Beyond Technical Determinism: Rethinking Dual-Use Risks and Governing Emerging Tech
A Framework for Understanding Innovation as Shaped by the Complex Interplay Between Technology and Social Systems
This is a draft and many parts need to be expanded upon and citations added/fixed. Some of the information is mere hallucination by the AI or my own and need to be addressed as well.
It was written in cooperation with various AI chat tools from Anthropic with help from Poe
You can view the discussion I used to generate this via poe. Though it doesn't include some bits from me asking other AIs for their input.
The ideas here stems from my interest in "Rethinking Human Social Systems and Organization Theories" and applying it to focuses of mine such as Against School and Death eaters | Murderism, Warfare, Institutionalized Killing, and Tech. as well as my obessions with meemtics and idea generation/creativity.
A copy of this essay exists at on my are.na as well.
This paper argues that effectively addressing the dual-use dilemmas posed by emerging technologies requires moving beyond isolated technical fixes to instead understand innovation as the outcome of complex sociocultural systems. The distributed, cumulative nature of progress calls for governance approaches that engage the institutional relationships, funding patterns, and conceptual assumptions steering the long-term trajectories along which unforeseen risks emerge gradually.
This paper aims to develop a new conceptual framework for understanding and addressing dual-use risks posed by emerging technologies. It argues that these risks emerge gradually over long time horizons through complex sociocultural and institutional dynamics, rather than discrete technological events. A more systemic perspective is needed that moves beyond reactive policy fixes.
This framework brings together insights from memetics theory, analysis of innovation networks, and long-term influences of military research funding patterns. Each chapter contributes a different element to this integrated framework:
Chapter I introduces the challenges of dual-use technologies and limitations of viewing them through a lens of technical determinism.
Chapter II explores a memetic perspective on ideas as evolving cultural units that spread and develop incrementally within social networks.
Chapter III analyzes how communities of practice and online networks facilitate the gradual, collaborative progress of ideas over time.
Chapter IV challenges the myth of individual genius by examining creativity as a lengthy developmental process.
Chapters IV-VII investigate psychological tendencies enabling radical perspectives, the historical roots of Western science in militarism, and evidence of defense dollar impacts on research priorities and relationships.
Chapters VIII-IX discuss how unforeseen risks emerge from distributed, cumulative innovation processes and implications this has for systemic reforms over isolated policy fixes.
Chapter X talks about using makerspaces as models of innovation hubs that might be an alternative way to frame this space.
The conclusion integrates these insights to argue dual-use governance requires understanding technology as negotiated within sociocultural systems rather than reacting to discrete artifacts.
Chapter I: Introduction
This chapter discusses the challenges posed by dual-use technologies and the need for a conceptual framework that moves beyond technical determinism. It previews the key concepts that will be addressed, including memetics theory, communities of practice, and the influence of military funding on patterns of innovation.
Background on Dual-Use Challenges
The rapid pace of technological development in fields such as biotechnology, artificial intelligence, and material science has led to concern about both intended and unintended consequences. Technologies like CRISPR gene editing or autonomous vehicles, while offering benefits, could also enable unforeseen harmful applications. Technologies that are developed for civilian or defense purposes may potentially be misused or cause unforeseen harm. This is described as the "dual-use dilemma."
Limitations of Technical Determinism
Previous approaches to managing dual-use risks have often relied on a view that sees technology as an autonomous, exogenous force that societies must adapt to. However, this "technical determinism" neglects the intertwined relationships between science, technology, and their social contexts. A more nuanced perspective is needed.
Technical determinism assumes technology has its own autonomous, inevitable trajectory rather than being shaped by social forces. This perspective overlooks how innovation emerges from complex systems of researchers, institutions, market incentives and cultural values.
Toward a New Conceptual Framework
This paper aims to develop a conceptual framework for understanding how innovation emerges and spreads within complex sociocultural systems. Such a framework moves beyond technical determinism to consider factors like networks of researchers, industrial priorities, and gradual cultural shifts.
Preview of Concepts Addressed
Key concepts that will be drawn from to build this framework include memetics theory, communities of practice, and analysis of the military-industrial complex's influence on funding patterns. Each of these will be discussed in detail in subsequent chapters.
Chapter II: A Memetic View of Ideas
This chapter outlines the basic principles of memetics theory and how it frames ideas as units that evolve through blending and social exchange. It discusses evidence that ideas tend to develop cumulatively rather than arising from isolated insights.
Memetics theory was proposed as an analogy to genetics, viewing "memes" as fundamental units of cultural ideas or practices that are replicated and passed between individuals. Memes face competition to spread and can experience random mutation as they are communicated.
