Addiction Antifragile Art Artificial Intelligence Beauty Bias Book review Change Chaos Complexity Craft Creativity Deep Why Delusions Design Dopamine Dreams Entropy Heuristics Lenses Mattering Meaning Meaning crisis Motivation Myth Neuroscience Principles Problem solving Quest Retreats Ritual Search space Technology Trends Updates Values Visions Workshop
- Notes on appreciation
- Context of uncertainty and trying to create something of value
- Participating in a non-zero sum game (win-win) moves from competition to collaboration for mutual benefit
- Appreciation: mattering, a social bond
- Relevance realisation – in the face of uncertainty / entropy, what is salient?
- Appreciation is highlighting what is valuable (etymology of word literally – ‘price’) to the group, salient.
- Signals to brain that we have done something relevant – moving on the right path.
- Doing better than expected on path towards goal or reducing group uncertainty
- Positive feedback loop – dopaminergic release, reinforcing the behaviour which typically means we want to continue doing this
- Excess “uncertainty reduction” is extensible – can be shared with others (all benefit from reduced uncertainty)
- Thus the appreciation is like a currency
- Lenses
In a recent talk about Free Energy Principle, Andres Gomez Emilsson relates how ‘Free Energy Principle’ is a fantastic lens through which to view the world.
I thought about some of the lenses at Ripplty that we have used in recent years:
- Antifragility
- Meaning crisis
- Relevance realisation
- Enabling and governing constraints
- Pattern Languages
- Entropy
- The Platonic triad (Beauty, truth, goodness)
- Faustian spirit
- Altered states of consciousness
- Non-objective search
- Addiction, meaning and uncertainty
Excellent paper here about addiction and meaning
It forms the link between meaning and addictive bahaviours.
This model of addiction links Friston’s predictive processing (i.e. the brain’s function to avoid uncertainty or surprise) by choosing paths (seeking relevance) towards a goal (e.g. substance or state of mind or a feeling of certainty) which can become habitual and therefore ‘addictive’.
This active movement towards ‘reducing uncertainty’ is linked to the dopaminergic release because end state (taking the substance) was not a surprise in the end. It feels like the completion of navigating from one state to a desired future state successfully – and it is. The fact that this limited path towards a fake ‘certainty’ in the context of uncertainty gives the impression of successfully navigating uncertainty towards a goal. The neurochemical release is therefore signalling that the brain did successfully what it was designed to find this path. And in the face of further uncertainty (everyday life!), this limited path towards uncertainty can become habitual (done over and over again).
But the entire feedback loop has become delusional because the habit is bad in the long term for the person’s survival because they lose perspective on other things that are important for long term survival – connections, sustenance, relationships etc. It is therefore a bad habit or an addiction even though the person feels that they have atuned to their environment.
The way out of this delusional cycle is the realisation of this maladapation to survival (a shock realisation of reality) and the openness to finding the things that really matter. It is therefore a new way of a life (a new path that needs to be found).
This links a lot of the work that we did on the Dopaminferno with finding meaning. In many ways, addiction is a type of ‘inverse just cause’ at the human level.
Written by Mark Miller et al (colleague of Vervaeke, I believe)
- The Human Purpose
“The human purpose, if such a thing can be considered, is to pursue meaning – to extend the domain of light, of consciousness – despite limitation. A meaningful event exists on the boundary between order and chaos. The pursuit of meaning exposes the individual to the unknown in gradual fashion, allowing him to develop strength and adaptive ability in proportion to the seriousness of his pursuit. It is during contact with the unknown that human power grows, individually and then historically. Meaning is the subjective experience associated with that contact, in sufficient proportion… Meaning is the most profound manifestation of instinct. Man is a creature attracted by the unknown; a creature adapted for its conquest. The subjective sense of meaning is the instinct governing rate of contact with the unknown. Too much exposure turns change to chaos; too little promotes stagnation and degeneration. The appropriate balance produces a powerful individual, confident in the ability to withstand life, ever more able to deal with nature and society, ever closer to the heroic ideal. Each individual, constitutionally unique, finds meaning in different pursuits, if he has the courage to maintain his difference.” (Jordan Peterson, Maps of Meaning, p. 468)
- The importance of creativity to thrive
Yesterday we talked about the continuing trend of automation and machine learning, and what implications this has on people in the future: i.e. how more roles will ultimately be replaced.
Of course, new roles will emerge, and it was our feeling that these roles will increasingly require creativity and innovation: after all, where are the next innovations going to come from? This will surely become the source of value for many companies.
