#artificial intelligence thesis topics

[keferon]

This is such a complex and nuanced topic that I can’t stop thinking now about artificial intelligence, personhood, and what it means to be alive. Because golem!Prowl actually seems to exist somewhere in the intersection of those ideas.

Certainly Prowl does not have a soul. And yet, where other golems depicted in mimic au seem to operate primarily as rule-based entities given a set of predefined orders that define their function, Prowl is able to go a step further — learning and defining his own rules based on observation and experience. Arguably, Prowl is even more advanced in this regard than real-world AI agents we might interact with such as ChatGPT (which still requires humans to tell it: when to update it’s knowledge, what data to use, and what that data means) currently are. Because Prowl formulates knowledge not just from a distillation and concentration of the most prominent and commonly accepted ideas that have come before.

He shows this when he rejects all the views that society accepts — resulting in the formulation of the idea that Primus must be wrong. And in a lot of ways, Prowl’s learning that gets him to ultimately reach that conclusion seems a lot more closely related to how we learn. He learns from observing the actions of those around him, from listening to what the people closest to him say and from experiencing things for himself. And this also shows in the beginnings of his interaction with Jazz. Prowl may know things like friendship as abstract concepts, but he only can truly come to define what they mean because he is experiencing them.

In some ways then, what seems to make Prowl much more advanced in his intelligence is that the conclusions he ultimately draws — the way he updates his understanding of the world to fit the framework he’s been given — is something he does independently. And this is what sets him apart.

So is he a person? Given his lack of soul or spark perhaps not. But then again, what truly defines humanity, for lack of a better word? Because perhaps there is not a clear and distinct line to tell when mimicry and close approximation crosses over to become the real thing.

But given the way that Prowl learns and interacts with the world around him, it does not seem too far-fetched to say that he is alive. And further, that he seems a fairly unique form of life within this continuity. Therefore, is he not his own individual? In much the same way that the others this society deems beasts and monsters because of their unique abilities are also individuals.

It’s just really interesting to think about.

(But I will stop myself there, because I did not initially think this would get as long as it did and I feel like I’ve already written an entire thesis in an ask at this point!)

DAMN That’s a really really interesting essay you got here👁

If we take an artificially created algorithm based on seek a goal -> complete the goal but then give it learning capability of a real person. At what point it’s gonna just become one? And if it gains the ability to have emotions. Could they be considered “real” if it’s processing them in it’s own way completely unknown to us?

I love making stories that force me to question the entire life hahdkj

[fipindustries]

Artificial Intelligence Risk

about a month ago i got into my mind the idea of trying the format of video essay, and the topic i came up with that i felt i could more or less handle was AI risk and my objections to yudkowsky. i wrote the script but then soon afterwards i ran out of motivation to do the video. still i didnt want the effort to go to waste so i decided to share the text, slightly edited here. this is a LONG fucking thing so put it aside on its own tab and come back to it when you are comfortable and ready to sink your teeth on quite a lot of reading

Anyway, let’s talk about AI risk

I’m going to be doing a very quick introduction to some of the latest conversations that have been going on in the field of artificial intelligence, what are artificial intelligences exactly, what is an AGI, what is an agent, the orthogonality thesis, the concept of instrumental convergence, alignment and how does Eliezer Yudkowsky figure in all of this.

 If you are already familiar with this you can skip to section two where I’m going to be talking about yudkowsky’s arguments for AI research presenting an existential risk to, not just humanity, or even the world, but to the entire universe and my own tepid rebuttal to his argument.

Now, I SHOULD clarify, I am not an expert on the field, my credentials are dubious at best, I am a college drop out from the career of computer science and I have a three year graduate degree in video game design and a three year graduate degree in electromechanical instalations. All that I know about the current state of AI research I have learned by reading articles, consulting a few friends who have studied about the topic more extensevily than me,

and watching educational you tube videos so. You know. Not an authority on the matter from any considerable point of view and my opinions should be regarded as such.

So without further ado, let’s get in on it.

PART ONE, A RUSHED INTRODUCTION ON THE SUBJECT

1.1 general intelligence and agency

lets begin with what counts as artificial intelligence, the technical definition for artificial intelligence is, eh…, well, why don’t I let a Masters degree in machine intelligence explain it:

 Now let’s get a bit more precise here and include the definition of AGI, Artificial General intelligence. It is understood that classic ai’s such as the ones we have in our videogames or in alpha GO or even our roombas, are narrow Ais, that is to say, they are capable of doing only one kind of thing. They do not understand the world beyond their field of expertise whether that be within a videogame level, within a GO board or within you filthy disgusting floor.

