction in statistics. Journal of Science Education and Technology, 23(4), 538-548. Blikstein, P., & Wilensky, U. (2010). MaterialSim: A constructionist agent-based modelling approach to engineering education. In M. J. Jacobson & P. Riemann (Eds.), Designs for learning environments of the future: International perspectives from the learning sciences (pp. 17-60). New York: Springer. Bonawitz, E., Shafto, P., Gwen, H., Goodman, N. D., Spelke, E., & Schultz, L. (2011). The double-edged sword of pedagogy: Instruction limits spontaneous exploration and discovery. Cognition, 120(3), 322-330. DeCaro, M.S., & Rittle-Johnson, B. (2012). Exploring mathematics problems prepares children to learn from instruction. Journal of Experimental Child Psychology, 113(4), 552-568. Michael, A., Klee, T., Bransford, J., & Warren, S. (1993). The transition from theory to therapy: Test of two instructional methods. Applied Cognitive Psychology, 7(2), 139-154. Schwartz, D., & Bransford, J. (1998). A time for telling. Cognition and Instruction, 16(4), 475-522. Schwartz, D. L., Tsang, J. M., & Blair, K. P. (2016). The ABCs of how we learn: 26 scientifically proven approaches, how they work, and when to use them, kap J. WW Norton & Company.

人一生下来就会哭、会呼吸，男孩子到了青春期就会长胡子，这些能力和成长毫无疑问都是与生俱来的。那么其他一些重要的知识和能力是否也是先天就有的呢？譬如知道红色和蓝色是不同的，明白5块小饼干和10块小饼干不一样多，以及能区分行为的善恶，这些知识和认知能力从何而来呢？你或许会觉得这些都是需要学习的，人之初就如洛克所说的白板一样，什么都没有，一切都要靠后天学习和塑造。想要解决这些知识和认知能力的先天与后天之争，小婴儿是很好的研究对象，毕竟TA们刚刚来到这个世界。小婴儿看起来什么都不懂，什么也不会做，我们很难想象TA能明白数量的差异，育儿专家也会说如果小婴儿看不见妈妈就会以为妈妈消失了从而哭闹，甚至还有专门为“看不见颜色”的小婴儿设计的黑白色卡…… 但是小婴儿们真的什么知识和认知能力都没有吗？这种对婴儿的看法会不会是人类难以摆脱的偏见？抑或是我们缺乏了解婴儿心智的研究方式？ Wang, J., & Feigenson, L. (2019). Is empiricism innate? Preference for nurture over nature in people's beliefs about the origins of human knowledge. Open Mind, 3, 89-100. 【嘉宾】 Jinjing(Jenny) Wang，Rutgers大学New Brunswick校区心理学系助理教授 【支持我们】 欢迎大家在Patreon和爱发电上支持我们的节目。 Patreon: https://www.patreon.com/jzyd 爱发电:https://afdian.net/@jzyd-cn 【关注我们】 大家可以在y2intelligences.com看到我们的最新消息、文献链接和相关资料，也可以关注我们的微信公众号《午后的笛卡尔》。我们的节目目前可以在Apple Podcasts, Google Podcasts, Spotify, Castbox, Pocket Casts, AnchorFM等平台收听到。相关平台的登录页面也可以在我们的网站首页的链接找到。 【内容提要】 [00:04:40] 1岁的小婴儿已经可以把数数和数量联系起来(Wang & Feigenson, 2019b)。婴儿对数量的基本概念可能是今后学习复杂数学概念的基石。 [00:17:07] 两三个月大的婴儿就已经有了对重力的基本认识，TA们知道物体没有支撑物就会往下掉。但是孩子对于重力的理解是随着年龄逐渐完善的(Baillargeon, 1994)。 [00:21:20] 物体恒常性(object permanence)指的是一个物体被藏起来以后，仍然存在，没有消失。皮亚杰(Piaget)开启了婴儿理解物体恒常性的研究，并认为婴儿要在18-24个月才能理解物体恒常性。但是Baillargeon(1985, 1987)通过聪明的实验说明婴儿在半岁之前就已经对物体恒常性有了很好的理解。 [00:29:48] 通过调查网民、研究者以及参观科技馆的孩子，王老师发现一般人都认为人类的很多知识和认知能力是比较大了以后才获得的，而且通常是学会的。(Wang & Feigenson, 2019) 。但是教育经历似乎可以一定程度矫正这个看法。 [00:46:07] 为什么要争论先天与后天(Nature vs. Nurture)这个问题？ [00:53:10] 了解对于婴儿知识和认知能力的偏见，对我们的生活有什么用？ 【更多参考文献】 Baillargeon, R. (1987). Object permanence in 3½-and 4½-month-old infants. Developmental psychology, 23(5), 655. Baillargeon, R., Spelke, E. S., & Wasserman, S. (1985). Object permanence in five-month-old infants. Cognition, 20(3), 191-208. Baillargeon, R. (1994). How do infants learn about the physical world?. Current Directions in Psychological Science, 3(5), 133-140. Wang, J., & Feigenson, L. (2019b). Infants recognize counting as numerically relevant. Developmental Science, 22(6), e12805. Xu, F., & Spelke, E. S. (2000). Large number discrimination in 6-month-old infants. Cognition, 74(1), B1-B11. --- Support this podcast: https://anchor.fm/jzyd/support

