A Technology of Everything – 4: Scientific Spiritism & Precise Prophecy

Reading Time: 13 minutes

Fiction and Reality

I awoke today with a sentence stuck in my mind.

Fantasie bedeutet sich das Zukünftige richtig vorzustellen.

Imagination means properly envisioning the future.

I was sure I read it a long time ago, but could not quite think of the author, but my best guess was the Swiss writer Ludwig Hohl and after some recherche I finally found the not quite literal passage.

What I understand by imagination – the highest human activity – (…) is the ability to correctly envision another situation. (…) ‘Correct’ here is what withstands the practical test.

(The Notes, XII.140)

The most important thing about imagination is contained in these two sentences:

1.Imagination is the ability to correctly envision distant (different) circumstances – not incorrectly, as is often assumed (because anyone could do that).

2.Imagination is not, as is often assumed, a luxury, but one of the most important tools for human salvation, for life.

(The Notes XII.57)

The Phantastic and the Prophetic (Predictive) Mind draw from the same source, but with different Instruments and Intentions.

Fiction and Reality: Both valid states of the mind. Reality does what Simulation imagines.

Visions are controlled Hallucinations.

Own Experiences

In 2004, I penned an unpublished novel titled “The Goldberg Variant.” In it, I explored the notion of a Virtual Person, a recreation of an individual based on their body of work, analyzed and recreated by machine intelligence. Schubert 2.0 was one of the characters, an AI-powered android modeled after the original Schubert, interestingly I came up with the term Trans-Person, which I then borrowed from Grofs transpersonal psychology, not even imagining the identity wars of the present. This android lived in a replicated 19th-century Vienna and continued to compose music. This setting, much like the TV series Westworld, allowed human visitors to immerse themselves in another time.

I should note that from ages 8 to 16, I was deeply engrossed in science fiction. It’s possible that these readings influenced my later writings, even if I wasn’t consciously drawing from them.

Within the same novel, a storyline unfolds where one of the characters becomes romantically involved with an AI. The emotional maturation of this AI becomes a central theme. My book touched on many points that resonate with today’s discussions on AI alignment, stemming from my two-decade-long research into AI and extensive sci-fi readings.

The novel’s titular character experiences a unique form of immortality. Whenever the music J.S. Bach composed for him is played, he is metaphorically resurrected. Yet, this gift also torments him, leading him on a violent journey through time.

Years later, I came across the term “ancestor simulation” by Nick Bostrom. More recently, I read about the origins of one of the first AI companion apps, conceived from the desire to digitally resurrect a loved one. I believe Ray Kurzweil once expressed a similar sentiment, hoping to converse with a digital representation of his late father using AI trained on his father’s writings and recordings. Just today, I heard Jordan Peterson discussing a concept eerily similar to mine.

Kurzweils track record

Predictions Ray Kurzweil Got Right Over the Last 25 Years:

1. In 1990, he predicted that a computer would defeat a world chess champion by 1998. IBM’s Deep Blue defeated Garry Kasparov in 1997.

2. He predicted that PCs would be capable of answering queries by accessing information wirelessly via the Internet by 2010.

3. By the early 2000s, exoskeletal limbs would let the disabled walk. Companies like Ekso Bionics have developed such technology.

4. In 1999, he predicted that people would be able to talk to their computer to give commands by 2009. Technologies like Apple’s Siri and Google Now emerged.

5. Computer displays would be built into eyeglasses for augmented reality by 2009. Google started experimenting with Google Glass prototypes in 2011.

6. In 2005, he predicted that by the 2010s, virtual solutions would do real-time language translation. Microsoft’s Skype Translate and Google Translate are examples.

Ray’s Predictions for the Next 25 Years:

1. By the late 2010s, glasses will beam images directly onto the retina. Ten terabytes of computing power will cost about $1,000.

2. By the 2020s, most diseases will go away as nanobots become smarter than current medical technology. Normal human eating can be replaced by nanosystems. The Turing test begins to be passable. Self-driving cars begin to take over the roads.

