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To say that something has a positive contribution, we need to know the common terminal goal first.
Quote from: hamdani yusuf on 01/06/2022 10:42:02To say that something has a positive contribution, we need to know the common terminal goal first.No. It just has to make people happy or healthy.
Can we live forever in the cloud? Will we ever bend time to our will?Can we live forever in a machine?Imagine you pass away but your brain lives on as an android. Well some scientists are working on this already, they are trying to map the ENTIRE brain and upload it to a computer. Dr Josie Peters leads a group of scientists to tell us if we can really live forever.
Giving birth is dangerous. Are artificial wombs a solution?Full ectogenesis is the idea of conceiving a baby in vitro and gestating the child for the entire gestational period of 40 weeks.We already have partial ectogenesis implemented in neonatal intensive care units across the world from 21 weeks of gestation to full-term. This means almost half of the gestational period required to make a healthy human being can happen outside of the body already.Traditional natural gestation is very costly, and it's often one of the most dangerous things that many women will choose to do. Artificial wombs allow women to choose where they want to direct their labor and their physical resources, while also not sacrificing having children.
How I learned to stop worrying and love Artificial Super IntelligenceI think fears of artificial super intelligence (in pop culture, specifically) are a bit overblown. I lay out my case in this vodeo.
SpaceX's Starship launch vehicle has the potential to explore the solar system in a bold, new -- and supersized -- way. Planetary scientist Jennifer Heldmann talks about how reusable, large-scale spacecraft like Starship could help humanity achieve its next galactic leaps and usher in a new era of space exploration, from investigating the solar system's many ocean worlds to launching bigger telescopes that can see deeper into the universe.
https://thereader.mitpress.mit.edu/how-did-consciousness-evolve-an-illustrated-guide/How can we develop an evolutionary theory of consciousness when there is so much disagreement over what consciousness is and which organisms are conscious? Our way of approaching this question takes as its inspiration the way the Hungarian chemist Tibor Gánti tackled a similar problem, the problem of how life (another elusive notion) originated. Gánti started by compiling a list of capacities that, in spite of the different views about the nature of life, are generally deemed jointly sufficient for the simplest, “minimal” life. He then built a theoretical model of a minimal living system that implements all these capacities.What is the evolutionary transition marker of minimal consciousness? Following Gánti’s methodology we started by compiling a consensus list of consciousness characteristics based on the work of psychologists, philosophers, and neurobiologists:Binding/unification: seeing the apple as a composite whole (red, round, smooth) yet with discernable featuresGlobal accessibility and broadcast: back and forth interactions among specialized brain modules allowing comparisons, discriminations, generalizations, and evaluations that inform decision-makingSelective attention and active exclusion: excluding or amplifying signals according to past and present contextIntentionality (aboutness; representation): the mapping (representations) of body, world, action, and their relationsIntegration through time: Holding on to incoming information long enough for it to be integrated and evaluated, so the present can be said to have durationFlexible evaluative system and goals: evaluating perceptions and actions as rewarding or punishing according to contextAgency and embodiment: inherent spontaneous activity and goal-directed behaviorA sense of self: registration of self/other and a stable perspectiveOn the basis of this list, we suggest that the evolutionary transition marker of minimal consciousness, which is the within-lifetime analog of unlimited heredity in evolutionary time, is Unlimited associative learning (UAL). UAL is the within-lifetime analog of unlimited heredity in evolutionary time. An organism with a capacity for UAL can, during its own lifetime, go on learning from experience about the world and about itself in a practically unrestricted way.If an animal shows unlimited associative learning (that is, practically unrestricted learning) it means that all the capacities of consciousness are in place.
DeepMind’s AI develops popular policy for distributing public moneyDeepMind researchers have trained an AI system to find a popular policy for distributing public funds in an online game – but they also warn against “AI government”A “democratic” AI system has learned how to develop the most popular policy for redistributing public money among people playing an online game.“Many of the problems that humans face are not merely technological, but require us to coordinate in society and in our economies for the greater good,” says Raphael Koster at UK-based AI company DeepMind. “For AI to be able to help, it needs to learn directly about human values.”The DeepMind team trained its artificial intelligence to learn from more than 4000 people as well as from computer simulations in an online, four-player economic game. In the game, players start with different amounts of money and must decide how much to contribute to help grow a pool of public funds, eventually receiving a share of the pot in return. Players also voted on their favourite policies for doling out public money.The policy developed by the AI after this training generally tried to reduce wealth disparities between players by redistributing public money according to how much of their starting pot each player contributed. It also discouraged free-riders by giving back almost nothing to players unless they contributed approximately half their starting funds.This AI-devised policy won more votes from human players than either an “egalitarian” approach of redistributing funds equally regardless of how much each person contributed, or a “libertarian” approach of handing out funds according to the proportion each person’s contribution makes up of the public pot.“One thing we found surprising was that the AI learned a policy that reflects a mixture of views from across the political spectrum,” says Christopher Summerfield at DeepMind.When there was the highest inequality between players at the start, a “liberal egalitarian” policy – which redistributed money according to the proportion of starting funds each player contributed, but didn’t discourage free-riders – proved as popular as the AI proposal, by getting more than 50 per cent of the vote share in a head-to-head contest.The DeepMind researchers warn that their work doesn’t represent a recipe for “AI government”. They say they don’t plan to build AI-powered tools for policy-making.That may be as well, because the AI proposal isn’t necessarily unique compared with what some people have already suggested, says Annette Zimmermann at the University of York, UK. Zimmermann also warned against focusing on a narrow idea of democracy as a “preference satisfaction” system for finding the most popular policies.“Democracy isn’t just about winning, about getting whatever policy you like best implemented – it’s about creating processes during which citizens can encounter each other and deliberate with each other as equals,” says Zimmermann.The DeepMind researchers do raise concerns about an AI-powered “tyranny of the majority” situation in which the needs of people in minority groups are overlooked. But that isn’t a huge worry among political scientists, says Mathias Risse at Harvard University. He says modern democracies face a bigger problem of “the many” becoming disenfranchised by the small minority of the economic elite, and dropping out of the political process altogether.Still, Risse says the DeepMind research is “fascinating” in how it delivered a version of the liberal egalitarianism policy. “Since I’m in the liberal-egalitarian camp anyway, I find that a rather satisfactory result,” he says.
