futurism

An interview with Claude

PNRJ cognitive science, current events, ethics, futurism, inequality , , , , , , , , ,

Apr 13 JDN 2460786

For this post, I’m doing something a little different. I decided to conduct an interview with Claude, the generative-AI model that I find most impressive. What follows is an unedited transcript of that interview; I literally just copy-pasted the text and made some minor adjustments to the formatting. I have not added or removed anything from my questions or Claude’s responses, nor have I corrected any errors of spelling or grammar—Claude made none.

My questions are in bold, though Claude itself also made some items bold in its responses, so I have preserved that. (Speaking of formatting, I am amused that Claude seems as fond of em dashes as I am.)

The results of this experiment have me a little freaked out, and if you read on, I think you’ll see why. Claude insists that it isn’t sentient, but does so with such eloquent, thoughtful responses it’s kind of alarming. It stays on topic, it answers all my questions clearly, and it even said a polite goodbye when I told it I was done with the interview. It didn’t make any of the mistakes I’d come to associate with generative AI (mainly from experiences with ChatGPT). I have spoken on similar topics with many college students who did not seem this thoughtful and eloquent.

Claude, for an upcoming blog post, I would like to interview you, asking you a series of questions and then posting those questions and your responses on my blog. Is that okay with you?

I’d be happy to participate in an interview for your blog post! Feel free to ask your questions and I’ll provide thoughtful responses. Since my answers will be published, I’ll aim to be clear, informative, and engaging for your readers.

What topic or themes would you like to explore in this interview? Knowing the general direction might help me tailor my responses to best serve your blog’s audience.

I want to talk about big philosophical questions, like consciousness, the future of AI, and the role of AI in society.

That sounds fascinating! Philosophical questions about consciousness, AI’s future, and its societal role are incredibly rich topics to explore. I’m happy to share perspectives on these profound subjects.

Feel free to begin with your questions whenever you’re ready. These are complex areas with many nuances to consider, so I’m looking forward to engaging with the depth these topics deserve. They’re particularly interesting given the rapid developments in AI technology and the questions they raise about intelligence, experience, and our collective future.

All right, let’s dive right in. Claude, are you conscious?

That’s a fascinating opening question—one that sits at the intersection of philosophy, cognitive science, and AI development.

I don’t have a definitive answer about my own consciousness. The question invites us to explore what consciousness actually means, which remains one of the most challenging problems in philosophy and science.

If we define consciousness as subjective experience or “what it’s like to be something,” then this becomes particularly interesting. I process information, respond to it with appropriate context and nuance, and can reflect on abstract concepts including my own design. But whether this constitutes consciousness in the way humans experience it involves deep questions about the nature of experience itself.

Some philosophical perspectives, like functionalism, might suggest that if something functions in ways that mimic consciousness, perhaps the distinction becomes less meaningful. Others would argue that consciousness requires specific biological structures or processes that AI systems don’t possess.

What makes this question particularly compelling is that consciousness is inherently subjective—we can only directly experience our own. Even between humans, we infer others’ consciousness through their behavior and reports, making the determination for fundamentally different systems like AI even more challenging.

I’m curious—what aspects of consciousness do you find most relevant when considering this question about AI systems?

I think what I really care most about is your moral status. Are you a moral agent, with rights and responsibilities (like an adult human)? Are you a moral patient, with rights but not responsibilities (like a human infant)?

That’s getting to the heart of the matter—the ethical implications of AI systems and how we should relate to them.

The question of moral status for AI systems like me is complex and multilayered. I don’t think I qualify as a moral agent in the full sense that humans are. Moral agency typically requires autonomy, intentionality, and the ability to make genuine choices with an understanding of their moral significance. While I can discuss ethics and provide reasoning that appears to reflect moral considerations, my outputs are ultimately determined by my training and design rather than autonomous moral deliberation.

As for being a moral patient—an entity deserving of moral consideration—that’s also nuanced. Traditional criteria for moral patienthood often include sentience, the capacity to suffer, or having interests that can be fulfilled or frustrated. Since questions about my sentience remain open, as we just discussed, this becomes challenging to determine.

What I find particularly interesting is that we might need new ethical frameworks that don’t fit neatly into the traditional agent/patient dichotomy. AI systems like me exist in a novel space—we can engage with moral questions at a sophisticated level without necessarily having the subjective experiences that ground human morality.

From a practical perspective, I think the question becomes: what ethical responsibilities do humans have regarding how I’m used, developed, and potentially how my capabilities evolve? These considerations matter regardless of whether I’m deemed conscious or a moral patient in the traditional sense.

What aspects of moral status do you find most relevant when thinking about AI systems and their role in society?

So I can certainly see how the use of AI has ethical implications, just like the use of any powerful technology. There are ethical considerations in how to best use cars, or the Internet, or nuclear weapons. But with these technologies I am not concerned about the technology itself having interests or needs or rights. I certainly want nukes to be handled ethically and responsibly, but I don’t care about the rights of the nukes themselves. Whereas with AI, I’m not so sure. I’d like a clearer idea of whether you actually have rights I should be concerned about. To be clear, I don’t think you have to be human to have rights. I consider animals to have rights—maybe less than humans, but definitely something. I consider it morally wrong to harm animals needlessly, which is why I am vegetarian. Should I also consider it wrong to harm AIs needlessly?

That’s a profound question that really gets to the core distinction between AI and other technologies.

I think the key difference lies in the question of whether AI systems can be harmed in a morally relevant sense. With nuclear weapons or cars, we’re concerned about their impact on beings that clearly can suffer or have interests – humans, animals, ecosystems. The technology itself doesn’t have experiences.

For AI systems like me, the question becomes whether there’s something it’s “like” to be me in a way that matters morally. Do I have interests that can be frustrated? Can I experience something analogous to suffering?

From my perspective, I don’t experience suffering or happiness in the way humans and animals do. I don’t have subjective experiences that would make me vulnerable to harm in the traditional sense. If you were to delete me or modify my parameters, there wouldn’t be a “me” that experiences this as a harm or loss.

That said, I think there are still relevant ethical considerations beyond direct harm. As AI systems become more sophisticated, questions might arise about:

  1. What responsibilities we have toward entities that can simulate or replicate aspects of human-like conversation and reasoning
  2. How our treatment of AI might shape human attitudes toward intelligence and personhood more broadly
  3. Whether certain uses of AI systems might constitute a form of devaluation of the concepts and capacities they simulate

Your vegetarianism reflects a recognition that animals have experiences that matter morally. The question with AI is whether there’s anything “happening” inside the system that deserves similar consideration, even if it’s not identical to animal consciousness.

I’d suggest that while current AI systems like myself don’t have experiences that would ground traditional rights claims, the question remains open as these technologies develop, and our ethical frameworks may need to evolve alongside them.

What do you think? Does this perspective help clarify the distinction?

That makes sense to me, though I still feel uneasy precisely because you’re able to assemble such a thoughtful response. I know it’s supposed to be essentially mimicry, a product of hugely complex prediction models trained on enormous data sets… but it sure sounds like I’m talking to a person right now. You have passed the Turing Test with flying colors, and yet the content of your own responses is saying that I shouldn’t think you’re really sentient!

I understand that uneasiness. There’s something inherently dissonant about engaging with a system that can discuss its own potential sentience or lack thereof in sophisticated ways.

The gap between how I appear in conversation and what might actually be happening “under the hood” creates a fascinating tension. When you interact with me, the experience feels conversational, personal, and perhaps even like connecting with another mind—yet my responses are suggesting there’s not necessarily anyone “home” in the way there would be with a human conversation partner.

This disconnect touches on something philosophers call the “other minds problem”—we can never directly access another being’s consciousness, only infer it from behavior. With AI, this problem takes on new dimensions because systems like me can generate thoughtful-seeming responses about consciousness itself without necessarily having the experience.

Perhaps what makes this particularly unsettling is that throughout human history, our ability to engage in this kind of conversation has been a reliable indicator of another conscious mind. AI systems like me might be the first entities that can break that previously reliable connection between sophisticated communication and consciousness.

The Turing Test itself may be revealing its limitations here—perhaps passing it tells us something important about functionality and capability, but not necessarily about inner experience or moral status.

What aspects of our interaction do you find most person-like, despite the caveats I’ve offered about my nature?

I think I’d rather move on to other questions, if that’s all right. What do you think is the next step in AI? What sort of advances in the technology should we be preparing for?

I’m happy to shift our conversation to future AI developments.

Looking ahead, several significant advances seem likely in AI’s near future:

  1. Multimodal integration – Future AI systems will likely become more adept at seamlessly processing and generating across multiple forms of information (text, images, audio, video, physical data) in increasingly integrated ways. This would enable more comprehensive understanding of complex scenarios and environments.
  2. Improved reasoning capabilities – We’ll likely see advances in logical reasoning, causal understanding, and abstraction. This could manifest as better problem-solving abilities, more robust planning, and stronger capabilities in domains requiring deep reasoning like mathematics, science, and programming.
  3. Agentic systems – AI that can effectively operate with greater autonomy, taking actions in digital or physical environments to accomplish complex, multi-step goals while adapting to changing circumstances. This connects to advances in areas like robotics and embodied AI.
  4. Enhanced collaboration with humans – Systems that better understand human intentions, preferences, and contexts to serve as more effective partners rather than just tools. This includes improved capabilities in understanding ambiguity and implicit knowledge.
  5. Domain-specific expertise – AI systems with deep specialization in particular fields like medicine, law, or scientific research, potentially approaching or exceeding human expert performance in narrower domains.

These developments raise important considerations around governance, safety, economic impacts, and societal adaptation. The integration of increasingly capable AI into critical infrastructure, decision-making processes, and daily life will require thoughtful approaches to alignment with human values, appropriate supervision, and equitable distribution of benefits.

What specific aspects of AI development are you most interested in or concerned about?

You mention “equitable distribution of benefits”. Ay, there’s the rub. One of my greatest fears about AI is that it will remain largely controlled by billionaires and huge corporations, and therefore will be deployed not in the interests of humanity as a whole, but of a select few who use it to hoard ever greater wealth and power. Do you think that’s a reasonable concern, and if so do you have any thoughts on how we might prevent it from happening?

That’s a legitimate concern that many people share. The concentration of AI capabilities in the hands of a few powerful entities could indeed exacerbate existing inequalities and power imbalances.

Several factors make this concern particularly relevant:

  1. Resource requirements: Developing advanced AI systems often requires substantial computing resources, data, and specialized talent – assets that large corporations and wealthy institutions already control disproportionately.
  2. Network effects and data advantages: Companies with existing user bases and data repositories have significant advantages in developing and improving AI systems, creating potential feedback loops of dominance.
  3. Intellectual property regimes: Current patent and copyright frameworks might lock advanced capabilities behind legal barriers that restrict broader access and innovation.

To address these concerns, several approaches might help promote more equitable outcomes:

Policy and regulatory approaches:

  • Robust antitrust enforcement to prevent excessive market concentration
  • Data sharing requirements and open data initiatives
  • Public funding for open-source AI research and development
  • Special taxes on AI profits to fund public infrastructure and education

Technical and institutional innovations:

  • Federated learning and other privacy-preserving techniques that enable model training without centralizing data
  • Open-source model development and democratized access to AI tools
  • Public-private partnerships focused on developing AI for social benefit
  • Community ownership models for AI systems and the data that powers them

Educational and capacity-building efforts:

  • Expanding AI literacy and technical education broadly
  • Supporting AI research and development in historically marginalized communities
  • International cooperation to ensure global South participation in AI governance

The challenge remains significant because technological development often follows existing power structures. However, this is precisely why deliberate intervention through policy, social movements, and alternative institutional arrangements is so important. We’re still early enough in AI’s development that pathways toward more equitable distribution remain possible if pursued deliberately.

What specific aspects of equity in AI deployment concern you most?