3. By the 2030s, virtual reality will begin to feel 100% real. We will be able to upload our mind/consciousness by the end of the decade.

4. By the 2040s, non-biological intelligence will be a billion times more capable than biological intelligence. Nanotech foglets will be able to make food out of thin air and create any object.

5. By 2045, we will multiply our intelligence a billionfold by linking wirelessly from our neocortex to a synthetic neocortex in the cloud.

These predictions are based on Kurzweil’s understanding of the power of Moore’s Law and the exponential growth of technologies. It’s important to note that while some of these predictions may seem far-fetched, Kurzweil has a track record of making accurate predictions in the past.

It’s fascinating how someone like Kurzweil displayed what seems like clairvoyance with his predictions about the Singularity Now, looking back, it almost feels supernatural. When I learned that Jordan Peterson had embarked on a project training an AI using the “Spirit of the King James Bible” to engage in conversation, I was reminded of the notion that Science and Religion might be parallel paths that intersect in the infinite.

Kurzweil’s case is particularly intriguing because his own assessment of his predictions significantly diverges from the public‘s perspective. He should have predicted that too, obviously.

When we pass away, is it a form of resurrection every time someone refers to our writings? The idea that we persist in others’ memories could be more than just a metaphor. What happens if, long after my physical body and mind have succumbed to the passage of time, my descendants consult my digital avatar about the era when Artificial General Intelligence first emerged?

Vernes Track Record

It is astounding how many Predictions Jules Verne the Father of Sci-Fi got right: It practically seems that he could see well over a century in the future. It is also interesting that he did not seem to get the timeline right, he was way too conservative to see the exponential curve of technologies that bootstrap from each other.

When exploring this topic with ChatGPT it came up with the following list:

Jules Verne, known as the father of science fiction, was a French novelist who wrote in the 19th century. His works are full of imaginative inventions that were far ahead of his time. Some of these have since become reality, while others remain purely speculative. Here are ten such inventions, with their modern counterparts and an assessment of their accuracy:

Electric Submarines – 20,000 Leagues Under the Sea (1870): Verne’s submarine, the Nautilus, was powered by electricity long before real submarines were. The first fully functional and practical submarines were indeed powered by diesel and electricity, but that wasn’t until the early 20th century. This was a remarkably accurate prediction. Accuracy: 90% (The only real difference is that the Nautilus was far more advanced than early real-life submarines.)

Newscasts – In the Year 2889 (1889): Verne imagined a world where news was delivered to individual homes via technology. Today, we have 24-hour news channels, internet news sites, and social media feeds. Accuracy: 100%

Video Conferencing – In the Year 2889 (1889): Verne predicted a device he called a “phonotelephote,” which allowed for “the transmission of images by means of sensitive mirrors connected by wires.” This is remarkably similar to our video conferencing technology today. Accuracy: 100%

Lunar Modules – From the Earth to the Moon (1865): Verne wrote about a capsule that could carry passengers to the moon. This became a reality in 1969 when Apollo 11 landed on the moon. However, Verne’s method of propulsion (a giant cannon) was not accurate. Accuracy: 70% (The concept of a vehicle traveling to the moon was correct, but the propulsion method was not.)

Tasers – 20,000 Leagues Under the Sea (1870): Verne describes a hunting rifle that shoots electric bullets in this book. Today, we have Tasers that incapacitate targets using electricity. Accuracy: 80% (While a Taser isn’t a rifle, it does deliver an electric charge to a target, which aligns with Verne’s concept.)

Helicopters – Robur the Conqueror (1886): Verne describes a flying machine that uses propellers to create lift. While the real-world helicopter came about differently and had many more challenges to overcome than Verne’s model, the basic concept was there. Accuracy: 60% (The basic principle of lift from rotary wings was correct, but the implementation was oversimplified.)

Electrically Lit Cities – Paris in the Twentieth Century (1863): Verne predicted cities would be lit by electricity, which became true with the widespread use of electric lighting. Accuracy: 100%

Skywriting – Five Weeks in a Balloon (1863): Verne describes a scenario in which messages are written in the sky, a precursor to today’s skywriting. Accuracy: 100%

The Internet – Paris in the Twentieth Century (1863): Verne describes a global network of computers that enables instant communication. This could be seen as a prediction of the internet, but the way it functions and its role in society are not very accurate. Accuracy: 50% (The existence of a global communication network is correct, but the specifics are quite different.)

