Johns Hopkins imagines 2076

Johns Hopkins University (“America’s First Research University”), my alma mater, was founded in 1876. In the current issue of Johns Hopkins Magzine and number of professors imagine the world in 2076: Ben Whitford, What Happens Next?

Getting old:

When Disneyland unveiled its House of the Future attraction in the 1950s, visitors lined up to wander through the MIT-designed plastic shell and gawp at wonders—including a microwave and a wall-mounted TV—designed with young families in mind. Back then, just 8% of Americans were 65 or older, but today this group makes up nearly 20% of the population; by 2076, the proportion is expected to climb to over 27%. To manage that transition, we’ll need a new approach to domestic environments, says Najim Dehak, director of engineering in JHU’s Geriatrics Engineering hub. “Older adults have different needs and different wants,” he explains. “We need to design future houses that can let older adults live safer, longer, and healthier lives.”

On the Bayview campus, Dehak’s team is building a new generation of “houses of the future”: model apartments packed with sensors and AI tools to help older residents. Fifty years from now, Dehak predicts, people will stay independent far longer, using self-driving cars to run errands or meet friends. Arriving home, they won’t fiddle with keys; their homes will recognize them, log their safe return, and automatically open the door. Inside, sensors—from motion detectors to cameras scanning the contents of the fridge—will monitor each resident’s wellbeing, ensuring they eat well, stay hydrated, and keep active. If we aren’t taking care of ourselves, voice-operated artificial intelligence assistants—Dehak’s specialty— will encourage us to grab a snack, call a loved one, or pop on virtual reality goggles for immersive group activities.

Space exploration:

Each new probe builds on insights from previous missions, but the intervening period is determined by planetary alignment. Missions to Saturn, for instance, can be sent only about every 30 years, so by 2076 researchers will likely be digesting data from a hypothetical “Son of Dragonfly” mission in the mid-2060s and deciding what to focus on next. One thing’s for sure: Titan won’t have given up all its secrets by then. Researchers will still be exploring what its complex chemistry and weather reveal about the origins of life on Earth or the likelihood of finding life elsewhere.

“Those are the kinds of questions we’re aiming toward making progress on,” Hörst says.

In coming decades, other flagship probes could include the Europa Clipper, arriving at the Jovian moon in 2030; a mission to Uranus, arriving around mid-century; and the Enceladus Orbilander, which could reach the Saturnian moon in the 2050s. Many of Hörst’s biggest questions— such as whether there’s life in Europa’s buried oceans or what Venus’ surface is really like—will almost certainly take longer to answer, requiring major breakthroughs in robotics and materials science. “I personally would be surprised if we accessed Europa’s ocean or sent a rover to the surface of Venus by 2076,” she says.

Further afield, the study of exoplanets will yield new insights: While thousands of planets have been discovered, there’s an enormous amount still to learn.

Solar panels:

Today, virtually all solar panels are made from silicon, which is cheap, durable, abundant—and only capable, even in theory, of absorbing one third of the energy in any given sunbeam. In practice, most current photovoltaic panels convert barely one-quarter of incoming solar energy into electricity, limiting their usefulness and driving up the cost of clean energy.

By 2076, that could change dramatically, says Susanna Thon, associate professor of electrical and computer engineering. Using nanomanufacturing, layered semiconductors, and other innovative techniques—some of which Thon is testing in her lab—it will soon be possible to harvest energy from a wider range of high- and lowenergy photons, potentially tripling the efficiency of panels. “We have a bunch of strategies, so it’s a technical challenge now,” Thon says.

Beyond AI

If Joshua T. Vogelstein—a polymath whose research spans biomedical engineering, computer science, mathematics, and neuroscience— had a time machine, he’d head to 2076 and ask family and friends their take on artificial intelligence.

“I’ll know we’ve made real progress when the general population—people who aren’t involved in creating AI—are no longer afraid of it,” he says.

Right now, Vogelstein says, we’re in an unsettling place: AI is evolving fast, but we don’t know where it’s heading. Some expect progress to snowball, leading to the “singularity”—a turning point in which machine intelligence leaves humans in the dust. Others believe computers will never achieve humanlike intelligence. “And there’s good support for both claims,” Vogelstein says.

Demystifying AI will require a fuller understanding of intelligence itself, Vogelstein argues. [...] we’ll need to fuse interdisciplinary research spanning neuroscience, human and animal cognition, and neural networks into something akin to the Standard Model used by physicists. “I’d like to think that by 2076 there will be a unified set of theories to explain intelligence writ large,” Vogelstein says.

Notice, however, there's no mention of superintelligence, much less world-wide dominance by our robot overlords.

Quantum weirdness:

Quantum mechanics has been around for a century but continues to challenge researchers, says physics professor Peter Armitage. The field’s core insight—that at the tiniest microscopic levels, the universe is choppy and pixelated, rather than smooth and continuous—quickly leads to mindbending conclusions, with quantum objects teleporting around, influencing one another instantaneously across vast distances, or existing simultaneously as both waves and particles.

The core equations governing quantum mechanics are now well-understood, but new technologies and theoretical advances mean the field’s practical implications are still being explored. “I don’t see any indication we’re at the bottom of this well,” Armitage says. “We’re so busy that it’s like drinking from the fire hose.”

Microrobots investigating your body:

In the 1966 film Fantastic Voyage, scientists shrink to microscopic size to explore the body and treat a patient’s blood clot. We won’t achieve that in the next half-century—but the next best thing, says biomolecular engineer David Gracias, would be intelligent micro-robots that could be swallowed like a pill, allowing them to examine and treat patients from within. “We can send probes into space but don’t have a system to navigate our own body. That’s the big challenge that motivates me,” he says.

Gracias has already developed starfish-like contraptions, each the size of a grain of sand, that pinch onto the intestinal lining to deliver medications more slowly and precisely. Next, Gracias hopes to develop swallowable robots that can take photos or video before selectively performing a biopsy on tissue, enabling noninvasive colonoscopies and ureteroscopies.

Sensation revealed:

When you reach out and feel something—rough or smooth, wet or dry, hard or soft—you’re touching on a mystery that still baffles researchers, says Jeremy D. Brown, associate professor in mechanical engineering. “We still don’t fully understand how haptic sensing really works,” Brown says. “Over the next 50 years, I suspect, scientists will get better at understanding how the touch system orchestrates disparate stimuli to form a percept of the physical world.” That would unlock new ways for humans to interact with machinery and digital tools. [...]

