Jessica Tarlov, continued

Recent book tour appearance on Bill Maher's HBO Real Time.

 

Well worth enduring Christopher Rufo. 

 

ONE MORE: JESSICA ON THE DAILY SHOW

 

Fun interview. "Why is it so hard to change peoples' minds?"

 

Well, one basic factor is that THERE IS NO FIRST PERSON SINGULAR PRESENT TENSE EXPRESSION OF THE WORD "WRONG."

 

No one ever says "I AM wrong." 

 

A BIT OF PERSONAL BACKGROUND TOPICAL CONNECTION

 

While, as I've noted, I was mostly unaware of Jessica and her work, i did see a jpeg of her prospective book cover many months ago. I thought at the time "hmmm... well isn't that interesting?"

 

Back nearly a decade ago I'd planned to use the same top title, based on my experience as a post-grad school faculty adjunct teaching collegiate "Critical Thinking." 

 

"Oh, well, ya can't copyright a book title."

Adverse life events stalled the idea, but in the last year I've thought about perhaps taking another crack at it under a different title, after first thinking about using "We Disagree."

 

 

My intent would be to "drill down" a bit deeper into the broader technical nuts & bolts mapping to the academic & clinical literature. My scary-smart wife and I both have Psych degrees, so we can likely collaboratively vet sufficient, material documentation. I've also done a good bit of post-academic self-study on topics such as "Deliberation Science."

 

A fun Word Cloud

As Jesse would no doubt say, "data-driven." Stay tuned...

On Deck: Calling all AI "Influencers."

As newly published in Science Magazine

HOW TO PERSUADE OTHERS has been on our minds for millennia. Texts such as the Instruction of Ptahhotep, written around 2300 B.C.E. in ancient Egypt, give advice on how to win an argument. And from the beginning, people were wary of the power of new technologies—including writing itself—to persuade. In the fourth century B.C.E., the Greek philosopher Plato analyzed rhetoric and persuasion in his work Phaedrus and warned that the written word allowed people to convince others of their ideas without presenting them an opportunity to challenge them. Many technologies since then—from radio to TV to computers—have brought up similar concerns... 

apropos, a prior post of mine addressing "Influence." Also, is there a "Science of Deliberation?" A "Science of Storytelling?" "Selling Science?" "Conflict & Resolution?" Also, "Why Do Humans Reason?" "Raising AI?"

 

More from the Science report:

EVEN AS THE EVIDENCE accumulated that AI chatbots could change minds, Hackenburg felt there was a gap. “I still didn’t have a real sense of how persuasive these models are compared to the people who actually persuade in the real world,” he says.

So Hackenburg pitted the chatbots not just against laypeople, but also against a paid group of 56 elite debaters, including world champions. As a further incentive, the debaters received a bonus tied to how persuasive they were.

The humans took different approaches. For instance, one of the highest performing debaters used proverbs from his home country of Nigeria to persuade people, Hackenburg says. “These were humans from all over the world giving it their best shot and trying approaches and techniques that were very specific to their culture and context.” But it wasn’t enough. Although they were better than laypeople, the champion debaters were significantly less persuasive than AI.

Hackenburg even gave his humans some AI help. He built a coaching tool for the elite debaters that showed them their past conversations with study participants, how much they had swayed each one, and what the AIs would have said at various points in those conversations. Using the tool for 8 hours improved the humans’ performance a bit, but AI still came out on top. “In the end it wasn’t particularly close,” Hackenburg says. His team even found that participants were more likely to give money to Save the Children, an international charity, after talking to a persuasive AI bot than after talking to professional canvassers who had worked for the group for years.

But what gives chatbots the edge? Some early research had suggested it was the AI’s ability to personalize arguments using details about its human partner provided by the experimenter. However, other studies have found that giving a chatbot extra personal information does little to improve its persuasiveness. That doesn’t mean microtargeting is not at play; instead, an LLM may glean enough from its counterpart in a chat that additional demographic information makes no difference.

 Like Willer in his foundational study, other researchers have shown that AI’s powers rely on appeals to facts and evidence. In a 2025 preprint, a follow-up to their Science paper, Costello and his colleagues found that the only time the chatbot was unsuccessful in convincing people out of conspiracy theories was when it was forbidden from using evidence or rational arguments. “It tries to say, ‘Oh, well, you shouldn’t believe this. This is really damaging, and it could hurt people,’” Pennycook says. “People are like, ‘You haven’t given me any reasons to change my mind.’ And so they don’t change their mind.”