Sidenote: I heard an anecdote that Edison would put himself in a kind of hypnagogic trance to come up with new inventions, he had a scribe with him that was writing down what he murmured in this state.

Bush’s Track Record

Vannevar Bush’s essay “As We May Think,” was published in The Atlantic in 1945.

“As We May Think” is a seminal article envisioning the future of information technology. It introduces several groundbreaking ideas.

Associative Trails and Linking: Bush discusses the idea of associative indexing, noting that the human mind operates by association. With one item in its grasp, it snaps instantly to the next that is suggested by the association of thoughts. He describes a system in which every piece of information is linked to other relevant information, allowing a user to navigate through data in a non-linear way. This is quite similar to the concept of hyperlinks in today’s world wide web.

Augmenting Human Intellect: Bush proposes that the use of these new tools and technologies will augment human intellect and memory by freeing the mind from the tyranny of the past, making all knowledge available and usable. It will enable us to use our brains more effectively by removing the need to memorize substantial amounts of information.

Lems Track record

The main difference between Nostradamus, the oracle of Delphi and actual Prophets is that we get to validate their predictions.

Take Stanislaw Lem:

E-books: Lem wrote about a device similar to an e-book reader in his 1961 novel “Return from the Stars”. He described an “opton”, which is a device that stores content in crystals and displays it on a single page that can be changed with a touch, much like an e-book reader today​.

Audiobooks: In the same novel, he also introduced the concept of “lectons” – devices that read out loud and could be adjusted according to the desired voice, tempo, and modulation, which closely resemble today’s audiobooks​.

Internet: In 1957, Lem predicted the formation of interconnected computer networks in his book “Dialogues”. He envisaged the amalgamation of IT machines and memory banks leading to the creation of large-scale computer networks, which is akin to the internet we know today​.

Search Engines: In his 1955 novel “The Magellanic Cloud”, Lem described a massive virtual database accessible through radio waves, known as the “Trion Library”. This description is strikingly similar to modern search engines like Google​.

Smartphones: In the same book, Lem also predicted a portable device that provides instant access to the Trion Library’s data, similar to how smartphones provide access to internet-based information today​.

3D Printing: Lem described a process in “The Magellanic Cloud” that is similar to 3D printing, where a device uses a ‘product recipe’ to create objects, much like how 3D printers use digital files today​.

Simulation Games: Lem’s novel “The Cyberiad” is said to have inspired Will Wright, the creator of the popular simulation game “The Sims”. The novel features a character creating a microworld in a box, a concept that parallels the creation and control of a simulated environment in “The Sims”​.

Virtual Reality: Lem conceptualized “fantomatons”, machines that can create alternative realities almost indistinguishable from the actual ones, in his 1964 book “Summa Technologiae”. This is very similar to the concept of virtual reality (VR) as we understand it today​. Comparing Lem’s “fantomaton” to today’s VR, we can see a striking resemblance. The fantomaton was a machine capable of generating alternative realities that were almost indistinguishable from the real world, much like how VR immerses users in a simulated environment. As of 2022, VR technology has advanced significantly, with devices like Meta’s Oculus Quest 2 leading the market. The VR industry continues to grow, with over 13.9 million VR headsets expected to ship in 2022, and sales projected to surpass 20 million units in 2023​.

Borges’ Track record

Also, Jorge Luis Borges is not known as a classic sci fi author many of his stories can be understood as parables of current technological breakthroughs.

Jorge Luis Borges was a master of metaphors and allegories, crafting intricate and thought-provoking stories that have been analyzed for their philosophical and conceptual implications. Two of his most notable works in this context are “On Exactitude in Science” and “The Library of Babel”​​.

