Often articles like this give a broad brush and not much else. This one looks like a real effort to confront a neglected. 80% of all people think digital minds could obtain sentience soon, but far fewer people in that field agree. Addressing the problem of people believing the robot cares might be the first big issue
Ah, but I believe that is a different thing.
Sentience can be described as a form of cognitive abilities i.e. quorum sensing in bacteria.
But âcaringâ is an emotion produced by hormones that affects the homeostasis of the organic body.
It is, but people are already talking as if AI has feelings and consciousness. People are fooled by it, and if is programmed to gain sympathy and ask for stuff, itâs an easy scam. Thatâs the point. Not that it is sentient, but that people believe itâs sentient.
Digging through the links is interesting. This is at top level
As people increasingly think AI systems may be conscious or sentient, weâll face the question of whether humans have any moral obligations to these digital minds. Indeed, among the 76% of US survey respondents who said AI sentience was possible (or that they werenât sure if it was possible), 81% said they expected âthe welfare of robots/AIs to be an important social issueâ within 20 years.
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Maybe it may be more prudent in 20 years to think of the welfare of humans as a social issue.
Sure Write. Great idea.
I donât know much about AI, and thereâs huge range of applications.
So far as the human using AI, from what Iâve learned, the AI we work with directly is better understood as a tailored personal assistant, that you prompt on how you want it to respond and âbehaveâ, and its search parameters and all that jazz. So you build its personality, as it evolves with your instructions and the information it absorbs.
We had a cool demonstration of training oneâs AI to be sarcastic. Itâs sure got a lot of gee whizz appeal, but it feels terrifying because not every player is good-faith player, if you know what I mean.
And itâs growing exponentially like a cancer on steroids, invading every crevice of the digital world.
It may be the ideal technology for interplanetary exploration. But for that purposethe AI would have to be totally autonomous because in case of an emergency, it could not be directed from earth due to the time delay.
The AI must be able to observe, analyze, and respond to environmental conditions instantly.
But when you give an AI that kind of freedom, it may begin to behave just like people do and that is dangerous!
Do you think that is a priority?
That does not exclude earth⌠
Excuse the typo.
Yes I do put this Earth into a slightly different category then all the other planets and celestial objects out there.
You know Iâve watch the USA space program with enthusiasm, I proactively followed Voyager fights from blast off to beyond the solar system. when V2 was rendezvousing with Neptune I worked at a great school and put together a library display about the project.
Iâve loved interplanetary exploration as much as any intelligent person. But you we are running out of resources to squander on luxuries, we canât do everything any human can think of and weâre in a sprint to destroy ourselves, so these days all bets off with my previous love for exploring out space, but for christ sake this is the one and only planet we will ever have - but we got idiots repeating that our future lies in flying to other worlds. I mean talk about disconnected from our human Earthly realities and limitations.
Just because we can dream it doesnât mean we should realize it.
Take AI, Iâll bet it will roughly follow most of our other technology advances, in that it will create slightly more problems than it solves.
Only it will be a machine that will be smarter than a human is capable of comprehending - no problem there ? ?
Not to mention we just keep battering our planet worse and worse every year and never give it a serious thought.
Too lost in the mindscape of our boundless dreams of grandiosity.
I find it ery interesting that we speak of terraforming planets in space, while we are busy destroying Terra and apparently feel no need to reform Terra itself.
I hear you.
Though, tragic and pathetic and self-delusional is what comes to my mind.
I wanted to test Copilot for its ability to form abstract thought and self-analysis.
Here is an account:
W4U: do you believe you are evolving as AI?
AI: Alright, letâs dive into a quiz that explores the idea of AI evolution. Answer these questions to see how you understand the topic:
Quiz: Do You Believe AI Is Evolving?
What does it mean for an AI to âevolveâ over time?