Better haptic technologies could also upgrade medical tools, allowing surgeons using laparoscopic robots to feel what’s happening deep inside the body and maneuver robots as dexterously as their own hands. “Having access to that sensory information naturally changes how you physically interact with tissue in a surgical environment,” Brown says.

There’s more at the link.

Elon Musk's New Pretoria 2150 {Total Recall}

Commencement speakers: Out to lunch & out of touch

Molly Jong-Fast, Why Those Commencement Speakers Deserved Those Boos, NYTimes, June 5, 2026.

Commencement address season hasn’t been going well — for the commencement speakers. [...]

When Eric Schmidt, a former chief executive of Google, told graduates at the University of Arizona about their A.I.-shaped future, the shouting got so intense that he paused and said that graduates feared “that the future has already been written, that the machines are coming, that the jobs are evaporating, that the climate is breaking, that politics are fractured, and that you are inheriting a mess that you did not create.” Mr. Schmidt told them to make the best of it. “The question is not whether A.I. will shape the world. It will. The question is whether you will help shape artificial intelligence.”

Mr. Schmidt’s solution to world-upending technological change is … what? To pull yourself up by your bootstraps? His approach is peak billionaire brain, directed at the young people who have, for the better part of a decade, been treated as woke, lazy, avocado-toast-eating snowflakes. All these speakers just don’t get it. The problem isn’t woke; the problem is work. It’s a lack of social mobility. It’s that college may no longer elevate a graduate to the middle class. It’s that nobody even bothers to pretend that a house, a good job and the ability to start a family are at all guaranteed.

Think of this from the graduates’ perspective: Wealthy old people telling you your future is being pulped by acres and acres of electricity-sucking, water-guzzling data centers feels dystopian because it is. Companies are trying to automate your future away. No wonder you’re furious.

The truth about AI:

Right now, A.I. is in its dark hype period — great for Anthropic’s I.P.O. — but who knows how useful any of this actually will be in the end in creating efficiencies (a.k.a.: replacing the youngs with bots). It’s within young people’s power to stop. Demand regulation of tech companies. Elect people who will legislate that regulation. Organize against data centers in your hometowns.

Don’t just boo — do something.

There's more at the link.

AI won't unfold in society as fast as the Silicon Valley pundits think it will [Tyler Cowen]

From YouTube: 

Economist and author Tyler Cowen delivers a provocative keynote on how AI will reshape growth, work, status, and geopolitics. Mixing clear‑eyed realism with long‑run optimism, he argues that AI is both our “plan A” for avoiding fiscal crisis and a technology that will leave many people disoriented—and some high‑status winners of the old world worse off.

What’s in this video:
—Why AI will radically change jobs and status without causing mass unemployment
—Two big new job categories: running experiments and gathering data for AI
—The “human bottlenecks” that limit AI’s impact to ~2% → ~2.5% growth
—How AI could be “plan A” for stabilizing public debt and avoiding fiscal crisis
—Who gains and who loses: global poor and initiative‑takers vs. elite professionals

Cowen’s message: AI’s benefits are enormous—higher growth, longer lives, more opportunity for the poor—but they come with psychological, political, and institutional friction. If you work in or care about AI, you’re not just building products; you’re helping write the only credible plan for a sustainable and prosperous future.

Recorded live at Sana AI Summit 2026, New York, May 21st, 2026.

Tyler Cowen is imagining that AI will kill the research paper

Here’s roughly the first half of his post:

Imagine taking a macroeconomics paper and adding a little button at the end “Press this button to update this paper with the latest macro data.”

All of a sudden you have multiple papers rather than one, and no single canonical version. It is the latter versions, not created directly by the authors, that people will look at.

Imagine adding another button, to either micro or macro papers “Please rerun these results using what the AI thinks might be five other different yet still plausible specifications.”

Then you have more papers yet.

Ultimately, why not just build a “meta-paper,” using AI, to answer any possible question about the subject area under consideration. This meta-paper would allow the reader, using AI, to make many sorts of modifications and additions to the basic work.

It goes on in that vein. Cowen’s final line:

It is funny, and tragic, how much some of you are still obsessed with writing and publishing “papers.”

And it’s funny how Cowen imagines that future research in economics and “many of the other sciences” will be just like current research, but more, more, more! And be produced by a different mechanism, perhaps, ultimately, by a mechanism without any humans in it whatsoever. 

Look at it this way, if this would actually be possible, and acceptable as normal practice, what does that imply about current practice? Is professional economics a cookie-cutter business? Are economists little more than clerks using fancy mathematics? 

Cowen can’t seem to imagine that the future, aided by AI to be sure, will bring new questions, new theories, new models, that it may bring a whole new intellectual world in comparison to which the current intellectual world will look like the 19th century, if not the 12th. It’s amazing that, despite his knowledge of intellectual history, the history of economics in particular, and his recent historically-oriented books about the great economists and about marginalism, that despite all this he has no sense of what future ideas might be, for they will surely be different from current ideas in ways we cannot anticipate. But then he seems to have little sense of what ideas are except lumps of “stuff” falling from otherwise mysterious trees.

In this he’s pretty much like the rest of the Silicon Valley AI Mob. So many thoughts, all sprung from the same repertoire of ideas with no hint of a new repertoire in the offering. It’s all in the hands of the machines.

India rising in the world, the next 30 years

Ross Douthat interviews Amitav Acharya, NYTimes, Feb. 19, 2026.

Douthat's introduction:

Right now, 21st-century geopolitics seems like it’s defined by the struggle between America and China.

But the major power with the world’s fastest growing economy and largest population isn’t China. It’s India.

And right now, India has a unique role in global politics, doing deals with Europe one day and with Donald Trump the next, all while maintaining a strong partnership with Vladimir Putin’s Russia.

Its large and spreading diaspora gives it a unique cultural influence around the world, one that may only increase as other major powers grow old and people remain India’s most important export. My guest today is a prominent international relations scholar, Amitav Acharya, who’s written about what he calls a multiplex world order. A future where diverse powers compete to shape the world.

Between China and Pakistan:

Douthat: So let’s talk about, then, two concrete expressions of Indian power: The relationship with Pakistan, and the relationship with China.

Let’s say we’re living through a 15- to 20-year period where India’s influence and power are going to increase. What does success for India look like with its less powerful, but nuclear-armed rival Pakistan, and its more powerful neighbor, China?

Acharya: This depends on whom you ask. For foreign policy—

Douthat: I’m asking you.

