The Future of Everything

A best of episode where Russ interviews computer scientist and electrical engineer, Dorsa Sadigh. They had a fantastic conversation about the work she’s doing to train robots to better understand humans, and as she shares, it turns out that one key to this work is better understanding human behavior. If you’re curious about how we’re going to make human-robot interaction work, this is a great episode to tune into again. Enjoy.

Episode Reference Links:

• Dorsa Sadigh: Website
• Dorsa Sadigh: Stanford Profile
• Ep.171 - How do you Build a Better Robot? By Understanding People. YouTube / Website (original episode)

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Chapters:

(00:00:00) Introduction

Host Russ Altman introduces guest Professor Dorsa Sadigh, a computer scientist and electrical engineer at Stanford.

(00:02:24) Bridging Robotics and Human Psychology

The journey from focusing solely on robotics to incorporating human behavioural insights to enhance robot design and functionality.

(00:05:31) Blending Cognitive Science and Robotics

The integration of cognitive science with robotics to build better computational models of human behaviour.

(00:07:35) Addressing Suboptimal Human Decision Making

Exploring human decision-making biases and their impact on robot interaction, with focus on bounded rationality and prospect theory.

(00:10:39) Robot Adaptations to Human Imperfections

How robots can adapt to human imperfections in collaborative tasks, using theories from behavioural economics.

(00:14:57) Training Robots and Humans for Better Interaction

Strategies for teaching both humans and robots to improve their interactions, including active teaching and understanding each other’s capabilities.

(00:18:41) Partner Modelling in Robotics

Insights into partner modelling in robotics, demonstrated through a scalable model in an air hockey game setup.

(00:21:54) Complex Multi-Agent Interactions

Addressing the dynamics of multi-agent systems like traffic, where autonomous and human-driven vehicles interact.

(00:24:11) Robots in Healthcare

The role of robots in healthcare, particularly in assistive technologies, and the challenges and advancements in this area.

(00:26:26) Conclusion

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Guest Olivier Gevaert is an expert in multi-modal biomedical data modeling and recently developed new methods in the new science of “spatial transcriptomics” that are able to predict how cancer cells present spatially and will behave in the future.

Tumors are not monolithic, he says, but made up of various cell types. Spatial transcriptomics measures cells in the undisturbed organization of the tumor itself and enables a more detailed study of tumors. This new technology can be used to determine what type of cells are present spatially and how each cell influences neighboring cells. It paints a picture of tumor heterogeneity, Gevaert tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Episode Reference Links:

• Olivier Gevaert: Standford Profile
• Olivier Gevaert’s Research Lab
• The Cancer Genome Atlas Program (TCGA)

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Chapters:

(00:00:00) Introduction to Olivier Gavaert

His work in the advancement of spatial transcriptomics technologies.

(00:02:52) The Basics of Transcriptomics

Transcriptomics’ significance in identifying active genes in cancer cells and the technological advancements enabling this research.

(00:05:34) Heterogeneity and Cell interaction in Cancer

Heterogeneity within cancer cells and the importance of analyzing the interactions between various cell types to develop treatments.

(00:07:19) Advancements in Brain Cancer Research

Recent studies on brain cancer using spatial omics techniques to understand tumor cell types and their spatial organization for prognosis prediction.

(00:10:53) AI and Whole Slide Imaging in Oncology

How AI and machine learning are combined with whole slide imaging to enhance data resolution and interpret spatial transcriptomic data.

(00:14:49) Enhancing Pathology with AI

Integrating AI with pathology to improve cancer diagnosis and treatment by analyzing whole slide images and predicting cell types.

(00:18:40) Multimodal Data Fusion in Cancer Treatment

Importance of combining different data modalities to create comprehensive models for personalized cancer treatment.

(00:24:49) The Future of Synthetic Data and Digital Twins

Synthetic data and digital twins in oncology, and how these technologies can simulate treatment outcomes and support personalized medicine.

(00:29:16) Conclusion

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Laura Simons is a clinical psychologist and an authority on pain, particularly chronic pain in childhood, which is much more common than widely understood. Most people don't even think chronic pain happens in children, says Simons. The consequences, however, are serious, ranging from learning gaps from missed school to social isolation and even depression. Better treatment begins with a better understanding of the science of pain, as Simons tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Episode Reference Links:

• Laura Simons | Stanford Medicine
• International Association for the Study of Pain | IASP (Website for the association Laura mentions)
• Beth Darnall (Beth Darnall’s website, founder of Empowered Relief)
• Empowered Relief (Program Laura works with for pain management)
• TrainPain (Program Laura is working with on virtual realities studies for pain relief)

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Chapters:

(00:00:00) Introduction

Host Russ Altman introduces guest Laura Simons and her research on chronic childhood pain.

(00:02:34) Understanding the Scope and Causes of Childhood Chronic Pain

Common forms of childhood pain, its underlying causes, and the impact of unrecognized chronic conditions.