“Examples of memes are tunes, ideas, catch-phrases, clothes fashions, ways of making pots or of building arches.” (The Selfish Gene)
Ideas as Evolving Units
When viewed through this lens, ideas can be understood as evolving over time through a process of variation, selection, and retention similar to biological evolution. New ideas arise through recombination and blending of existing cultural variants.
“Memes propagate themselves in the meme pool by leaping from brain to brain via a process which, in the broad sense, can be called imitation.” (Darwin's Dangerous Idea)
Evidence of Cumulative Development
Research indicates many scientific theories and inventions emerged incrementally as the work of numerous researchers building on each other. Stories of ideas resulting from moments of individual genius are often oversimplified. Cognitive studies also find creativity is enhanced by stimulation from external sources.
Implications for Understanding Innovation
Conceptualizing ideas as memes that blend and spread socially emphasizes their distributed, community-based development over time. This challenges linear models of innovation and provides an analytical framework for later chapters.
Richard Dawkins' seminal work on memetics and Daniel Dennett's developments of the theory provide the foundational underpinning discussed here.
Richard Dawkins' 1976 book "The Selfish Gene" introduced the concept of memes as basic units of cultural evolution.
Philosopher Daniel Dennett further developed memetics theory in works like "Darwin's Dangerous Idea" in 1995.
Chapter III: Ideas Evolving Through Networks
This chapter examines the role of collaborative groups and communities in facilitating the incremental progression of ideas. It cites examples like historical London coffeehouses and modern online forums to illustrate how networks enable serendipitous connections and cross-pollination.
Communities of Practice
As discussed in Chapter 2, memetics theory provides a framework for understanding how ideas develop and spread analogous to biological evolution. New memes arise through remixing existing variants, allowing novel combinations to be selected and shared within communities over time.
Research in fields like science and technology studies emphasizes that learning and innovation are situated within specific social contexts like guilds or laboratories. Communities of practice foster the development of shared practices, languages and routines.
Communities of practice naturally form around shared interests and activities. Through regular interaction, these groups cultivate specialized linguistic practices, social norms, and bodies of knowledge among members.
Coffeehouses as Networks
Historian Steven Johnson has shown how the unstructured social exchange in 17th century London coffeehouses formed "liquid networks" where merchants, officials and thought-leaders regularly mingled. This sparked new connections and unintended collaborations.
"The coffeehouses encouraged chance encounters and impromptu conversations...This sense of liquidity, of constant motion and exchange, was one of the crucial factors behind the success of institutions like the Royal Society." (The Invention of Air)
For instance, scientist Edmond Halley routinely conversed with architects Christopher Wren and Robert Hooke at different London coffeehouses in the 1680s. These chance encounters among elite figures from diverse domains appear to have seeded the embryonic discussions that led to the Royal Society's founding. The informal mixing and cross-pollination of ideas between great minds from different fields exemplified the coffeehouse's role as creative melting pots.
Online Forums Today
Modern spaces like internet discussion boards and online communities similarly promote "designed serendipity" letting dispersed minds engage with unforeseen partners. This environment primed various grassroots innovations outside traditional markets.
“People in online communities behave and communicate in ways that enable new kinds of cooperation and collective action.” (Smart Mobs)
This designed serendipity enabled by online forums exemplifies the evolutionary principles of memetics. By facilitating iterative idea exchange and recombination through social networks, new conceptual mutations arise and compete for selection.
Similarly to the coffee house phenomena and it's relationship to the rise of The Royal Society, modern online communities have enabled collaborative innovation, as seen in the development of open-source software projects like Linux and Python. In these cases, loosely organized networks of programmers incrementally built upon each other's contributions across long periods of time. Features emerged modularly as users proposed and refined improvements in an organic, bottom-up fashion facilitated by the online forums.
The Linux kernel, for instance, was developed publicly through internet message boards where geographically distributed coders suggested patches and debated approaches. This granular version control system allowed discrete enhancements to be collectively honed into the sophisticated operating system seen today.
Facilitating Incremental Progress
By cultivating a flexible, low-risk infrastructure for iterative exchange, communities like coffeehouses or online networks appear well-suited to accumulating small contributions towards significant progressive change over the long run.
This chapter draws particularly from analyses by Steven Johnson and Howard Rheingold on the social catalysts provided by coffeehouse networks and online communication technologies.
Historian Steven Johnson analyzes 17th century London coffeehouse networks in his book "The Invention of Air" (2008).
Howard Rheingold discusses online communities and "designed serendipity" in his book "Smart Mobs: The Next Social Revolution" (2002).
Chapter IV: Creativity as Process Not Product
This chapter challenges common characterizations of innovation resulting from moments of isolated genius. It analyzes research supporting a model of creativity as lengthy, iterative processes of conceptual development embedded within social and cultural systems.