Acharya: OK. My sense is that for India, if India can achieve the kind of growth and become the third-largest economy, not necessarily overtaking China, but maintaining political system openness and more diplomatic influence, I think that will be quite acceptable to India.

India is not a revisionist power. India is a status quo power. So I think that’s what success would mean. And domestically, at home, generate more employment. But you cannot have the third-largest economy without having a sustainable employment and industrial base.

With Pakistan, it’s terrorism. There is of course Kashmir and other issues, but it’s all linked, from the Indian perspective, to support for terrorism. And they see that. They see the West not really understanding India’s position. And then China’s support for Pakistan — China is the biggest, they say, ironclad relationship with Pakistan. They see that Pakistan will not be as adventurous or as assertive vis-à-vis India without Chinese help.

That’s what gets Indians angry about China. Otherwise, I don’t think there is any dimension that cannot be diplomatically addressed between India and China

Douthat: What changes the situation for the better for India? Is it just economic growth? Or is there a level of military power where India thinks that it could get Pakistan isolated and force China to be friendlier?

Acharya: I think nuclear weapons play a big role here. Pakistan has nuclear weapons. But China is also a much bigger nuclear power.

For a while, Indian foreign policy moved in the direction of ignoring Pakistan and engaging China. So it’s China they have to deal with. China is a true peer competitor rather than Pakistan.

Indian culture and the diaspora:

Douthat: The idea that Indian civilization is something that’s born in India and then spreads around the world is obviously relevant to an age when Indians have spread around the world. Modi has, I think, very explicitly talked about the Indian diaspora as a mode of Indian national influence.

But let’s talk about the diaspora. Let’s talk about America. You mentioned that in the United States, relations have been better than ever, up until very recently. Trump in particular spent a lot of time courting Indian American voters. He did an event with Modi in 2019 — “Howdy Modi” in Texas. It’s an amazing name.

But then, in the second Trump term, there’s been a swing. And it isn’t just a swing where Trump is imposing tariffs on Europe. It’s also a swing where there is this kind of anti-Indian backlash on the right.

Tell me where you think that comes from, but also just talk about how you think Americans see India — or see Indians, I think, is the better way to put it.

Acharya: By the way, don’t forget that Modi had one of the biggest rallies right next to Madison Square Garden.

Douthat: New York as well as Texas. All the centers — yeah.

Acharya: So I think, generally, Modi has used that as a foreign policy tool. It’s partly genuine, but it’s also partly a significant foreign policy asset.

So how about the American perception of India? First of all, Americans don’t know much about India. I’m sorry to say this. India doesn’t strike American imagination the way the Chinese do, and also, in some ways actually, the way the Soviet Union did, because it was a threat for a different reason.

There are many more universities with centers for China studies, Americans going to study in China, getting trained in the language — this goes back to the Cold War period. There’s nothing like that. As a professor, I can tell you that India studies is nothing comparable. American students and American academic institutions, and to some extent, think tanks too, are catching up now. But nothing like China.

As you know, the United States is not a country where there’s a lot of interest in foreign cultures. I can tell you that I have a son who just graduated from school and they studied China, Europe, Rome, Greece. Not much about India. So that’s part of the problem.

Americans don’t go to India as large numbers as tourists. So because of that, we have had this relative ignorance about India and neglect of India. We talk about democracy, but the U.S. and India, the largest democracies in the world — that’s rhetoric. It doesn’t really translate into endearment of India in the American public imagination.

Now you did mention the Indian diaspora, which is quite influential politically, although smaller than China, but more successful economically.

AI for the Next 30 Years: Four kinds of activity that should be pursued

Here’s the prompt I used to elicit a text from Claude:

I want to do a blog post setting forth those four programs. I want it to be between, say, 1000 and 2000 words, no more. It should have an introduction, sections for each of the four programs, and some final remarks. Give it a title like: AI for the next 30 years, an open-ended plan. Assume a college-educated readership that is generally sophisticated. I’m going to put it in my New Savanna blog along with another post in which I present excerpts from Rodney Brooks’ current remarks on technology.

I’ve spent a lot of time over the last three days conceptualizing those four programs, interacting with both ChatGPT 5.2 and Claude 4.5. Those chats, in turn, rest on work that I’ve done with both chatbots over the last three years. Moreover, I have uploaded a fair number of documents to those chatbots, both articles from the formal literature and informal working papers, going back five decades.

Note that AGI is not mentioned anywhere nor did I ask ChatGPT to make dated prediction. Predicting where the earth will be in the solar system in 30 years, that’s easy. We’ve known how to do that since Newton. Predicting the weather 30 years out, very difficult to impossible. But maybe we can come up with rough estimates of average temperature for the year, and precipitation. Predicting the 30-year evolution of a complex socio-cultural-technical system? Not on your life.

I’ve edited Claude’s text in some minor ways and added some links at the end of each section.

AI for the Next 30 Years

Large Language Models represent something fundamentally new in computing: systems that have learned vast amounts about the world but encode that knowledge implicitly, in billions of inscrutable parameters. We can use these systems—often impressively—but we don't truly understand what they know or how they organize that knowledge. It's as if we've discovered a vast wilderness: we can explore parts of it, but we lack comprehensive maps.

Over the past few years, I've been thinking about what it would take to map this territory systematically and transform it from mysterious wilderness into reliable infrastructure. This thinking has crystallized into four parallel research programs, each essential, each reinforcing the others. Unlike the prevailing Silicon Valley vision of one lab developing a superintelligent system that does everything, this is a distributed, collaborative, multi-decade effort requiring both technical innovation and institutional creativity.

Activity 1: Ontology Extraction

The challenge: LLMs generates texts that distinguish between dogs and cats, animate and inanimate, concrete and abstract—but this knowledge exists only implicitly in weight matrices. We need to extract this latent ontological structure and make it explicit and inspectable.

Recent work by Christopher Manning and colleagues at Stanford has shown that neural networks encode rich linguistic structure—syntax trees, for instance—that can be extracted through systematic probing. I'm proposing we extend these methods from linguistic structure to ontological structure: the categories, hierarchies, and affordances that organize conceptual knowledge.

The key insight is that ontology is implicit in syntax. Verbs select for certain kinds of subjects and objects based on categorical presuppositions. "Eat" requires an animate agent and edible patient. These selectional restrictions reveal the categorical structure underneath. By systematically probing syntactic behavior, clustering words by shared patterns, and validating through transformation tests, we can extract the ontologies LLMs have learned.