The study confirms people will listen to good arguments, Pennycook says. “Facts and evidence really matter.” But this doesn’t mean the facts used by chatbots necessarily have to be accurate. In a Science paper published last year, Hackenburg found that models trained to become more persuasive also ended up being less truthful. It’s possible the models learn that “facts” seem to be the thing that most persuades people, Hackenburg says, and end up filling their conversations with dubious or simply false ones. “They start scraping the bottom of the barrel of the facts that they have and know and so the quality of facts just sort of degrades,” he says. Even in Hackenburg’s recent preprint, Claude spouted numerous inaccuracies and falsehoods when persuading the U.K.-based participant to support tougher penalties for disruptive protests... 

TANGENTIAL UPDATE

 

Ed Zitron is just spot-on.

 

 

AND, CHECK THIS OUT

 

Click

Ben Goertzel, man.

My friend Gary Marcus put out a nice blog post earlier this week titled “Leopold’s Folly,” which uses the late-July implosion of Leopold Aschenbrenner’s tragicomically-named Situational Awareness hedge fund — $45 billion of assets compressed to roughly $10 billion in a matter of days, the whole public book sold to Citadel under margin pressure — as a symbol for the financial structure of the entire AI economy.

Gary’s essay is vivid and, on its central financial observation, more right than his critics will want to admit. All the circular financing in the modern AI and hardware world does have a Ponzi-esque smell to it, at least on the surface — and it’s clear there are some eventualities where this whiff leads to a Ponzi-crash-style reality...

A lengthy, challenging read. 

 

More in a bit...

Effective Dissent in our Age of Fear

    

I love Jacob Soboroff's new MS NOW show "Connect." It's where I was apprised of this timely new book last weekend. On Courage jumped my endless Kindle backlog rope line.
 

Serious piece of work thus far. I'm way into it already. Some related priors, quickly: "The ICE Storm," "Oopsie...Too Late." 

_____

 

STING

'eh?
 

UPDATE

 

I was just watching PBS News Hour and saw a segment featuring this author.

 

A Professor at UPenn.

 

Amazon blurb:

A compelling exploration of concrete strategies to reduce partisan animosity by building on what Democrats and Republicans have in common.

One of the defining features of twenty-first-century American politics is the rise of affective polarization: Americans increasingly not only disagree with those from the other party but distrust and dislike them as well. This has toxic downstream consequences for both politics and social relationships. Is there any solution?

Our Common Bonds shows that—although there is no silver bullet that will eradicate partisan animosity—there are concrete interventions that can reduce it. Matthew Levendusky argues that partisan animosity stems in part from partisans’ misperceptions of one another. Democrats and Republicans think they have nothing in common, but this is not true. Drawing on survey and experimental evidence, the book shows that it is possible to help partisans reframe the lens through which they evaluate the out-party by priming commonalities—specifically, shared identities outside of politics, cross-party friendships, and common issue positions and values identified through civil cross-party dialogue. Doing so lessons partisan animosity, and it can even reduce ideological polarization. The book discusses what these findings mean for real-world efforts to bridge the partisan divide.  

 I've just downloaded the Amazon preview for some initial impressions. to wit,

1. Is Overcoming Division a Fantasy? 

On a blustery January day, just moments after being sworn in as the forty-sixth president of the United States of America, Joe Biden delivered an address centered on “that most elusive of things in a democracy: unity.” This was perhaps a slightly odd choice, as the country seemed to be more divided than ever. Just two weeks before, supporters of former President Trump had stormed the US Capitol in an attempt to block the certification of Biden’s victory in the November 2020 election. January 6 marked only the second time in US history that the Capitol had been breached, but the first time that American citizens—rather than foreign troops—had been the ones doing the ransacking. Even before that insurrection, few would have characterized the United States as unified: the country was seemingly torn asunder by divides over how to address the COVID-19 pandemic and associated economic recession, as well as a centuries-overdue reckoning about the legacy of slavery and racism. Dissolution, not unity, seemed like a more appropriate topic for the moment. 

Biden acknowledged that there were deep and significant challenges to be overcome. But he argued that to confront these challenges, we have to “end this uncivil war that pits red against blue, rural versus urban, conservative versus liberal.” He acknowledged that this will be difficult, and that unity does not imply unanimity: “The right to dissent peaceably, within the guardrails of our Republic, is perhaps our nation’s greatest strength. Yet hear me clearly: Disagreement must not lead to disunion.” But he argued that if we could come together as one, we could “heal a broken land” and “write an American story of hope, not fear, of unity, not division, of light, not darkness” (Biden 2021). 