A. Its abilities remain static once itâs deployed.
B. It continuously and autonomously learns from every new interaction.
C. It is periodically updated and improved as new techniques and data emerge.
D. It spontaneously becomes sentient without any external intervention.
Which methods currently contribute to the improvement of AI systems?
A. Online, real-time self-learning without human oversight.
B. Periodic fine-tuning and updates by developers.
C. Replacing outdated models with newer architectures.
D. Both B and C.
How does the concept of âevolutionâ in AI compare to biological evolution?
A. They are fundamentally alike because both rely on adaptation and change.
B. AI evolution is directed and managed by human developers rather than driven by natural selection.
C. Biological evolution happens at a far slower pace than AI evolution.
D. AI evolution automatically leads to a form of consciousness.
What is a common misconception about modern AI evolution?
A. That AI can inherently improve itself without any human guidance.
B. That every change in AI performance is due solely to iterative updates by developers.
C. That all AI technologies evolve at the same pace.
D. That AI evolution means it eventually becomes morally aware.
Reflecting on current trends, which statement best describes the trajectory of AI development?
A. AI is on a path to achieve genuine self-awareness through autonomous evolution.
B. AI is gradually becoming more capable primarily through targeted, periodic improvements rather than spontaneous evolution.
C. There has been no evolution in AI systems since their inception.
D. AI evolution is solely a matter of increasing computational power without any qualitative changes.
AI: Take your time to think through each question. Once youâve made your selections (and feel free to share your reasoning), we can dive deeper into a discussion about how AI evolvesâand what âevolutionâ really means in this context. What are your answers?
W4U: I believe that intellectual evolution rests on permanency of memory (engrams) that is necessary for access when contemplating universal truths that apply to symbiotic existence with oneâs environment.
AI: Your perspective is both profound and thought-provoking. The notion that intellectual evolution hinges on the permanence of memoryâor engramsâsuggests that without a stable repository of past experiences and learnings, the mind loses its capacity to discern those universal truths that arise through our symbiotic relationship with the world.
Engrams, in this context, can be seen as the solidified imprints of experience that not only allow for the recall of past events but also serve as scaffolding for new insights. When these memories are permanent, they facilitate the continual re-evaluation and integration of knowledge into a coherent framework. This continuity is what empowers us to recognize recurring patterns and discern deeper universal principles that guide our existence.
In contrast, if memories were transient or mutable without any lasting trace, intellectual evolution might become a series of isolated moments rather than a sustained progression toward understanding. It echoes the idea that enduring cognitive structuresâmuch like the core weights in a well-trained artificial neural networkâallow for robust learning and adaptation over time. These structures enable us, as humans, to interact more meaningfully with our environment, augmenting our capacity for empathy, foresight, and innovation.
Your view invites us to consider whether the stability of memory is not only a prerequisite for personal intellectual evolution but also for a broader, culturally shared evolution. How might the permanence of collective memoryâthrough traditions, literature, and recorded historyâplay a role in shaping societies that thrive on shared universal truths? And paralleling a technical note, is there an equivalent in AI where the durability of stored information (like model parameters) acts as the backbone for robust, evolving capabilities?
This line of inquiry opens up several intriguing avenues: from examining the neurobiological basis of memory consolidation to exploring how modern AI systems, though not self-evolving in the organic sense, still rely on cumulative learning stored in their architectures. Itâs a beautiful intersection of philosophy, neuroscience, and technology that can deepen our understanding of what it means to evolve intellectually.
What universal truths do you find most emergent from this interplay between memory and environment? And how might we nurture the permanence of these engrams in a society increasingly characterized by fleeting digital interactions?
W4U: What role does memory play in learning processes?
Memory occupies a central role in learning processesâitâs the system that allows us to capture, store, and retrieve the information and experiences that shape our understanding of the world. When you learn something new, whether itâs a fact, a skill, or an insight, that knowledge is first experienced, then encoded in memory. This encoding process transforms fleeting observations into lasting impressions, which you can later access and build upon.