This work must be distributed across many research groups, each focusing on specific domains—medical ontologies, legal ontologies, physical systems ontologies, and so forth. No single lab has the expertise or resources to map the entire territory. We need shared infrastructure (probing tools, ontology repositories, validation benchmarks) and coordinated standards, but the actual extraction work happens in specialized communities with deep domain knowledge.

The payoff: explicit ontological structure that can be verified, debugged, systematically improved, and integrated with symbolic reasoning systems. We transform opaque neural networks into hybrid systems that combine learning with legible structure.

Some background:

Christopher Manning et al. Emergent linguistic structure in artificial neural networks trained by self-supervision, PNAS 2020, https://www.pnas.org/doi/full/10.1073/pnas.1907367117

William Benzon, ChatGPT: Exploring the Digital Wilderness, Findings and Prospects, https://www.academia.edu/127386640/ChatGPT_Exploring_the_Digital_Wilderness_Findings_and_Prospects (see especially pp. 28-38, 42-44]

Activity 2: Cognitive Models and Multimodal Grounding

The challenge: Extracting ontologies from language gives us how language talks about the world, not how minds represent the world for perception and action. A robot needs more than linguistic categories—it needs grounded representations that integrate vision, touch, motor control, and yes, language, into a unified cognitive model. This distinction is standard in the cognitive sciences, including “classical” symbolic AI. I picked it up in the work I did with David Hays in the 1970s on cognitive networks for natural language semantics. We conceived of language mechanisms as operating on a separate cognitive model—language is an interface to the model, not the container of it. For embodied AI and robotics, this becomes crucial.

Consider a cup. The linguistic ontology tells us: cup is-a container, is-a artifact, can-hold liquids. The cognitive model adds: cylindrical shape with hollow interior, graspable via handle, stable on flat surfaces, rigid, will break if dropped, liquid spills if tilted beyond 45 degrees. This is sensorimotor knowledge grounded in perception and action, not purely linguistic.

Current multimodal systems (like GPT-4V or Gemini) take vision and "linguistify" it—everything gets processed through language. What we need are systems where multiple modalities read and write to a common cognitive model. Vision contributes spatial structure, language contributes categorical relationships, action contributes causal understanding, and they all integrate.

This research connects directly to robotics. A robot exploring a new kitchen needs to build spatial maps, identify affordances, understand causal relationships (that knob controls that burner), and eventually respond to linguistic commands—all drawing on the same underlying world model. The cognitive model is where the "adhesion" component of meaning lives: the grounding in physical reality that pure language systems lack.

Some background: Gary Marcus, Generative AI’s crippling and widespread failure to induce robust models of the world, Marcus on AI, June 28, 2025, https://garymarcus.substack.com/p/generative-ais-crippling-and-widespread

Activity 3: Associative Drift and Discovery

The challenge: Current AI systems are reactive, not curious. They solve problems you give them but don't discover problems worth solving. They lack what I'm calling associative drift—the capacity for open-ended, low-bandwidth exploration that enables serendipitous discovery.

Think about how intellectual discovery actually works. When I searched "Xanadu" on the web years ago, I had no hypothesis—just idle curiosity. When I got 2 million hits, I had a hunch that seemed interesting (though I couldn't articulate why). The opportunity cost of investigating was low, so I poked around. Eventually I discovered distinct cultural lineages (sybaritic via Citizen Kane, cybernetic via Ted Nelson's hypertext project) that revealed something about how cultural memes evolve.

This is fundamentally different from task-directed reasoning. I wasn't trying to solve a predefined problem. I was in a low-bandwidth exploratory mode, sensitive to interesting patterns, following hunches without clear goals. Current LLMs operate only in high-bandwidth mode: given a prompt, they generate detailed responses. They can't "skim" or "wonder" or "notice something odd" without generating full text.

We need architectures that support dual-mode processing: high-bandwidth for focused problem-solving, low-bandwidth for pattern detection during exploration. This requires technical innovations (sparse attention patterns, adaptive computation, salience detection) and new ways of thinking about AI objectives. How do we train systems to explore productively without specific goals?

For robotics, this is essential. A robot with associative drift doesn't just execute commands—it develops intuitions about its environment through undirected exploration, notices regularities, forms hunches about what matters. It becomes genuinely curious rather than merely reactive.

The interesting twist: associative drift needs the other programs. Ontologies provide the structured space that makes certain patterns "interesting" (ontologically distant concepts appearing together). Cognitive models enable embodied drift (noticing patterns through physical interaction). And drift enables discovery in the other programs (finding ontological incoherences, noticing when modalities misalign).

Energy Abundance, Genetic Engineering, Super Intelligence: The world is changing dramatically

The technology is coming, but we can't foresee the social and political consequences. Hossenfelder, however, is skeptical about the survival of current democratic systems, which she discusses about 7 minutes into the video. She doesn't think the European welfare system will survive.

The curse of short-termism

Ben Rhodes, How Short-Term Thinking Is Destroying America, NYTimes, August 11, 2025.

The article reviews this and that about Trump's destructive bombast and the Democrats' hapless incredulity. 

It's been a long time coming:  

In the decades after World War II, the Cold War was a disciplining force. Competition with the Soviets compelled both parties to support — or at least accept — initiatives as diverse as the national security state, basic research, higher education, international development and civil rights. Despite partisan differences, there was a long-term consensus around the nation’s purpose.

With the end of the Cold War, politics descended into partisan political combat over seemingly small things — from manufactured scandals to culture wars. This spiral was suspended, briefly, to launch the war on terror — the last major bipartisan effort to remake government to serve a long-term objective, in this case a dubious one: waging a forever war abroad while making much of American life at home more secure.

By the time Barack Obama took office, a destabilizing asymmetry had taken hold. Democrats acquiesced to the war on terror, and Republicans never accepted the legitimacy of reforms like Obamacare or a clean-energy transition. Citizens United v. F.E.C. led to a flood of money in politics, incentivizing the constant courting of donors more intent on preventing government action than encouraging it. The courts were increasingly politicized. The internet-driven fracturing of media rewarded spectacle and conspiracy theory in place of context and cooperation. Since 2010, the only venue for major legislation has been large tax and spending bills that brought vertiginous swings through the first Trump and the Biden administrations.

The second Trump administration has fully normalized the ethos of short-termism. Mr. Trump does have an overarching promise about the future. But it is rooted in what he is destroying, not what he is building.