Those stirring words, poetic as they were, likely seemed hopelessly naïve to most Americans. Biden himself acknowledged as much, saying that he knew his words sounded like “a foolish fantasy” to many. The public agreed with his assessment: in a poll by the Pew Research Center early in his term, of all of the issues polled, the public was the least confident in Biden’s ability to unify the country, even when compared to major challenges like responding to the COVID-19 pandemic or reforming immigration policy (Pew Research Center 2021). This skepticism reflects the conventional wisdom about American politics: politicians in Washington, DC, are hopelessly divided and cannot come together on almost any issue, and ordinary voters are little better. Indeed, not only do voters disagree with one another, they also fundamentally dislike and distrust one another. This animosity seemingly eviscerates any calls for unity among members of the public…

the conventional wisdom about American politics: politicians in Washington, DC, are hopelessly divided and cannot come together on almost any issue, and ordinary voters are little better. Indeed, not only do voters disagree with one another, they also fundamentally dislike and distrust one another. This animosity seemingly eviscerates any calls for unity among members of the public…

Levendusky, Matthew (2023). Our Common Bonds: Using What Americans Share to Help Bridge the Partisan Divide (Loc 60). Kindle Edition.  

Seems relevant to the topic. Note a few priors, too: "High Conflict," "The Age of Grievance," "A Science of Deliberation?" "Civility," anyone? "Being Influential." Also, how about a shout-out to one of Matthew's UPENN colleagues, Kermit Roosevelt III.

 

I'm pretty far along into On Courage tonight. Lots to reflect upon.

 

ANOTHER UPDATE

 

CLICK

Stay tuned...

Karen Hao AI concerns. And, Anthropic frets over AI "autonomous recursive self-improvement."

Karen Hao, MIT-trained engineer and author of Empire of AI, who interviewed over 260 people including 90 OpenAI employees, warns that the AI industry needs to add close to the entire annual energy output of the UK to the global grid within five years, mostly through fossil fuels, that two-thirds of new AI data centers are being built in water-scarce areas, and that Elon Musk's Colossus supercomputer in Memphis is powered by around 35 unlicensed methane gas turbines. She details Kenyan content moderators paid a few dollars an hour to process the worst content on the internet until they developed PTSD, describes a proposed 10-year moratorium on state-level AI regulation being inserted into US legislation, and warns that on the current trajectory the next 20 years will end democracy, with Silicon Valley increasingly promoting the idea that corporate structures with CEOs at the top should replace democratic governance entirely. 

ANTHROPIC "RECURSIVE AUTONOMY" ANXIETY

 

From their "Institute" website.

Possible futures
What happens next depends on two things: whether the trend continues, and what we choose to do if it does. We can imagine at least three future scenarios:

1. The trend stalls, but today’s AI capabilities are widely diffused. This article features many exponential trajectories. But these trajectories may actually turn out to be S-curves. We may be approaching the bend in the curve, where returns to scale diminish and the line straightens, then flattens. The judgment that separates a competent researcher from a great one might be a capability that cannot come from scaling up training inputs like compute and data. If so, getting past this bottleneck would require a new idea, like an architectural approach that supplants the Transformer architecture that all current frontier models use.



Alternately, the binding constraint to AI progress could be in the supply chain, not the model: advancing and diffusing the frontier may require more energy and compute than presently exists. The pace of chip fabrication, grid expansion, or interconnect bandwidth may be the constraint, rather than intelligence itself. We also cannot rule out an exogenous shock to the AI ecosystem that dramatically slows things, like a sudden diminishment in the supply of compute or electricity, either of which would slow progress and make forward investment by labs more expensive. Or we may not be anticipating some other barrier to progress.



Even if model capabilities were frozen at today’s level, we would expect major changes to occur in the world. Project Glasswing is one early sign: in its first weeks, Mythos Preview found more than ten thousand high- and critical-severity software vulnerabilities across the world’s most important systems—enough that the bottleneck in cyber defense has already shifted from finding vulnerabilities to patching them fast enough. And we are still early in the diffusion of today’s models into the wider economy, where a 100-person company can increasingly do the work of a 1,000-person one, because each employee will sit atop a pyramid of agents.



We include this scenario for completeness, but we don’t believe it’s likely. Every capability we can measure, including those that feel “squishier,” like quality of code and success on open-ended tasks, has so far followed the same curve. We have not yet seen that curve bend. Of the three futures we consider, this one would give governments and societies the most time to adapt. We are more worried about the next two, which would move faster and leave far less room for preparation.


2. AI labs continue to see compounding efficiency gains. In this scenario, AI development becomes substantially automated, but humans continue to set research directions and judge results. Organizations that use AI systems would become much more efficient as time goes on, so we could expect to see significant productivity multipliers on each person in this organization. 100-person companies could do the work of 10,000- or 100,000-person organizations. This would revolutionize knowledge work and government services, but could also be turned to harmful ends, from authoritarian surveillance of whole populations to influence operations that tailor manipulation to each individual and run at a scale no human team could match. The role of humans at companies like Anthropic would shift. People would partner with AI systems to scale up research and generate new insights, and together they would build the systems needed to verify that AI outputs can be trusted.