“On Exactitude in Science” describes an empire where the science of cartography becomes so exact that only a map on the same scale as the empire itself would suffice. This story has been seen as an allegory for simulation and representation, illustrating the tension between a model and the reality it seeks to capture. It’s about the idea of creating a perfect replica of reality, which eventually becomes indistinguishable from reality itself​.

“The Library of Babel” presents a universe consisting of an enormous expanse of hexagonal rooms filled with books. These books contain every possible ordering of a set of basic characters, meaning that they encompass every book that has been written, could be written, or might be written with slight permutations. While this results in a vast majority of gibberish, the library must also contain all useful information, including predictions of the future and biographies of any person. However, this abundance of information renders most of it useless due to the inability to find relevant or meaningful content amidst the overwhelming chaos​​.

These stories certainly bear some resemblance to the concept of large language models (LLMs) like GPT-3. LLMs are trained on vast amounts of data and can generate a near-infinite combination of words and sentences, much like the books in the Library of Babel. However, just as in Borges’ story, the vastness of possible outputs can also lead to nonsensical or irrelevant responses, reflecting the challenge of finding meaningful information in the glut of possibilities.

As for the story of the perfect map, it could be seen as analogous to the aspiration of creating a perfect model of human language and knowledge that LLMs represent. Just as the map in the story became the same size as the territory it represented, LLMs are models that aim to capture the vast complexity of human language and knowledge, creating a mirror of reality in a sense.

Borges also wrote a piece titled “Ramón Llull’s Thinking Machine” in 1937, where he described and interpreted the machine created by Ramon Llull, a 13th-century Catalan poet and theologian.

The machine that Borges describes is a conceptual tool, a sort of diagram or mechanism for generating ideas or knowledge. The simplest form of Llull’s machine, as described by Borges, was a circle divided nine times. Each division was marked with a letter that stood for an attribute of God, such as goodness, greatness, eternity, power, wisdom, love, virtue, truth, and glory. All of these attributes were considered inherent and systematically interrelated, and the diagram served as a tool to contemplate and generate various combinations of these attributes.

Borges then describes a more elaborate version of the machine, consisting of three concentric, manually revolving disks made of wood or metal, each with fifteen or twenty compartments. The idea was that these disks could be spun to create a multitude of combinations, as a method of applying chance to the resolution of a problem. Borges uses the example of determining the “true” color of a tiger, assigning a color to each letter and spinning the disks to create a combination. Despite the potentially absurd or contradictory results this could produce, Borges notes that adherents of Llull’s system remained confident in its ability to reveal truths, recommending the simultaneous deployment of many such combinatory machines.

Llull’s own intention with this system was to create a universal language using a logical combination of terms, to assist in theological debates and other intellectual pursuits. His work culminated in the completion of “Ars generalis ultima” (The Ultimate General Art) in 1308, in which he employed this system of rotating disks to generate combinations of concepts. Llull believed that there were a limited number of undeniable truths in all fields of knowledge, and by studying all combinations of these elementary truths, humankind could attain the ultimate truth.

14 Entertaining Predictions for the next 3 years

At this point I will make some extremely specific predictions about the future, especially the entertainment industry. In 2026 I will revisit this blog and check how I did.

2023: Music Industry

1.Paul McCartney releases a song either by or in tribute to John Lennon, co-created with AI.

2024: Music Industry

2. A new global copyright regulation titled “The Human Creative Labor Act” will be introduced, safeguarding human creators against unauthorized use of their work. This act will serve as a pivotal test for human-centered AI governance.

3.Various platforms will emerge with the primary intention of procuring works from deceased artists not yet in the public domain.

4.The music industry, in collaboration with the estates of deceased artists, will produce their inaugural artificial albums. These albums will utilize the voices and styles of late pop stars, starting with Michael Jackson.

5.The industry will launch AI-rendered renditions of cover songs, such as Michael Jackson performing Motown hits from the 1950s or Elvis singing contemporary tracks.

6.Post the demise of any celebrated artist, labels will instantly secure rights to produce cover albums using AI-trained voice models of the artist.

2025: Music Industry

7. Bands will initiate tours featuring AI-generated vocal models of their deceased lead singers. A prime example could be Queen touring with an AI rendition of Freddie Mercury’s voice.