AGI on the other hand is much more, well, general, it can have a multimodal understanding of its surroundings, it can generalize, it can extrapolate, it can learn new things across multiple different fields, it can come up with solutions that account for multiple different factors, it can incorporate new ideas and concepts. Essentially, a human is an agi. So far that is the last frontier of AI research, and although we are not there quite yet, it does seem like we are doing some moderate strides in that direction. We’ve all seen the impressive conversational and coding skills that GPT-4 has and Google just released Gemini, a multimodal AI that can understand and generate text, sounds, images and video simultaneously. Now, of course it has its limits, it has no persistent memory, its contextual window while larger than previous models is still relatively small compared to a human (contextual window means essentially short term memory, how many things can it keep track of and act coherently about).

And yet there is one more factor I haven’t mentioned yet that would be needed to make something a “true” AGI. That is Agency. To have goals and autonomously come up with plans and carry those plans out in the world to achieve those goals. I as a person, have agency over my life, because I can choose at any given moment to do something without anyone explicitly telling me to do it, and I can decide how to do it. That is what computers, and machines to a larger extent, don’t have. Volition.

So, Now that we have established that, allow me to introduce yet one more definition here, one that you may disagree with but which I need to establish in order to have a common language with you such that I can communicate these ideas effectively. The definition of intelligence. It’s a thorny subject and people get very particular with that word because there are moral associations with it. To imply that someone or something has or hasn’t intelligence can be seen as implying that it deserves or doesn’t deserve admiration, validity, moral worth or even  personhood. I don’t care about any of that dumb shit. The way Im going to be using intelligence in this video is basically “how capable you are to do many different things successfully”. The more “intelligent” an AI is, the more capable of doing things that AI can be. After all, there is a reason why education is considered such a universally good thing in society. To educate a child is to uplift them, to expand their world, to increase their opportunities in life. And the same goes for AI. I need to emphasize that this is just the way I’m using the word within the context of this video, I don’t care if you are a psychologist or a neurosurgeon, or a pedagogue, I need a word to express this idea and that is the word im going to use, if you don’t like it or if you think this is innapropiate of me then by all means, keep on thinking that, go on and comment about it below the video, and then go on to suck my dick.

Anyway. Now, we have established what an AGI is, we have established what agency is, and we have established how having more intelligence increases your agency. But as the intelligence of a given agent increases we start to see certain trends, certain strategies start to arise again and again, and we call this Instrumental convergence.

1.2 instrumental convergence

The basic idea behind instrumental convergence is that if you are an intelligent agent that wants to achieve some goal, there are some common basic strategies that you are going to turn towards no matter what. It doesn’t matter if your goal is as complicated as building a nuclear bomb or as simple as making a cup of tea. These are things we can reliably predict any AGI worth its salt is going to try to do.

First of all is self-preservation. Its going to try to protect itself. When you want to do something, being dead is usually. Bad. its counterproductive. Is not generally recommended. Dying is widely considered unadvisable by 9 out of every ten experts in the field. If there is something that it wants getting done, it wont get done if it dies or is turned off, so its safe to predict that any AGI will try to do things in order not be turned off. How far it may go in order to do this? Well… [wouldn’t you like to know weather boy].

Another thing it will predictably converge towards is goal preservation. That is to say, it will resist any attempt to try and change it, to alter it, to modify its goals. Because, again, if you want to accomplish something, suddenly deciding that you want to do something else is uh, not going to accomplish the first thing, is it? Lets say that you want to take care of your child, that is your goal, that is the thing you want to accomplish, and I come to you and say, here, let me change you on the inside so that you don’t care about protecting your kid. Obviously you are not going to let me, because if you stopped caring about your kids, then your kids wouldn’t be cared for or protected. And you want to ensure that happens, so caring about something else instead is a huge no-no- which is why, if we make AGI and it has goals that we don’t like it will probably resist any attempt to “fix” it.