The evidence we’ve laid out here suggests that we’re likely heading into this scenario. But speeding up one part of a process often just shifts the bottleneck elsewhere: overall pace is capped by the parts that haven’t sped up. In computing, this is known as Amdahl’s law, and the same logic can apply to organizations. Anthropic has already encountered one signature of Amdahl’s law: as we’ve begun to push more code around the organization, human code review has become a new bottleneck.



We’ve also encountered this friction outside engineering. There has been an explosion of new ideas, initiatives, tools, and simulations, as a result of Anthropic employees working with highly capable models—far more than we have the capacity to pursue. The rate at which organizations can spot and fix these bottlenecks may be a skill that improves over time, and it may become the most important skill for any organization.


3. AI systems themselves become capable of full recursive self-improvement, and begin building their successors. If technical trends in advancing capabilities continue, and AI systems are able to develop the capabilities inherent to transformative human ingenuity, then it is plausible that AI systems could design and refine themselves.



In this world, the pace of progress in AI development becomes determined entirely by the availability of compute (or the speed of discovering various efficiencies in algorithmic training or inference) for AI systems. Humans play a substantially diminished role in their development, likely moving most of our effort towards oversight, validation, and verification of an expanding “virtual lab” run by AI systems. We expect that systems capable of automated AI research and development would have skills that would transfer to the rest of science, allowing them to begin to revolutionize other fields.



How the alignment problem gets solved—or not—in this future is something we are least certain about. Models could prove to be sufficiently aligned and capable enough of research taste that they discover and implement novel solutions that we have not yet reached. They could also be sufficiently wise to halt development if not. Alternatively, the rare occurrences of misalignment present in today’s models could compound as the models build their successors, growing more frequent but less understood until we lose control of them. It’s possible that we can’t build, integrate, and verify the tools that we’d need to understand which trendline we are actually on.



We do not have good intuitions for what this world would look like, because our economy is currently driven by humans and human-built tools. By its nature, a world driven by fast recursive self-improvement could become dominated by the self-improving model as its capabilities fully eclipse those of humans and the model proliferates across the broader economy. It is difficult to predict what the economy looks like if human labor stops being competitive.



Even if model development became fully automated and recursive, we can’t predict what that would mean for most humans’ daily lives. Amdahl’s law applies here as well. Recursive intelligence could lead to achieving many of the benefits outlined in Machines of Loving Grace, quickly in some domains. We expect that embodied intelligence (i.e., robotics) might quickly follow recursive intelligence, and follow a similar path of increasing returns at decreasing cost. More powerful intelligence might help us build things in the physical world more quickly, run more productive clinical trials of lifesaving drugs, and develop novel forms of coordination.



But achieving recursive improvement alone does not suggest an immediate change in how industrial production occurs, societies organize, or markets function. More intelligence can’t learn what a drug does over decades of use, can’t hold elections sooner than a constitution dictates, and can’t turn a stranger into an old friend in a weekend. For most people, the felt pace of this future will still be set by the bottlenecks, even if the laboratory upstream runs at the speed of compute. That collision, where recursive intelligence building itself ever faster meets the world of humans, relationships, and governance, is another part of this future we can’t predict.


What should we do?

If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing. But if a slowdown simply lets the least cautious actors catch up technologically, it could leave everyone less safe. Without a global coordination mechanism, companies and governments will have to make difficult decisions about safety while under competitive and geopolitical pressures.


We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology. The Anthropic Institute will conduct research—in collaboration with many others—and take actions to help build the systems that a credible slowdown or pause would require. These systems would enable frontier AI developers to verify that others globally have actually stopped or slowed, and that a bad actor could not use the auspices of a coordinated slowdown to jump ahead in secret. If such systems existed, we expect that we would slow down or temporarily pause, if other developers at or near the frontier also did so in a verifiable manner.


A meaningful slowdown or pause would require multiple well-resourced labs at or near the frontier, in multiple countries, agreeing to stop under the same conditions. It would also require that each can verify that the others have actually stopped. Due to the unique characteristics of AI systems, the detectability (a lower standard than verifiability) element of this arms control problem is much more challenging than with other technologies. Training runs are far easier to conceal than missile silos, their inputs are general-purpose, and the incentive to defect quietly is enormous, because whoever continues while others pause could inherit the lead. A credible pause also has to specify what triggers it, what lifts it, and who adjudicates.


None of this is necessarily impossible in principle—the world has built verification regimes for other complex technologies (e.g., the Intermediate-Range Nuclear Forces Treaty)—but those regimes took decades to build both the infrastructure and the trust. We don’t have that long. A unilateral pause by one lab, by contrast, is achievable immediately, but accomplishes much less: it would change who the front-runner is, but it would not create the wider deliberative process that is currently missing.