It also became clear that whilst many companies are currently willing to invest finance and resources to becoming, let’s say, more agile, what about becoming more creative? How is that practically achieved? Moreover, how is creativity increased without it being forced and contrived?
It’s a huge topic, but there was one interesting notion that Matt brought into the conversation about ‘relaxing the boundaries’ (no doubt explored in a different post) and also the importance of support required during this stage. It’s important when relaxing the boundaries that the support is there!
This incidentally aligns back with the two of the core principles that we are exploring as a community: to challenge and to support.
- Humour and Stressors
Something I’ve been pondering about is the fact that we need stressors to be impactful enough for a system to adapt. Stressors can be painful and perhaps that’s what’s required to prompt a costly adaption, but as a result there should also be a positive feeling. I think you kind of notice that with sport – that buzz after sport, the endorphins released after exertion bringing us delight, knowing we’ve stressed the body but it was a good stress. We’re better off afterwards. Something that we might want to do again (and again).
I then thought about paradigm shifts. And hacking! Paradigms are these models that we use all the time to aid our understanding, and people often hold on dearly to some paradigms because they don’t want or need to change their outlook on the world. Again it would be upsetting and hurtful to remove such paradigms. But how could we hack a paradigm, and how could it have a positive after feeling after that hacking?
Humour?
Is humour, irony, joking … and the resulting laughter basically the human (natural) response to a paradigm being broken, but with an enjoyable outcome (so that the updated paradigm sticks or and the neurological system is updated!)
- Do Creative People see the World differently?
Key points
- Creativity often measured by divergent thinking (e.g. how many different uses for a brick can you think of)
- Linked to the psychological trait ‘openness’
- Test reveals creative people may see things differently (even at a visual level) – less ‘rivalry suppression’ of visual inputs (can accept and see both things)
- Personality is malleable: people with low divergent thinking can change
- travel truly does ‘broaden the mind’
- psilocybin (1 standard deviation great trait opennes)
- cognitive training interventions)
- Bottegas of the 15th Century
Key points:
- The Renaissance put knowledge at the heart of value creation
- Florentine workshops were communities of creativity and innovation where dreams, passions, and projects could intertwine. The apprentices, workers, artisans, engineers, budding artists, and guest artists were interdependent yet independent
- The bottegas’ three major selling points were turning ideas into action, fostering dialogue, and facilitating the convergence of art and science
- Renaissance workshop was transdisciplinary. This helped create a holistic approach to creativity
- https://hbr.org/2016/04/the-innovative-coworking-spaces-of-15th-century-italy
- Considerations to encourage Creativity
Key points:
- The trick is striking the right balance between structure and creativity by keeping the opposing forces in check and letting them complement—and not override—one another.
- Judgment has no place in the world of art and creativity.
- Protect creativity from ‘order police’
- Be more child-like
- Creativity needs its own time
- Some constraints are necessary
Some similarity here to ‘Restrictions set you free’ by Derek Rivers: https://sive.rs/restr
- Avoiding the Einstellung Effect
- Einstellung (German: approach / prior belief)
- When faced with a problem, the brain works according to familiar patterns (avoiding Combinatorial explosion)
- I.e. When I think I know the answer, my vision tunnels. I’m a hammer, so the problem is surely a nail.
- When the actual solution is beyond this immediate response, a helpful approach is to assume the ‘first answer the brain comes up with’ isn’t possible
- The result will be an opening of further possibility (the search space expands for new solutions to be found)
- This appears to be a key element of creative thinking
- Reality isn’t Real
Matt recently equipped himself with VR equipment. He was interested in what this technology could do for his research in neuroscience. One day, I came around his place to catch-up, and I tried it.
There was this “game” where your hands were captured by sensors from the headset and recreated in this 3D virtual reality. The “game” has a set of tasks for the player to complete with their hands, like separating red balls from yellow ones in 2 different bowls, or stacking up cubes, etc. And sometimes the “game” introduces “defects”, like having spaghetti fingers, or numb hands, which makes it harder to accomplish the task. What struck me was the way the system tried to predict the movement of my hands and fingers when interacting with those red/yellow balls and these cubes. I could see that, as I was about to grasp or move a ball or a cube, the “game” projected the movement of my 3D rendered hands to the desired future state I was trying to reach in the “real world”. It was like a lag where my eye could see in the future before my actions fully happened, and it is a very weird sensation.