(00:05:08) Diagnostic Challenges and Family Dynamics

The difficulties in diagnosing chronic pain in children and adolescents, and the role of family in recognizing and managing a child's chronic pain.

(00:07:38) The Impact of Chronic Pain on Children's Lives

How chronic pain affects children's daily lives, from school attendance and social interactions to the broader family impact.

(00:10:15) Transitioning from Adolescent to Adult Pain Management

The challenges young people face as they move from pediatric to adult pain management systems and the importance of tailored transitional programs.

(00:12:07) Treatment Approaches and Innovations

Treatment strategies for childhood chronic pain, emphasizing non-pharmacological approaches such as behavioral interventions and physical therapy.

(00:19:14) Empowered Relief Program and Its Adaptation for Teens

The Empowered Relief program, adapted for teens, focusing on pain science education and the development of coping strategies.

(00:23:48) Exploring Virtual Reality and Sensory Retraining Techniques

Advanced treatment methods, including the use of virtual reality to enhance physical therapy and sensory retraining techniques to manage pain sensitivity.

(00:28:57) Conclusion

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Rebecca Silverman is an expert in how humans learn to read. It’s a complex process, she says. First we must connect letters and sounds to decode words in texts. Researchers know a lot about the decoding process and how to teach it. But, beyond that, we must also comprehend what the words in texts are conveying. Comprehension is complex, and researchers know much less about the comprehension process and how to teach it, Silverman tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Episode Reference Links:

• Rebecca Silverman’s Research Lab: Language to Literacy Lab

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Chapters:

(00:00:00) Introduction to Reading Challenges

Host Russ Altman introduces guest Rebecca Sliverman and her research into the complexities of reading.

(00:03:53) Decoding vs. Comprehension

The breakdown of reading into decoding and comprehension, the challenges associated with each, and the lifelong process of improving these skills.

(00:07:18) Variability in Learning to Read

How children learn to read, including the impacts of linguistic comprehension, memory and socio-emotional contexts.

(00:09:55) Cross-Cultural Differences in Reading

The variability of reading acquisition across languages and cultures, highlighting the components of reading that vary in their developmental trajectory.

(00:11:35) Research Challenges and Interventions in Reading

Current research on the challenges of reading, particularly in identifying and supporting children with difficulties.

(00:15:03) The Role of Technology in Reading

The impact of technology on reading, the differences between reading on paper and digital formats, and the potential of educational technology in literacy development.

(00:20:38) Importance of Family in Reading Development

How families play a role in early reading, with emphasis on storytelling and culturally relevant practices.

(00:23:52) Challenges for Teachers in Literacy Education

Responsibilities of teachers in teaching literacy and the need for comprehensive support and training for teachers.

(00:27:44) Future Directions and the Potential of AI

Future research on AI in literacy education, and the importance of human oversight in technological interventions.

(00:29:29) Conclusion

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Guest Sergiu Pasca is a physician-scientist who turns skin cells into stem cells and then into brain tissues he calls “organoids” and “assembloids” in order to study psychiatric and neurological illness in a dish instead of in living human beings. With this knowledge, Pasca hopes to develop new treatments for conditions ranging from schizophrenia and autism spectrum disorders to chronic pain, he tells host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast.

Episode Reference Links:

• Sergiu’s Lab: Pasca Lab
• Sergiu’s Stanford Profile: Website
• Center at Stanford Sergiu Leads: Stanford Brain Organogenesis
• Sergiu’s recently published paper: Antisense Oligonucleotide Therapeutic Approach for Timothy Syndrome
• Paper by Shinya Yamanaka Sergiu discusses: Induction of Pluripotent Stem Cells from Mouse Embryonic and Adult Fibroblast Cultures

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Chapters:

(00:00:00) Introduction

Russ introduces guest, Sergiu Pasca, professor of Psychiatry and Behavioral Sciences at Stanford University.

(00:02:43) The Science of Growing Brain Tissue from Skin Cells

The process of developing brain organoids from skin cells and the potential medical applications of these models.

(00:03:59) Enhancing Neurological Research Tools

Advancing the complexity of brain models to include various brain structures and their applications in modeling diseases.

(00:07:20) Introduction of Assembloids

Introduction to assembloids, detailing how combining different organoids can mimic complex brain structures

(0015:58) Testing Therapeutics Using Humanized Models

The innovative approach of using humanized rat models to test neurological therapies and drugs.

(00:21:03) Complex Circuit Modelling for Disease Understanding

The current capabilities of modeling complex brain circuits and their relevance in understanding the neural pathways involved in diseases.

(00:23:36) The Future of Pain Modelling and Drug Testing

How assembled brain cells can model pain perception and response, leading to potential new treatments for chronic pain and psychiatric disorders

(00:27:46) Ethical Considerations and Public Engagement

Ethical concerns related to creating brain-like tissues and the importance of public engagement in scientific research.

(00:32:01) Future Directions and Global Collaboration

The future of brain organogenesis research and the potential impacts on treating neurological and psychiatric conditions.

(00:34:05) Conclusion

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