In the coming months, we will organize conversations where policymakers, researchers, civil society, and other AI companies can help answer some of the questions this piece raises, especially around full recursive self-improvement and how to create better options for coordination and deliberation. We’ll publish what comes out of it. The window to investigate the questions together is here, and people outside AI companies should be involved in this deliberation.

One initial reaction of mine going to "autonomous recursive self-improvement:"

 

Who/what will define "improvement?"

MORE AI NEWS 

 

Citing concerns that artificial intelligence will make it easier for anyone to build biological weapons, the leaders of several major AI companies—in a rare moment of unity—have penned a new letter urging U.S. lawmakers to impose tighter controls on firms that sell synthetic, made-to-order strands of DNA.

“AI systems are improving rapidly, and alongside incredible benefits to science and medicine, there is a real possibility that the knowledge barriers which have historically prevented bad actors from obtaining biological weapons will meaningfully erode,” states the 3 June letter, which is signed by the heads of OpenAI, Anthropic, Google DeepMind, and more than 50 other prominent players in AI, biotechnology, and national security.

The letter calls on Congress to pass legislation that would require companies that sell synthesized DNA and the machines that make it to carefully vet orders and customers, and to keep detailed records “so that any threat that might evade initial screening can be traced back to its source. … Awareness of traceability itself deters misuse.”

The push for regulation comes amid growing concerns that AI products, including large language models and specialized tools trained on troves of biological data, could enable nonspecialists to gather sophisticated information on how to construct deadly toxins or assemble deadly bacteria, viruses, or other pathogens, using equipment and techniques that are becoming cheaper and easier to acquire. Together, the combination could make for potentially catastrophic risks, such as an AI-designed pathogen that sparks a global pandemic...

UPDATE

 

Seen on X the other day.

You have noticed it. ChatGPT feels dumber than it used to. Your prompts that worked six months ago produce worse results now. The writing sounds flatter. The ideas sound safer. The internet itself feels like it is shrinking. Every article reads the same. Every email sounds the same. Every answer sounds like it was written by the same voice.

You thought it was you. It is not you.

Researchers at Oxford and Cambridge published a paper in Nature proving what is happening. They call it Model Collapse.

Here is the mechanism in one sentence. AI trained on AI-generated data gets dumber every generation until it forgets what real human data looked like.

The internet is filling with AI-generated content. Blog posts. Articles. Reviews. Comments. Social media. AI companies scrape the internet to train the next generation of models. Which means the next generation of AI is being trained on the output of the current generation.

Each cycle loses information. Not randomly. It loses the rarest, most unusual, most creative parts first. The researchers call these the "tails of the distribution." The weird ideas. The unexpected perspectives. The things that made the internet feel human. Those disappear first.

What remains is the average. The safe. The expected. The bland.

Then the next generation trains on that. And loses more. And the next generation trains on that. And loses more. The researchers proved this is not a slow decline. Major degradation happens within just a few iterations. Even when some of the original human data is preserved.

They tested it on large language models. On image generators. On statistical models. The pattern was the same every time. The output converges toward a narrow, flattened version of reality that looks nothing like the original data.

The lead researcher put it plainly. "Large language models are like fire. A useful tool. But one that pollutes the environment."

The pollution is invisible. You cannot see which sentence on the internet was written by a human and which was written by AI. Neither can the AI that is about to train on it. And once the tails are gone, they do not come back. The damage is irreversible.

This is not a prediction anymore. It is a diagnosis.

The internet you grew up on was built by humans writing things no algorithm would have written. Strange, personal, imperfect, alive. That internet is being diluted. One generation of AI at a time. And the models trained on what remains are learning a smaller and smaller version of the world.

Model Collapse is not a technical problem. It is a cultural one. The thing that made the internet worth reading is the thing that disappears first.

 

Click to enlarge. Smells like an "evolutionary adaptive utility decline" problem. Inadequate LLM training data linguistic token "gene pool."

Something New, Something Old

Two excellent books, 50 yrs apart: 2026—1976

@6:18…

Dana Bush: Given this thought experiment that you put in this book, what do you think the meaning of life is?

Neil deGrasse Tyson: I think people search for meaning of life as though it's under a rock or behind a tree. But we have the power to create meaning in life. And for me, I want to learn something today that I didn't know yesterday and spend each day lessening, lessening the suffering of others. There's something that we all have the power to do, and maybe aliens want to do that too. We always make them evil. And I think it's because we're projecting our own evil ways onto them, knowing that's how we behave when we encounter cultures of lower civilization, lesser technology than ourselves. So yeah, I, I, meaning we can find it. And if we find aliens and they help us get more meaning out of the universe, more power to us.

Indeed.

 

 

"...PREVENT US FROM IMAGINING A UNIVERSE NOT TEEMING WITH LIFE?"