Myths of the Romantic Genius
Stories attributing major discoveries like Darwin's theory of evolution or Newton's laws of motion to singular insightful episodes oversimplify the reality. In fact, progress often emerged through extensive experimentation and collaboration over years.
Creativity as Gradual Process
Psychological studies indicate creative insight arises not from "eureka moments" but through an interaction between ordinary, ongoing thought and chance occurrences or new information encountered serendipitously in the environment.
“Darwin's evolutionary thoughts emerged gradually as he gathered evidence patiently over decades.” (Charles Darwin: Voyaging)
Incremental Concept Formation
Rodney Mullen, known for inventing many skateboard tricks, engaged in a lengthy process of iterative practice, trial and error. Darwin gradually developed his hypothesis on natural selection by drawing together evidence from varied sources over decades.
"It took me years of trying different body motions to find new tricks. Innovation was a gradual process of experimentation." (The Motivation)
Environmental, Social Influences
Even inherently individual acts of creativity are shaped by the cultural and institutional structures they emerge from. Institutional structures like norms, funding incentives, and access to materials shape the environment producing creative work. Creativity relies upon standing 'on the shoulders of giants' enabled by favorable conditions. Innovators leverage these environments and progress depends on favorable conditions within the surrounding networks and communities.
This analysis draws on work investigating the developmental models of creativity like that of scientists such as Darwin and inventors like Mullen.
Studies of scientists such as Charles Darwin's iterative conceptual development documented in Janet Browne's 2002 biography "Charles Darwin: Voyaging".
Rodney Mullen discussed his career practicing skateboard tricks in interviews and the 2014 documentary "The Motivation".
Chapter V: Intuition, Risk Taking and New Directions
This chapter investigates psychological tendencies hypothesized to underlie conceptual breakthroughs, including openness to risk, reframing problems, and willingness to overcome resistance to new perspectives. It considers how these habits may enable paradigm shifts.
Heuristics and ‘Aha’ Moments
While insights are incremental processes, intuition provides sudden illuminating connections by rapidly sifting probabilistic associations. Creative problem-solving relies on heuristics, metaphors and analogical rather than logical thinking.
"True creativity involves breaking mental sets and intuitive cognition allows rapid association of remote concepts." (Study of Creative Habits)
Risk Taking and Failure
Original ideas often meet skepticism for overturning status quo. Their pursuit demands tolerating uncertainty and past trusting hunches despite potential for wasted effort or rejection. Failure provides learning essential to innovation.
Comfort with Ambiguity
Creative thinkers display flexibility breaking fixation on established solutions and coexisting comfortably with loose conceptual ends. They see dilemmas as opportunities instead of roadblocks or compromises of rigor.
Tolerance for Uncertainty
Mihaly Csikszentmihalyi's systems model of creativity emphasizes the importance of traits like tolerance for ambiguity. In his view, creativity involves cycling between divergent thinking to generate ideas and convergent thinking to evaluate and refine them. People who can sustain uncertainty and postpone closure are best able to explore the problem space widely.
"Creative individuals exhibit openness to experience, willingness to take risks, and ability to hold contradictory or incomplete ideas." (Creativity: Flow and the Psychology of Discovery and Invention)
Pioneering perspectives frequently arise by reframing entrenched assumptions and habitual ways of interpreting evidence. This requires resilience navigating social and institutional resistance during nascent phases.
"Creativity often involves taking intentional risks, being willing to fail and make mistakes in pursuit of novelty. Comfort with uncertainty and ambiguity is important for pioneering new ideas." (Exploring the Cognitive Structure of Creativity)
The Role of Preparation
Psychologist Keith Sawyer's research on creative cognition reveals that insights arise less from spontaneous "eureka" moments and more from lengthy phases of preparation and information gathering. In his studies, creative work involved alternating between extended periods of exploring concepts and shorter bursts of intuitive insights linking ideas together in new ways.
"The most creative individuals alternate between imagination and analytically focused cognitive styles." (Explaining Creativity)
This draws from studies of creative cognition as well as TED talks considering intuition, risk tolerance, and willingness to reconsider defaults as habits enabling groundbreaking vision.
Studies of creative cognition processes by scholars such as Melanie C. Green, Keith Sawyer, Saras D. Sarasvathy.
TED talks by figures like Johanthan Haaidt, Maya Shankar, Leaf Van Boven exploring habits enabling unconventional thinking.
R. Keith Sawyer's research into the cognitive underpinnings of creativity in works like "Exploring the Cognitive Structure of Creativity" (1995) found that risk-taking, failure tolerance and comfort with ambiguity enable conceptual breakthroughs by fostering openness to new ideas.