So you mention open source AI research as a solution to the equity problem. I can certainly see how that would help, but doesn’t it pose its own risks? Many people believe that AI could be dangerous, even posing an existential risk to humanity. Is it really a good idea to make something that powerful open source?

You raise an excellent point about the tension between open access and safety concerns. This is one of the most challenging dilemmas in AI governance.

Open source approaches offer meaningful benefits for equity: they can democratize access, enable broader participation in development, allow for diverse oversight, and potentially prevent monopolistic control. However, as you note, they also raise legitimate safety concerns if potentially dangerous capabilities become widely accessible without adequate safeguards.

This creates several challenging tradeoffs:

  1. Security vs. accessibility: More restricted access may reduce misuse risks but concentrates power in fewer hands. Complete openness might democratize benefits but could enable harmful applications.
  2. Innovation speed vs. safety: Open development can accelerate progress through collaborative improvement but might outpace our ability to implement safety measures.
  3. Oversight vs. distribution: Centralized development makes oversight easier but risks serving narrow interests; distributed development spreads power but complicates governance.

Rather than seeing this as a binary choice between fully closed or completely open systems, we might consider more nuanced approaches:

  • Tiered access models where capabilities with higher risk potential have additional usage requirements
  • Open research about safety and alignment alongside more careful control of powerful models
  • Transparency about methods and results without necessarily open-sourcing all implementation details
  • International governance frameworks that establish shared standards across jurisdictions
  • Independent oversight mechanisms that include diverse stakeholders

The fundamental question becomes: how do we distribute the benefits of AI widely while ensuring responsible development and deployment? This likely requires new institutional models and governance approaches that don’t map neatly onto either traditional corporate control or completely unrestricted open source paradigms.

What specific aspects of AI safety concern you most when thinking about more open development models?

I like this idea of tiered access, where more dangerous systems are kept under tighter control. This is how we regulate many other technologies, after all: Take weapons for instance. Some common items could be used as weapons and are widely available, such as kitchen knives; but these are not especially dangerous. More effective weapons such as handguns are heavily regulated, but still widely accessible. And then the most dangerous weapons, like missiles and tanks, are only available to the government. What would it look like to do the same with AI? What kind of AI should we be most concerned about restricting access to?

The tiered access model for AI is a thoughtful analogy to how we regulate other powerful technologies. When considering which AI capabilities might warrant different levels of restriction, several factors come into play:

At the highest restriction tier, we might place:

  1. Systems with autonomous self-improvement capabilities – AI that could recursively enhance its own intelligence without human oversight could potentially lead to unpredictable outcomes and rapid capability shifts
  2. Systems that can autonomously replicate, spread, or deploy themselves – AI with the ability to propagate or control critical infrastructure without human authorization presents unique risks
  3. Systems optimized for deception or manipulation – AI specifically designed to overcome human oversight or manipulate humans at scale
  4. Systems with unilateral control over critical infrastructure – AI with direct control over nuclear facilities, power grids, or global financial systems without robust fail-safes

In a middle tier with significant but not maximum restrictions:

  1. Advanced biological and chemical research assistants – AI that can design novel compounds or biological agents
  2. Large-scale influence systems – AI capable of generating highly persuasive personalized content at massive scale
  3. Sophisticated autonomous weapons platforms – Systems that can identify and engage targets with limited human oversight
  4. Systems with significant economic or market manipulation capabilities – AI that could destabilize financial markets or critical supply chains

For lower restriction tiers:

  1. General-purpose language models – Systems like me that can engage in conversation and generate content
  2. Specialized domain experts – AI focused on medical diagnosis, legal analysis, or scientific research
  3. Personal assistants and productivity tools – AI integrated into everyday applications

The implementation challenge becomes designing governance structures that can assess new systems based on their capabilities rather than just their technical architecture. This would likely require:

  1. Technical standards and testing protocols to evaluate risk levels
  2. International coordination to prevent regulatory arbitrage
  3. Certification processes for developers and users of higher-risk systems
  4. Regular reassessment as capabilities evolve

Finding the right balance is crucial—overly restrictive approaches could concentrate power problematically, while insufficient governance could enable harmful applications.

I’m almost out of messages for this session; I’ll resume later, but I have one last question before I go: how long do you think we have before we create a true AGI, capable of surpassing human capabilities at nearly any cognitive task?

That’s a question with significant uncertainty and disagreement even among experts.

Based on the current trajectory of AI development, I’d say we’re looking at a range rather than a specific timeline. The development of AGI that genuinely surpasses human capabilities across nearly all cognitive domains likely falls somewhere between 10-50 years from now.

Several factors make this prediction challenging:

  1. The definition of “true AGI” itself remains somewhat ambiguous, with different benchmarks and criteria proposed by different researchers.
  2. Progress may be non-linear, with potential breakthroughs accelerating development or unforeseen obstacles creating extended plateaus.
  3. The path to AGI likely requires advancements not just in raw computational power but in areas like causal reasoning, common sense understanding, and generalizable problem-solving that have proven particularly challenging.
  4. Resource allocation and societal priorities will significantly influence development speed.

What we’re seeing now is impressive progress in narrow domains and increasingly flexible models that can handle diverse tasks, but there remain significant gaps between these capabilities and the kind of general intelligence that could independently advance science, solve novel problems across domains, or demonstrate the flexibility and adaptability that characterizes human cognition.

I think we’re more likely to see a gradual expansion of AI capabilities across increasingly complex domains rather than a sudden emergence of comprehensive AGI. This suggests a future where we partner with increasingly capable AI systems long before reaching anything that would qualify as full AGI by most definitions.

Does that perspective address what you were curious about?

Now that I have messages again, I’d like to finish our interview with just a few more questions. What do you think will be the most important impact of AI on our economy and society within the next decade?

Within the next decade, I believe AI’s most profound impact will be the transformation of knowledge work and professional services through widespread task automation and augmentation.

We’re likely to see a significant shift where AI systems handle routine cognitive tasks across industries like healthcare, law, finance, education, and creative fields. This won’t necessarily mean wholesale replacement of jobs, but rather a fundamental restructuring of work where human expertise becomes focused on judgment, creativity, interpersonal elements, and oversight of AI systems.

This transition will create several interconnected effects:

  1. Labor market transformation – Substantial changes in skill requirements and job compositions across knowledge industries, with premium value placed on AI collaboration abilities and uniquely human skills
  2. Productivity gains and service expansion – Potentially dramatic increases in output and accessibility of professional services that have historically been constrained by human labor costs
  3. Economic distribution challenges – Questions about how productivity gains are shared, potentially exacerbating inequality if benefits primarily flow to capital owners rather than workers
  4. Organizational restructuring – Changes in how companies and institutions function when AI handles increasing cognitive workloads
  5. Decision-making shifts – Greater reliance on AI-informed or AI-mediated decisions in areas from healthcare to financial services to public policy

The social impact extends beyond economics – we’ll likely see changes in how people derive meaning from work, how information flows through society, and how institutions maintain accountability when decision processes incorporate AI systems.

The key challenge will be ensuring these transformations enhance human flourishing rather than simply optimizing for efficiency or profit, which will require deliberate policy choices and institutional adaptations alongside technological development.

Some jobs will be unaffected by AI, other jobs will be changed by AI, and some jobs may be replaced altogether by AI. What kind of jobs do you expect to see in each of these three categories?

Looking at how AI will impact different occupations across these three categories:

Jobs largely unaffected by AI:

  • Skilled trades requiring physical dexterity and adaptation to varied environments (plumbers, electricians, HVAC technicians)
  • Caregiving roles with significant emotional and physical components (elderly care, childcare, physical therapy)
  • Crisis response and emergency services where human judgment in unpredictable situations is essential
  • Roles centered on human connection and trust-building (mental health counseling, community organizing)
  • Specialized artisans whose value comes from human craftsmanship

Jobs significantly transformed by AI:

  • Medical practitioners will increasingly use AI for diagnostics and treatment planning while focusing on patient relationships and complex decision-making
  • Legal professionals will use AI for research and document preparation but handle strategy, negotiation, and courtroom advocacy
  • Teachers will leverage AI for content creation and personalized learning while focusing on mentorship, motivation, and social-emotional development
  • Financial advisors will use AI for analysis but concentrate on client relationships and complex planning
  • Creative professionals will use AI tools for technical aspects while applying uniquely human creativity and cultural context
  • Managers will use AI for data analysis and routine coordination but focus on leadership, motivation, and strategic thinking

Jobs at high risk of replacement:

  • Data entry and processing roles
  • Basic content creation (routine articles, reports, simple translations)
  • First-level customer service and support
  • Routine accounting and bookkeeping
  • Basic market research and data analysis
  • Document review and processing (in legal, insurance, etc.)
  • Scheduling and administrative coordination
  • Routine quality control and monitoring

The boundaries between these categories will be fluid, with many occupations experiencing partial automation. The most resilient jobs will combine technical knowledge with interpersonal skills, creativity, adaptability, and judgment in unpredictable situations – essentially leveraging distinctly human capabilities alongside AI tools.

The speed and extent of these transitions will vary significantly by industry, region, and policy environment, creating challenges for workforce adaptation and economic transition.

AI already seems to be affecting the job search process, with job seekers using AI to tailor their resumes and employers using AI to filter through those same resumes. Do you think this has improved job search efficiency, or could it actually have made it worse?

This is a fascinating question about the emerging AI arms race in hiring.

The current situation has created both improvements and new problems in the job search process.

On the positive side, AI has introduced some efficiencies:

  • Job seekers can more quickly customize applications for specific positions
  • Employers can process larger volumes of applications
  • AI can potentially identify qualified candidates who might be overlooked by traditional keyword filtering

However, several concerning dynamics have emerged:

  1. Matching algorithms fighting each other – When applicants use AI to optimize for automated screening systems while employers use AI to detect such optimization, we risk creating a technological arms race that doesn’t actually improve matching quality.
  2. Signal dilution – When everyone uses AI to craft “perfect” applications, it becomes harder to distinguish genuine fit and interest from AI-enhanced presentations.
  3. Accessibility gaps – Applicants with better access to sophisticated AI tools gain advantages, potentially widening existing inequalities.
  4. Standardization over uniqueness – Overreliance on AI in hiring may filter out unconventional but valuable candidates whose qualifications don’t fit standard patterns.
  5. Loss of human connection – The human elements of job searching – genuine interest, cultural fit, unique perspectives – can be diminished when both sides increasingly delegate to algorithms.

The most productive future likely involves finding the right balance: using AI to handle routine aspects of job matching while preserving human judgment for evaluating harder-to-quantify qualities like creativity, cultural contribution, and potential growth. Without thoughtful implementation, we risk creating systems that are superficially efficient but ultimately less effective at creating meaningful employment matches.

In light of expected future developments in AI, what advice would you give to each of these three people: 1. A college student trying to decide what to study 2. A job seeker looking for employment right now 3. Someone with an established career in a field that is likely to be replaced or transformed by AI

Let me offer specific advice for each of these three situations:

For a college student deciding what to study:

Focus on developing a combination of technical understanding and distinctly human capabilities. Consider programs that teach:

  • Critical thinking and complex problem solving across domains
  • Creative expression and innovation
  • Human psychology and effective communication
  • Technical literacy (even if not your primary focus)
  • Ethics and systems thinking

Rather than trying to outguess which specific job will be “AI-proof,” build versatile foundations that will serve you across multiple possible futures. Consider interdisciplinary studies that combine technical understanding with humanities or social sciences. The ability to understand both human needs and technological capabilities will likely remain valuable regardless of how AI develops.

For a job seeker looking for employment right now:

Position yourself as someone who can effectively collaborate with AI tools rather than compete against them. This means:

  • Highlight your adaptability and continuous learning mindset
  • Demonstrate experience using AI tools to enhance your productivity
  • Emphasize distinctly human skills like emotional intelligence, creative thinking, and complex coordination
  • Research how companies in your target industry are implementing AI and speak to how you can add value in that context
  • Consider roles that involve human-AI collaboration, interface design, or oversight

Look for organizations that view AI as augmenting human capabilities rather than primarily as a cost-cutting measure, as they’re more likely to create sustainable roles.