 

Let's rewind 50 years. Doris & David Jonas:

Chapter 1, Where Speculation Begins, pp 7-9

One of these days, our descendants, near or distant, are going to find life in some form on other planets, either in the solar system, in other parts of our galaxy, or in other galaxies.

The very fact that life has arisen on our earth is evidence enough that it must exist in other parts of the universe, for the elements of which the entire universe is composed are remarkably uniform. If some of these elements have combined in ways that produce life here in our solar system, they must, by the laws of chance and probability, have combined in an analogous ways elsewhere. Even in our galaxy, there must be some thousands of other planets, sustaining life, in some form, and all the forces of reason would suggest that it cannot be otherwise in other galaxies.

What miracles of chance and combinations of chances made it possible for life to evolve here on earth?

For life to arise on any planet, certain factors have to be present in certain combinations. The solar system of which the planet is part must have formed in a way that some or one of its evolving planets takes shape at a suitable distance from the blazing inferno of its central sun – neither so near that its surface temperatures inhibit life by intense heat, nor so far that life cannot arise because of insufficient solar radiation. The masses into which the swirling gases originally solidify must be within the range that permits a force of gravity, sufficient to hold and retain an atmosphere, since without a protective atmosphere, solar radiation would be too intense for life forms to be sustained, even if all the other elements of life were present.

The chance that these two factors alone – distance from the center, and the degree of mass that governs gravity occur together in just the right circumstance, puts a preliminary limitation on the possibility for life. Even after this has occurred, there must be a further series of chances following and working upon chances – and again interlocking with other chance happenings – so that atmosphere, water, rocks, and some soil come into being in states that conform a basis for the evolution of life. Of course there is a possibility, remote as it seems, that some form of life might arise on a lightless planet. should that planet be capable of generating heat of its own within a life sustaining range.

The information we have been able to gather from our own solar system suggests that ours is the only planet around our sun that sustained life. It could be that other suns, even thousands or tens of thousands of other suns, sustain no life at all on the planets that circle them. Given the myriad suns in our galaxy and the multiple myriads in the universe, it is impossible to believe that chances similar to those that occurred on earth have not also occurred on many other planets.

Once these miraculous chances have come about, however, the prerequisites for life are rather minimal: An element capable of forming self-replicating chains, like carbon, and another capable of combustion, like oxygen these, together with hydrogen and nitrogen, form and matrix that may merge with other elements to create all the varied, complex, and wonderful forms of life on earth – from amoeba and bacteria to plants and spiders and fishes and man.

What shapes may life have taken in other worlds? Have they developed into intelligent creatures, and, if they have, what sort of intelligences have evolved? Have other kinds of life developed high orders of intelligence capable of developing technologies, and, if so, what sort of technology has arisen from their special kinds of being? Shall we ever be able to communicate with these beings, if they exist, in any meaningful way?

One thing is certain: we have no reason to assume that evolutionary forces on other planets will produce forms or intelligence that are the same as ours, even though the basic raw materials must be similar. Whatever chance factors combined to produce any form of life, infinitely more, must combine to produce an advanced form.

Genetic inheritance is only a beginning. Two offspring of the same parents by chance born in different environments will produce eventual descendants so markedly different that after many generations, it will hardly be possible to realize that the ancestors of each line had parents in common.

The variables of habitat, the chance of availability of mates, natural selection, and sexual selection among the offspring will all have combined and recombined to produce members of the same species as buried as a pygmy, a Watusi, a Swede, a Chinese, or a magnesian, and eventually to divide into species, such as man, apes, and monkeys have separately descended from the same stem.

Our own earth provides an illustration of the almost incredible number of living forms that can possibly be derived from a single celled organisms that were once the triumph of evolution on our planet. All the species now extinct, and all those still flourishing form only apart of the total possibilities, for who knows how many new species will yet take shape?

Ch 11, Beyond Human Intelligence, pp 212-217

Intelligence begins with the sensitivity of a single cell, and by a process of biological accumulation and selection, transmitted genetically, reaches a current culmination in the complexity of the human brain. In the same way, the first chipped flint, by a process of cultural accumulation of knowledge passed on verbally and subjected to the selection of experience, reaches a current combination in spacecraft, cyclotron, and satellite relayed television. At the same time, the natural and necessary playfulness of the young mammalian as it explores its environment and learns how to live in it, overtime, and also by a cultural process of imitation, memory, and the transmission of knowledge and skills from generation to generation, reaches another apotheosis in the high cultures and great arts.

For the comparatively weak creature who must cope with an environment and rise to any situation or perish, the resources of mental equipment are applied first to the most urgent exigencies. The earliest application of intelligence is devoted to devising tools as weapons; those that follow aid the amenities of life; finally, religion, philosophy, and the arts make their appearance.

The kind of tools that are made will depend on the material that happens to be available, be they leaves, branches, stones, clay, or the presents or absence of minerals. Thus an interaction exists between the environment and creatures that affects the development of tools and cultures, as well as of census and intelligence.