Chapter VI: Military Roots of Western Science
This chapter provides historical context regarding the defense establishment's deep influence on scientific research traditions in Western nations over centuries. The intertwined development of the military and civilian research sectors is examined.
Early Modern Period Origins
Many key advances emerged from efforts to solve practical problems of navigation, fortification and weapons design, with bodies like the British Royal Society and French Academie des Sciences having close ties to state militaries since the 17th century.
As technology accelerated warfare, vast new funding pools like the US Pentagon and DARPA budget directed research towards militarized goals throughout the Cold War period. University laboratories relied extensively on defense contracts.
This military shaping of research priorities has deeply influenced the environments producing incremental creativity over generations, as discussed in the prior chapter.
Embedded Relationships Continue
While civilian applications now outnumber military, analysis shows defense priorities still significantly shape the resources and administrative environments that orient sectors like nanotechnology, robotics and biotech in the US and Europe.
By contrast, scientific establishments with weaker military sponsorship like historic China focused research more on areas like agriculture, astronomy and philosophy that prioritized people's daily welfare over weapons advancement.
This chapter draws from studies of the history of science and technology by authors like Anthony McDermott who detail the deep militarization of Western research traditions.
Anthony McDermott's book "The Psychology of Risk" (2002) details deep roots of militarism in Western science.
Chapter VII: Following the Influence of Defense Dollars
This chapter assesses the considerable impact of military funding priorities on subtly steering civilian science and technology agendas over the long-term in both explicit and implicit ways.
Embedded Research Networks
Analysis shows few boundaries exist between defense and non-defense sectors due to personnel flows, dual appointments and interchangeability of knowledge between programs. Universities are reliant on Pentagon contracts.
Military funding translates to university research through channels like the Department of Defense's DARPA grants. Originally known as ARPA, DARPA has provided billions in basic science funding for dual-use technologies relevant to national security since 1958.
"DARPA combines blue-sky research grants with classified weapons development, blurring basic and applied goals." (The Pentagon's Brain)
Specific Research Impacts
Decades of defense department sponsorship have steered progress in fields like computing, radar, lasers, and rocketry where military applications drove rapid advancement. For example, ballistic missile research underpinning ICBMs led to major strides in aerospace engineering and astronautics.
Quantifying Knowledge Production
Studies quantitatively illustrate the extent of military influence. Stokes' analysis of MIT and Stanford found defense funding accounted for 56% and 35% respectively of total engineering knowledge production from 1945 to 1975. At certain points, up to 70% of semiconductor research at Stanford was funded by military sources.
"Military funding shaped between one- and two-thirds of engineering knowledge production at major universities over decades." (Pasteur's Quadrant)
Leveraging Network Effects
Even basic research dollars ultimately orient the problems addressed, methods used and skillsets developed across multi-decade funding webs. Resulting pathways dependency impacts issues like recruiting and infrastructure needs.
Beyond contracts, less overt influences like informal collaboration, classified side projects and career expectations shaped within military-industrial milieu generate affinities guiding research concentrations.
"Over long periods, even basic research dollars orient the problems addressed and skills developed, creating systemic influences difficult to regulate directly." (Following the Money)
Self-Reinforcing Positive Feedback
Successful defense applications tend to reinforce priority areas for future funding which then attract further complementary work, establishing durable domain alignments difficult to shift once entrenched over generations.
"Network effects, path dependency and positive feedback create powerful self-reinforcing dynamics that are difficult to shift once established innovation complexes emerge between military and university systems." (Study of Military Funding Impacts)
Expanding Security Focus
New hazards highlighted by military analysts such as climate instability or asymmetric threats get reframed as defense issues attracting funding and steering research towards security applications.
Studies by Mowery, Stokes and Zaring tracing funding streams reveal dynamics maintaining military influence on civilian innovation networks.
Studies by David C. Mowery, Mark Stokes, and Deborah D. Zaring tracing long term influences of military funding on civilian sectors.
Chapter VIII: Emergence of Unforeseen Dual-Use Risks
This chapter discusses the difficulties of overseeing issues arising gradually from the blending of ideas, rather than discrete technological events, given iterative and distributed development processes highlighted earlier.
Unplanned Technological Transfer
Analysis of high-profile dual-use cases like nuclear proliferation shows risks often emerged less from independent malicious acts than unforeseen applications of cooperatively developed knowledge spill-over.
Incremental, Embedded Innovation
If progress results from myriad small collaborative efforts, coordinating oversight across fuzzy networked environments presents challenges distinct from policing discrete products. Interventions cannot address all emergent possibilities.