That got me thinking… What is the perception of reality if not the projection of “predictive mental models”? Is reality like an interface that allows it’s actors (here humans) to interact with? How do we know what is real from what isn’t? Do we actually perceive reality as it is or are we hallucinating it in shapes and forms that comfort our beliefs?
In his book “The case against reality” Donald Hoffman explains how our brain is literally hallucinating reality, modelled after common sense. For example, if I throw a pebble in the air, I will expect it to drop on the ground within a certain amount of time. And it will be perceived as uncommon (or alien almost) if at some point in the fall the pebble stops, slows down, or reverses direction. This predictive processing has been fine tuned from thousands of years of evolution to compress information at such a level we can today intuit some aspects of the world, and it is a good thing for most aspects of life, like the smell and color of rotten food triggering disgust is designed to put us off from eating something what might be poisonous. Today, most Machine-Learning and AI algorithms that aim at cognifying information, work in the same way, and I suspect this is what has been used in this “game”. I will even speculate it may have been created for capturing data from real hand movements from its gamers and feeding the algorithm back for making more accurate predictions to other future applications.
For humans, the reason our brains are constantly building a predictive picture of the reality we experience is to help us identify quickly what can be a pay-off and what can be a cost. In short, our brains are saving energy by compressing information through learning and practice, to such an extent that it becomes innate (or intuitive ). It is partly what Daniel Khaneman describes in his book “Thinking fast and slow” when someone has practiced and experienced a situation so often and in many different contexts, they develop a form of intuition and the task becomes effortless.
Going back to the compression of information, there is a huge amount of data that qualifies, let’s say, an apple. When we look at an apple we perhaps first see its color. If it’s red, it will trigger some hunger, making us salivate, meaning we deeply recognise its nutritional value. It also usually means it’s ripe to eat, and that tells us we can have its value now. All the information is nested one into another, compressed layers after layers of evolution, at a level such that today, we became biologically wired to spot and desire the sweet and juicy grapes hanging on the top of the fridge, like fruits hanging on trees.
Although it’s way more complex and nuanced than what I just wrote, the idea is that a lot of information from reality is a projection made by our brains and not the raw reality itself. And it’s mostly a good thing for us. But as the world around us changes fast, our biology evolution is lagging behind (some things take time). For example, when you encounter a red berry you need to be careful that it isn’t poisonous. You perhaps know not to eat this particular red berry because your father, mother, someone who encountered it before can tell you not to eat that specific berry, or more generally tell you not to eat what you don’t recognise. This information hasn’t been wired in our biology, and that’s why we have to pass it on from generation to generation. But we sometimes get fooled by thinking that, because one thing is good for us the other thing might be good too. Take the wild potato, it closely resembles the wild sweet pea, and while the former is a good source of nutrients the latter is in fact poisonous (that’s how Chris McCandless sadly died as reported in the bestseller book Into the wild).
We make bets, we guess this or that will bring us benefits at some point in the future. But sometimes we get the prediction wrong. Yes, we may win the bet 9 times out of 10, but it doesn’t mean we will never lose, like mistaking a simple plant can lead to death.
In his book The Black Swan, Nicholas Nassim Taleb’s talks about the impact, often extremes, of rare and unpredictable events. He made a point about the human tendency to find simplistic explanations for these events, wrongly predicting an event will occur because it has always occurred in the past, and reciprocally. A key idea in Taleb’s book is not to attempt to predict these Black Swan events, but to see how we might benefit from disorder and uncertainty by recognising these positive unpredicted events (opportunities) and be less fragile, or more Antifragile, to the negative events.
We cannot truly predict. Our brain’s process in trying to predict the future is in fact the process of looking at “reality”, mainly show us the narratives that fit our expectations most of the time. How could one imagine the very first car when all that was around was horses? Indeed, we often fall short when trying to predict the future, we stay with what is familiar, like imagining a flying car instead of ideating on the more general idea of commuting using 3D space, without being too attached to pre-existing constructs and models. We can and should exercise our power of “guesstimating”, but we have to be humble and raise our awareness as we are living in a fast-paced environment, where volatility, ambiguity, complexity and uncertainty seem to be the default. In such an environment, future projections are becoming less and less reliable (if they ever were).
Reality isn’t real, it’s a game of perceptions that has been fine-tuned by millennia of evolution and culture. But that doesn’t mean we cannot play with these features! I believe we could train ourselves to relax the boundaries of these predictive models and try to open the doors of perception by exercising a form of “continuously envisioning” (but you can call it whatever you want). In doing so, we are opening our minds to explore the possible futures in front of us, a sort of axe-sharpening exercise that pro-actively tries to seize up-coming opportunities.