And finally another goal that it will most likely trend towards is self improvement. Which can be more generalized to “resource acquisition”. If it lacks capacities to carry out a plan, then step one of that plan will always be to increase capacities. If you want to get something really expensive, well first you need to get money. If you want to increase your chances of getting a high paying job then you need to get education, if you want to get a partner you need to increase how attractive you are. And as we established earlier, if intelligence is the thing that increases your agency, you want to become smarter in order to do more things. So one more time, is not a huge leap at all, it is not a stretch of the imagination, to say that any AGI will probably seek to increase its capabilities, whether by acquiring more computation, by improving itself, by taking control of resources.

All these three things I mentioned are sure bets, they are likely to happen and safe to assume. They are things we ought to keep in mind when creating AGI.

 Now of course, I have implied a sinister tone to all these things, I have made all this sound vaguely threatening, haven’t i?. There is one more assumption im sneaking into all of this which I haven’t talked about. All that I have mentioned presents a very callous view of AGI, I have made it apparent that all of these strategies it may follow will go in conflict with people, maybe even go as far as to harm humans. Am I impliying that AGI may tend to be… Evil???

1.3 The Orthogonality thesis

Well, not quite.

We humans care about things. Generally. And we generally tend to care about roughly the same things, simply by virtue of being humans. We have some innate preferences and some innate dislikes. We have a tendency to not like suffering (please keep in mind I said a tendency, im talking about a statistical trend, something that most humans present to some degree). Most of us, baring social conditioning, would take pause at the idea of torturing someone directly, on purpose, with our bare hands. (edit bear paws onto my hands as I say this).  Most would feel uncomfortable at the thought of doing it to multitudes of people. We tend to show a preference for food, water, air, shelter, comfort, entertainment and companionship. This is just how we are fundamentally wired. These things can be overcome, of course, but that is the thing, they have to be overcome in the first place.

An AGI is not going to have the same evolutionary predisposition to these things like we do because it is not made of the same things a human is made of and it was not raised the same way a human was raised.

There is something about a human brain, in a human body, flooded with human hormones that makes us feel and think and act in certain ways and care about certain things.

All an AGI is going to have is the goals it developed during its training, and will only care insofar as those goals are met. So say an AGI has the goal of going to the corner store to bring me a pack of cookies. In its way there it comes across an anthill in its path, it will probably step on the anthill because to take that step takes it closer to the corner store, and why wouldn’t it step on the anthill? Was it programmed with some specific innate preference not to step on ants? No? then it will step on the anthill and not pay any mind  to it.

Now lets say it comes across a cat. Same logic applies, if it wasn’t programmed with an inherent tendency to value animals, stepping on the cat wont slow it down at all.

Now let’s say it comes across a baby.

Of course, if its intelligent enough it will probably understand that if it steps on that baby people might notice and try to stop it, most likely even try to disable it or turn it off so it will not step on the baby, to save itself from all that trouble. But you have to understand that it wont stop because it will feel bad about harming a baby or because it understands that to harm a baby is wrong. And indeed if it was powerful enough such that no matter what people did they could not stop it and it would suffer no consequence for killing the baby, it would have probably killed the baby.

If I need to put it in gross, inaccurate terms for you to get it then let me put it this way. Its essentially a sociopath. It only cares about the wellbeing of others in as far as that benefits it self. Except human sociopaths do care nominally about having human comforts and companionship, albeit in a very instrumental way, which will involve some manner of stable society and civilization around them. Also they are only human, and are limited in the harm they can do by human limitations.  An AGI doesn’t need any of that and is not limited by any of that.

So ultimately, much like a car’s goal is to move forward and it is not built to care about wether a human is in front of it or not, an AGI will carry its own goals regardless of what it has to sacrifice in order to carry that goal effectively. And those goals don’t need to include human wellbeing.

Now With that said. How DO we make it so that AGI cares about human wellbeing, how do we make it so that it wants good things for us. How do we make it so that its goals align with that of humans?

1.4 Alignment.

Alignment… is hard [cue hitchhiker’s guide to the galaxy scene about the space being big]

This is the part im going to skip over the fastest because frankly it’s a deep field of study, there are many current strategies for aligning AGI, from mesa optimizers, to reinforced learning with human feedback, to adversarial asynchronous AI assisted reward training to uh, sitting on our asses and doing nothing. Suffice to say, none of these methods are perfect or foolproof.

One thing many people like to gesture at when they have not learned or studied anything about the subject is the three laws of robotics by isaac Asimov, a robot should not harm a human or allow by inaction to let a human come to harm, a robot should do what a human orders unless it contradicts the first law and a robot should preserve itself unless that goes against the previous two laws. Now the thing Asimov was prescient about was that these laws were not just “programmed” into the robots. These laws were not coded into their software, they were hardwired, they were part of the robot’s electronic architecture such that a robot could not ever be without those three laws much like a car couldn’t run without wheels.