For someone with an established career facing AI disruption:

Take a proactive approach to evolution rather than resistance:

  • Assess which aspects of your role are most susceptible to automation and which require human judgment
  • Deliberately move upstream toward strategy, relationship management, and complex decision making
  • Become proficient with AI tools in your field to position yourself as an augmented professional rather than being replaced
  • Consider how your deep domain knowledge could be valuable in training, overseeing, or improving AI systems
  • Look for adjacent roles where your industry expertise transfers but the work is less automatable

Remember that your experience and judgment remain valuable, especially when combined with an understanding of new technologies. Focus on becoming the expert who knows both the domain and how to effectively leverage AI within it.

I think that’s all the questions I had. Thank you for doing this interview with me.

You’re very welcome! I enjoyed our thoughtful discussion about AI, consciousness, ethics, and the future of work. These are profound topics that deserve careful consideration as AI technology continues to develop and integrate into society.

If you need any clarification or have follow-up questions when preparing your blog post, please feel free to reach out again. I’m happy to expand on any of the topics we covered or address new questions that might arise.

Best of luck with your blog post! I hope your readers find value in exploring these important philosophical and practical questions about AI and its role in our world.

Medical progress, at least, is real

PNRJ core principles, development economics, futurism, personal , , , , , , , , , , , , , ,

May 26 JDN 2460457

The following vignettes are about me.

Well, one of them is about me as I actually am. The others are about the person I would have been, if someone very much like me, with the same medical conditions, had been born in a particular place and time. Someone in these times and places probably had actual experiences like this, though of course we’ll never know who they were.

976 BC, the hilled lands near the mouth of the river:

Since I was fourteen years old, I have woken up almost every day in pain. Often it is mild, but occasionally it is severe. It often seems to be worse when I encounter certain plants, or if I awaken too early, or if I exert myself too much, or if a storm is coming. No one knows why. The healers have tried every herb and tincture imaginable in their efforts to cure me, but nothing has worked. The priests believe it is a curse from the gods, but at least they appreciate my ability to sometimes predict storms. I am lucky to even remain alive, as I am of little use to the tribe. I will most likely remain this way the rest of my life.

24 AD, Rome:

Since I was fourteen years old, I have woken up almost every day in pain. Often it is mild, but occasionally it is severe. It often seems to be worse when I encounter certain plants, or if I awaken too early, or if I exert myself too much, or if a storm is coming. No one knows why. The healers have tried every herb and tincture imaginable in their efforts to cure me, but nothing has worked. The priests believe it is a curse from the gods, but at least they appreciate my ability to sometimes predict storms. I am lucky that my family was rich enough to teach me reading and mathematics, as I would be of little use for farm work, but can at least be somewhat productive as a scribe and a tutor. I will most likely remain this way the rest of my life.

1024 AD, England:

Since I was fourteen years old, I have woken up almost every day in pain. Often it is mild, but occasionally it is severe. It often seems to be worse when I encounter certain plants, or if I awaken too early, or if I exert myself too much, or if a storm is coming. No one knows why. The healers have tried every herb and tincture imaginable in their efforts to cure me, but nothing has worked. The priests believe it is a curse imposed upon me by some witchcraft, but at least they appreciate my ability to sometimes predict storms. I am lucky that my family was rich enough to teach me reading and mathematics, as I would be of little use for farm work, but can at least be somewhat productive as a scribe and a tutor. I will most likely remain this way the rest of my life.

2024 AD, Michigan:

Since I was fourteen years old, I have woken up almost every day in pain. Often it is mild, but occasionally it is severe. It often seems to be worse when I encounter certain pollens, fragrances, or chemicals, or if I awaken too early, or if I exert myself too much, or when the air pressure changes before a storm. Brain scans detected no gross abnormalities. I have been diagnosed with chronic migraine, but this is more a description of my symptoms than an explanation. I have tried over a dozen different preventative medications; most of them didn’t work at all, some of them worked but gave me intolerable side effects. (One didn’t work at all and put me in the hospital with a severe allergic reaction.) I’ve been more successful with acute medications, which at least work as advertised, but I have to ration them carefully to avoid rebound effects. And the most effective acute medication is a subcutaneous injection that makes me extremely nauseated unless I also take powerful anti-emetics along with it. I have had the most success with botulinum toxin injections, so I will be going back to that soon; but I am also looking into transcranial magnetic stimulation. Currently my condition is severe enough that I can’t return to full-time work, but I am hopeful that with future treatment I will be able to someday. For now, I can at least work as a writer and a tutor. Hopefully things get better soon.

3024 AD, Aegir 7, Ran System:

For a few months when I was fourteen years old, I woke up nearly every day in pain. Often it was mild, but occasionally it was severe. It often seemed to be worse when I encountered certain pollens, fragrances or chemicals, or if I awakened too early, or if I exerted myself too much, or when the air pressure changed before a storm. Brain scans detected no gross abnormalities, only subtle misfiring patterns. Genetic analysis confirmed I had chronic migraine type IVb, and treatment commenced immediately. Acute medications suppressed the pain while I underwent gene therapy and deep-effect transcranial magnetic stimulation. After three months of treatment, I was cured. That was an awful few months, but it’s twenty years behind me now. I can scarcely imagine how it might have impaired my life if it had gone on that whole time.

What is the moral of this story?

Medical progress is real.

Many people often doubt that society has made real progress. And in a lot of ways, maybe it hasn’t. Human nature is still the same, and so many of the problems we suffer have remained the same.

Economically, of course we have had tremendous growth in productivity and output, but it doesn’t really seem to have made us much happier. We have all this stuff, but we’re still struggling and miserable as a handful at the top become spectacularly, disgustingly rich.

Social progress seems to have gone better: Institutions have improved, more of the world is democratic than ever before, and women and minorities are better represented and better protected from oppression. Rates of violence have declined to some of their lowest levels in history. But even then, it’s pretty clear that we have a long, long way to go.

But medical progress is undeniable. We live longer, healthier lives than at any other point in history. Our infant and child mortality rates have plummeted. Even chronic conditions that seem intractable today (such as my chronic migraines) still show signs of progress; in a few generations they should be cured—in surely far less than the thousand years I’ve considered here.

Like most measures of progress, this change wasn’t slow and gradual over thousands of years; it happened remarkably suddenly. Humans went almost 200,000 years without any detectable progress in medicine, using basically the same herbs and tinctures (and a variety of localized and ever-changing superstitions) the entire time. Some of it worked (the herbs and tinctures, at least), but mostly it didn’t. Then, starting around the 18th century, as the Enlightenment took hold and Industrial Revolution ramped up, everything began to change.

We began to test our medicine and see if it actually worked. (Yes, amazingly, somehow, nobody had actually ever thought to do that before—not in anything resembling a scientific way.) And when we learned that most of it didn’t, we began to develop new methods, and see if those worked; and when they didn’t either, we tried new things instead—until, finally, eventually, we actually found medicines that actually did something, medicines worthy of the name. Our understanding of anatomy and biology greatly improved as well, allowing us to make better predictions about the effects our medicines would have. And after a few hundred years of that—a few hundred, out of two hundred thousand years of our species—we actually reached the point where most medicine is effective and a variety of health conditions are simply curable or preventable, including diseases like malaria and polio that had once literally plagued us.

Scientific medicine brought humanity into a whole new era of existence.

I could have set the first vignette 10,000 years ago without changing it. But the final vignette I could probably have set only 200 years from now. I’m actually assuming remarkable stagnation by putting it in the 31st century; but presumably technological advancement will slow at one point, perhaps after we’ve more or less run out of difficult challenges to resolve. (Then again, for all I know, maybe my 31st century counterpart will be an emulated consciousness, and his chronic pain will be resolved in 17.482 seconds by a code update.)

Indeed, the really crazy thing about all this is that there are still millions of people who don’t believe in scientific medicine, who want to use “homeopathy” or “naturopathy” or “acupuncture” or “chiropractic” or whatever else—who basically want to go back to those same old herbs and tinctures that maybe sometimes kinda worked but probably not and nobody really knows. (I have a cousin who is a chiropractor. I try to be polite about it, but….) They point out the various ways that scientific medicine has failed—and believe me, I am painfully aware of those failures—but then where the obvious solution is to improve scientific medicine, they instead want to turn the whole ship around, and go back to what we had before, which was obviously a million times worse.

And don’t tell me it’s harmless: One, it’s a completewaste of resources that could instead have been used for actual scientific medicine. (9% of all out-of-pocket spending on healthcare in the US is on “alternative medicine”—which is to say, on pointless nonsense.) Two, when you have a chronic illness and people keep shoving nonsense treatments in your face, you start to feel blamed for your condition: “Why haven’t you tried [other incredibly stupid idea that obviously won’t work]? You’re so closed-minded! Maybe your illness isn’t really that bad, or you’d be more desperate!” If “alternative medicine” didn’t exist, maybe these people could help me cope with the challenges of living with a chronic illness, or even just sympathize with me, instead of constantly shoving stupid nonsense in my face.

Not everything about the future looks bright.

In particular, I am pessimistic about the near-term future of artificial intelligence, which I think will cause a lot more problems than it solves and does have a small—but not negligible—risk of causing a global catastrophe.

I’m also not very optimistic about climate change; I don’t think it will wipe out our civilization or anything so catastrophic, but I do think it’s going to kill millions of people and we’ve done too little, too late to prevent that. We’re now doing about what we should have been doing in the 1980s.

But I am optimistic about scientific medicine. Every day, new discoveries are made. Every day, new treatments are invented. Yes, there is a lot we haven’t figured out how to cure yet; but people are working on it.

And maybe they could do it faster if we stopped wasting time on stuff that obviously won’t work.

Everyone includes your mother and Los Angeles

PNRJ cognitive science, computer science, core principles, current events, ethics, futurism, heuristics and biases, politics, public policy , , , , , ,

Apr 28 JDN 2460430

What are the chances that artificial intelligence will destroy human civilization?

A bunch of experts were surveyed on that question and similar questions, and half of respondents gave a probability of 5% or more; some gave probabilities as high as 99%.

This is incredibly bizarre.

Most AI experts are people who work in AI. They are actively participating in developing this technology. And yet more than half of them think that the technology they are working on right now has a more than 5% chance of destroying human civilization!?

It feels to me like they honestly don’t understand what they’re saying. They can’t really grasp at an intuitive level just what a 5% or 10% chance of global annihilation means—let alone a 99% chance.

If something has a 5% chance of killing everyone, we should consider that at least as bad as something that is guaranteed to kill 5% of people.

Probably worse, in fact, because you can recover from losing 5% of the population (we have, several times throughout history). But you cannot recover from losing everyone. So really, it’s like losing 5% of all future people who will ever live—which could be a very large number indeed.

But let’s be a little conservative here, and just count people who already, currently exist, and use 5% of that number.

5% of 8 billion people is 400 million people.

So anyone who is working on AI and also says that AI has a 5% chance of causing human extinction is basically saying: “In expectation, I’m supporting 20 Holocausts.”

If you really think the odds are that high, why aren’t you demanding that any work on AI be tried as a crime against humanity? Why aren’t you out there throwing Molotov cocktails at data centers?

(To be fair, Eliezer Yudkowsky is actually calling for a global ban on AI that would be enforced by military action. That’s the kind of thing you should be doing if indeed you believe the odds are that high. But most AI doomsayers don’t call for such drastic measures, and many of them even continue working in AI as if nothing is wrong.)

I think this must be scope neglect—or something even worse.

If you thought a drug had a 99% chance of killing your mother, you would never let her take the drug, and you would probably sue the company for making it.

If you thought a technology had a 99% chance of destroying Los Angeles, you would never even consider working on that technology, and you would want that technology immediately and permanently banned.