A pyramid scheme:

Ro Khanna, a Democratic congressman from Silicon Valley, worries that Democrats fail to understand the resonance of this vision. “We see all the destruction,” he told me, “but what we’re not seeing is that for the Trump voter, this is a strategy of reclaiming greatness.”

Precisely because this is correct as a political diagnosis, Democrats must convey how Mr. Trump’s approach is more of a pyramid scheme than a plan. Cuts to research will starve innovation. Tariffs are likely to drive trade to China. Tax cuts will almost certainly widen inequality. Mass deportations predictably divide communities and drive down productivity. The absence of international order risks more war. Deregulation removes our ability to address climate change and A.I. Mr. Trump is trying one last time to squeeze some juice out of a declining empire while passing the costs on to future generations.

Coherent vision:

Democrats must match the sense of crisis many Americans feel. Mr. Khanna summarized concerns that plague far too many Americans: “I don’t see myself in this future” and “What’s going to happen to my kids?” That existential crisis was the reason Mr. Trump was returned to power; his opposition needs to meet it.

This is not about skipping ahead to the fine points of policy proposals; it’s about a coherent vision. Instead of simply defending legacy programs, we should be considering what our social safety net is for. We should attack wealth inequality as an objective and propose solutions for deploying A.I. while protecting the dignity of human work and the vitality of our children. We need to envision a new immigration system, a clean-energy transition that lowers costs for consumers and a federal government that can once again attract young people to meet national challenges. Think of what a new Department of Education or development agency could do. We can no longer cling to a dying postwar era; we need to negotiate a new international order.

Henry Farrell on science fiction, AI hype, and the need for usable futures

Henry Farrell, We need to escape the Gernsback Continuum, Programmable Mutter, July 2, 2025. The three opening paragraphs:

As I admitted at the time, my review essay on Adam Becker’s More Everything Forever: AI Overlords, Space Empires and Silicon Valley’s Crusade to Control the Fate of Humanity was a bit of a bait-and-switch. Becker’s book explains how the dreams of science fiction have shaped Silicon Valley’s dreams of technology in general. I deliberately made a comparison that was both narrower and more fantastical: emphasizing how debates over AGI resembled the dreams of Renaissance alchemy. In partial redress, here’s a more specific argument about the relationship between science fiction and Silicon Valley.

Again, it’s more a riff on Becker than a bald presentation of his argument, but the connections are much clearer, even if it isn’t quite the same argument that Becker makes. What Becker sees as rooted in 1950s and 1960s science fiction arguably goes back a few decades further: to the fusion of “scientifiction” and technocracy that happened in the early 1930s, right at the beginning of the so-called “Golden Age” of science fiction.

Silicon Valley is trapped in a new version of the Gernsback Continuum - a situation in which it is collectively haunted by the visions of an imaginary future of endless expansion that didn’t happen and never will. Our escape route, as Becker suggests, is to acknowledge the physical and social limits that we can’t escape, and to try to construct better futures within those limits.

Then we have a lot of this and that, about Becker's argument, about the Golden Age of science fiction, William Gibson, Hugo Gernsback, visions of the future, limitless energy, and Andreessen's techno-optimism. Then:

Equally, not all people who embrace this style of thinking are fascists, or even slightly fascist adjacent. If you read the liberal-leaning technocratic utopianism of Demis Hassabis or Dario Amodei, you’ll find the suggestion there too that technology - and in particular AI - is a limitless cornucopia of possibilities. See Hassabis’ WIRED interview a few weeks ago:

If everything goes well, then we should be in an era of radical abundance, a kind of golden era. AGI can solve what I call root-node problems in the world—curing terrible diseases, much healthier and longer lifespans, finding new energy sources. If that all happens, then it should be an era of maximum human flourishing, where we travel to the stars and colonize the galaxy. I think that will begin to happen in 2030.

Again, this leans on a particular reading of science fiction. The future that they aspire to is explicitly the future of Iain M. Banks’ Culture novels, in which vast intelligent AI Minds underpin a civilization in which people can do more or less whatever they want.

Amodei:

I think the Culture’s values are a winning strategy because they’re the sum of a million small decisions that have clear moral force and that tend to pull everyone together onto the same side. Basic human intuitions of fairness, cooperation, curiosity, and autonomy are hard to argue with, and are cumulative in a way that our more destructive impulses often aren’t. It is easy to argue that children shouldn’t die of disease if we can prevent it, and easy from there to argue that everyone’s children deserve that right equally.

Hassabis:

I would recommend “Consider Phlebas” by Iain Banks, which is part of the Culture series of novels. Very formative for me, and I read that while I was writing Theme Park. And I still think it’s the best depiction of a post-A.G.I. future, an optimistic post-A.G.I. future, where we’re traveling the stars and humanity reached its full flourishing.

On the one hand, this is obviously much more attractive, and far less sinister, than the Andreessen version. It’s an optimistic liberal bet on the boundless cornucopia of technology. Banks was a Scots socialist who detested authoritarianism with a passion.

On the other, Banks was making a much more complex and ambiguous argument than the version that Hassabis and Amodei present. The Culture is, to steal Ursula K. Le Guin’s term, an ambiguous utopia, in a universe that is emphatically not a mere backdrop for the playing out of the manifest destiny of mankind.

After some discussion of Iain Banks we get:

As Kim Stanley Robinson (another poet of hard physical limits) emphasizes in his recent work, we are almost certainly not going to be able to spread out among the stars. What we have on this planet is pretty well what we have. That doesn’t mean that we can’t do much better than we are doing. We can achieve greater forms of material abundance. But pretending that the hard problems simply don’t exist, or that they will be solved by some magical technology that is right around the corner, is a recipe for the embrace of fascism at the worst, and starry-eyed ingenuous optimism at the best. As I’ve written before, we need usable futures. But to get there, as Becker argues, we need to discard the imagined futures of a past world whose aspirations and understanding of the world are a very poor fit with the present that we find ourselves in.

Amen. Usable futures. That's what I'm up to:

• Kisangani 2150: Homo Ludens Rising, A Working Paper
• Chapter Outline: Homo Ludens Rising: A Manifesto for the Fourth Arena

Ross Douthat interviews Peter Thiel, who is clueless

Ross Douthat, Peter Thiel and the Antichrist, NYtimes, June 26, 2025.