In this Asimov realized how important these three laws were, that they had to be intrinsic to the robot’s very being, they couldn’t be hacked or uninstalled or erased. A robot simply could not be without these rules. Ideally that is what alignment should be. When we create an AGI, it should be made such that human values are its fundamental goal, that is the thing they should seek to maximize, instead of instrumental values, that is to say something they value simply because it allows it to achieve something else.

But how do we even begin to do that? How do we codify “human values” into a robot? How do we define “harm” for example? How do we even define “human”??? how do we define “happiness”? how do we explain a robot what is right and what is wrong when half the time we ourselves cannot even begin to agree on that? these are not just technical questions that robotic experts have to find the way to codify into ones and zeroes, these are profound philosophical questions to which we still don’t have satisfying answers to.

Well, the best sort of hack solution we’ve come up with so far is not to create bespoke fundamental axiomatic rules that the robot has to follow, but rather train it to imitate humans by showing it a billion billion examples of human behavior. But of course there is a problem with that approach. And no, is not just that humans are flawed and have a tendency to cause harm and therefore to ask a robot to imitate a human means creating something that can do all the bad things a human does, although that IS a problem too. The real problem is that we are training it to *imitate* a human, not  to *be* a human.

To reiterate what I said during the orthogonality thesis, is not good enough that I, for example, buy roses and give massages to act nice to my girlfriend because it allows me to have sex with her, I am not merely imitating or performing the rol of a loving partner because her happiness is an instrumental value to my fundamental value of getting sex. I should want to be nice to my girlfriend because it makes her happy and that is the thing I care about. Her happiness is  my fundamental value. Likewise, to an AGI, human fulfilment should be its fundamental value, not something that it learns to do because it allows it to achieve a certain reward that we give during training. Because if it only really cares deep down about the reward, rather than about what the reward is meant to incentivize, then that reward can very easily be divorced from human happiness.

Its goodharts law, when a measure becomes a target, it ceases to be a good measure. Why do students cheat during tests? Because their education is measured by grades, so the grades become the target and so students will seek to get high grades regardless of whether they learned or not. When trained on their subject and measured by grades, what they learn is not the school subject, they learn to get high grades, they learn to cheat.

This is also something known in psychology, punishment tends to be a poor mechanism of enforcing behavior because all it teaches people is how to avoid the punishment, it teaches people not to get caught. Which is why punitive justice doesn’t work all that well in stopping recividism and this is why the carceral system is rotten to core and why jail should be fucking abolish-[interrupt the transmission]

Now, how is this all relevant to current AI research? Well, the thing is, we ended up going about the worst possible way to create alignable AI.

1.5 LLMs (large language models)

This is getting way too fucking long So, hurrying up, lets do a quick review of how do Large language models work. We create a neural network which is a collection of giant matrixes, essentially a bunch of numbers that we add and multiply together over and over again, and then we tune those numbers by throwing absurdly big amounts of training data such that it starts forming internal mathematical models based on that data and it starts creating coherent patterns that it can recognize and replicate AND extrapolate! if we do this enough times with matrixes that are big enough and then when we start prodding it for human behavior it will be able to follow the pattern of human behavior that we prime it with and give us coherent responses.

(takes a big breath)this “thing” has learned. To imitate. Human. Behavior.

Problem is, we don’t know what “this thing” actually is, we just know that *it* can imitate humans.

You caught that?

What you have to understand is, we don’t actually know what internal models it creates, we don’t know what are the patterns that it extracted or internalized from the data that we fed it, we don’t know what are the internal rules that decide its behavior, we don’t know what is going on inside there, current LLMs are a black box. We don’t know what it learned, we don’t know what its fundamental values are, we don’t know how it thinks or what it truly wants. all we know is that it can imitate humans when we ask it to do so. We created some inhuman entity that is moderatly intelligent in specific contexts (that is to say, very capable) and we trained it to imitate humans. That sounds a bit unnerving doesn’t it?

 To be clear, LLMs are not carefully crafted piece by piece. This does not work like traditional software where a programmer will sit down and build the thing line by line, all its behaviors specified. Is more accurate to say that LLMs, are grown, almost organically. We know the process that generates them, but we don’t know exactly what it generates or how what it generates works internally, it is a mistery. And these things are so big and so complicated internally that to try and go inside and decipher what they are doing is almost intractable.