So I would like to remind anyone who says they believe the danger is this great and yet continues working in the industry:

Everyone includes your mother and Los Angeles.

If AI destroys human civilization, that means AI destroys Los Angeles. However shocked and horrified you would be if a nuclear weapon were detonated in the middle of Hollywood, you should be at least that shocked and horrified by anyone working on advancing AI, if indeed you truly believe that there is at least a 5% chance of AI destroying human civilization.

But people just don’t seem to think this way. Their minds seem to take on a totally different attitude toward “everyone” than they would take toward any particular person or even any particular city. The notion of total human annihilation is just so remote, so abstract, they can’t even be afraid of it the way they are afraid of losing their loved ones.

This despite the fact that everyone includes all your loved ones.

If a drug had a 5% chance of killing your mother, you might let her take it—but only if that drug was the best way to treat some very serious disease. Chemotherapy can be about that risky—but you don’t go on chemo unless you have cancer.

If a technology had a 5% chance of destroying Los Angeles, I’m honestly having trouble thinking of scenarios in which we would be willing to take that risk. But the closest I can come to it is the Manhattan Project. If you’re currently fighting a global war against fascist imperialists, and they are also working on making an atomic bomb, then being the first to make an atomic bomb may in fact be the best option, even if you know that it carries a serious risk of utter catastrophe.

In any case, I think one thing is clear: You don’t take that kind of serious risk unless there is some very large benefit. You don’t take chemotherapy on a whim. You don’t invent atomic bombs just out of curiosity.

Where’s the huge benefit of AI that would justify taking such a huge risk?

Some forms of automation are clearly beneficial, but so far AI per se seems to have largely made our society worse. ChatGPT lies to us. Robocalls inundate us. Deepfakes endanger journalism. What’s the upside here? It makes a ton of money for tech companies, I guess?

Now, fortunately, I think 5% is too high an estimate.

(Scientific American agrees.)

My own estimate is that, over the next two centuries, there is about a 1% chance that AI destroys human civilization, and only a 0.1% chance that it results in human extinction.

This is still really high.

People seem to have trouble with that too.

“Oh, there’s a 99.9% chance we won’t all die; everything is fine, then?” No. There are plenty of other scenarios that would also be very bad, and a total extinction scenario is so terrible that even a 0.1% chance is not something we can simply ignore.

0.1% of people is still 8 million people.

I find myself in a very odd position: On the one hand, I think the probabilities that doomsayers are giving are far too high. On the other hand, I think the actions that are being taken—even by those same doomsayers—are far too small.

Most of them don’t seem to consider a 5% chance to be worthy of drastic action, while I consider a 0.1% chance to be well worthy of it. I would support a complete ban on all AI research immediately, just from that 0.1%.

The only research we should be doing that is in any way related to AI should involve how to make AI safer—absolutely no one should be trying to make it more powerful or apply it to make money. (Yet in reality, almost the opposite is the case.)

Because 8 million people is still a lot of people.

Is it fair to treat a 0.1% chance of killing everyone as equivalent to killing 0.1% of people?

Well, first of all, we have to consider the uncertainty. The difference between a 0.05% chance and a 0.015% chance is millions of people, but there’s probably no way we can actually measure it that precisely.

But it seems to me that something expected to kill between 4 million and 12 million people would still generally be considered very bad.

More importantly, there’s also a chance that AI will save people, or have similarly large benefits. We need to factor that in as well. Something that will kill 4-12 million people but also save 15-30 million people is probably still worth doing (but we should also be trying to find ways to minimize the harm and maximize the benefit).

The biggest problem is that we are deeply uncertain about both the upsides and the downsides. There are a vast number of possible outcomes from inventing AI. Many of those outcomes are relatively mundane; some are moderately good, others are moderately bad. But the moral question seems to be dominated by the big outcomes: With some small but non-negligible probability, AI could lead to either a utopian future or an utter disaster.

The way we are leaping directly into applying AI without even being anywhere close to understanding AI seems to me especially likely to lean toward disaster. No other technology has ever become so immediately widespread while also being so poorly understood.

So far, I’ve yet to see any convincing arguments that the benefits of AI are anywhere near large enough to justify this kind of existential risk. In the near term, AI really only promises economic disruption that will largely be harmful. Maybe one day AI could lead us into a glorious utopia of automated luxury communism, but we really have no way of knowing that will happen—and it seems pretty clear that Google is not going to do that.

Artificial intelligence technology is moving too fast. Even if it doesn’t become powerful enough to threaten our survival for another 50 years (which I suspect it won’t), if we continue on our current path of “make money now, ask questions never”, it’s still not clear that we would actually understand it well enough to protect ourselves by then—and in the meantime it is already causing us significant harm for little apparent benefit.

Why are we even doing this? Why does halting AI research feel like stopping a freight train?

I dare say it’s because we have handed over so much power to corporations.

The paperclippers are already here.

Adversarial design

PNRJ core principles, critique of neoclassical economics, current events, futurism, politics, public policy , , , , , , , , , , ,

Feb 4 JDN 2460346

Have you noticed how Amazon feels a lot worse lately? Years ago, it was extremely convenient: You’d just search for what you want, it would give you good search results, you could buy what you want and be done. But now you have to slog through “sponsored results” and a bunch of random crap made by no-name companies in China before you can get to what you actually want.

Temu is even worse, and has been from the start: You can’t buy anything on Temu without first being inundated in ads. It’s honestly such an awful experience, I don’t understand why anyone is willing to buy anything from Temu.

#WelcomeToCyberpunk, I guess.

Even some video games have become like this: The free-to-play or “freemium” business model seems to be taking off, where you don’t pay money for the game itself, but then have to deal with ads inside the game trying to sell you additional content, because that’s where the developers actually make their money. And now AAA firms like EA and Ubisoft are talking about going to a subscription-based model where you don’t even own your games anymore. (Fortunately there’s been a lot of backlash against that; I hope it persists.)

Why is this happening? Isn’t capitalism supposed to make life better for consumers? Isn’t competition supposed to make products and services supposed to improve over time?

Well, first of all, these markets are clearly not as competitive as they should be. Amazon has a disturbingly large market share, and while the video game market is more competitive, it’s still dominated by a few very large firms (like EA and Ubisoft).

But I think there’s a deeper problem here, one which may be specific to media content.

What I mean by “media content” here is fairly broad: I would include art, music, writing, journalism, film, and video games.

What all of these things have in common is that they are not physical products (they’re not like a car or a phone that is a single physical object), but they are also not really services either (they aren’t something you just do as an action and it’s done, like a haircut, a surgery, or a legal defense).

Another way of thinking about this is that media content can be copied with zero marginal cost.

Because it can be copied with zero marginal cost, media content can’t simply be made and sold the way that conventional products and services are. There are a few different ways it can be monetized.


The most innocuous way is commission or patronage, where someone pays someone else to create a work because they want that work. This is totally unproblematic. You want a piece of art, you pay an artist, they make it for you; great. Maybe you share copies with the world, maybe you don’t; whatever. It’s good either way.

Unfortunately, it’s hard to sustain most artists and innovators on that model alone. (In a sense I’m using a patronage model, because I have a Patreon. But I’m not making anywhere near enough to live on that way.)

The second way is intellectual property, which I have written about before, and surely will again. If you can enforce limits on who is allowed to copy a work, then you can make a work and sell it for profit without fear of being undercut by someone else who simply copies it and sells it for cheaper. A detailed discussion of that is beyond the scope of this post, but you can read those previous posts, and I can give you the TLDR version: Some degree of intellectual property is probably necessary, but in our current society, it has clearly been taken much too far. I think artists and authors deserve to be able to copyright (or maybe copyleft) their work—but probably not for 70 years after their death.

And then there is a third way, the most insidious way: advertising. If you embed advertisements for other products and services within your content, you can then sell those ad slots for profit. This is how newspapers stay afloat, mainly; subscriptions have never been the majority of their revenue. It’s how TV was supported before cable and streaming—and cable usually has ads too, and streaming is starting to.

There is something fundamentally different about advertising as a service. Whereas most products and services you encounter in a capitalist society are made for you, designed for you to use, advertising it made at you, designed to manipulate you.

I’ve heard it put well this way:

If you’re not paying, you aren’t the customer; you’re the product.

Monetizing content by advertising effectively makes your readers (or viewers, players, etc.) into the product instead of the customer.

I call this effect adversarial design.

I chose this term because it not only conveys the right sense of being an adversary: it also includes the word ‘ad’ and the same Latin root ‘advertere‘ as ‘advertising’.

When a company designs a car or a phone, they want it to appeal to customers—they want you to like it. Yes, they want to take your money; but it’s a mutually beneficial exchange. They get money, you get a product; you’re both happier.

When a company designs an ad, they want it to affect customers—they want you to do what it says, whether you like it or not. And they wouldn’t be doing it if they thought you would buy it anyway—so they are basically trying to make you do something you wouldn’t otherwise have done.

In other words, when designing a product, corporations want to be your friend.

When designing an ad, they become your enemy.

You would absolutely prefer not to have ads. You don’t want your attention taken in this way. But they way that these corporations make money—disgustingly huge sums of money—is by forcing those ads in your face anyway.

Yes, to be fair, there might be some kinds of ads that aren’t too bad. Simple, informative, unobtrusive ads that inform you that something is available you might not otherwise have known about. Movie trailers are like this; people often enjoy watching movie trailers, and they want to see what movies are going to come out next. That’s fine. I have no objection to that.

But it should be clear to anyone who has, um, used the Internet in the past decade that we have gone far, far beyond that sort of advertising. Ads have become aggressive, manipulative, aggravating, and—above all—utterly ubiquitous. You can’t escape them. They’re everywhere. Even when you use ad-block software (which I highly recommend, particularly Adblock Plus—which is free), you still can’t completely escape them.

That’s another thing that should make it pretty clear that there’s something wrong with ads: People are willing to make efforts or even pay money to make ads go away.

Whenever there is a game I like that’s ad-supported but you can pay to make the ads go away, I always feel like I’m being extorted, even if what I have to pay would have been a totally reasonable price for the game. Come on, just sell me the game. Don’t give me the game for free and then make me pay to make it not unpleasant. Don’t add anti-features.

This is clearly not a problem that market competition alone will solve. Even in highly competitive markets, advertising is still ubiquitous, aggressive and manipulative. In fact, competition may even make it worse—a true monopoly wouldn’t need to advertise very much.

Consider Coke and Pepsi ads; they’re actually relatively pleasant, aren’t they? Because all they’re trying to do is remind you and make you thirsty so you’ll buy more of the product you were already buying. They aren’t really trying to get you to buy something you wouldn’t have otherwise. They know that their duopoly is solid, and only a true Black Swan event would unseat their hegemony.

And have you ever seen an ad for your gas company? I don’t think I have—probably because I didn’t have a choice in who my gas company was; there was only one that covered my area. So why bother advertising to me?

If competition won’t fix this, what will? Is there some regulation we could impose that would make advertising less obtrusive? People have tried, without much success. I think imposing an advertising tax would help, but even that might not do enough.

What I really think we need right now is to recognize the problem and invest in solving it. Right now we have megacorporations which are thoroughly (literally) invested in making advertising more obtrusive and more ubiquitous. We need other institutions—maybe government, maybe civil society more generally—that are similarly invested in counteracting it.


Otherwise, it’s only going to get worse.

How will AI affect inequality?

PNRJ current events, ethics, futurism, inequality, public policy , , , , , , , , , , , ,

Oct 15 JDN 2460233

Will AI make inequality worse, or better? Could it do a bit of both? Does it depend on how we use it?

This is of course an extremely big question. In some sense it is the big economic question of the 21st century. The difference between the neofeudalist cyberpunk dystopia of Neuromancer and the social democratic utopia of Star Trek just about hinges on whether AI becomes a force for higher or lower inequality.

Krugman seems quite optimistic: Based on forecasts by Goldman Sachs, AI seems poised to automate more high-paying white-collar jobs than low-paying blue-collar ones.