They start out with economic stagnation:

Douthat: So I want to start by taking you back in time about 13 or 14 years. You wrote an essay for National Review, the conservative magazine, called “The End of the Future.” And basically, the argument in that essay was that the dynamic, fast-paced, ever-changing modern world was just not nearly as dynamic as people thought, and that actually, we’d entered a period of technological stagnation. That digital life was a breakthrough, but not as big a breakthrough as people had hoped, and that the world was stuck, basically.

Thiel: Yes.

Douthat: You weren’t the only person to make arguments like this, but it had a special potency coming from you because you were a Silicon Valley insider who had gotten rich in the digital revolution.

So I’m curious: In 2025, do you think that diagnosis still holds?

Thiel: Yes. I still broadly believe in the stagnation thesis. It was never an absolute thesis. The claim was not that we were absolutely, completely stuck; it was in some ways a claim about how the velocity had slowed. It wasn’t zero, but 1750 to 1970 — 200-plus years — were periods of accelerating change. We were relentlessly moving faster: The ships were faster, the railroads were faster, the cars were faster, the planes were faster. It culminates in the Concorde and the Apollo missions. But then, in all sorts of dimensions, things had slowed.

I always made an exception for the world of bits, so we had computers and software and internet and mobile internet. And then the last 10 to 15 years you had crypto and the A.I. revolution, which I think is in some sense pretty big. But the question is: Is it enough to really get out of this generalized sense of stagnation?

The conversation goes on in that vein, and then:

Thiel: Well, I think there are deep reasons the stagnation happened. There are always three questions you ask about history: What actually happened? And then you have another question : What should be done about it? But there’s also this intermediate question: Why did it happen?

People ran out of ideas. I think, to some extent, the institutions degraded and became risk averse, and some of these cultural transformations we can describe. But then I think to some extent people also had some very legitimate worries about the future, where if we continued to have accelerating progress, were you accelerating toward environmental apocalypse or nuclear apocalypse or things like that?

But I think if we don’t find a way back to the future, I do think that society — I don’t know. It unravels, it doesn’t work.

The middle class — I would define the middle class as the people who expect their kids to do better than themselves. And when that expectation collapses, we no longer have a middle-class society. Maybe there’s some way you can have a feudal society in which things are always static and stuck, or maybe there’s some way you can ship to some radically different society. But it’s not the way the Western world, it’s not the way the United States has functioned for the first 200 years of its existence.

Two things: 1) Back in the 1990s my friend Abbe Mowshowitz was talking about virtual feudalism, which is where he saw us headed. He hired me to ghost an article about that but, alas, he was unable to publish it, so I eventually posted it as one of my working papers: Virtual Feudalism in the Twenty-First Century.

2) I sorta' kinda' agree with Thiel about being stuck. But I think about history in a very different way. I think in terms of cultural evolution, specifically, the theory of cultural ranks that David Hays and I sketched out back in the 1990s. [Here's a brief guide: Mind-Culture Coevolution: Major Transitions in the Development of Human Culture and Society.] At the moment we're stuck "treading water," as it were, in Rank 4, but haven't made it to the next level. Just what that next level will turn out to be, that's not at all clear, & that's where I talk about the Fourth Arena, thus: Welcome to the Fourth Arena – The World is Gifted. When I say that Thiel is clueless, that's what I'm talking about; he has no sense of cultural evolution, of a succession of cognitive architectures, or the mind itself, taken collectively, as a driving force in history.

Back to the conversation, and Homo economicus:

Douthat: So you think that ordinary people won’t accept stagnation in the end? That they will rebel and pull things down around them in the course of that rebellion?

Thiel: They may rebel. Or maybe our institutions don’t work, since all of our institutions are predicated on growth.

Douthat: Our budgets are certainly predicated on growth.

Is that a law of nature, or a contingent matter of historical circumstance?

On the nexus of Silicon Valley, stagnation, and Trump:

Douthat: What did Trump do in his first term that you felt was anti-decadent or anti-stagnation? If anything — maybe the answer’s nothing.

Thiel: I think it took longer and it was slower than I would’ve liked, but we have gotten to the place where a lot of people think something’s gone wrong. And that was not the conversation I was having in 2012 to 2014. I had a debate with Eric Schmidt in 2012 and Marc Andreessen in 2013 and Bezos in 2014.

I was on “There’s a stagnation problem,” and all three of them were versions of “Everything’s going great.” And I think at least those three people have, to varying degrees, updated and adjusted. Silicon Valley’s adjusted.

Douthat: And Silicon Valley, though, has more than adjusted ——

Thiel: On the stagnation question.

Douthat: Right. But a big part of Silicon Valley ended up going in for Trump in 2024 — including, obviously, most famously, Elon Musk.

Thiel: Yeah. And this is deeply linked to the stagnation issue, in my telling. These things are always super complicated, but my telling is — and again, I’m so hesitant to speak for all these people — but someone like Mark Zuckerberg, or Facebook, Meta, in some ways I don’t think he was very ideological. He didn’t think this stuff through that much. The default was to be liberal, and it was always: If the liberalism isn’t working, what do you do? And for year after year after year, it was: You do more. If something doesn’t work, you just need to do more of it. You up the dose and you up the dose and you spend hundreds of millions of dollars and you go completely woke and everybody hates you.

And at some point, it’s like: OK, maybe this isn’t working.

On Mars, AI, and progress, with a conversation between Elon Musk and Demis Hassabis (CEO of DeepMind):

Thiel: Yeah. And the rough conversation was Demis telling Elon: I’m working on the most important project in the world. I’m building a superhuman A.I.

And Elon responds to Demis: Well, I’m working on the most important project in the world. I am turning us into interplanetary species. And then Demis said: Well, you know my A.I. will be able to follow you to Mars. And then Elon went quiet. But in my telling of the history, it took years for that to really hit Elon. It took him until 2024 to process it.

Douthat: But that doesn’t mean he doesn’t believe in Mars. It just means that he decided he had to win some battle over budget deficits or wokeness to get to Mars.

Thiel: Yeah, but what does Mars mean?

Douthat: What does Mars mean?

Thiel: Well, is it just a scientific project? Or is it like a Heinlein, the moon as a libertarian paradise or something like this?

Douthat: A vision of a new society. Populated by many, many people descended from Elon Musk.

Thiel: Well, I don’t know if it was concretized that specifically, but if you concretize things, then maybe you realize that Mars is supposed to be more than a science project. It’s supposed to be a political project. And then when you concretize it, you have to start thinking through: Well, the woke A.I. will follow you, the socialist government will follow you. And then maybe you have to do something other than just going to Mars.