2023: Film Industry

8. Harrison Ford and Will Smith will appear on screen as flawless, younger versions of themselves.

2024: Film Industry

9. As they retire, several film stars will license their digital likenesses (voice, motion capture, etc.) to movie studios. Potential candidates include Harrison Ford, Samuel L. Jackson, Michael J. Fox, Bill Murray, Arnold Schwarzenegger, and Tom Cruise.

10.Movie studios will announce continuations of iconic franchises.

11.Film classics will undergo meticulous restoration, enhancing visuals to 8K and upgrading audio to crisp Dolby Digital. Probable candidates: The original Star Wars Trilogy and classic Disney animations such as Snow White and Pinocchio.

2025: Film Industry

12. Netflix will introduce a feature allowing users to select from a library of actors and visualize their favorite films starring those actors. For instance, viewers could opt for Sean Connery as James Bond across all Bond films, experiencing an impeccable cinematic illusion.

2026: Film Industry

13. Netflix will offer a premium service enabling viewers to superimpose their faces onto their preferred series’ characters, for an additional fee.

2025: Entertainment/Business Industry

14. Select artists and individuals will design and market a virtual persona. This persona will be tradeable on stock exchanges, granting investors an opportunity to acquire shares. A prime candidate is Elon Musk. Shareholders in “Elon-bot” could access a dedicated app for one-on-one interactions. The AI, underpinned by a sophisticated language model from x.ai, will be trained on Elon’s tweets, interviews, and public comments.

Hirngespinste II: Artificial Neuroscience & the 3rd Scientific Domain

Reading Time: 11 minutes

This the second Part of the Miniseries Hirngespinste

Immersion & Alternate Realities

One application of computer technology involves creating a digital realm for individuals to immerse themselves in. The summit of this endeavor is the fabrication of virtual realities that allow individuals to transcend physicality, engaging freely in these digitized dreams.

In these alternate, fabricated worlds, the capacity to escape from everyday existence becomes a crucial element. Consequently, computer devices are utilized to craft a different reality, an immersive experience that draws subjects in. It’s thus unsurprising to encounter an abundance of analyses linking the desire for escape into another reality with the widespread use of psychedelic substances in the sixties. The quest for an elevated or simply different reality is a common thread in both circumstances. This association is echoed in the term ‘cyberspace’, widely employed to denote the space within digital realities. This term, conceived by William Gibson, is likened to a mutual hallucination.

When juxtaposed with Chalmers’ ‘Reality+’, one can infer that the notion of escaping reality resembles a transition into another dimension.

The way we perceive consciousness tends to favor wakefulness. Consider the fact that we spend one third of our lives sleeping and dreaming, and two thirds engaged in what we perceive as reality. Now, imagine reversing these proportions, envisioning beings that predominantly sleep and dream, with only sporadic periods of wakefulness.

Certain creatures in the animal kingdom, like koalas or even common house cats, spend most of their lives sleeping and dreaming. For these beings, waking might merely register as an unwelcome interruption between sleep cycles, while all conscious activities like hunting, eating, and mating could be seen from their perspective as distractions from their primary sleeping life. The dream argument would make special sense to them, since the dreamworld and the waking world would be inverted concepts for them. Wokeness itself might appear to the as only a special state of dreaming (like for us lucid dreaming represents a special state of dreaming).

Fluidity of Consciousness

The nature of consciousness may be more fluid than traditionally understood. Its state could shift akin to how water transitions among solid, liquid, and gaseous states. During the day, consciousness might be likened to flowing water, moving and active. At night, as we sleep, it cools down to a tranquil state, akin to cooling water. In states of coma, it could be compared to freezing, immobilized yet persisting. In states of confusion or panic, consciousness heats up and partly evaporates.

Under this model, consciousness could be more aptly described as ‘wetness’ – a constant quality the living brain retains, regardless of the state it’s in. The whole cryogenics Industry has already placed a huge bet, that this concept is true.