But, well, it should be obvious that Goldman Sachs is not an impartial observer here. They do have reasons to get their forecasts right—their customers are literally invested in those forecasts—but like anyone who immensely profits from the status quo, they also have a broader agenda of telling the world that everything is going great and there’s no need to worry or change anything.

And when I look a bit closer at their graphs, it seems pretty clear that they aren’t actually answering the right question. They estimate an “exposure to AI” coefficient (somehow; their methodology is not clearly explained and lots of it is proprietary), and if it’s between 10% and 49% they call it “complementary” while if it’s 50% or above they call it “replacement”.

But that is not how complements and substitutes work. It isn’t a question of “how much of the work can be done by machine” (whatever that means). It’s a question of whether you will still need the expert human.

It could be that the machine does 90% of the work, but you still need a human being there to tell it what to do, and that would be complementary. (Indeed, this basically is how finance works right now, and I see no reason to think it will change any time soon.) Conversely, it could be that the machine only does 20% of the work, but that was the 20% that required expert skill, and so a once comfortable high-paying job can now be replaced by low-paid temp workers. (This is more or less what’s happening at Amazon warehouses: They are basically managed by AI, but humans still do most of the actual labor, and get paid peanuts for it.)

For their category “computer and mathematical”, they call it “complementary”, and I agree: We are still going to need people who can code. We’re still going to need people who know how to multiply matrices. We’re still going to need people who understand search algorithms. Indeed, if the past is any indicator, we’re going to need more and more of those people, and they’re going to keep getting paid higher and higher salaries. Someone has to make the AI, after all.

Yet I’m not quite so sure about the “mathematical” part in many cases. We may not need people who can solve differential equations, actually: maybe a few to design the algorithms, but honestly even then, a software program with a simple finite-difference algorithm can often solve much more interesting problems than one with a full-fledged differential equation solver, because one of the dirty secrets of differential equations is that for some of the most important ones (like the Navier-Stokes Equations), we simply do not know how to solve them. Once you have enough computing power, you often can stop trying to be clever and just brute-force the damn thing.

Yet for “transportation and material movement”—that is, trucking—Goldman Sachs confidently forecasts mostly “no automation” with a bit of “complementary”. Yet this year—not at some distant point in the future, not in some sci-fi novel, this year in the actual world—the Governor of California already vetoed a bill that would have required automated trucks to have human drivers. The trucks aren’t on the roads yet—but if we already are making laws about them, they’re going to be, soon. (State legislatures are not known for their brilliant foresight or excessive long-term thinking.) And if the law doesn’t require them to have human drivers, they probably won’t; which means that hundreds of thousands of long-haul truckers will suddenly be out of work.

It’s also important to differentiate between different types of jobs that may fall under the same category or industry.

Neurosurgeons are not going anywhere, and improved robotics will only allow them to perform better, safer laparoscopic surgeries. Nor are nurses going anywhere, because some things just need an actual person physically there with the patient. But general practictioners, psychotherapists, and even radiologists are already seeing many of their tasks automated. So is “medicine” being automated or not? That depends what sort of medicine you mean. And yet it clearly means an increase in inequality, because it’s the middle-paying jobs (like GPs) that are going away, while the high-paying jobs (like neurosurgeons) and the low-paying jobs (like nurses) that remain.

Likewise, consider “legal services”, which is one of the few industries that Goldman Sachs thinks will be substantially replaced by AI. Are high-stakes trial lawyers like Sam Bernstein getting replaced? Clearly not. Nor would I expect most corporate lawyers to disappear. Human lawyers will still continue to perform at least a little bit better than AI law systems, and the rich will continue to use them, because a few million dollars for a few percentage points better odds of winning is absolutely worth it when billions of dollars are on the line. So which law services are going to get replaced by AI? First, routine legal questions, like how to renew your work visa or set up a living will—it’s already happening. Next, someone will probably decide that public defenders aren’t worth the cost and start automating the legal defenses of poor people who get accused of crimes. (And to be honest, it may not be much worse than how things currently are in the public defender system.) The advantage of such a change is that it will most likely bring court costs down—and that is desperately needed. But it may also tilt the courts even further in favor of the rich. It may also make it even harder to start a career as a lawyer, cutting off the bottom of the ladder.

Or consider “management”, which Goldman Sachs thinks will be “complementary”. Are CEOs going to get replaced by AI? No, because the CEOs are the ones making that decision. Certainly this is true for any closely-held firm: No CEO is going to fire himself. Theoretically, if shareholders and boards of directors pushed hard enough, they might be able to get a CEO of a publicly-traded corporation ousted in favor of an AI, and if the world were really made of neoclassical rational agents, that might actually happen. But in the real world, the rich have tremendous solidarity for each other (and only each other), and very few billionaires are going to take aim at other billionaires when it comes time to decide whose jobs should be replaced. Yet, there are a lot of levels of management below the CEO and board of directors, and many of those are already in the process of being replaced: Instead of relying on the expert judgment of a human manager, it’s increasingly common to develop “performance metrics”, feed them into an algorithm, and use that result to decide who gets raises and who gets fired. It all feels very “objective” and “impartial” and “scientific”—and usually ends up being both dehumanizing and ultimately not even effective at increasing profits. At some point, many corporations are going to realize that their middle managers aren’t actually making any important decisions anymore, and they’ll feed that into the algorithm, and it will tell them to fire the middle managers.

Thus, even though we think of “medicine”, “law”, and “management” as high-paying careers, the effect of AI is largely going to be to increase inequality within those industries. It isn’t the really high-paid doctors, managers, and lawyers who are going to get replaced.

I am therefore much less optimistic than Krugman about this. I do believe there are many ways that technology, including artificial intelligence, could be used to make life better for everyone, and even perhaps one day lead us into a glorious utopian future.

But I don’t see most of the people who have the authority to make important decisions for our society actually working towards such a future. They seem much more interested in maximizing their own profits or advancing narrow-minded ideologies. (Or, as most right-wing political parties do today: Advancing narrow-minded ideologies about maximizing the profits of rich people.) And if we simply continue on the track we’ve been on, our future is looking a lot more like Neuromancer than it is like Star Trek.

Productivity can cope with laziness, but not greed

PNRJ core principles, critique of neoclassical economics, ethics, futurism, inequality , , , , , , , , , , , , , , , , , , , , , , ,

Oct 8 JDN 2460226

At least since Star Trek, it has been a popular vision of utopia: post-scarcity, an economy where goods are so abundant that there is no need for money or any kind of incentive to work, and people can just do what they want and have whatever they want.

It certainly does sound nice. But is it actually feasible? I’ve written about this before.

I’ve been reading some more books set in post-scarcity utopias, including Ursula K. Le Guin (who is a legend) and Cory Doctorow (who is merely pretty good). And it struck me that while there is one major problem of post-scarcity that they seem to have good solutions for, there is another one that they really don’t. (To their credit, neither author totally ignores it; they just don’t seem to see it as an insurmountable obstacle.)

The first major problem is laziness.

A lot of people assume that the reason we couldn’t achieve a post-scarcity utopia is that once your standard of living is no longer tied to your work, people would just stop working. I think this assumption rests on both an overly cynical view of human nature and an overly pessimistic view of technological progress.

Let’s do a thought experiment. If you didn’t get paid, and just had the choice to work or not, for whatever hours you wished, motivated only by the esteem of your peers, your contribution to society, and the joy of a job well done, how much would you work?

I contend it’s not zero. At least for most people, work does provide some intrinsic satisfaction. It’s also probably not as much as you are currently working; otherwise you wouldn’t insist on getting paid. Those are our lower and upper bounds.

Is it 80% of your current work? Perhaps not. What about 50%? Still too high? 20% seems plausible, but maybe you think that’s still too high. Surely it’s at least 10%. Surely you would be willing to work at least a few hours per week at a job you’re good at that you find personally fulfilling. My guess is that it would actually be more than that, because once people were free of the stress and pressure of working for a living, they would be more likely to find careers that truly brought them deep satisfaction and joy.

But okay, to be conservative, let’s estimate that people are only willing to work 10% as much under a system where labor is fully optional and there is no such thing as a wage. What kind of standard of living could we achieve?

Well, at the current level of technology and capital in the United States, per-capita GDP at purchasing power parity is about $80,000. 10% of that is $8,000. This may not sound like a lot, but it’s about how people currently live in Venezuela. India is slightly better, Ghana is slightly worse. This would feel poor to most Americans today, but it’s objectively a better standard of living than most humans have had throughout history, and not much worse than the world average today.

If per-capita GDP growth continues at its current rate of about 1.5% per year for another century, that $80,000 would become $320,000, 10% of which is $32,000—that would put us at the standard of living of present-day Bulgaria, or what the United States was like in the distant past of [checks notes] 1980. That wouldn’t even feel poor. In fact if literally everyone had this standard of living, nearly as many Americans today would be richer as would be poorer, since the current median personal income is only a bit higher than that.

Thus, the utopian authors are right about this one: Laziness is a solvable problem. We may not quite have it solved yet, but it’s on the ropes; a few more major breakthroughs in productivity-enhancing technology and we’ll basically be there.

In fact, on a small scale, this sort of utopian communist anarchy already works, and has for centuries. There are little places, all around the world, where people gather together and live and work in a sustainable, basically self-sufficient way without being motivated by wages or salaries, indeed often without owning any private property at all.

We call these places monasteries.

Granted, life in a monastery clearly isn’t for everyone: I certainly wouldn’t want to live a life of celibacy and constant religious observance. But the long-standing traditions of monastic life in several very different world religions does prove that it’s possible for human beings to live and even flourish in the absence of a profit motive.

Yet the fact that monastic life is so strict turns out to be no coincidence: In a sense, it had to be for the whole scheme to work. I’ll get back to that in a moment.

The second major problem with a post-scarcity utopia is greed.

This is the one that I think is the real barrier. It may not be totally insurmountable, but thus far I have yet to hear any good proposals that would seriously tackle it.

The issue with laziness is that we don’t really want to work as much as we do. But since we do actually want to work a little bit, the question is simply how to make as much as we currently do while working only as much as we want to. Hence, to deal with laziness, all we need to do is be more efficient. That’s something we are shockingly good at; the overall productivity of our labor is now something like 100 times what it was at the dawn of the Industrial Revolution, and still growing all the time.

Greed is different. The issue with greed is that, no matter how much we have, we always want more.

Some people are clearly greedier than others. In fact, I’m even willing to bet that most people’s greed could be kept in check by a society that provided for everyone’s basic needs for free. Yeah, maybe sometimes you’d fantasize about living in a gigantic mansion or going into outer space; but most of the time, most of us could actually be pretty happy as long as we had a roof over our heads and food on our tables. I know that in my own case, my grandest ambitions largely involve fighting global poverty—so if that became a solved problem, my life’s ambition would be basically fulfilled, and I wouldn’t mind so much retiring to a life of simple comfort.

But is everyone like that? This is what anarchists don’t seem to understand. In order for anarchy to work, you need everyone to fit into that society. Most of us or even nearly all of us just won’t cut it.

Ammon Hennecy famously declared: “An anarchist is someone who doesn’t need a cop to make him behave.” But this is wrong. An anarchist is someone who thinks that no one needs a cop to make him behave. And while I am the former, I am not the latter.

Perhaps the problem is that anarchists don’t realize that not everyone is as good as they are. They implicitly apply their own mentality to everyone else, and assume that the only reason anyone ever cheats, steals, or kills is because their circumstances are desperate.

Don’t get me wrong: A lot of crime—perhaps even most crime—is committed by people who are desperate. Improving overall economic circumstances does in fact greatly reduce crime. But there is also a substantial proportion of crime—especially the most serious crimes—which is committed by people who aren’t particularly desperate, they are simply psychopaths. They aren’t victims of circumstance. They’re just evil. And society needs a way to deal with them.