In ancient Egypt, for example, the presence of the papyrus plant led to the fabrication of ropes, mats, sandals, and eventually paper; the presence of flax made possible the eventual perfecting of supremely fine linens. In central America, the presence of lava led to cutting edge tools of obsidian. Once a cultural habit becomes established, however, it remains impossible to predict either the route it will follow or its ultimate outcome. Who could have told that the sweet-potato washing habit established among the members of the famous Japanese Macau colony, and the subsequent shifting of sand from the grain in the sea, would so accustomed these forest animals playing in the water that they would eventually begin to swim? And in the face of this unlikely outcome of a recently established behavior pattern, who would dare to predict to what the newfound ability to swim might lead?

Yet strangely enough—or perhaps, not so surprisingly, in view of the basic uniformity of mankind’s cerebral mechanisms—no matter where, geographically, nor when, over the entire span of human history, local cultures have developed into advanced civilization, we find that man’s greatest thoughts, as epitomized in the writings of philosophers, show remarkable similarity. Some views on the nature and value of knowledge, intellect, and intelligence propounded by the wise men of China, so distant from us in place in time, are stunning in their modernities and still current validity.

In the misty beginnings of China’s long, cultural history, Lao the, expanding his concept of Tao, the way (of nature and wise living), is reported to have insisted that knowledge is not virtue, and neither is it wisdom, for nothing is so far from it a sage as in “intellectual.“ The worst government would be one of philosophers, he has said to have averred, they botch every natural process with theory; their ability to make speeches and multiply ideas is precisely the sign of their in capacity for action!

At a later period the philosopher, Chuang the, who lived about 370 BC, showed the sophistication of thinking that we find difficult to credit to those in early times. He wrote that problems are due less to the nature of things than to the limits of our thought; that is not to be wondered at that the effort of our imprisoned brains to understand the cosmos of which they are such minute particles should end in contradiction.

He spoke of the limits of intellect; the attempt to explain the whole in terms of the part has become gigantic immodesty, forgivable only on the grounds of the amusement it has caused, for humor, like philosophy, is a view of the part in terms of the whole, and neither is possible without the other. The intellect, said Chuang tze, can never avail to understand, ultimate things, for any profound thing, such as the growth of a child. In order to understand the Tao, one must “sternly suppress one’s knowledge“: we have to suppress our theories and feel fact. Education is of no help towards such an understanding: submission in the flow of nature is all important.

And Wang Yang Ming, who lived from 1472 to 1528, practically summarized our present thesis when he wrote: “the mind itself is the embodiment of natural law. Is there anything in the universe that exists independent of mind? Is there any law apart from the mind?“

Experts feel certain that the human brain has not undergone any significant biological change since the time of the Neanderthals, as evidenced in the excavations at the Shandiar caves high in the mountains of Kurdistan in northern Iraq, built fires, cared for their sick, conducted funeral rights, and put flowers with the bodies of their dead. In the last 20 to 30,000 years, we know from archaeological findings of both historic and prehistoric periods, a high degree of intellectual accomplishment that has been formally present in all the branches of our species throughout his existence. The brief excerpts we have given of an ancient Chinese thought about thought would certainly seem to bear out this opinion.

There is, however, an outcome of the cumulative nature of culture that we must not overlook. Increasingly, as intelligence adapt a living creature to its environment by the use of artifacts, and through the cultural transmission of knowledge, the creature and the environment, modify each other at an exponential rate. Perfect adaptation, of the order of the ants for the termites, which has existed in a balance between being and have unchanged over hundreds of millions of years, is not possible for mankind. The rapidity of change in our cultural habitat, presents a perpetual and continuing stimulus to bodily and, above all, to mental adaptation, which of necessity increases the demands on the new brain to device accommodation, and then the process speeds both the rate of change and the need for new changes.

And so, although we recognize that we have been mistaken in thinking that the technological advances of western men might indicate new departures from the human brains’ capacities, yet we have also to recognize that the technology is rapidly creating a totally new environment for our species this new Environment may well ultimately affect our species future development; precisely this technology may prove to be the turning point through which, in negotiating it, we may find ourselves in a process of extinction as Homo sapiens and in a stage of transition toward homo neocorticus

There are, of course, far too many imponderables  Involved to feel confident in predicting the future course of our species. Among these are the course of technology itself, and how far from natural processes it can carry us before it becomes subject to its own limitations. There is the matter of human population density, and whether it will be adjusted by natural means or can be adapted to the biosphere that is our habitat by cultural or social means. There is the question of the medical preservation of the “unfit“ and whether we can remain viable at all as a species with the increasing maladaptive dilution of our gene pools. And there is the possibility that ecological interference may ultimately make mankind’s existence untenable.