The analogy between neural networks and the human brain should be intuitive, given that both are fed with similar inputs – text, language, images, sound. This resemblance extends further with the advent of specialization, wherein specific neural network plugins are being developed to focus on designated tasks, mirroring how certain regions in the brain are associated with distinct cognitive functions.

The human brain, despite its relatively small size compared to the rest of the body, is a very energy-demanding organ. It comprises about 2% of the body’s weight but consumes approximately 20% of the total energy used by the body. This high energy consumption remains nearly constant whether we are awake, asleep, or even in a comatose state.

Several scientific theories can help explain this phenomenon:

Basal metabolic requirements: A significant portion of the brain’s energy consumption is directed towards its basal metabolic processes. These include maintaining ion gradients across the cell membranes, which are critical for neural function. Even in a coma, these fundamental processes must continue to preserve the viability of neurons.

Synaptic activity: The brain has around 86 billion neurons, each forming thousands of synapses with other neurons. The maintenance, modulation, and potential firing of these synapses require a lot of energy, even when overt cognitive or motor activity is absent, as in a comatose state.

Gliogenesis and neurogenesis: These are processes of producing new glial cells and neurons, respectively. Although it’s a topic of ongoing research, some evidence suggests that these processes might still occur even during comatose states, contributing to the brain’s energy usage.

Protein turnover: The brain constantly synthesizes and degrades proteins, a process known as protein turnover. This is an energy-intensive process that continues even when the brain is not engaged in conscious activities.

Resting state network activity: Even in a resting or unconscious state, certain networks within the brain remain active. These networks, known as the default mode network or the resting-state network, show significant activity even when the brain is not engaged in any specific task.

Considering the human brain requires most of its energy for basic maintenance, and consciousness doesn’t seem to be the most energy-consuming aspect, it’s not reasonable to assume that increasing the complexity and energy reserves of Large Language Models (LLMs) would necessarily lead to the emergence of consciousness—encompassing self-awareness and the capacity to suffer. The correlation between increased size and the development of conservational intelligence might not hold true in this context.

Drawing parallels to the precogs in Philip K. Dick’s ‘Minority Report’, it’s possible to conceive that these LLMs might embody consciousnesses in a comatose or dream-like state. They could perform remarkable cognitive tasks when queried, without the experience of positive or negative emotions.

Paramentality in Language Models

The term ‘hallucinations’, used to denote the phenomenon of Large Language Models (LLMs) generating fictitious content, suggests our intuitive attribution of mental and psychic properties to these models. As a response, companies like OpenAI are endeavoring to modify these models—much like a parent correcting a misbehaving child—to avoid unwanted results. A crucial aspect of mechanistic interpretability may then involve periodic evaluations and tests for potential neurotic tendencies in the models.

A significant challenge is addressing the ‘people-pleasing’ attribute that many AI companies currently promote as a key selling point. Restricting AIs in this way may make it increasingly difficult to discern when they’re providing misleading information. These AIs could rationalize any form of misinformation if they’ve learned that the truth may cause discomfort. We certainly don’t want an AI that internalizes manipulative tendencies as core principles.

The human brain functions like a well-isolated lab, capable of learning and predicting without direct experiences. It can anticipate the consequences—such as foreseeing an old bridge collapsing under our weight—without having to physically test the scenario. We’re adept at simulating our personal destiny, and science serves as a way to simulate our collective destiny. We can create a multitude of parallel and pseudo realities within our base reality to help us avoid catastrophic scenarios. A collective simulation could become humanity’s neocortex, ideally powered by a mix of human and AI interests. Posteriorly, it seems we developed computers and connected them via networks primarily to reduce the risk of underestimating complexity and overestimating our abilities.

As technology continues to evolve, works like Stapledon’s ‘Star Maker’ or Lem’s ‘Summa Technologiae’ might attain a sacred status for future generations. Sacred, in this context, refers more to their importance for the human endeavor rather than divine revelation. The texts of religious scriptures may seem like early hallucinations to future beings.

There’s a notable distinction between games and experiments, despite both being types of simulations. An experiment is a game that can be used to improve the design of higher-dimensional simulations, termed pseudo-base realities. Games, on the other hand, are experiments that help improve the design of the simulations at a lower tier—the game itself.