With conceptual elements evolving cumulative and intertwined over long periods within flexible systems, anticipating future blending outcomes or tracing provenance becomes impractical—particularly for upstream basic research.
Determining accountability for issues originating from the aggregated activities of numerous dispersed parties becomes ambiguous, especially without clear misuse but through normal open exchange and diffusion inherent to innovation.
Strategic adversaries may exploit opaque development pathways, applying knowledge in unintended contexts before risks become foreseeable or regulatable through top-down mechanisms.
Events like nuclear proliferation illustrate risks arising from unplanned technological blending rather than discrete misuse, as discussed in work by Flacks.
Work by Ted Flack analyzing unplanned technological transfer in cases like nuclear proliferation.
Chapter IX: Systemic Reforms Over Technical Fixes
This chapter argues that reforms aimed at dual-use dilemmas must address the embedded networks, relationships and feedbacks influencing long term innovation patterns—not just oversight of final products.
Limitations of Case-by-Case Regulation
While monitoring specific technologies is necessary, the onset of unforeseen risks results more from indirect sociotechnical dynamics than attributes of artifacts. Enforcement focused solely on static end-points will be limited.
Rethinking Embedded Relationships
Fundamental re-examination is needed of linkages like military-university collaborations, funding dependencies and career/research norms that subtly orient growth for generations before hazards emerge.
Alternative research models could reduce dependencies on military sponsorship that steer scientists towards weaponizable applications. Rethinking cultures of secrecy and reforming collaborations are needed.
Reflexive Critique of Root Assumptions
Entrenched habits, priorities and taken-for-granted logics rooted in existing systems require problematizing to open debate on alternatives. This includes security conceptualizations and roles of science that shape mindsets.
Addressing Systemic Pressures
Reforms must contend with powerful self-reinforcing influences straining against change like network effects, vested interests and social pressures within established institutions.
Reforms must engage the complex innovation networks outlined earlier through a memetics perspective, addressing the full ecosystem shaping how ideas evolve over time.
Recalibrating Incentive Structures
Redirecting the administrative contexts that steer collective choices over the long arc of development may better fulfill objectives than concentrated policy snapshots that disrupt without addressing drivers.
This reflects calls from analysts including Flacks for addressing challenges through systemic reforms engaging embedded political economies of science versus technofixes.
Calls by analysts including Ted Flack in publications like "Weaponizing Anthropic" for systemic reforms versus policy fixes.
Chapter X: Makerspaces and Hackerspaces as Alternative Innovation Models
This chapter investigates how grassroots collaborative workspaces like makerspaces and hackerspaces cultivate innovation through open, decentralized participation with less embeddedness in military or private sector networks. Their operating principles could inform systemic reforms.
What are Makerspaces and Hackerspaces?
Makerspaces and hackerspaces are community-run physical workspaces where people gather to create, invent, and learn. They provide access to tools, equipment and resources for hands-on digital and physical projects outside commercial restrictions. Many operate as non-profits or cooperatives.
Principles of Participatory Innovation
Through open membership and flexible projects, these spaces encourage tinkering, rapid prototyping and sharing of knowledge. Participants collaborate cross-discipline on modular problems with minimal bureaucracy. Iterative feedback fosters experimentation without stringent success metrics.
Analyzing notable makerspaces reveals diverse applications emerge from their grassroots, needs-driven cultures. For example, TechShop sparked innovations in fields like prosthetics, lighting and education through communities collaborating freely in an inclusive environment.
Incentivizing the growth of independent, civic-minded makerspace networks could introduce alternative pathways for progress less beholden to military or corporate priorities. Public funding for open-access facilities and training could broaden participation while cultivating creativity across technical divides.
Implications, Potential Applications, and Considerations for Reform
The distributed, participatory operating models of makerspaces and hackerspaces demonstrate feasible alternatives to top-down, centralized innovation. Their ground-up approaches merit study to identify reforms fostering organic creativity outside embedded industrial complexes influencing technological trajectories over the long term.
By cultivating non-dependent, civic-focused innovation networks, makerspaces point to further opportunities to introduce alternative pathways for progress less beholden to military or corporate priorities.
Incentivizing the growth of independent, grassroots makerspace networks through public funding and support could provide diversified routes for innovation outside traditional defense and private sector influence. Their principles of open participation and modular collaboration suggest potential applications for democratizing innovation.
Grassroots models like makerspaces provide case studies worth considering to inform systemic reforms aimed at diversifying where and how emerging technologies are conceived on a societal level over the long run.
Chapter XI: Conclusion
This concluding chapter recapitulates the need for sociocultural models understanding dual-use issues as emergent outcomes of complex interacting systems, not isolated decisions. It emphasizes ongoing work required.