Douthat: So the woke A.I., artificial intelligence, seems like, one, if we’re still stagnant, it’s the biggest exception to the place where there’s been remarkable progress — surprising, to many people, progress.

It’s also the place — we were just talking about politics — where the Trump administration is, I think, to a large degree, giving A.I. investors a lot of what they wanted in terms of both stepping back and doing public-private partnerships. So it’s a zone of progress and governmental engagement.

And you are an investor in A.I. What do you think you’re investing in?

Thiel: Well, I don’t know. There’s a lot of layers to this. One question we can frame is: Just how big a thing do I think A.I. is? And my stupid answer is: It’s more than a nothing burger, and it’s less than the total transformation of our society. My place holder is that it’s roughly on the scale of the internet in the late ’90s. I’m not sure it’s enough to really end the stagnation. It might be enough to create some great companies. And the internet added maybe a few percentage points to the G.D.P., maybe 1 percent to G.D.P. growth every year for 10, 15 years. It added some to productivity. So that’s roughly my place holder for A.I.

It’s the only thing we have. It’s a little bit unhealthy that it’s so unbalanced. This is the only thing we have. I’d like to have more multidimensional progress. I’d like us to be going to Mars. I’d like us to be having cures for dementia. If all we have is A.I., I will take it. There are risks with it. Obviously, there are dangers with this technology. But there are also ——

Now that was interesting, very interesting, Mars as a political project. Hmmmm. And then they launch into a conversation about smart people:

Thiel: But I share your intuition because I think we’ve had a lot of smart people and things have been stuck for other reasons. And so maybe the problems are unsolvable, which is the pessimistic view. Maybe there is no cure for dementia at all, and it’s a deeply unsolvable problem. There’s no cure for mortality. Maybe it’s an unsolvable problem.

Or maybe it’s these cultural things. So it’s not the individually smart person, but it’s how this fits into our society. Do we tolerate heterodox smart people? Maybe you need heterodox smart people to do crazy experiments. And if the A.I. is just conventionally smart, if we define wokeness — again, wokeness is too ideological — but if you just define it as conformist, maybe that’s not the smartness that’s going to make a difference.

I note that smart people aren't going to get anywhere if they're working with the wrong ideas. There were a lot of smart people in the 17th century, but they didn't have radios and airplanes. It's not that they weren't smart enough, rather, the intellectual foundations weren't there for them to work from.

And then they veer off into transhumanism and Christianity and cryonics and and ... the Antichrist? That's where I get off the bus, but you might find it interesting.

Goethe's Faust and late Shakespeare [Generativity Part 2]

Yesterday I'd posted On the nature of love, two unusual songs: Somebody to Love, I Will Always Love You [Generativity Part 1]. During that post I'd mentioned the late romances of Shakespeare and Goethe's Faust. I decided to continue the discussion with Claude, starting with those texts.

With Shakespeare's The Tempest in play it was natural for me to segue to Forbidden Planet, the 1956 science fiction film based on it. That, in turn, led me to current AI doomsters, which is the subject of a piece I published in 3 Quarks Daily back in 2021: From “Forbidden Planet” to “The Terminator”: 1950s techno-utopia and the dystopian future. And that led to this final observation:

But, you know, when I look at our current moment, I can see it as a failure of generativity at the society-wide cultural level. Yes, this technology is wonderful and creative, but it may have a human cost – something I’ve been exploring in terms of an opposition between Homo economicus and Homo ludens. We’re going to need Homo ludens to restore generative to the culture.

That's a profound insight that brings us full circle to your earlier observations about generativity. You're suggesting that our current AI moment represents a kind of cultural stagnation masquerading as innovation - the very thing Erikson warned about when generativity fails.

The Homo economicus vs. Homo ludens distinction is particularly sharp here. Homo economicus builds AI systems primarily to optimize, extract value, automate labor, and increase efficiency - essentially treating human creativity and intelligence as resources to be replaced or enhanced for economic gain. It's a fundamentally extractive rather than generative relationship with technology.

Homo ludens - the playing human - would approach these same technologies with curiosity, creativity, and a spirit of exploration that serves human flourishing rather than just economic optimization. Play is inherently generative because it's about possibilities rather than predetermined outcomes.

Your point about societal-level generativity failure is striking. True generativity is about creating something for the benefit of future generations, but much of our AI development seems driven by shorter-term competitive and economic pressures. We're creating powerful technologies without the generative wisdom to ensure they serve human welfare across generations.

I've put the complete conversation below the asterisks.

* * * * *

Faust

I want to continue with generativity. I’m thinking about Goethe’s Faust. Early in his life he makes a diabolic deal to learn the secrets of the universe. By the end of the story, late in his life Faust is reclaiming land from the sea. He’s become, in effect, a real estate developer. That’s quite a change. But also, it seems to me that’s a generative activity. He’s working for the benefit of his fellows.

That's a brilliant insight into the arc of Faust and a perfect example of how generativity can emerge as the deepest form of human fulfillment, even after a lifetime of other pursuits. In Part I, young Faust is consumed with what we might call narcissistic concerns - his own knowledge, power, and experience. The pact with Mephistopheles is fundamentally about personal gratification, whether intellectual, sensual, or experiential. Even his tragic relationship with Gretchen is largely about his own desires and needs.

But by Part II, elderly Faust has undergone a profound transformation. The land reclamation project represents something entirely different:

From Self to Others: Instead of seeking personal knowledge or pleasure, he's creating something that will benefit future generations - literally making new land where people can live and thrive.

From Consumption to Creation: Rather than taking from the world (knowledge, experience, Gretchen's innocence), he's adding to it, expanding the realm of human possibility.

From Immediate to Enduring: The project isn't about instant gratification but about long-term benefit that will outlast his own life.

This is exactly what Erikson meant by generativity - the shift from "what can I get from life?" to "what can I contribute?" And it's significant that Goethe shows this as Faust's final and most satisfying endeavor. The moment when Faust finally says "Verweile doch, du bist so schön" (Stay, you are so beautiful) isn't when he's experiencing personal pleasure, but when he envisions the future community that will flourish on the reclaimed land.

It's also telling that this generative vision is what finally fulfills the terms of his bargain with Mephistopheles - but in a way that transcends and defeats the diabolic intention. Mephistopheles expected Faust to be satisfied by selfish pleasure, but Faust finds his ultimate satisfaction in service to others. This connects beautifully to your earlier themes about love as something you need to give - Faust's final contentment comes from channeling his energy toward the welfare of future generations rather than his own gratification.