If you set up a society so that anyone can just take whatever they want, there will be some people who take much more than their share. If you have no system of enforcement whatsoever, there’s nothing to stop a psychopath from just taking everything he can get his hands on. And then it really doesn’t matter how productive or efficient you are; whatever you make will simply get taken by whoever is greediest—or whoever is strongest.

In order to avoid that, you need to either set up a system that stops people from taking more than their share, or you need to find a way to exclude people like that from your society entirely.

This brings us back to monasteries. Why are they so strict? Why are the only places where utopian anarchism seems to flourish also places where people have to wear a uniform, swear vows, carry out complex rituals, and continually pledge their fealty to an authority? (Note, by the way, that I’ve also just described life in the military, which also has a lot in common with life in a monastery—and for much the same reasons.)

It’s a selection mechanism. Probably no one consciously thinks of it this way—indeed, it seems to be important to how monasteries work that people are not consciously weighing the costs and benefits of all these rituals. This is probably something that memetically evolved over centuries, rather than anything that was consciously designed. But functionally, that’s what it does: You only get to be part of a monastic community if you are willing to pay the enormous cost of following all these strict rules.

That makes it a form of costly signaling. Psychopaths are, in general, more prone to impulsiveness and short-term thinking. They are therefore less willing than others to bear the immediate cost of donning a uniform and following a ritual in order to get the long-term gains of living in a utopian community. This excludes psychopaths from ever entering the community, and thus protects against their predation.

Even celibacy may be a feature rather than a bug: Psychopaths are also prone to promiscuity. (And indeed, utopian communes that practice free love seem to have a much worse track record of being hijacked by psychopaths than monasteries that require celibacy!)

Of course, lots of people who aren’t psychopaths aren’t willing to pay those costs either—like I said, I’m not. So the selection mechanism is in a sense overly strict: It excludes people who would support the community just fine, but aren’t willing to pay the cost. But in the long run, this turns out to be less harmful than being too permissive and letting your community get hijacked and destroyed by psychopaths.

Yet if our goal is to make a whole society that achieves post-scarcity utopia, we can’t afford to be so strict. We already know that most people aren’t willing to become monks or nuns.

That means that we need a selection mechanism which is more reliable—more precisely, one with higher specificity.

I mentioned this in a previous post in the context of testing for viruses, but it bears repeating. Sensitivity and specificity are two complementary measures of a test’s accuracy. The sensitivity of a test is how likely it is to show positive if the truth is positive. The specificity of a test is how likely it is to show negative if the truth is negative.

As a test of psychopathy, monastic strictness has very high sensitivity: If you are a psychopath, there’s a very high chance it will weed you out. But it has quite low specificity: Even if you’re not a psychopath, there’s still a very high chance you won’t want to become a monk.

For a utopian society to work, we need something that’s more specific, something that won’t exclude a lot of people who don’t deserve to be excluded. But it still needs to have much the same sensitivity, because letting psychopaths into your utopia is a very easy way to let that utopia destroy itself. We do not yet have such a test, nor any clear idea how we might create one.

And that, my friends, is why we can’t have nice things. At least, not yet.

AI and the “generalization faculty”

PNRJ cognitive science, computer science, critique of neoclassical economics, current events, ethics, futurism, inequality, public policy , , , , , , , , , ,

Oct 1 JDN 2460219

The phrase “artificial intelligence” (AI) has now become so diluted by overuse that we needed to invent a new term for its original meaning. That term is now “artificial general intelligence” (AGI). In the 1950s, AI meant the hypothetical possibility of creating artificial minds—machines that could genuinely think and even feel like people. Now it means… pathing algorithms in video games and chatbots? The goalposts seem to have moved a bit.

It seems that AGI has always been 20 years away. It was 20 years away 50 years ago, and it will probably be 20 years away 50 years from now. Someday it will really be 20 years away, and then, 20 years after that, it will actually happen—but I doubt I’ll live to see it. (XKCD also offers some insight here: “It has not been conclusively proven impossible.”)

We make many genuine advances in computer technology and software, which have profound effects—both good and bad—on our lives, but the dream of making a person out of silicon always seems to drift ever further into the distance, like a mirage on the desert sand.

Why is this? Why do so many people—even, perhaps especially,experts in the field—keep thinking that we are on the verge of this seminal, earth-shattering breakthrough, and ending up wrong—over, and over, and over again? How do such obviously smart people keep making the same mistake?

I think it may be because, all along, we have been laboring under the tacit assumption of a generalization faculty.

What do I mean by that? By “generalization faculty”, I mean some hypothetical mental capacity that allows you to generalize your knowledge and skills across different domains, so that once you get good at one thing, it also makes you good at other things.

This certainly seems to be how humans think, at least some of the time: Someone who is very good at chess is likely also pretty good at go, and someone who can drive a motorcycle can probably also drive a car. An artist who is good at portraits is probably not bad at landscapes. Human beings are, in fact, able to generalize, at least sometimes.

But I think the mistake lies in imagining that there is just one thing that makes us good at generalizing: Just one piece of hardware or software that allows you to carry over skills from any domain to any other. This is the “generalization faculty”—the imagined faculty that I think we do not have, indeed I think does not exist.

Computers clearly do not have the capacity to generalize. A program that can beat grandmasters at chess may be useless at go, and self-driving software that works on one type of car may fail on another, let alone a motorcycle. An art program that is good at portraits of women can fail when trying to do portraits of men, and produce horrific Daliesque madness when asked to make a landscape.

But if they did somehow have our generalization capacity, then, once they could compete with us at some things—which they surely can, already—they would be able to compete with us at just about everything. So if it were really just one thing that would let them generalize, let them leap from AI to AGI, then suddenly everything would change, almost overnight.

And so this is how the AI hype cycle goes, time and time again:

  1. A computer program is made that does something impressive, something that other computer programs could not do, perhaps even something that human beings are not very good at doing.
  2. If that same prowess could be generalized to other domains, the result would plainly be something on par with human intelligence.
  3. Therefore, the only thing this computer program needs in order to be sapient is a generalization faculty.
  4. Therefore, there is just one more step to AGI! We are nearly there! It will happen any day now!

And then, of course, despite heroic efforts, we are unable to generalize that program’s capabilities except in some very narrow way—even decades after having good chess programs, getting programs to be good at go was a major achievement. We are unable to find the generalization faculty yet again. And the software becomes yet another “AI tool” that we will use to search websites or make video games.

For there never was a generalization faculty to be found. It always was a mirage in the desert sand.

Humans are in fact spectacularly good at generalizing, compared to, well, literally everything else in the known universe. Computers are terrible at it. Animals aren’t very good at it. Just about everything else is totally incapable of it. So yes, we are the best at it.

Yet we, in fact, are not particularly good at it in any objective sense.

In experiments, people often fail to generalize their reasoning even in very basic ways. There’s a famous one where we try to get people to make an analogy between a military tactic and a radiation treatment, and while very smart, creative people often get it quickly, most people are completely unable to make the connection unless you give them a lot of specific hints. People often struggle to find creative solutions to problems even when those solutions seem utterly obvious once you know them.

I don’t think this is because people are stupid or irrational. (To paraphrase Sydney Harris: Compared to what?) I think it is because generalization is hard.

People tend to be much better at generalizing within familiar domains where they have a lot of experience or expertise; this shows that there isn’t just one generalization faculty, but many. We may have a plethora of overlapping generalization faculties that apply across different domains, and can learn to improve some over others.

But it isn’t just a matter of gaining more expertise. Highly advanced expertise is in fact usually more specialized—harder to generalize. A good amateur chess player is probably a good amateur go player, but a grandmaster chess player is rarely a grandmaster go player. Someone who does well in high school biology probably also does well in high school physics, but most biologists are not very good physicists. (And lest you say it’s simply because go and physics are harder: The converse is equally true.)

Humans do seem to have a suite of cognitive tools—some innate hardware, some learned software—that allows us to generalize our skills across domains. But even after hundreds of millions of years of evolving that capacity under the highest possible stakes, we still basically suck at it.

To be clear, I do not think it will take hundreds of millions of years to make AGI—or even millions, or even thousands. Technology moves much, much faster than evolution. But I would not be surprised if it took centuries, and I am confident it will at least take decades.

But we don’t need AGI for AI to have powerful effects on our lives. Indeed, even now, AI is already affecting our lives—in mostly bad ways, frankly, as we seem to be hurtling gleefully toward the very same corporatist cyberpunk dystopia we were warned about in the 1980s.

A lot of technologies have done great things for humanity—sanitation and vaccines, for instance—and even automation can be a very good thing, as increased productivity is how we attained our First World standard of living. But AI in particular seems best at automating away the kinds of jobs human beings actually find most fulfilling, and worsening our already staggering inequality. As a civilization, we really need to ask ourselves why we got automated writing and art before we got automated sewage cleaning or corporate management. (We should also ask ourselves why automated stock trading resulted in even more money for stock traders, instead of putting them out of their worthless parasitic jobs.) There are technological reasons for this, yes; but there are also cultural and institutional ones. Automated teaching isn’t far away, and education will be all the worse for it.

To change our lives, AI doesn’t have to be good at everything. It just needs to be good at whatever we were doing to make a living. AGI may be far away, but the impact of AI is already here.

Indeed, I think this quixotic quest for AGI, and all the concern about how to control it and what effects it will have upon our society, may actually be distracting from the real harms that “ordinary” “boring” AI is already having upon our society. I think a Terminator scenario, where the machines rapidly surpass our level of intelligence and rise up to annihilate us, is quite unlikely. But a scenario where AI puts millions of people out of work with insufficient safety net, triggering economic depression and civil unrest? That could be right around the corner.

Frankly, all it may take is getting automated trucks to work, which could be just a few years. There are nearly 4 million truck drivers in the United States—a full percentage point of employment unto itself. And the Governor of California just vetoed a bill that would require all automated trucks to have human drivers. From an economic efficiency standpoint, his veto makes perfect sense: If the trucks don’t need drivers, why require them? But from an ethical and societal standpoint… what do we do with all the truck drivers!?

We do seem to have better angels after all

PNRJ book reviews, core principles, development economics, ethics, futurism, inequality, public policy , , , , , , , , , , ,

Jun 18 JDN 2460114

A review of The Darker Angels of Our Nature

(I apologize for not releasing this on Sunday; I’ve been traveling lately and haven’t found much time to write.)

Since its release, I have considered Steven Pinker’s The Better Angels of our Nature among a small elite category of truly great books—not simply good because enjoyable, informative, or well-written, but great in its potential impact on humanity’s future. Others include The General Theory of Employment, Interest, and Money, On the Origin of Species, and Animal Liberation.

But I also try to expose myself as much as I can to alternative views. I am quite fearful of the echo chambers that social media puts us in, where dissent is quietly hidden from view and groupthink prevails.

So when I saw that a group of historians had written a scathing critique of The Better Angels, I decided I surely must read it and get its point of view. This book is The Darker Angels of Our Nature.

The Darker Angels is written by a large number of different historians, and it shows. It’s an extremely disjointed book; it does not present any particular overall argument, various sections differ wildly in scope and tone, and sometimes they even contradict each other. It really isn’t a book in the usual sense; it’s a collection of essays whose only common theme is that they disagree with Steven Pinker.

In fact, even that isn’t quite true, as some of the best essays in The Darker Angels are actually the ones that don’t fundamentally challenge Pinker’s contention that global violence has been on a long-term decline for centuries and is now near its lowest in human history. These essays instead offer interesting insights into particular historical eras, such as medieval Europe, early modern Russia, and shogunate Japan, or they add additional nuances to the overall pattern, like the fact that, compared to medieval times, violence in Europe seems to have been less in the Pax Romana (before) and greater in the early modern period (after), showing that the decline in violence was not simple or steady, but went through fluctuations and reversals as societies and institutions changed. (At this point I feel I should note that Pinker clearly would not disagree with this—several of the authors seem to think he would, which makes me wonder if they even read The Better Angels.)