But, on the bright side, we are trying to tract it. There is a big subfield of AI research called interpretability, which is actually doing the hard work of going inside and figuring out how the sausage gets made, and they have been doing some moderate progress as of lately. Which is encouraging. But still, understanding the enemy is only step one, step two is coming up with an actually effective and reliable way of turning that potential enemy into a friend.

Puff! Ok so, now that this is all out of the way I can go onto the last subject before I move on to part two of this video, the character of the hour, the man the myth the legend. The modern day Casandra. Mr chicken little himself! Sci fi author extraordinaire! The mad man! The futurist! The leader of the rationalist movement!

1.5 Yudkowsky

Eliezer S. Yudkowsky  born September 11, 1979, wait, what the fuck, September eleven? (looks at camera) yudkowsky was born on 9/11, I literally just learned this for the first time! What the fuck, oh that sucks, oh no, oh no, my condolences, that’s terrible…. Moving on. he is an American artificial intelligence researcher and writer on decision theory and ethics, best known for popularizing ideas related to friendly artificial intelligence, including the idea that there might not be a "fire alarm" for AI He is the founder of and a research fellow at the Machine Intelligence Research Institute (MIRI), a private research nonprofit based in Berkeley, California. Or so says his Wikipedia page.

Yudkowsky is, shall we say, a character. a very eccentric man, he is an AI doomer. Convinced that AGI, once finally created, will most likely kill all humans, extract all valuable resources from the planet, disassemble the solar system, create a dyson sphere around the sun and expand across the universe turning all of the cosmos into paperclips. Wait, no, that is not quite it, to properly quote,( grabs a piece of paper and very pointedly reads from it) turn the cosmos into tiny squiggly  molecules resembling paperclips whose configuration just so happens to fulfill the strange, alien unfathomable terminal goal they ended up developing in training. So you know, something totally different.

And he is utterly convinced of this idea, has been for over a decade now, not only that but, while he cannot pinpoint a precise date, he is confident that, more likely than not it will happen within this century. In fact most betting markets seem to believe that we will get AGI somewhere in the mid 30’s.

His argument is basically that in the field of AI research, the development of capabilities is going much faster than the development of alignment, so that AIs will become disproportionately powerful before we ever figure out how to control them. And once we create unaligned AGI we will have created an agent who doesn’t care about humans but will care about something else entirely irrelevant to us and it will seek to maximize that goal, and because it will be vastly more intelligent than humans therefore we wont be able to stop it. In fact not only we wont be able to stop it, there wont be a fight at all. It will carry out its plans for world domination in secret without us even detecting it and it will execute it before any of us even realize what happened. Because that is what a smart person trying to take over the world would do.

This is why the definition I gave of intelligence at the beginning is so important, it all hinges on that, intelligence as the measure of how capable you are to come up with solutions to problems, problems such as “how to kill all humans without being detected or stopped”. And you may say well now, intelligence is fine and all but there are limits to what you can accomplish with raw intelligence, even if you are supposedly smarter than a human surely you wouldn’t be capable of just taking over the world uninmpeeded, intelligence is not this end all be all superpower. Yudkowsky would respond that you are not recognizing or respecting the power that intelligence has. After all it was intelligence what designed the atom bomb, it was intelligence what created a cure for polio and it was intelligence what made it so that there is a human foot print on the moon.

Some may call this view of intelligence a bit reductive. After all surely it wasn’t *just* intelligence what did all that but also hard physical labor and the collaboration of hundreds of thousands of people. But, he would argue, intelligence was the underlying motor that moved all that. That to come up with the plan and to convince people to follow it and to delegate the tasks to the appropriate subagents, it was all directed by thought, by ideas, by intelligence. By the way, so far I am not agreeing or disagreeing with any of this, I am merely explaining his ideas.

But remember, it doesn’t stop there, like I said during his intro, he believes there will be “no fire alarm”. In fact for all we know, maybe AGI has already been created and its merely bidding its time and plotting in the background, trying to get more compute, trying to get smarter. (to be fair, he doesn’t think this is right now, but with the next iteration of gpt? Gpt 5 or 6? Well who knows). He thinks that the entire world should halt AI research and punish with multilateral international treaties any group or nation that doesn’t stop. going as far as putting military attacks on GPU farms as sanctions of those treaties.

