The Future of Everything

In the dotcom era, communication professor Angèle Christin embedded herself in newsrooms, where she witnessed how audience metrics tilted journalism toward viral content over in-depth reporting. Christin now researches the influencer economy and how content creators monetize their production by any of three means – brand sponsorships, engagement-based payments from social media platforms, and direct-to-audience subscriptions, donations, or sales. She says this engagement-based ecosystem steers communication toward what captures attention, not always what best informs. To improve our reeling national dialogue, we must first change the financial model of social media content, Christin tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Angèle Christin, a professor of sociology at Stanford University.

(00:02:28) From Journalism to Social Media

How Angèle’s research moved from journalism to influencers.

(00:03:23) Journalism’s Digital Disruption

How platforms and advertising shifts changed the news industry.

(00:06:16) Metrics in Newsrooms

Why journalists began tracking clicks, traffic, and audience behavior.

(00:09:01) Redefining Success

The tension between editorial quality and online popularity.

(00:14:08) Unbundling Media

How digital platforms changed the way audiences consume news.

(00:15:29) The Pull of Virality

Why going viral can be both rewarding and distorting.

(00:16:22) The Creator Economy

How influencers emerged as a new media ecosystem.

(00:19:09) Studying Influencers Online

How Christin researched creators during the pandemic.

(00:23:59) The Passion Principle

Why many creators begin by sharing expertise or personal experience.

(00:25:44) Influencer Revenue Models

The three main ways creators make money online, and the pitfalls of each model 

(00:33:59) Rethinking Monetization

The case for subscriptions, donations, and direct support.

(00:35:09) Future In a Minute

Rapid-fire Q&A: incentives, social media, and research.

(00:36:23) Conclusion

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Earlier this year, we got to witness the incredible launch and return of Artemis II, a NASA mission meant to lay the groundwork for a future lunar landing. Among the many accomplishments of the Artemis II mission, the crew successfully gathered real-time observations of the Moon that will contribute to our increased understanding of the cosmos. If you were inspired the same way we were, we thought it would be an opportune time to re-share an episode we recorded with astrophysicist Risa Wechsler on the future of the universe. We hope you’ll take another listen and that this episode will help you tap into more of that wonder the Artemis II crew sparked.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to [email protected].

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Stanford Profile: Risa Wechsler

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Risa Wechsler, a professor of astrophysics from Stanford University.

(00:01:30) Big Questions About the Universe

What the universe is made of, how it evolved, and how galaxies formed.

(00:02:15) Mapping the Universe

New surveys and telescopes enabling more detailed cosmic maps.

(00:04:22) What Is a “Map” of the Universe?

2D images, 3D structure, and looking back in time through light.

(00:05:48) Spectroscopy & Redshift

How astronomers measure distance and motion using light.

(00:08:41) Our Place in the Universe

Why there is no clear center or edge in the observable universe.

(00:10:54) A Clumpy Universe

How small early fluctuations led to galaxies and large-scale structure.

(00:12:06) How Galaxies Form

The role of dark matter and gas in building galaxies over time.

(00:14:35) Types of Galaxies

Why galaxies vary in size, structure, and environment.

(00:17:06) Gravity Across Scales

How the same laws govern everything from planets to galaxies.

(00:19:02) What Is the Universe Made Of?

The invisible matter shaping galaxies and cosmic structure.

(00:22:03) Using Maps to Study the Unknown

How large-scale surveys reveal dark matter and energy effects.

(00:24:43) The Milky Way as a Laboratory

Studying nearby galaxies to understand fundamental physics.

(00:26:48) Diversity in Galaxy Formation

How different histories shape galaxies.

(00:28:02) Reading Cosmic History

Using observations to reconstruct galaxy evolution.

(00:28:50) Observing Nearby Galaxies

Why distance matters for studying full galactic systems.

(00:29:17) Conclusion

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Michael Jewett is a pioneer of cell-free biotechnology. Instead of using living microbes as factories, he uses their internal molecular machinery to make valuable proteins, medicines, diagnostics, and other chemicals. Jewett recently used the technique for vaccine production in an approach that could produce up to 150,000 doses from one liter. He believes cell-free biotech could democratize the production of essential medicines, improve water safety, and help convert atmospheric carbon into useful products, among other promising possibilities. “It’s just-add-water biotechnology,” Jewett tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to [email protected].

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Stanford Profile: Michael Christopher Jewett

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Chapters:

(00:00:00) Introduction

Russ Altman introduces Mike Jewett, a professor of bioengineering and chemical engineering at Stanford University.

(00:03:23) What Is Cell-Free Biotechnology?

Using the internal machinery of cells without the cells themselves.

(00:04:20) Removing “Evolutionary Baggage”

Why cells’ natural priorities can conflict with engineering goals.

(00:07:41) Advantages of Cell-Free Systems

From large-scale production to decentralized, on-demand manufacturing.

(00:11:40) Making Proteins Outside Cells

How DNA instructions are used to produce functional proteins.