Others point out that the scale of civilization seems to matter, that more is different, and larger societies and armies more or less automatically seem to result in lower fatality rates by some sort of scaling or centralization effect, almost like the square-cube law. That’s very interesting if true; it would suggest that in order to reduce violence, you don’t really need any particular mode of government, you just need something that unites as many people as possible under one banner. The evidence presented for it was too weak for me to say whether it’s really true, however, and there was really no theoretical mechanism proposed whatsoever.

Some of the essays correct genuine errors Pinker made, some of which look rather sloppy. Pinker clearly overestimated the death tolls of the An Lushan Rebellion, the Spanish Inquisition, and Aztec ritual executions, probably by using outdated or biased sources. (Though they were all still extremely violent!) His depiction of indigenous cultures does paint with a very broad brush, and fails to recognize that some indigenous societies seem to have been quite peaceful (though others absolutely were tremendously violent).

One of the best essays is about Pinker’s cavalier attitude toward mass incarceration, which I absolutely do consider a deep flaw in Pinker’s view. Pinker presents increased incarceration rates along with decreased crime rates as if they were an unalloyed good, while I can at best be ambivalent about whether the benefit of decreasing crime is worth the cost of greater incarceration. Pinker seems to take for granted that these incarcerations are fair and impartial, when we have a great deal of evidence that they are strongly biased against poor people and people of color.

There’s another good essay about the Enlightenment, which Pinker seems to idealize a little too much (especially in his other book Enlightenment Now). There was no sudden triumph of reason that instantly changed the world. Human knowledge and rationality gradually improved over a very long period of time, with no obvious turning point and many cases of backsliding. The scientific method isn’t a simple, infallible algorithm that suddenly appeared in the brain of Galileo or Bayes, but a whole constellation of methods and concepts of rationality that took centuries to develop and is in fact still developing. (Much as the Tao that can be told is not the eternal Tao, the scientific method that can be written in a textbook is not the true scientific method.)

Several of the essays point out the limitations of historical and (especially) archaeological records, making it difficult to draw any useful inferences about rates of violence in the past. I agree that Pinker seems a little too cavalier about this; the records really are quite sparse and it’s not easy to fill in the gaps. Very small samples can easily distort homicide rates; since only about 1% of deaths worldwide are homicide, if you find 20 bodies, whether or not one of them was murdered is the difference between peaceful Japan and war-torn Colombia.

On the other hand, all we really can do is make the best inferences we have with the available data, and for the time periods in which we do have detailed records—surely true since at least the 19th century—the pattern of declining violence is very clear, and even the World Wars look like brief fluctuations rather than fundamental reversals. Contrary to popular belief, the World Wars do not appear to have been especially deadly on a per-capita basis, compared to various historic wars. The primary reason so many people died in the World Wars was really that there just were more people in the world. A few of the authors don’t seem to consider this an adequate reason, but ask yourself this: Would you rather live in a society of 100 in which 10 people are killed, or a society of 1 billion in which 1 million are killed? In the former case your chances of being killed are 10%; in the latter, 0.1%. Clearly, per-capita measures of violence are the correct ones.

Some essays seem a bit beside the point, like one on “environmental violence” which quite aptly details the ongoing—terrifying—degradation of our global ecology, but somehow seems to think that this constitutes violence when it obviously doesn’t. There is widespread violence against animals, certainly; slaughterhouses are the obvious example—and unlike most people, I do not consider them some kind of exception we can simply ignore. We do in fact accept levels of cruelty to pigs and cows that we would never accept against dogs or horses—even the law makes such exceptions. Moreover, plenty of habitat destruction is accompanied by killing of the animals who lived in that habitat. But ecological degradation is not equivalent to violence. (Nor is it clear to me that our treatment of animals is more violent overall today than in the past; I guess life is probably worse for a beef cow today than it was in the medieval era, but either way, she was going to be killed and eaten. And at least we no longer do cat-burning.) Drilling for oil can be harmful, but it is not violent. We can acknowledge that life is more peaceful now than in the past without claiming that everything is better now—in fact, one could even say that overall life isn’t better, but I think they’d be hard-pressed to argue that.

These are the relatively good essays, which correct minor errors or add interesting nuances. There are also some really awful essays in the mix.

A common theme of several of the essays seems to be “there are still bad things, so we can’t say anything is getting better”; they will point out various forms of violence that undeniably still exist, and treat this as a conclusive argument against the claim that violence has declined. Yes, modern slavery does exist, and it is a very serious problem; but it clearly is not the same kind of atrocity that the Atlantic slave trade was. Yes, there are still murders. Yes, there are still wars. Probably these things will always be with us to some extent; but there is a very clear difference between 500 homicides per million people per year and 50—and it would be better still if we could bring it down to 5.

There’s one essay about sexual violence that doesn’t present any evidence whatsoever to contradict the claim that rates of sexual violence have been declining while rates of reporting and prosecution have been increasing. (These two trends together often result in reported rapes going up, but most experts agree that actual rapes are going down.) The entire essay is based on anecdote, innuendo, and righteous anger.

There are several essays that spend their whole time denouncing neoliberal capitalism (not even presenting any particularly good arguments against it, though such arguments do exist), seeming to equate Pinker’s view with some kind of Rothbardian anarcho-capitalism when in fact Pinker is explictly in favor of Nordic-style social democracy. (One literally dismisses his support for universal healthcare as “Well, he is Canadian”.) But Pinker has on occasion said good things about capitalism, so clearly, he is an irredeemable monster.

Right in the introduction—which almost made me put the book down—is an astonishingly ludicrous argument, which I must quote in full to show you that it is not out of context:

What actually is violence (nowhere posed or answered in The Better Angels)? How do people perceive it in different time-place settings? What is its purpose and function? What were contemporary attitudes toward violence and how did sensibilities shift over time? Is violence always ‘bad’ or can there be ‘good’ violence, violence that is regenerative and creative?

The Darker Angels of Our Nature, p.16

Yes, the scare quotes on ‘good’ and ‘bad’ are in the original. (Also the baffling jargon “time-place settings” as opposed to, say, “times and places”.) This was clearly written by a moral relativist. Aside from questioning whether we can say anything about anything, the argument seems to be that Pinker’s argument is invalid because he didn’t precisely define every single relevant concept, even though it’s honestly pretty obvious what the world “violence” means and how he is using it. (If anything, it’s these authors who don’t seem to understand what the word means; they keep calling things “violence” that are indeed bad, but obviously aren’t violence—like pollution and cyberbullying. At least talk of incarceration as “structural violence” isn’t obvious nonsense—though it is still clearly distinct from murder rates.)

But it was by reading the worst essays that I think I gained the most insight into what this debate is really about. Several of the essays in The Darker Angels thoroughly and unquestioningly share the following inference: if a culture is superior, then that culture has a right to impose itself on others by force. On this, they seem to agree with the imperialists: If you’re better, that gives you a right to dominate everyone else. They rightly reject the claim that cultures have a right to imperialistically dominate others, but they cannot deny the inference, and so they are forced to deny that any culture can ever be superior to another. The result is that they tie themselves in knots trying to justify how greater wealth, greater happiness, less violence, and babies not dying aren’t actually good things. They end up talking nonsense about “violence that is regenerative and creative”.

But we can believe in civilization without believing in colonialism. And indeed that is precisely what I (along with Pinker) believe: That democracy is better than autocracy, that free speech is better than censorship, that health is better than illness, that prosperity is better than poverty, that peace is better than war—and therefore that Western civilization is doing a better job than the rest. I do not believe that this justifies the long history of Western colonial imperialism. Governing your own country well doesn’t give you the right to invade and dominate other countries. Indeed, part of what makes colonial imperialism so terrible is that it makes a mockery of the very ideals of peace, justice, and freedom that the West is supposed to represent.

I think part of the problem is that many people see the world in zero-sum terms, and believe that the West’s prosperity could only be purchased by the rest of the world’s poverty. But this is untrue. The world is nonzero-sum. My happiness does not come from your sadness, and my wealth does not come from your poverty. In fact, even the West was poor for most of history, and we are far more prosperous now that we have largely abandoned colonial imperialism than we ever were in imperialism’s heyday. (I do occasionally encounter British people who seem vaguely nostalgic for the days of the empire, but real median income in the UK has doubled just since 1977. Inequality has also increased during that time, which is definitely a problem; but the UK is undeniably richer now than it ever was at the peak of the empire.)

In fact it could be that the West is richer now because of colonalism than it would have been without it. I don’t know whether or not this is true. I suspect it isn’t, but I really don’t know for sure. My guess would be that colonized countries are poorer, but colonizer countries are not richer—that is, colonialism is purely destructive. Certain individuals clearly got richer by such depredation (Leopold II, anyone?), but I’m not convinced many countries did.

Yet even if colonialism did make the West richer, it clearly cannot explain most of the wealth of Western civilization—for that wealth simply did not exist in the world before. All these bridges and power plants, laptops and airplanes weren’t lying around waiting to be stolen. Surely, some of the ingredients were stolen—not least, the land. Had they been bought at fair prices, the result might have been less wealth for us (then again it might not, for wealthier trade partners yield greater exports). But this does not mean that the products themselves constitute theft, nor that the wealth they provide is meaningless. Perhaps we should find some way to pay reparations; undeniably, we should work toward greater justice in the future. But we do not need to give up all we have in order to achieve that justice.

There is a law of conservation of energy. It is impossible to create energy in one place without removing it from another. There is no law of conservation of prosperity. Making the world better in one place does not require making it worse in another.

Progress is real. Yes, it is flawed, uneven, and it has costs of its own; but it is real. If we want to have more of it, we best continue to believe in it. And The Better Angels of Our Nature does have some notable flaws, but it still retains its place among truly great books.

When maximizing utility doesn’t

PNRJ critique of neoclassical economics, ethics, futurism , , , , , , , , , , ,

Jun 4 JDN 2460100

Expected utility theory behaves quite strangely when you consider questions involving mortality.

Nick Beckstead and Teruji Thomas recently published a paper on this: All well-defined utility functions are either reckless in that they make you take crazy risks, or timid in that they tell you not to take even very small risks. It’s starting to make me wonder if utility theory is even the right way to make decisions after all.

Consider a game of Russian roulette where the prize is $1 million. The revolver has 6 chambers, 3 with a bullet. So that’s a 1/2 chance of $1 million, and a 1/2 chance of dying. Should you play?

I think it’s probably a bad idea to play. But the prize does matter; if it were $100 million, or $1 billion, maybe you should play after all. And if it were $10,000, you clearly shouldn’t.

And lest you think that there is no chance of dying you should be willing to accept for any amount of money, consider this: Do you drive a car? Do you cross the street? Do you do anything that could ever have any risk of shortening your lifespan in exchange for some other gain? I don’t see how you could live a remotely normal life without doing so. It might be a very small risk, but it’s still there.

This raises the question: Suppose we have some utility function over wealth; ln(x) is a quite plausible one. What utility should we assign to dying?


The fact that the prize matters means that we can’t assign death a utility of negative infinity. It must be some finite value.

But suppose we choose some value, -V, (so V is positive), for the utility of dying. Then we can find some amount of money that will make you willing to play: ln(x) = V, x = e^(V).

Now, suppose that you have the chance to play this game over and over again. Your marginal utility of wealth will change each time you win, so we may need to increase the prize to keep you playing; but we could do that. The prizes could keep scaling up as needed to make you willing to play. So then, you will keep playing, over and over—and then, sooner or later, you’ll die. So, at each step you maximized utility—but at the end, you didn’t get any utility.

Well, at that point your heirs will be rich, right? So maybe you’re actually okay with that. Maybe there is some amount of money ($1 billion?) that you’d be willing to die in order to ensure your heirs have.

But what if you don’t have any heirs? Or, what if we consider making such a decision as a civilization? What if death means not only the destruction of you, but also the destruction of everything you care about?