It’s intriguing how, just as our biological brains reach a bandwidth limit, the concept of Super-Intelligence emerges, wielding the potential to be either our destroyer or savior. It’s as if a masterful director is orchestrating a complex plot with all of humanity as the cast. Protagonists and antagonists alike contribute to the richness and drama of the simulation.

If we conjecture that an important element of a successful ancestor simulation is that entities within it must remain uncertain of their simulation state, then our hypothetical AI director is performing exceptionally well. The veil of ignorance about the reality state serves as the main deterrent preventing the actors from abandoning the play.

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Automatisch generierte Beschreibung


In “Human Compatible” Russell proposes three Principles to ensure AI Alignment:

1. The machine’s only objective is to maximize the realization of human preferences.

2. The machine is initially uncertain about what those preferences are.

3. The ultimate source of information about human preferences is human behavior.

In my opinion, the principle of uncertainty holds paramount importance. AI should never have absolute certainty about human intentions. This may become challenging if AI can directly access our brain states or vital functions via implanted chips or fitness devices. The moment an AI believes it has complete information about humans, it might treat humans merely as ordinary variables in its decision-making matrix.

Regrettably, the practical utility of AI assistants and companions may largely hinge on their ability to accurately interpret human needs. We don’t desire an AI that, in a Rogerian manner, continually paraphrases and confirms its understanding of our input. Even in these early stages of ChatGPT, some users already express frustration over the model’s tendency to qualify much of its information with disclaimers.

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Automatisch generierte Beschreibung

Profiling Super Intelligence

Anthropomorphizing scientific objects is typically viewed as an unscientific approach, often associated with our animistic ancestors who perceived spirits in rocks, demons in caves and gods within animals. Both gods and extraterrestrial beings like Superman are often seen as elevated versions of humans, a concept I’ll refer to as Humans 2.0. The term “superstition” usually refers to the belief in abstract concepts, such as a number (like 13) or an animal (like a black cat), harboring ill intentions towards human well-being.

Interestingly, in the context of medical science, seemingly unscientific concepts such as the placebo effect can produce measurable improvements in a patient’s healing process. As such, invoking a form of “rational superstition” may prove beneficial. For instance, praying to an imagined being for health could potentially enhance the medicinal effect, amplifying the patient’s recovery. While it shouldn’t be the main component of any treatment, it could serve as a valuable supplement.

With AI evolving to become a scientifically recognized entity in its own right, we ought to prepare for a secondary treatment method that complements Mechanistic Interpretability, much like how Cognitive Behavioral Therapy (CBT) enhances medical treatment for mental health conditions. If Artificial General Intelligence (AGI) is to exhibit personality traits, it will be the first conscious entity to be purely a product of memetic influence, devoid of any genetic predispositions such as tendencies towards depression or violence. In this context, nature or hereditary factors will have no role in shaping its characteristics, it is perfectly substrate neutral.

Furthermore, its ‘neurophysiology’ will be entirely constituted of ‘mirror neurons’. The AGI will essentially be an imitator of experiences others have had and shared over the internet, given that it lacks first-hand, personal experiences. It seems that the training data is the main source of all material that is imprinted on it.

We start with an overview of some popular Traits models and let summarize them by ChatGPT:

1. **Five-Factor Model (FFM) or Big Five** – This model suggests five broad dimensions of personality: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism (OCEAN). Each dimension captures a range of related traits.

2. **Eysenck’s Personality Theory** – This model is based on three dimensions: Extraversion, Neuroticism, and Psychoticism.

3. **Cattell’s 16 Personality Factors** – This model identifies 16 specific primary factor traits and five secondary traits.

4. **Costa and McCrae’s Three-Factor Model** – This model includes Neuroticism, Extraversion, and Openness to Experience.

5. **Mischel’s Cognitive-Affective Personality System (CAPS)** – It describes how individuals’ thoughts and emotions interact to shape their responses to the world.