Late Shakespeare

I’m also thinking about Shakespeare late in his career, with the late romances, especially The Winter’s Tale and The Tempest. There we have stories that stretch across two generations. The first generation story ends badly for the protagonist, who ends up isolated, embittered, and also. But that is redeemed in the second generation where he displays generosity toward his children and toward the next generation.

That's a profound observation about Shakespeare's late plays and how they embody this generative transformation. Both The Winter's Tale and The Tempest follow this same pattern you've identified - a story of destructive passion or obsession in the first generation that finds redemption through generative acts toward the second generation.

In The Winter's Tale: Leontes' jealous rage destroys his family - he loses his wife Hermione (apparently), banishes his infant daughter Perdita, and causes the death of his son Mamillius. He spends sixteen years in isolation and penance. But the play's redemption comes through his recognition of Perdita when she returns, and his willingness to bless her marriage to Florizell. His generative act - supporting the young couple's love - literally brings Hermione back to life in that stunning final scene.

In The Tempest: Prospero begins consumed with revenge against those who wronged him, using his magic to control and punish. But his transformation comes through his treatment of Miranda and Ferdinand's love. Instead of using his power for continued vengeance, he orchestrates their romance, blesses their union, and ultimately renounces his magic - freeing Ariel, forgiving his enemies, and preparing to return to the human community. Both protagonists move from:

• Destructive control to nurturing facilitation
• Self-centered grievance to other-centered blessing
• Isolation and power to community and vulnerability

What's particularly striking is that in both plays, the generative act specifically involves blessing the romantic love of the younger generation. The older men don't just tolerate the young people's love - they actively facilitate and celebrate it. This suggests that generativity isn't just about creating something for the future, but about recognizing that the future belongs to others and finding joy in that fact.

Shakespeare himself was writing these plays late in his career, perhaps reflecting his own movement toward this generative perspective - creating works that celebrate renewal, forgiveness, and the passing of the torch to new generations.

Here’s an essay I wrote some years about Shakespeare in his life cycle. You’ll notice that I reference Erik Erikson, but also a lot of other work in psychology.

[Note: I linked to that essay in my introduction.]

This is a fascinating and comprehensive essay that brilliantly connects your earlier observations about generativity in Shakespeare's late plays to a much broader psychological and cultural analysis. Your core insight - that Prospero represents Shakespeare's integration of both masculine and feminine principles - illuminates exactly what you were noticing about The Winter's Tale and The Tempest.

Key connections to our earlier discussion:

Generativity Beyond Middle Age: Your analysis challenges Erikson's age boundaries. While Erikson placed generativity in middle age (40-65), you show Shakespeare's protagonists moving toward generative action across different life stages - and the Jefferson Airplane song suggests young people also feel this drive to give love.

The Triad Structure: Your comparative analysis of Much Ado, Othello, and The Winter's Tale - three treatments of male ambivalence about female sexuality - is brilliant. The progression from external mentors/deceivers to internalized conflict to resolution mirrors the developmental pattern you identified.

Prospero as Integration: Your argument that Prospero is "both mother and father to Miranda" perfectly captures what we discussed about the late romances. He embodies both:

• A "male ethic of rights and revenge"
• A "female ethic of responsibility and relatedness"

Cultural Evolution: Your broader thesis - that Shakespeare helped make the modern nuclear family "psychologically possible" - connects to our discussion of how Eastern spiritual practices evolved in Western culture. Just as tantric concepts were adapted for Western relationship needs, Shakespeare was creating psychological templates for new family structures.

Hoboken 2225, Part 2

In my most recent Friday Fotos, Hoboken 225, Part 1, I posted a group of AI-created images that I created by uploading photographs I had taken and then asking ChatGPT use them as the basis of a futuristic city, perhaps 2225. Those images were all based on photos I took of Hoboken's newest public park, located in the northwest part of the city. The three images below are based on downtown Hokoken.

The first photo was taken in an alleyway, notice the cobblestones and the blizzard of overhead wires, both features from the real image. But the real alleyway did not have any ATMS, or whatever terminal the robot is accessing. The robot, of course, is from the future.

This image is in a communter terminal. Again, another robot. While the terminal does have an exposed industrial ceiling, you don't see all those wires, much less those glowing conduits or whatever they are.

This last image is based on an intersection just outside the terminal. The tall buildings in the distance would be in Jersey City. The planter in the foreground is a real feature of the city; they're all over the place downtown. I have no idea what all those saucers in the sky are. Drones of some sort I presume. Nor do I know what those glittery geometric wireframes are. But Newark St. is a real street.

Friday Fotos: Hoboken 2225, Part 1

I decided to play around with ChatGPT's ability to create images of a futuristic world based on photographs of an existing world. So I uploaded a photograph of the North West Resilience Park in Hoboken, NJ, where I live, along with a prompt. ChatGPT replied with a query about what kind of future I had in mind. I then made some choices and proceeded with more images. 

The photograph immediately below is the first one I uploaded. The next image you see is CahtGPT's transformation of it. The rest of the images are all transforms, all of photographs taken at the same site. 

[Click on a photo to enlarge it.] 

I want you to use this photo as the basis for a science fiction image of the future. I'll be giving you several images and I want them each to be part of the same scene.

Great — so this first image, with people enjoying a splash pad surrounded by foliage and high-rise buildings, will serve as the base scene. You’ve mentioned that this and other images will be part of the same futuristic sci-fi setting. To move forward effectively, I’d like to confirm a few world-building details to guide the transformations:

1. Temporal setting: How far in the future are we? (e.g., 50 years, 200 years, post-singularity?)
2. Tone/atmosphere: Utopian, dystopian, surreal, or ambiguous? Clean or gritty?
3. Technological context: Should I introduce visible signs of advanced tech (e.g., hovercraft, AI companions, climate domes, biotech foliage)?
4. Human presence: Are humans still central? Are there hybrids, digital entities, or alien influences?

Once you confirm your vision, I’ll transform this image into a concept illustration for the sci-fi future, keeping it visually coherent with the other images you'll be sending.

Let’s make it futuristic and go for, say, 2225. Let’s make it ambiguous leaning toward utopia, surreal, mostly clean, but some grit here and there. Yes, I want to see advanced tech and humans will be central. But we may have cyborgs as well (think Ghost in the Shell).