Renouncing Technical Determinism
By developing a framework incorporating the memetics, social network, and military influence concepts discussed in Chapters II, III, VI, and VII, the origins of unforeseen hazards are best characterized as branching diffuse pathways versus autonomous forces of isolated technological momentum.
The sociocultural perspective developed across chapters via memetics, network analysis, and study of military funding patterns reveals innovation as an iterative, decentralized process dependent on its environmental conditions.
Recognizing Indirect Causality
Insights from Chapters IV, V, and VIII indicate dual-use risks stem not from attributes of discrete artifacts but distributed patterns of collaborative process, relationship, and conceptual development unfolding systemically over long time horizons.
Implications for Dual-Use Governance
While direct case-by-case oversight remains necessary, as argued throughout this paper dual-use risks emanate more from indirect sociotechnical dynamics than fixed artifacts. Effectively addressing embedded conditions requires reforms engaging the full sociocultural system influencing long-term innovation trends.
As argued in Chapter IX, effective response depends less on regulation of fixed end-points and more on reforming embedded conditions shaping innovation over generations. Some potential policy directions could include:
Diversifying public research funding away from heavy military dependence through direct civilian science budgets and alternative sponsorship models.
Conducting audits of university-defense collaborations to assess influence on priorities and incentivize broader benefit goals through revised contracting terms.
Piloting programs to proactively identify and nurture independent innovation hubs less embedded within military-industrial networks.
Introducing requirements for ongoing foresight analyses within large federally-funded projects to systematically assess long-term trajectories and flag potential emerging issues earlier.
Establishing reflexive oversight bodies including experts from outside science and technology fields to interrogate root assumptions and incentives influencing collective choices over decades.
While significant coordination challenges remain, a portfolio of reforms engaging the ecosystem shaping incremental progress may enable more agile and systemic dual-use risk stewardship than discrete policy snapshots. Continued analysis and debate is still needed.
Areas for Further Study
Empirical examination applying the analytical lenses from across this paper, such as network theory to case studies, is still needed as explored in Chapter III. Ongoing reflection on responsible innovation is likewise warranted.
As discussed in Chapter X, grassroots models like makerspaces demonstrate alternative innovation processes outside traditional top-down research environments. Their distributed, participatory operating principles provide an exemplar of creativity fostered through unconstrained collaboration beyond corporate or military auspices.
Drawing on the analysis of diverse innovation networks in makerspaces, policy approaches could explore cultivating independent spaces for open-ended creation. This may diversify creative pathways away from dependence on defense funding influences discussed in Chapters VI and VII.
Piloting programs drawing from makerspace principles of participatory problem-solving holds potential to proactively identify emerging issues and nurture alternatives outside entrenched industrial complexes. Systemic reforms engaging societal, not just technical determinants of progress are still needed.
In conclusion, this paper has argued for the need to analyze dual-use challenges as products of indirect and systemic dynamics within sociotechnical networks, not autonomous technological forces. By developing a conceptual framework incorporating theories like memetics and analysis of military funding influences, a perspective emerges recognizing the negotiated, path dependent nature of innovation. This understanding can inform governance approaches engaging the embedded environments shaping progress over generations rather than merely reacting to discrete artifacts.
Conceptualizing innovation socioculturally by drawing together the various concepts discussed in Chapters II through IX establishes a foundation recognizing its negotiated, path dependent nature. Though challenges persist, this perspective opens possibilities for stewardship attuned to indirect, long term influences critical to safety and benefits.
The framework draws together insights from diverse scholars across fields as cited while identifying future research applying and testing the approach.
Papers synthesizing prior scholarship on topics like responsible innovation, social shaping of technology, and governance of emergent risks.
Do ants fuck? Or do they mate?
On how language used to describe things matters.
and how associations with existing meaning changes how we think about things.
alternate title: "What arguments over language tells us about our own ideological thinking."
Content Warning: Mentions of rape and cannibalism, society and power. Armchair sociology. Raw unhindered frank discussion on a personal perspective about language games in society. Outsider discussion of politics around scientific disciplines and academia. Rude things about ants.
A friend of mine shared this Quillette piece ('What Computer-Generated Language Tells Us About Our Own Ideological Thinking') with me to try to describe a phenomena with how people confuse the linguistic symbol with the subject. It reminded me of the concept of 'The map–territory relation' and some older thoughts I had about how language itself is hard.
I went on to describe my take on this piece on how we label insect sex behavior in biology ('Insects can’t be virgins and you should stop calling them that').