(00:13:49) Biosensors for Water Safety

Detecting contaminants like lead using engineered proteins.

(00:17:05) Engineering Better Sensors

Improving sensitivity and selectivity through protein design.

(00:20:33) AI in Bioengineering

How data and models accelerate discovery and design.

(00:23:22) Sustainability & Carbon Capture

Turning atmospheric carbon into useful chemicals.

(00:26:18) Building New Biological Pathways

Combining chemistry and biology to create novel production systems.

(00:27:54) From Molecules to Materials

How acetyl-CoA enables fuels, plastics, and other products.

(00:30:51) Teaching Biotechnology

Making biotech accessible through hands-on, “just-add-water” kits.

(00:33:12) Future In a Minute

Rapid-fire Q&A: innovation, collaboration, and the future of biotech.

(00:35:32) Conclusion

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Education researcher Susanna Loeb studies the broad spectrum of learning experience, including ways to recruit and retain expert teachers, how to optimize classrooms, and the impact of technology on learning. She says pandemic-inspired innovations in tutoring have led to greater student engagement and improved learning outcomes. And on the growing influence of AI in education, Loeb counts herself an optimist. She sees it as a tool for good, enhancing personalized learning and supporting teachers. These innovations that didn’t exist a few years ago stand to help students to thrive, Loeb tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to [email protected].

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Stanford Profile: Susanna Loeb

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Susanna Loeb, a professor of education at Stanford University.

(00:02:58) Path into Education

Susanna’s journey from engineering to education and her focus on impact at scale.

(00:04:41) The Field of Learning Science

The different approaches and challenges in education and its research.

(00:07:06) Tutoring After the Pandemic

How COVID exposed learning gaps and accelerated interest in tutoring.

(00:10:14) What Makes Tutoring Effective

The different factors that go into making tutoring effective.

(00:12:16) Spreading Proven Practices

Using proof points and partnerships to drive adoption across districts.

(00:14:00) Building Education Networks

The importance of trusted relationships and communication channels.

(00:14:50) AI in the Classroom

How schools are beginning to adopt AI tools and respond to demand.

(00:16:00) AI & Education

How teachers are leading AI adoption, with limited direct student use.

(00:19:37) A Framework for Using AI

The focus on improving student experiences and personalized learning.

(00:21:23) Studying AI in Real Time

Challenges of evaluating fast-changing tools and the need for rapid testing.

(00:23:22) Partnering with AI Companies

Collaborating with industry to test tools like ChatGPT in schools.

(00:25:26) AI & Tutoring

Blending human tutors with AI support to improve outcomes.

(00:27:22) The Limits of AI Tutors

Why human motivation and relationships remain essential.

(00:28:54) The Future of Education Systems

Balancing innovation with equitable access and student engagement.

(00:30:51) Future In a Minute

Rapid-fire Q&A: optimism, scaling education, and collaboration.

(00:32:54) Conclusion

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Computer scientist Keith Winstein is an expert in how computers communicate. Computer networks create what he calls shared fictions – abstract realities, like a website or a Zoom call, that exist only because the computers on either end agree to act as if they are real. Unfortunately, today’s networks lack a shared notion of a “computation,” which hurts market efficiency in cloud computing and frustrates efforts to hold tech companies accountable for the results of their algorithms. As computational power becomes concentrated in a smaller number of companies, Winstein advocates for a shared language of “computational truths,” defining computations precisely so results are reproducible and auditable. His research group hopes this will lead to greater transparency and accountability in the cloud and, ultimately, to greater confidence in the computations that companies do every day on our behalf. The truth matters, Winstein tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to [email protected].

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Stanford Profile: Keith Winstein

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Keith Winstein, a professor of computer science and electrical engineering at Stanford University

(00:02:56) Why Choose Networking

The appeal of the shared digital “fictions” created by connected computers.

(00:04:22) The Internet’s Impact

The broader societal implications of networking technologies.

(00:05:35) Computational Truth

The concept of tracking how data is produced and verified.

(00:09:18) Misaligned Cloud Computing

How “pay for effort” models create inefficiencies in cloud systems.

(00:13:51) Determining Computational Truth

The need for verifiable computation that produces consistent results.

(00:18:19) Computations & Accountability

How identifying computations could improve trust in systems.

(00:20:56) Collaborating Online

Why latency challenges make online performance collaboration difficult.

(00:24:38) Real-Time Performance Systems

Creating a custom system for musicians to perform together online.

(00:28:00) Latency vs. Bandwidth

Why faster internet speeds don’t necessarily reduce delay.

(00:30:43) Eliminating Latency

How buffering layers in software create unnecessary delay.

(00:32:41) Balancing Audio Quality & Delay

The different trade-offs for musicians, actors, and audiences.

(00:34:20) Rethinking Computer Science Education

The need to bring playfulness and interactivity back into learning.

(00:35:46) The Xylophone-Based Class

Teaching computation through real-time sound and music.

(00:38:34) Future In a Minute

Rapid-fire Q&A: optimism, truth in computing, and innovation.

(00:41:01) Conclusion

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