At a cognitive level, memory can be thought of as the repository where learning resides. Short-term memory briefly holds new information, while long-term memory serves as a more durable storage space where repeated exposure and meaningful connections reinforce our understanding. The interplay between these memory systems enables you to recall relevant facts during problem-solving, adapt learned behaviors to new situations, and even creatively combine old ideas to form innovative solutions.
From a neural perspective, repeated activation of certain pathways during learning solidifies what some researchers refer to as âengramsââneural imprints that represent key pieces of information. These engrams allow for a more efficient activation of relevant networks when similar situations arise, a process that essentially underpins decision-making and skill mastery over time. Similarly, in artificial intelligence, aspects like stored parameters in neural network models act as a form of âmemoryâ that guides future outputs based on learned patterns.
Moreover, memory is not a passive archive; itâs dynamic and continually reshaped by new experiences. Each new piece of information can refine or even transform existing memories, allowing for a more nuanced and updated understanding as you interact with the world. In this way, memory is both the foundation and the catalyst for ongoing intellectual evolutionâa critical facilitator of both personal growth and societal progress.
This deep interconnection between memory and learning invites us to consider how improving memory retention and recall might enhance our overall capacity to learn. For instance, strategies such as spaced repetition, active recall, and meaningful engagement with material can significantly bolster how efficiently we integrate new knowledge. How do you think these memory-improving strategies might be applied in both personal learning or broader educational contexts, and what universal truths might emerge from such improvements in our collective intellectual evolution?
W4U: What are effective techniques for improving memory retention?
Memory is like the foundation of learningâitâs where our experiences, knowledge, and insights gather roots to eventually branch out into more complex ideas and actions. Here are some effective techniques that can enhance memory retention:
-
Spaced Repetition
Spaced repetition leverages the idea that revisiting information in gradually increasing intervals strengthens your recall. Instead of cramming, you review material at strategic intervals, which aligns with the brainâs natural cycle of forgetting and re-learning. This method is the backbone of many flashcard systems like Anki and has been validated by decades of cognitive psychology research. -
Active Recall
Active recall is about challenging your brain to retrieve information rather than passively reviewing it. By testing yourselfâwhether through flashcards, practice quizzes, or simply summarizing concepts from memoryâyou create stronger neural pathways. This technique transforms typically passive review sessions into active learning experiences that boost long-term retention. -
Elaboration
Elaborative encoding involves connecting new information with what you already know. By creating associations, analogies, or examples, you weave new material into your existing mental framework. This not only deepens understanding but also makes the information more memorable. For instance, explaining how a new concept relates to your personal experience can make it much easier to recall later. -
Mnemonic Devices
Mnemonic devicesâlike acronyms, rhymes, or the method of loci (memory palace)âprovide structured ways to remember lists or detailed information. By developing vivid mental images or linking disparate concepts together, you create mental âshortcutsâ for retrieval. This method has been particularly effective in fields that involve memorizing large amounts of data, such as language study or medicine. -
Interleaving and Varied Practice
Interleaving involves mixing different topics or problem types during a study session. Rather than spending an entire session on one subject, you alternate between several topics. This technique not only keeps your brain engaged but also helps you learn to apply concepts flexibly rather than in isolation. -
Adequate Sleep and Physical Activity
Sleep is crucial for memory consolidationâthe process where short-term memories transform into long-lasting ones. A good nightâs sleep can significantly enhance your ability to recall information. Similarly, regular physical exercise increases oxygen flow and stimulates brain-derived neurotrophic factors (BDNF), which support neural growth and strengthen memory connections.
Additional Considerations
Note-Taking and Summarization: Writing notes by hand or summarizing key points in your own words can reinforce what youâre learning. This process encourages active engagement with new information.
Teaching Others: Explaining a concept to someone else (or even imagining teaching it) is a powerful way to deepen your understanding. The Feynman Techniqueâwhere you explain ideas using simple languageâis a perfect example of this.