I liked that piece on biology labels because it was particularly enlightening to me. It's easy for many to dismiss it as someone complaining about their emotions being hurt. In fact, that was nature of my initial reaction. Introspecting my own aversions to the idea of 'mated' vs 'virgin' helped me to see how concerns over language may be due to unappreciated latent associations and conflicts in how one frames the situation. I feel it highlights a useful and misunderstood framing in how language is used in biology fields. This essay is an attempt at a more polished version of my thoughts, and an attempt at translating how I interpreted it.
The writer of that Sisterstem article is opposed to the way 'rape' and 'virgin' are used in the language around insects. They are pointing out that these terms are heavily loaded with social-cultural context. I'd go one further and point out how these problematic may even be baked into the core of western understandings of biology, with similar embedded biases stemming from plato.
I believe these kinds of concerns about language use are easily misinterpreted by people who don't often think about this space under lenses of power dynamics within society. It's only after listening to what the writer was saying that I could begin to Grant the Premise on the issue they are raising. I could then see the genuine frustration being expressed. A frustration that I also feel needs to be more widely understood.
An aside; As an autistic person who's thing is ants, I try my best to make sure everyone is willing to talk to me about them! Sadly, I often struggle with a sort of callousness to these kinds of things. So it is inherently useful for me to hear perspectives on how language framing impacts people. Language itself has been a general struggle for me, but I'm getting better. I've even come to appreciate how trauma can be associated with overloaded terms, reminding individuals of past strife, and how cultural differences put roadblocks up in having meaningful discussions.
So it seems reasonable to me to avoid using terms that bring up those associations where I can, and especially in an academic setting. This is why I attempt to use content warnings now when I recognize problematic content. But more than that, seeing how these emotional struggles come-about has also helped me to look beyond them to the underlying issues being raised (instead of simply being dismissive). It lets me listen better.
But even if I take on my naturally inclined stance of a cold clinical wannabe scientist who seeks to peruse knowledge, I still believe we should weight the argument about considering the social context of that language more highly. A lot of language arguments have nuances about definitions and accuracy that are often ignored. Looking at how gatekeeping phenomena bias how fields develop, which necessarily overlaps with how language norms develop with differing meanings, its not surprising we often don't even notice when these subtle divergences are happening.
To people who follow my questionable escapades learning about biology on twitter, it may seem hypocritical that I would write this piece. If I'm honest, many of my tweets are probably the best example for how problematic language is tied to biology. I'll happily talk about how there are giant insect orgies and use analogies with fuck-fests or other even talking about bees fingering flowers for the sake of communicating a metaphor that is in my head. Heck, my entire basis for reasoning about ants is to consider us to be more like ants than we realize. Sometimes quite litterally.
To be fair, my threads and ideas on twitter are being done under a lens that I'm knowingly abusing metaphor, pataphor, and intentionally breaking linguistic silos to generate more creative framings about the world. I like to imagine I am taking a poetic license and doing absurdist poetry to explore ideas. Tho it probably just comes off as insensitive and deranged. I'm sorry.
Still, I believe that one of the larger problems we have in our quest for knowledge is from biases stemming from how early views on how we differentiate ourselves from other lifeforms. So while I like to frame us as just another animal, I can see how being too dogmatic in one view also leads to neglecting the social aspects that make us uniquely human. One of the ways this inherent framing is most readily seen is in our use of language, and I do believe pointing out those biases is one of the first steps to unveiling the hidden areas they create.
In this way, I say we should absolutely be questioning and perhaps outright breaking existing language norms in the field, all the more-so if they are holding us back. Seems wise to avoid imposing artificial barriers on how we frame ourselves against other life, whether thru disagreements on shared language, or poor specificity in analogies we use to represent an idea.
My interest in breaking these frames that shackle our thoughts goes both ways tho. Questioning how we frame ants is why I even found the thing about 'virgin' queens! I feel a strong desire to do the reverse and not just call fledging queens as "virgins", but take that whole absurd analog to humans and run with it! Are there chad ants? Are their gamergates that use their stored sperm to impregnate other females? Can ant memorize a face (like wasps) and hold a grudge against another ant for violating their agency? What would a social power structure in an ant colony look like? Should we have a field studying ant polotics?
Do ants cannibalize their young?
This entire piece is predicated on how I've been thinking about how 'cannibalism' might be construed under that lens of language politics. I personally do not like the idea of people eating each other, which is why I've been research what causes it in human and animal societies. As problematic as the topic can be, it has been an extremely valuable mine of insights for me, touching on many aspects of biology and leading to interesting questions.
In the case of cannibalism, this is a taboo entrenched deeply in many western belief systems. It doesn't take long studying this space to quickly see how these powers end up encroaching on this space and are used in a political capacity to silence people. The whole "atheists eat babies" and older forms of blood libel are still alive and well AFAICT.