Zimmermann also warned against focusing on a narrow idea of democracy as a “preference satisfaction” system for finding the most popular policies.
A game was played at several informal United Nations social gatherings in the 1960s. People entering the room were given four playing cards and told that they could trade them with anyone else in the room. No rules, no advice. But the cards weren't distributed randomly. In every case, the guys who were given four picture cards ended up holding all the cards.
Consciousness plays a central role in identifying the universal terminal goal.
Peter Tse - What Makes Brains Conscious?Everything we know, think and feel—everything!—comes from our brains. But consciousness, our private sense of inner awareness, remains a mystery. Brain activities—spiking of neuronal impulses, sloshing of neurochemicals—are not at all the same thing as sights, sounds, smells, emotions. How on earth can our inner experiences be explained in physical terms?
Peter Tse - Why a Mind-Body Problem?How does the brain produce the mind? This is one of the most difficult problems in science, because how can physical qualities, no matter how complex and sophisticated, actually be mental experiences? Electrical impulses and chemical flows are not at all the kind of stuff that thoughts and feelings are. The physical and the mental are different categories.
The word terminal in the term universal terminal goal emphasizes time dimension over space and the others. It's better to have a finite number of conscious entities for infinite time rather than infinite number of conscious entities for a finite amount of time.
This short video covers the key points of Chapter One "The Lesson" from Henry Hazlitt's "Economics in One Lesson." Good economic policy analysis means assessing a policy's impacts on all groups in the long run, rather than the impacts on some in the short run. Produced by Access Communications in collaboration with the Frontier Centre for Public Policy.
Exploring the Deep Mystery of Life's OriginsAs an evolutionary biochemist at University College London, Nick Lane explores the deep mystery of how life evolved on Earth. His hypothesis that life arose through primitive metabolic reactions in deep-sea hydrothermal vents illuminates the outsized role that energy may have played in shaping evolution.
Longtermism is the idea that because humanity's future is potentially vast in size, we could have a massive altruistic impact by positively influencing it. In this video, we illustrate the papers "The Case for Strong Longtermism" by Hilary Greaves and William MacAskill and "Astronomical Waste: The Opportunity Cost of Delayed Technological Development" by Nick Bostrom (links below). We'll examine two main ways in which we might most positively influence the far future: accelerating technological development and reducing existential risk, which is the risk of human extinction and of catastrophes so large that would curtail humanity's potential forever. Advancing technological progress and preventing existential risk look much more compelling under a totalist view of population ethics, but they still look extremely important even under a person-affecting view.
In his new book about longtermism, What We Owe the Future, the philosopher William MacAskill argues that concern for the long-term future should be a key moral priority of our time. There are three central claims that justify this view. 1. Future people matter. 2. There could be a lot of them. 3. We can make their lives go better. In this video, we focus on the third claim. We've had the opportunity to read What We Owe the Future in advance thanks to the Forethought Foundation. They reached out asking if we could make a video on the occasion of the book launch. We were happy to collaborate, to help spread the ideas of the longtermist philosophy as far as possible
Here is a sequel.Can we make the future a million years from now go better?QuoteIn his new book about longtermism, What We Owe the Future, the philosopher William MacAskill argues that concern for the long-term future should be a key moral priority of our time. There are three central claims that justify this view. 1. Future people matter. 2. There could be a lot of them. 3. We can make their lives go better. In this video, we focus on the third claim. We've had the opportunity to read What We Owe the Future in advance thanks to the Forethought Foundation. They reached out asking if we could make a video on the occasion of the book launch. We were happy to collaborate, to help spread the ideas of the longtermist philosophy as far as possible My concern here, is the word "people" in the first central claim can be interpreted more broadly to make it more universal, to include various possible forms of consciousness in the future, not confined by what we already know from the past.