- Meaning Crisis and Cognitive Science
Meaning Crisis and Cognitive Science
We watched episode 26 of the meaning crisis together. Some things I enjoyed (not a summary)
- metaphors bring salience to the point being made
- sam is a pig – a good metaphor (he’s obviously not a pig but it gives salience to an element of him.
- bees are wasps – concepts are too close to be a metaphor – meaningless
- chairs are arguments – concpets are too far to be a metaphor – meaningless
- metaphors bring ‘meaning’
- a construct is useful when many different sources converge and it has large plausibility & applicability
- the opposite is ‘far-fetched’: low convergence but high ‘applicability’ to everything – conspiracy theory – connecting dots that aren’t there
- but also opposite: high convergence but zero applicability – trivial or even academic (something we assume Vervaeke doesn’t want to happen to his excellent work)
- meaning isn’t something we seek or make, it’s something we cultivate
- intelligence is akin to problem solving (high intellignce would be a general problem solver)
- problem solving is the ability to recognise the difference between the initial state and the goal state and find a path through towards it
- there are multiple paths (an explosive potential beyond the possibility of the mind to think through each option)
- But there’s also many problems at any given time
- the path is constrained / restricted by certain options (you don’t burn your house to cook the pizza but it is one way to cook it)
- A general problem solver needs to continue to solve multiple problems not just one (survival) at the expensive of cotinuing as a general problem solver
- thus: ‘sequence of operations in the search space between the initial state and the goal state and preserving me as a general problem solver’.
- Problem solving is therefore the same as strategy (Mintzberg’s definition: a pattern in a sequence of decisions’)
- many links here to ‘greatness cannot be planned’ – to be written up soon – that there are stepping stone towards a soltuion which we may not know… and the next step cannot be known until we complete the first. Also: our stepping stones may be picked up by others and take them onto the ultimate solution. E.g. computer couldn’t be invented without the existence of the radio but nobody invented the radio with a view to inventing computers, hence the stepping stones.
- metaphors bring salience to the point being made
- Meaning and Making
“Modern archaeology seeks for early evidence of human humanity in three areas of activity 1. artistic expression 2. religious practice and 3. tool making. These areas, it could be argued, take equal precedents in defining our humanity.
The pierced shell, pollen in the grave of Neaderthal man and the chipped Flint all testify to something uniquely human – the ability to shape, modify and effect surrounding world.
Unlike animals, whose bodies are highly specialised, humans are born naked vulnerable and at the beginning of along the road of learning we exist as creative and destructive beings-in-potential and in order to survive and make a home on Earth we need to develop tools and technology.
A study of so-called primitive cultures has revealed that tools originally had an artistic, ritualistic and functional dimension. They separated humans from the great ‘other’, the cosmos and nature, but were also means of tapping into it. So powerful was this sense of the appropriate ritualistic function of a tool, that taboos were laid down to limit new invention and inappropriate use.”
…
“Our civilisation has lost touch with the potential synergies of the three great pillars of culture: Science, Art and Religion.
Already drifting apart in there in essence, these are further separated and fragmented in modern times. Has science, natural spawn of philosophy and whose watchword should perhaps be ‘truth’, become even more susceptible to commercial interests? Has arts, which should perhaps be experience into beauty, become self obsessed, lost in the hall of mirrors? And has religion, whose business should perhaps be to nurture Goodness become an ineffectual club or platform for prejudice?
There are elements in our society that tend toward the kind of reductive fundamentalism, which denigrates the human being into the status of a machine and consciousness to that of a computer.
There is no purpose and meaning to life except the egotistical striving for the three Ps – power, pleasure and plenty.
The only way out of this dangerous quagmires to search for meaning.
Meaning is intimately bound up with purpose and identity. Is it because we have forgotten who we are, that we cannot evolve into what we might become?”
From ‘Crafting’ – Johannes Steuk
- AI Revolution Conference Notes
???? Legal Landscape for Gen-AI (images):
- UK ????????: Non-commercial research allowed. Tech data scraping IP review ongoing.
- Getty vs. Stability AI: Getty logo issue in output images.
- UK’s CDPA s9.3: Computer-generated work rights. Challenges defining ‘originality’ in AI.
- EU’s Draft AI Act ????????:
- Banned AI (e.g. instant face recognition ????)