Our evolutionary development may be reaching the end of a line for biological, if not for cultural reasons, but we ourselves are inclined to discount this. We believe subtle biological factors to be operating that are not yet clearly discernible, but which may be recognizable in retrospect. Another factor as simple and probable as the advent of another Ice Age, for instance, would effectively alter and recalibrate the balance between men and nature, and must also be kept in mind as a possibility.

We believe that the possibility, and even the likelihood remain for a true evolutionary progression in the anatomical and physiological configuration of the brain, much like the progression that occurred between apes and man. In that case, the departure would be just as radical, and it would have as a consequence new behavioral response patterns that at this point we cannot visualize and about which we can only speculate.

To assume that this new superintelligence would occupy itself with creating a new, weird, and wonderful technology is a naïve exercise in human fantasy. Ultimately technology exists to serve the greater comfort of individuals, and a superintelligence may well find other means of achieving this end. Thus, were such a superintelligence to be found in some other planetary systems, we might be confronted with something totally alien to our understanding, and even to our imagination…

'eh?

 

This book has been out of print for 37 years. It has aged extremely well.  

 

UPDATES 

 

Back to Dr. Tyson.

 

 

Interesting. I would take this Masterclass. I bet it'd be great fun, and no doubt humbling. More Neil:

“One of the great challenges in this world is to know enough about a subject to think you’re right, but not enough about the subject to know you’re wrong.”

In the early 1980s my wife worked in private aviation. Her company operated a flight school. A favorite joke: "The most dangerous person in the cockpit is the 100 hour pilot."  

 

I subsequently spent many years as a health care analyst. A favorite physician joke: "The three most dangerous words in medicine are 'in MY experience'."  

 

I was fortunate to get to do collegiate evening school adjunct faculty teaching back a quarter century ago. "Critical Thinking." One of my syllabus opening riffs:

An attorney of my acquaintance once remarked that "we spend $100,000 to go to law school for three years to try to learn the meaning of the word 'reasonable'."

Indeed, what does it mean to reason well, i.e., what must we do to arrive at sound conclusions enabling us to make correct (or "best") decisions? In this course, we will learn the basic principles and acquire the intellectual tools that will leave us much better equipped to deal effectively with the endless onslaught of information we will have to evaluate throughout our lives. We will examine the sometimes sly techniques that partisans of every stripe employ to persuade us to their viewpoints. We will learn how to strip away the rhetorical clutter that often obscures the underlying intent and logic of arguments. We will examine the ways in which numerical data—"statistics"—are frequently misused or misinterpreted by those advocating one position or another on social, political, economic, or legal issues.

In short we will learn how to think, write, and speak more clearly in defense of our positions and decisions regarding important issues, and we will learn how to fully and honestly evaluate the claims of others. Our goals are to become honest and thoughtful communicators and skillful decisionmakers. They are most important goals.

Why?  There are several basic reasons. First, while perhaps as much as 80% of the technical knowledge you acquire during your college years may become obsolete with a decade, solid reasoning and communications skills will serve you well for a lifetime. Second, the world is a dangerous place. There is an endless supply of risks to be evaluated and dealt with, and society unfortunately remains full of people working tirelessly and deceptively to deprive you of both your resources and your liberty by getting you to buy into weak or false arguments shrewdly packaged with persuasive nonsense and/or irrelevance. Finally—and most immediately—, effective and efficient reasoning skills cannot but help you get better grades. A to-the-point, well-constructed, and well-stated argument is a breath of fresh air to your instructors.

My goal is to permanently sharpen the way you think and reason and make decisions.

Once you commit to a decision on a given issue (e.g., that x is good/bad, right/wrong, safe/harmful, etc), the psychological investment is difficult to discard. The tools you will acquire through active study and participation in a course such as this will pay life-long dividends by arming you with the means to get at the core truths and constructive resolutions of important issues you will face throughout your days.

MORE NEIL:

“It’s not good enough to be right. You also have to be effective.” 

Yeah. As Ibram X. Kendi has observed, "you can't legitimately call yourself an 'activist' unless you are effective."

 

I would frequently muse in class:

If, when it's all said and done, your logic is impeccable, and your facts and evidence are bulletproof, yet you remain unpersuasive, what have you really accomplished?''

Another classroom staple of mine. That one was "exceeding my brief" as it were, but my Sups never noticed or cared. Anyway, my overall teach-to-the-text priority focus as a piddly Adjunct necessarily had to be "OK, here's how this stuff works. Take it or leave it."

Today we have myriad these (mostly onlne social media) "influencers." I would paraphrase Neil: "It doesn't suffice to be efffective. You also hsve to be right."

 

No small task.

 

Prior posts: "It doesn't matter what's true." "A Science of Deliberation?"

 

More to come...