Studying human ritual cannibalism from an anthropology perspective, we see all these complex social dynamics. When we go to study it in animals, we just see it framed in cold language about how they simply eat each other due to stress. We also get cannibalism-esque behavior from medical and nutritional conditions in many mammals (including humans), so like the whole "virgin" vs "mated" concept, I find it useful to distinguish between these phenomena by being explicit about social boundaries.
More directly, in exploring the history of cannibalism and 'soul' in the context of philosophy, it is essential to be aware of these elaborate social-political games to understand the context of how ideas interacted. Thomas Aquinas may not have been thinking about how his thought experiments on corporal entitivity and the relationship of body & soul would lead to witch-hunts. Nor would he expect his thought experiments would later found the notion of 'atoms' of matter, but that's where we are. So I find it very useful to consider directly the language framing issue as a way to explore our relationship to knowledge.
Like in the case of the use of "virgin ants' in biology: Ignoring that we have this extra political layer, one using language policing behaviors as a means of social control, would be folly. If you genuinely wanna explore cannibalism in human societies, you must necessarily explore how societies enact power. Not doing so would lead directly to a misunderstanding about how cannibalism is viewed in society. Ignoring this lets it further become weaponized, and then lines get drawn in the sand about how one frames a situation. With-us-or-against-us social grouping form and people see it as an opportunity to attack and de-status competitors. Worth considering how the latter group may be distinct phenomena from those who are genuinely concerned about how the language being used may be misleading.
As I want to literally figure out how to stop animals from suffering & maybe try to avoid eating each other. It makes me twisted inside to talk about this space. On one hand I hope to continue learning and discussing the nuances. But I also see how the very act of having discussions about cannibalism (or even less impactful things like ant sexual practice) leads to direct confrontations with social-cultural dynamics. Just pointing this out can cause undue harm leading to chilling effects.
I think engaging with these power games veiled within our use of language is important if we're to more fully understand a concept. Nonetheless, it is unimaginably uncomfortable to do, so I think I'll stop here.
Dunbar's studies are based roughly on an extrapolation from findings in brain-size correlations with troop size among some monkeys. The lesser known Bernard–Killworth number, which is based real world studies of human networks, puts it up to about 290.
You can listen to Dunbar talk about the 150 limit thing here: https://www.youtube.com/watch?v=9lPH-qqKHfI&t=1m35s
There are also a lot of criticisms that point out that there may be a large variation in the effective number. https://en.wikipedia.org/wiki/Dunbar%27s_number#Criticism and there have been a lot https://bigthink.com/mind-brain/dunbars-number
One of the more fascinating things we found in this space is that some birds actually change their brain size in response to their social network size. There are indications that this may be true of primates as well. https://greatergood.berkeley.edu/article/item/more_friends_bigger_brain
When you start to suspect of brain plasticity being involved, it suggests a lot of Dunbar's assumptions are exactly that (assumptions) and the numbers themselves cease to be meaningful extrapolations.
My own interest is in trying to expand my ability to interact and remember more people. I have been exploring stuff around this to try and fix my own health & anxiety issues, and again and again I keep finding weird ties between brain plasticity and the amygdala. You'll never guess which part of the brain seems to reflect social network size. https://www.nature.com/articles/news.2010.699
Tho a lot of that might be simply correlational, and not causative. There are other findings around grey matter that might also be at play. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4249478/
In either case, I strongly suggest a more nuanced look at these ideas is worthwhile if you want to base social network design around them. And I don't say this lightly; I managed to figure out how to reverse a lifelong prosopagnosia by exploring neuroscience around how we remember faces. Correctly guessing that the fusiform face area wasn't the thing going wrong in people with my condition. https://neurosciencenews.com/face-blindness-brain-15728/
Even if we assume that there is some limiting number that's an essential part of our brain and the plasticity thing is rare... We still have lots of evidence that there are huge individual variations in people's abilities in this space. IMHO Designing a social network under those "150" numbers as gospel, would be folly. Especially as even his own work cites ranges from 5 to 2500, with the 150 number being primarily for communities that would be cohesive as a unit with close physical proximity.
These villages or clans tend to be built out of smaller living groups of about 30-50 individuals, and several villages or clans can unite to form tribes or sub-tribes with between 250 and 2,500 individuals. Dunbar proposed that these larger groups were not built upon personal relationships, however, but on some group identity.
Especially worth considering is how much of the support for his work stems from neuroscience about things like touch and physical intimacy, and strange things around eyes, etc. Particularly paying attention to nuances around how that doesn't always apply in digital spaces. You can read about the support for the theory here: https://theconversation.com/dunbars-number-why-my-theory-that-humans-can-only-maintain-150-friendships-has-withstood-30-years-of-scrutiny-160676