Liz and I discuss her work on cognitive development, specially in infants, and what it can tell us about what makes human cognition different from other animals, what core cognitive abilities we’re born with, and how those abilities may form the foundation for much of our other cognitive abilities to develop. We also talk about natural language as the potential key faculty that synthesizes our early core abilities into the many higher cognitive functions that make us unique as a species, the potential for AI to capitalize on what we know about cognition in infants, plus plenty more.

In this talk, Elizabeth Spelke (Harvard Univ) asks whether studies of human infants provide insights into the origins and nature of uniquely human social cognitive capacities. Do the complex social judgments made by human adults develop from, and build on, simpler systems that are functional in infants? And do non-human animals share any of these systems, and therefore serve as models for studies of their development and functioning at multiple levels of analysis? Recent research on human infants suggests tentative answers to these questions. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 26083]

In this talk, Elizabeth Spelke (Harvard Univ) asks whether studies of human infants provide insights into the origins and nature of uniquely human social cognitive capacities. Do the complex social judgments made by human adults develop from, and build on, simpler systems that are functional in infants? And do non-human animals share any of these systems, and therefore serve as models for studies of their development and functioning at multiple levels of analysis? Recent research on human infants suggests tentative answers to these questions. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 26083]

This CARTA series explores the evolution of “Theory of Mind” (ToM), the ability to impute mental states such as beliefs, desires, and intentions to oneself and others, and how ToM makes us uniquely human. Elizabeth Spelke (Harvard Univ) begins with a discussion about What Makes Humans Different?, followed by Jason Mitchell (Harvard Univ) on Brain Imaging Studies, and Michael Arbib (Univ of Southern California) on Mirror Neurons and More. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 25936]

This CARTA series explores the evolution of “Theory of Mind” (ToM), the ability to impute mental states such as beliefs, desires, and intentions to oneself and others, and how ToM makes us uniquely human. Elizabeth Spelke (Harvard Univ) begins with a discussion about What Makes Humans Different?, followed by Jason Mitchell (Harvard Univ) on Brain Imaging Studies, and Michael Arbib (Univ of Southern California) on Mirror Neurons and More. Series: "CARTA - Center for Academic Research and Training in Anthropogeny" [Science] [Show ID: 25936]

Talk from "Fairness Conference: An Interdisciplinary Reflection on the Meanings of Fairness." Co-sponsored by the Emory Office of the Provost, the Emory Cognition Project, the Center for Mind, Brain, and Culture, and the Emory Center for Ethics, October 18-19, 2012.

Réponses d’E.Spelke aux interventions et mot de la fin par F.Marty et A.Streri.