- Registered AI ✅
- Transparency in AI training data ????
???? National Gallery X:
- Some big players in image industry embracing change!
- Innovations like performances guided by viewer heartbeats! ❤️????
???? Keywording Industry:
- Humans vs. AI: argument that humans add value AI can’t, but I’m not sure > Is it just a matter of training and time? ???? vs. ????
- AI’s challenge: Tackling the ‘Hard problem’ in creativity.
???? Getty Images & AI:
- Their stance: We’re on top of this and trying to build ‘safer AI’ ???? > PR exercise!
- Their Gen-AI models: Copyright-compliant & creator-friendly. BRIA’s on board too! ????> some interesting experiments with micro-payments but technical details not forthcoming
???? AI Image Stats:
- 79% brands: Using Gen AI in 4 years.
- 53%: AI for unique brand images, 17% for ideation & fun ????
- 87%: AI images should be labeled (short-term sense, but long-term? ????)
- 71% Gen Z & millennials: Excited about AI in art ???? (Older gens? Not so much.)
- AI Today and a Vision for the Future
Key points
- Humans could learn but computers couldn’t
- Neural networks allows us to program ‘parallel computers’
- Researchers Needed to figure out how learning in neural networks work. Nobody knew – it was experimentation / finding: what is the right question to ask
- Beginnings of generative models and question became: what gets the most traction – wasn’t clear it was the right question, but in hindsight turned out to be so.
- Seems that Supervised learning would get the traction (started as an intuition amongst researchers)
- If neural network is deep and large, it could be configured to solve a hard task
- A large and deep neural network can represent a good solution to the problem (most networks were small at the time).
- This Required a big data set and a lot of computing power (to actually do the work)
- Optimisation (for smaller networks?) was a bottleneck in development
- Train them, make it big, find the data and make it succeed
- OpenAI idea: unsupervised learning through compression
- Hypothesis: really good compression of data will lead to unsupervised learning
- If you compress data really well, you extract all the hidden secrets which exist in it, therefore compression is key
- Test: predicting the next character of amazon reviews, there will be a neuron inside the LSTM (long short term memory) that corresponds to its sentiment. That showed traction for unsupervised learning
- So: validated that predicting next character was clue to finding secrets in data
- Reinforcement learning: solving real time strategy game (competitive sport: smart, team work, fast and competing against another team) DOTA2 with the Goal to play against best (human) players in the world.
- Some work seemed like detours (but led up to outcomes) through convergence.
- Nice convergence where GPT created the foundation, and experiments with DOTA created reinforcement learning – learning from human feedback
- When training a large neural network to accurately predict the next character of word in lots of different contexts, what we are doing is learning a world model
- In order just to learn the statistical correlations, compress them really well, what is learned is the process that produced the text. This text is actually a projection of the world
- The more accurate the prediction, the higher the fidelity of this process
- Prediction can be accurate but to be helpful (like an assistant) requires reinforcement learning. Not a matter of teaching new knowledge, more related to ‘what we want it to be’
- The ability to learn everything from the world through the projection of text
Amazing how much of the conversation was about following intuition / looking for the right questions / experimenting and converging. Aligns fully with the non-objective search.
- AI Use Cases
- design, facilitating rapid prototyping, and simulating diverse testing scenarios.
- streamlining logistics and production processes within the supply chain
- marketing and sales by rapidly crafting captivating content and tailoring marketing strategies to individual consumer preferences.
- after-sales services, anticipates maintenance requirements,
- enriching customer support, notably through advanced chatbot interactions.
- enhancing feature development and fortifying security measures.
- Generative AI is not the same as retrieval
Excellent insights and conclusions by Alex Powell from a recent AI event:
- Search is more important now than ever
- We shouldn’t trust LLMs
- More progress is needed with evaluation [of search & discovery methods]
- RAG has gone ‘big time’
- The ‘Retrieval’ part of RAG is often neglected
- Search engines are turning into ‘answer engines’
- Users need to be educated to use AI in an informed way
- Creativity as a Search
It’s useful to think of achievement as a process of discovery – as if searching through all the possibilities for the one we want. Not like searching for a sock in the laundary, but more elevated, the kind an artist performs when exploring creative whims.
All these searches can be viewed as searches of some value – new art, theories or inventions but out of all the possibilies, which is the right one for us. So we can think of creativity as a kind of search.Paraphrased from The Myth Of the Objective – Stanley & Lehman
- Creating vs Creating for a living
This article overlaps with many of the things we’re trying to understand and reconcile.