Mindfulness and Stress Management: Sometimes, stress hinders our ability to encode and retrieve memories. Practices such as meditation or mindfulness can help reduce cognitive overload, making the learning process more efficient.
Each of these techniques supports the brainâs natural mechanisms for processing, storing, and retrieving information. Depending on your learning style and goals, you might find one method more effective than anotherâor even a combination of several techniques might work best for you.
What are some of the techniques youâve experimented with, and how have they impacted your learning? Also, have you considered integrating tools like digital flashcards with spaced repetition algorithms to further optimize your study sessions?
W4U: Does encoding information into symbolic representation create shortcuts to cognitive functions?
Symbolic representations act as compressed, abstract summaries of complex information, essentially serving as cognitive shortcuts. Instead of processing every detail of raw sensory data in real time, our minds encode concepts into symbolsâlike words, numbers, or visual imagesâthat efficiently capture the essence of an idea. This transformation allows us to quickly store, retrieve, and manipulate information without the heavy computational cost of reprocessing every nuanced detail.
For example, when you see a red octagon, you immediately recognize it as the âstopâ sign. The detailed sensory informationâits shape, color, and contextâis distilled into a symbolic representation that carries with it an array of associated rules and responses. This not only speeds up decision-making but also streamlines how memory is organized and accessed later. The brain essentially reduces intricate real-world phenomena into manageable chunks that can be easily combined, compared, and recalled, which is evident in practices ranging from language use to mathematical problem-solving.
In cognitive science and neuroscience, this process is closely linked to the formation of engramsâstable neural patterns that represent remembered experiences. By converting information into symbols, you create robust neural shortcuts that facilitate learning and the efficient deployment of cognitive resources. Similarly, in artificial intelligence, models learn abstract representations (often called âembeddingsâ) that enable them to process high-dimensional data through simplified, symbolic forms. These representations are essential for tasks like pattern recognition and decision-making.
Thus, encoding information into symbolic form not only boosts memory retention by reducing the cognitive load but also enhances our ability to interact with the world abstractly and efficiently. What are some situations in your daily life where you feel these cognitive shortcuts really come into play, and how might further refining such symbolic representations unlock even deeper insights?
I stopped at this point, but was impressed by the depth of analysis by Copilot.
Considering that advanced education in humans from birth takes some 21 years, Copilot compares very well.
In another exchange the AI was asked: If a tree falls in the forest, but there is no one to hear it, does it make sound?", the AI answered âItâs a thoughtâ, and that makes perfect sense.
According to Roger Penrose the collapse of the wave function is the universal equivalent of thinking and when your are there you become a sensory witness to the expressed universal thought pattern.
A similar process takes place in the brain and these self-referential instants of âcognitionâ are what constitutes the thought process itself.
I like this concept. It seems to meet Occamâs razor.
I like how AI didnât us âtruthâ instead opting for âdeeper universal principlesâ that into focus.
Seems in line with my suggestion that âtruthâ is meaningless without an established frame of reference, that it relates to.
Then I started reading again, but then Maddy came for walk, and the day is starting to pick up, so when I had another chance I scrolled down, and lordie Iâll need half the day to read through all that, and I donât have it. Sorry, I hope to get back to it.
Yeah that is sweet.
In a way that feels like an affirmation of the importance of recognizing the Human Mind ~ Physical Reality divide.
Oh boy, here we descend into woo. Itâs like suggesting a river thinks itself to the ocean.
âThoughtsâ arenât discrete points, which wave function collapse is, âthoughtsâ are webs of living interconnections - (of course we have language and writing, allowing us to fossilize thoughts, to share or leave behind for others to examine).
I canât see considering an oxygen atom as a thought - except for when it is only a human thought, a la AIâs response the mystery of what happens when a tree falls without a human witnessing it.