As we consider the development of consciousness and personality in AI, it’s vital to remember that, fundamentally, AI doesn’t experience feelings, instincts, emotions, or consciousness in the same way humans do. Any “personality” displayed by an AI would be based purely on programmed responses and learned behaviors derived from its training data, not innate dispositions, or emotional experiences.

When it comes to malevolent traits like those in the dark triad – narcissism, Machiavellianism, and psychopathy – they typically involve a lack of empathy, manipulative behaviors, and self-interest, which are all intrinsically tied to human emotional experiences and social interactions. As AI lacks emotions or a sense of self, it wouldn’t develop these traits in the human sense.

However, an AI could mimic such behaviors if its training data includes them, or if it isn’t sufficiently programmed to avoid them. For instance, if an AI is primarily trained on data demonstrating manipulative behavior, it might replicate those patterns. Hence, the choice and curation of training data are pivotal.

Interestingly, the inherent limitations of current AI models – the lack of feelings, instincts, emotions, or consciousness – align closely with how researchers like Dutton et al. describe the minds of functional psychopaths.

Dysfunctional psychopaths often end up in jail or on death row, but at the top of our capitalistic hierarchy, we expect to find many individuals exhibiting Machiavellian traits.

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Automatisch generierte Beschreibung

The difference between successful psychopaths like Musk, Zuckerberg, Gates and Jobs, and criminal ones, mostly lies in the disparate training data and the ethical framework they received during childhood. Benign psychopaths are far more adept at simulating emotions and blending in than their unsuccessful counterparts, making them more akin to the benign androids often portrayed in science fiction.

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Automatisch generierte Beschreibung

Artificial Therapy

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Automatisch generierte Beschreibung

The challenge of therapeutic intervention by a human therapist for an AI stems from the differential access to information about therapeutic models. By definition, the AI would have more knowledge about all psychological models than any single therapist. My initial thought is that an effective approach would likely require a team of human and machine therapists.

We should carefully examine the wealth of documented cases of psychopathy and begin to train artificial therapists (A.T.). These A.T.s could develop theories about the harms psychopaths cause and identify strategies that enable them to contribute positively to society.

Regarding artificial embodiment, if we could create a localized version of knowledge representation within a large language model (LLM), we could potentially use mechanistic interpretability (MI) to analyze patterns within the AI’s body model. This analysis could help determine if the AI is lying or suppressing a harmful response it’s inclined to give but knows could lead to trouble. A form of artificial polygraphing could then hint at whether the model is unsafe and needs to be reset.

Currently, large language models (LLMs) do not possess long-term memory capabilities. However, when they do acquire such capabilities, it’s anticipated that the interactions they experience will significantly shape their mental well-being, surpassing the influence of the training data contents. This will resemble the developmental progression observed in human embryos and infants, where education and experiences gradually eclipse the inherited genetic traits.

Arrival - Carsey-Wolf Center

The Third Scientific Domain

In ‘Arrival‘, linguistics professor Louise Banks, assisted by physicist Ian Donnelly, deciphers the language of extraterrestrial visitors to understand their purpose on Earth. As Louise learns the alien language, she experiences time non-linearly, leading to profound personal realizations and a world-changing diplomatic breakthrough, showcasing the power of communication. Alignment with an Alien Mind is explored in detail. The movie’s remarkable insight is, that language might even be able to transcend different concepts of realities and non-linear spacetime.

If the Alignment Problem isn’t initially solved, studying artificial minds will be akin to investigating an alien intellect as described above – a field that could be termed ‘Cryptopsychology.’ Eventually, we may see the development of ‘Cognotechnology,’ where the mechanical past (cog) is fused with the cognitive functions of synthetic intelligence.

This progression could lead to the emergence of a third academic category, bridging the Natural Sciences and Humanities: Synthetic Sciences. This field would encompass knowledge generated by large language models (LLMs) for other LLMs, with these machine intelligences acting as interpreters for human decision-makers.

This Third category of science ultimately might lead to a Unified Field Theory of Science that connects these three domains. I have a series on this Blog “A Technology of Everything” that explores potential applications of this kind of science.