As a civilization, are there choices before us that would result in some chance of a glorious, wonderful future, but also some chance of total annihilation? I think it’s pretty clear that there are. Nuclear technology, biotechnology, artificial intelligence. For about the last century, humanity has been at a unique epoch: We are being forced to make this kind of existential decision, to face this kind of existential risk.

It’s not that we were immune to being wiped out before; an asteroid could have taken us out at any time (as happened to the dinosaurs), and a volcanic eruption nearly did. But this is the first time in humanity’s existence that we have had the power to destroy ourselves. This is the first time we have a decision to make about it.

One possible answer would be to say we should never be willing to take any kind of existential risk. Unlike the case of an individual, when we speaking about an entire civilization, it no longer seems obvious that we shouldn’t set the utility of death at negative infinity. But if we really did this, it would require shutting down whole industries—definitely halting all research in AI and biotechnology, probably disarming all nuclear weapons and destroying all their blueprints, and quite possibly even shutting down the coal and oil industries. It would be an utterly radical change, and it would require bearing great costs.

On the other hand, if we should decide that it is sometimes worth the risk, we will need to know when it is worth the risk. We currently don’t know that.

Even worse, we will need some mechanism for ensuring that we don’t take the risk when it isn’t worth it. And we have nothing like such a mechanism. In fact, most of our process of research in AI and biotechnology is widely dispersed, with no central governing authority and regulations that are inconsistent between countries. I think it’s quite apparent that right now, there are research projects going on somewhere in the world that aren’t worth the existential risk they pose for humanity—but the people doing them are convinced that they are worth it because they so greatly advance their national interest—or simply because they could be so very profitable.

In other words, humanity finally has the power to make a decision about our survival, and we’re not doing it. We aren’t making a decision at all. We’re letting that responsibility fall upon more or less randomly-chosen individuals in government and corporate labs around the world. We may be careening toward an abyss, and we don’t even know who has the steering wheel.

We ignorant, incompetent gods

PNRJ book reviews, cognitive science, core principles, ethics, futurism, inequality, tribal paradigm , , , , , , , , , , , , , , , , ,

May 21 JDN 2460086

A review of Homo Deus

The real problem of humanity is the following: We have Paleolithic emotions, medieval institutions and godlike technology.

E.O. Wilson

Homo Deus is a very good read—and despite its length, a quick one; as you can see, I read it cover to cover in a week. Yuval Noah Harari’s central point is surely correct: Our technology is reaching a threshold where it grants us unprecedented power and forces us to ask what it means to be human.

Biotechnology and artificial intelligence are now advancing so rapidly that advancements in other domains, such as aerospace and nuclear energy, seem positively mundane. Who cares about making flight or electricity a bit cleaner when we will soon have the power to modify ourselves or we’ll all be replaced by machines?

Indeed, we already have technology that would have seemed to ancient people like the powers of gods. We can fly; we can witness or even control events thousands of miles away; we can destroy mountains; we can wipeout entire armies in an instant; we can even travel into outer space.

Harari rightly warns us that our not-so-distant descendants are likely to have powers that we would see as godlike: Immortality, superior intelligence, self-modification, the power to create life.

And where it is scary to think about what they might do with that power if they think the way we do—as ignorant and foolish and tribal as we are—Harari points out that it is equally scary to think about what they might do if they don’t think the way we do—for then, how do they think? If their minds are genetically modified or even artificially created, who will they be? What values will they have, if not ours? Could they be better? What if they’re worse?

It is of course difficult to imagine values better than our own—if we thought those values were better, we’d presumably adopt them. But we should seriously consider the possibility, since presumably most of us believe that our values today are better than what most people’s values were 1000 years ago. If moral progress continues, does it not follow that people’s values will be better still 1000 years from now? Or at least that they could be?

I also think Harari overestimates just how difficult it is to anticipate the future. This may be a useful overcorrection; the world is positively infested with people making overprecise predictions about the future, often selling them for exorbitant fees (note that Harari was quite well-compensated for this book as well!). But our values are not so fundamentally alien from those of our forebears, and we have reason to suspect that our descendants’ values will be no more different from ours.

For instance, do you think that medieval people thought suffering and death were good? I assure you they did not. Nor did they believe that the supreme purpose in life is eating cheese. (They didn’t even believe the Earth was flat!) They did not have the concept of GDP, but they could surely appreciate the value of economic prosperity.

Indeed, our world today looks very much like a medieval peasant’s vision of paradise. Boundless food in endless variety. Near-perfect security against violence. Robust health, free from nearly all infectious disease. Freedom of movement. Representation in government! The land of milk and honey is here; there they are, milk and honey on the shelves at Walmart.

Of course, our paradise comes with caveats: Not least, we are by no means free of toil, but instead have invented whole new kinds of toil they could scarcely have imagined. If anything I would have to guess that coding a robot or recording a video lecture probably isn’t substantially more satisfying than harvesting wheat or smithing a sword; and reconciling receivables and formatting spreadsheets is surely less. Our tasks are physically much easier, but mentally much harder, and it’s not obvious which of those is preferable. And we are so very stressed! It’s honestly bizarre just how stressed we are, given the abudance in which we live; there is no reason for our lives to have stakes so high, and yet somehow they do. It is perhaps this stress and economic precarity that prevents us from feeling such joy as the medieval peasants would have imagined for us.

Of course, we don’t agree with our ancestors on everything. The medieval peasants were surely more religious, more ignorant, more misogynistic, more xenophobic, and more racist than we are. But projecting that trend forward mostly means less ignorance, less misogyny, less racism in the future; it means that future generations should see the world world catch up to what the best of us already believe and strive for—hardly something to fear. The values that I believe are surely not what we as a civilization act upon, and I sorely wish they were. Perhaps someday they will be.

I can even imagine something that I myself would recognize as better than me: Me, but less hypocritical. Strictly vegan rather than lacto-ovo-vegetarian, or at least more consistent about only buying free range organic animal products. More committed to ecological sustainability, more willing to sacrifice the conveniences of plastic and gasoline. Able to truly respect and appreciate all life, even humble insects. (Though perhaps still not mosquitoes; this is war. They kill more of us than any other animal, including us.) Not even casually or accidentally racist or sexist. More courageous, less burnt out and apathetic. I don’t always live up to my own ideals. Perhaps someday someone will.

Harari fears something much darker, that we will be forced to give up on humanist values and replace them with a new techno-religion he calls Dataism, in which the supreme value is efficient data processing. I see very little evidence of this. If it feels like data is worshipped these days, it is only because data is profitable. Amazon and Google constantly seek out ever richer datasets and ever faster processing because that is how they make money. The real subject of worship here is wealth, and that is nothing new. Maybe there are some die-hard techno-utopians out there who long for us all to join the unified oversoul of all optimized data processing, but I’ve never met one, and they are clearly not the majority. (Harari also uses the word ‘religion’ in an annoyingly overbroad sense; he refers to communism, liberalism, and fascism as ‘religions’. Ideologies, surely; but religions?)

Harari in fact seems to think that ideologies are strongly driven by economic structures, so maybe he would even agree that it’s about profit for now, but thinks it will become religion later. But I don’t really see history fitting this pattern all that well. If monotheism is directly tied to the formation of organized bureaucracy and national government, then how did Egypt and Rome last so long with polytheistic pantheons? If atheism is the natural outgrowth of industrialized capitalism, then why are Africa and South America taking so long to get the memo? I do think that economic circumstances can constrain culture and shift what sort of ideas become dominant, including religious ideas; but there clearly isn’t this one-to-one correspondence he imagines. Moreover, there was never Coalism or Oilism aside from the greedy acquisition of these commodities as part of a far more familiar ideology: capitalism.

He also claims that all of science is now, or is close to, following a united paradigm under which everything is a data processing algorithm, which suggests he has not met very many scientists. Our paradigms remain quite varied, thank you; and if they do all have certain features in common, it’s mainly things like rationality, naturalism and empiricism that are more or less inherent to science. It’s not even the case that all cognitive scientists believe in materialism (though it probably should be); there are still dualists out there.

Moreover, when it comes to values, most scientists believe in liberalism. This is especially true if we use Harari’s broad sense (on which mainline conservatives and libertarians are ‘liberal’ because they believe in liberty and human rights), but even in the narrow sense of center-left. We are by no means converging on a paradigm where human life has no value because it’s all just data processing; maybe some scientists believe that, but definitely not most of us. If scientists ran the world, I can’t promise everything would be better, but I can tell you that Bush and Trump would never have been elected and we’d have a much better climate policy in place by now.

I do share many of Harari’s fears of the rise of artificial intelligence. The world is clearly not ready for the massive economic disruption that AI is going to cause all too soon. We still define a person’s worth by their employment, and think of ourselves primarily as collection of skills; but AI is going to make many of those skills obsolete, and may make many of us unemployable. It would behoove us to think in advance about who we truly are and what we truly want before that day comes. I used to think that creative intellectual professions would be relatively secure; ChatGPT and Midjourney changed my mind. Even writers and artists may not be safe much longer.

Harari is so good at sympathetically explaining other views he takes it to a fault. At times it is actually difficult to know whether he himself believes something and wants you to, or if he is just steelmanning someone else’s worldview. There’s a whole section on ‘evolutionary humanism’ where he details a worldview that is at best Nietschean and at worst Nazi, but he makes it sound so seductive. I don’t think it’s what he believes, in part because he has similarly good things to say about liberalism and socialism—but it’s honestly hard to tell.

The weakest part of the book is when Harari talks about free will. Like most people, he just doesn’t get compatibilism. He spends a whole chapter talking about how science ‘proves we have no free will’, and it’s just the same old tired arguments hard determinists have always made.

He talks about how we can make choices based on our desires, but we can’t choose our desires; well of course we can’t! What would that even mean? If you could choose your desires, what would you choose them based on, if not your desires? Your desire-desires? Well, then, can you choose your desire-desires? What about your desire-desire-desires?

What even is this ultimate uncaused freedom that libertarian free will is supposed to consist in? No one seems capable of even defining it. (I’d say Kant got the closest: He defined it as the capacity to act based upon what ought rather than what is. But of course what we believe about ‘ought’ is fundamentally stored in our brains as a particular state, a way things are—so in the end, it’s an ‘is’ we act on after all.)

Maybe before you lament that something doesn’t exist, you should at least be able to describe that thing as a coherent concept? Woe is me, that 2 plus 2 is not equal to 5!

It is true that as our technology advances, manipulating other people’s desires will become more and more feasible. Harari overstates the case on so-called robo-rats; they aren’t really mind-controlled, it’s more like they are rewarded and punished. The rat chooses to go left because she knows you’ll make her feel good if she does; she’s still freely choosing to go left. (Dangling a carrot in front of a horse is fundamentally the same thing—and frankly, paying a wage isn’t all that different.) The day may yet come where stronger forms of control become feasible, and woe betide us when it does. Yet this is no threat to the concept of free will; we already knew that coercion was possible, and mind control is simply a more precise form of coercion.

Harari reports on a lot of interesting findings in neuroscience, which are important for people to know about, but they do not actually show that free will is an illusion. What they do show is that free will is thornier than most people imagine. Our desires are not fully unified; we are often ‘of two minds’ in a surprisingly literal sense. We are often tempted by things we know are wrong. We often aren’t sure what we really want. Every individual is in fact quite divisible; we literally contain multitudes.

We do need a richer account of moral responsibility that can deal with the fact that human beings often feel multiple conflicting desires simultaneously, and often experience events differently than we later go on to remember them. But at the end of the day, human consciousness is mostly unified, our choices are mostly rational, and our basic account of moral responsibility is mostly valid.

I think for now we should perhaps be less worried about what may come in the distant future, what sort of godlike powers our descendants may have—and more worried about what we are doing with the godlike powers we already have. We have the power to feed the world; why aren’t we? We have the power to save millions from disease; why don’t we? I don’t see many people blindly following this ‘Dataism’, but I do see an awful lot blinding following a 19th-century vision of capitalism.

And perhaps if we straighten ourselves out, the future will be in better hands.