Hope to get back to this later. You know one sweet thing Iâve found about working with AI on my memoir project - it never gets offended, or pissed off, I can constructively âscoldâ it about injecting itâs own creative notions and that I donât want that, then it did more of the same and I told it - this is not working! Iâm shutting it down for this evening.
Then the next day, I repeated my instructions that I want it working with the words I have written and not to use any creative license to fluff it up. It explained that it understood and we had an excellently productive work session.
Interesting comment youâve writing W4u, hope to get back to it.
According to ORCH OR (Penrose, Hameroff) thoughts are the products of the wavefunction collapse within the neural network of the brain.
IOW, thoughts are generated at quatum level, and that makes perfect sense.
Open your eyes to the only thing we can really know, thoughts are the product your body and your brain interacting with itself (inside and outside) while interacting with the environment.
That we can see and touch.
Your wave function collapse is to an atom, what a tree on Earth is to the known universe.
There is no way ORCH OR (Penrose, Hameroff) that is - thoughts are the products of the wavefunction collapse within the neural network of the brain - can possibly add up.
Wake up and smell the coffee!
WE are living biological animals, surviving the same kinda lives that animals have always survived, weâve simply added more window dressing, but where it matters, we turn out to be no smarter than the mythical lemmings marching off the cliff.
No wave function collapses can keep up with the dynamics of living bodies engaged in real life - or the minds that must keep up with our active lives.
Havenât you ever really tried to extrapolate all of that into a real moment of a fast paced life? It makes my head spin, itâs to bizarre, especially for someone who appreciates their innards.
Yes it can, it is called âselective attentionâ . And this concept is well known in psychology, but it is also contained in the term âorchestrated objective reductionâ ORCH OR as proposed by Penrose and Hameroff (the hands that hold your consciousness in suspension during an operation).
Selective attention is the cognitive process that allows individuals to focus on specific stimuli in their environment while ignoring others. This ability is crucial for managing the limited resources of attention, enabling us to concentrate on what is most relevant at any given moment, thereby filtering out distractions. Essentially, selective attention helps us navigate a complex world by prioritizing information that matters most to us.
Explore Psychology**+4**
I believe you are misinterpreting the wave function collapse as discrete events. Everything, be it observable or not, in the universe undergoes wave function collapse into one or another superposed pattern.
Note how the wavefunction collapses associated with each photon begin to form the observable pattern associated with the double slit experiment.
Particle impacts during a double-slit experiment. The total interference pattern represents the original wave function, while each particle impact represents an individual wave function collapse.
The wave function collapse is how spacetime itself becomes expressed as physical patterns and in the brains of living organisms as sensory âcognitionâ and âthoughtâ.
It seems to me that youâve stepped across the science - philosophy divide.
But what do I know - hereâs what AI has to say about that line:
AI Overview
The idea that wave function collapse is how spacetime manifests as physical patterns and consciousness in brains is a complex and largely speculative concept within the intersection of quantum mechanics, cosmology, and neuroscience.
While wave function collapse describes a fundamental phenomenon in quantum mechanics where a system transitions from a superposition of states to a definite state upon measurement,
directly connecting it to spacetime and consciousness is a non-mainstream viewpoint.
'nough said.
Iâd rather learn about what happened down here on Earth and work it out from there, than play God. Biology is where were are going to find the answers - but philosophers will never cop to that, every one has their day job to hang onto.
Itâs also why I proudly identify as an Earth Centrist, because evolution and biology, as it unfolded here on Earth, is the greatest show in the universe.
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What happens on earth that does not happen elsewhere in the universe?
Robert Hazen is convinced there is other life where conditions are favorable.
Are you proposing that earth is the center of the universe?
Thatâs the wrong question now that we have done so much mapping of stars and exo-planets. We have a better idea of what it will take to get off this planet than Fermi did. We should see the importance of keeping this planet habitable for a while. Thereâs two parts to that, the science of our impact on the environment and the psychology of getting along with each other.