“The first, obvious answer is that people don’t want simply to create, but to make a living creating, to create as a profession. And this is vastly more difficult to achieve. Making a living on Etsy is notoriously difficult, with about 90% of Etsy stores earning less than $400 a month. Estimates for payouts for a thousand views on YouTube are around $18 dollars; less than 12% of videoseven reach that threshold. 90% of Twitch’s users stream to six average viewers or less, and a quarter of even the top 10,000 highest-paid accounts make less than minimum wage. The average OnlyFans account earns just $150 a month. It’s estimated that 99% of podcasts make no profit. 98.6% of Spotify artists make an average of just $36 a quarter. On Patreon, a platform that creators of all kinds use to monetize their work, less than 2% of users make even the federal monthly minimum wage. I have no numbers for Substack, but we can be sure that it’s a similar trend.”
https://www.persuasion.community/p/why-so-many-elites-feel-like-losers
- Heuristics
From Margaret Boden
A heuristic is a form of productive laziness. In other words, it is a way of thinking about a problem which follows the paths most likely to lead to the goal, leaving less promising avenues unexplored. Many heuristics take the current map of conceptual space for granted, directing the thinker on to this path rather than that one. Others change the map, superficially or otherwise, so that new paths are opened up which were not available before.
The study of heuristics as an aid to creativity has a long history.
Pappus of Alexandria, our fourth-century friend encountered in Chapter 3, mentioned them in his commentary on Euclid. The twentieth-century mathematician George Polya has identified a wide range of heuristics, some so general that they can be applied to many sorts of problem. 3 Advertising agents and management consultants use them continually, and often explicitly, in trying to encourage creative ideas by ‘brainstorming’, or ‘lateral thinking’. And several educational programmes, used in schools around the world, use heuristics to encourage exploratory problem-solving.*
Most heuristics are pragmatic rules of thumb, not surefire methods of proof. Although there is a reasonable chance that they will help you solve your problem, they can sometimes prevent you from doing so. For example, ‘Protect your queen’ is a very wise policy in chess, but it will stop you from sacrificing your queen on the few occasions where this would be a winning move.
Some heuristics are domain-specific, being the ‘tricks of the trade’ used by the skilled expert. These may be of no interest if one is concerned with a problem of a different type. ‘Protect your queen’, for instance, is useless as advice on how to play poker.
- Complexity, Entropy & Paradigms
Further to the theme of creatively seeking greatness, I think I’ve been lucky to make some more insights. This carries on from the notes of the conversation between Karl Friston and Sean Carroll about ‘Free energy principle’, whereby we aim to minimise uncertainty but also seek out some uncertainty (novelty). It’s a curious paradox but evidently necessary. The answer lay in Sean Carroll’s book which is next to me on my bookshelf (but of course, that’s far too obvious), I had to stumble across it elsewhere, through some convoluted journey of chance.
Essentially, the story starts with Per Bak insight’s into mounds of sand (in e.g. an egg timer). At a certain point the mound collapses. It can no longer support itself: One grain causes the entire structure to break. However, what’s happened is that through the collapse, the basis of a new potential structure has been afforded, from which a new and potentially larger mound can form.
In order for things to complexify, entropy is required to break the system so that something new (more complex) can emerge.
It seems it is the same with human brain and our beliefs.
In order for us break our belief systems and create new intricate and complex belief systems we need some entropy to enter the system.
Evidently, according to this Free energy principle we are pre-disposed to seeking out this novelty which will potentially allow some entropy to enter. We need to be able to have some kind of recursive way to allow belief systems to be updated, since we cannot be absolutely sure about our belief systems.
(NB: Too much entropy is undesirable in case it breaks too much of the existing system for a new system to emerge. What’s needed is a fine balance)
What’s more, from a physics point of view, entropy and complexity are sort of symbiotic.
I was also lucky enough to attend a fabulous talk yesterday about African divining practices. From what I understood, there seem to be deliberate practices to encourage entropy, in order to develop higher or more divine insights. So that’s given me lots to think about. - A handful of biases
Psychologists have posited hundreds of cognitive biases over the years. A fascinating new paper argues that they all boil down to one of a handful of fundamental beliefs coupled with confirmation bias. https://doi.org/10.1177/17456916221148147
This links to a lot of insights I made from the Zurich axioms which essentially lays out similar ‘delusions’ that one must overcome before one can invest opportunistically.