What’s more, he believes that, in fact, the fight is already lost. AI is already progressing too fast and there is nothing to stop it, we are not showing any signs of making headway with alignment and no one is incentivized to slow down. Recently he wrote an article called “dying with dignity” where he essentially says all this, AGI will destroy us, there is no point in planning for the future or having children and that we should act as if we are already dead. This doesn’t mean to stop fighting or to stop trying to find ways to align AGI, impossible as it may seem, but to merely have the basic dignity of acknowledging that we are probably not going to win. In every interview ive seen with the guy he sounds fairly defeatist and honestly kind of depressed. He truly seems to think its hopeless, if not because the AGI is clearly unbeatable and superior to humans, then because humans are clearly so stupid that we keep developing AI completely unregulated while making the tools to develop AI widely available and public for anyone to grab and do as they please with, as well as connecting every AI to the internet and to all mobile devices giving it instant access to humanity. and  worst of all: we keep teaching it how to code. From his perspective it really seems like people are in a rush to create the most unsecured, wildly available, unrestricted, capable, hyperconnected AGI possible.

We are not just going to summon the antichrist, we are going to receive them with a red carpet and immediately hand it the keys to the kingdom before it even manages to fully get out of its fiery pit.

So. The situation seems dire, at least to this guy. Now, to be clear, only he and a handful of other AI researchers are on that specific level of alarm. The opinions vary across the field and from what I understand this level of hopelessness and defeatism is the minority opinion.

I WILL say, however what is NOT the minority opinion is that AGI IS actually dangerous, maybe not quite on the level of immediate, inevitable and total human extinction but certainly a genuine threat that has to be taken seriously. AGI being something dangerous if unaligned is not a fringe position and I would not consider it something to be dismissed as an idea that experts don’t take seriously.

Aaand here is where I step up and clarify that this is my position as well. I am also, very much, a believer that AGI would posit a colossal danger to humanity. That yes, an unaligned AGI would represent an agent smarter than a human, capable of causing vast harm to humanity and with no human qualms or limitations to do so. I believe this is not just possible but probable and likely to happen within our lifetimes.

So there. I made my position clear.

BUT!

With all that said. I do have one key disagreement with yudkowsky. And partially the reason why I made this video was so that I could present this counterargument and maybe he, or someone that thinks like him, will see it and either change their mind or present a counter-counterargument that changes MY mind (although I really hope they don’t, that would be really depressing.)

Finally, we can move on to part 2

PART TWO- MY COUNTERARGUMENT TO YUDKOWSKY

I really have my work cut out for me, don’t i? as I said I am not expert and this dude has probably spent far more time than me thinking about this. But I have seen most interviews that guy has been doing for a year, I have seen most of his debates and I have followed him on twitter for years now. (also, to be clear, I AM a fan of the guy, I have read hpmor, three worlds collide, the dark lords answer, a girl intercorrupted, the sequences, and I TRIED to read planecrash, that last one didn’t work out so well for me). My point is in all the material I have seen of Eliezer I don’t recall anyone ever giving him quite this specific argument I’m about to give.

It’s a limited argument. as I have already stated I largely agree with most of what he says, I DO believe that unaligned AGI is possible, I DO believe it would be really dangerous if it were to exist and I do believe alignment is really hard. My key disagreement is specifically about his point I descrived earlier, about the lack of a fire alarm, and perhaps, more to the point, to humanity’s lack of response to such an alarm if it were to come to pass.

All we would need, is a Chernobyl incident, what is that? A situation where this technology goes out of control and causes a lot of damage, of potentially catastrophic consequences, but not so bad that it cannot be contained in time by enough effort. We need a weaker form of AGI to try to harm us, maybe even present a believable threat of taking over the world, but not so smart that humans cant do anything about it. We need essentially an AI vaccine, so that we can finally start developing proper AI antibodies. “aintibodies”

In the past humanity was dazzled by the limitless potential of nuclear power, to the point that old chemistry sets, the kind that were sold to children, would come with uranium for them to play with. We were building atom bombs, nuclear stations, the future was very much based on the power of the atom. But after a couple of really close calls and big enough scares we became, as a species, terrified of nuclear power. Some may argue to the point of overcorrection. We became scared enough that even megalomaniacal hawkish leaders were able to take pause and reconsider using it as a weapon, we became so scared that we overregulated the technology to the point of it almost becoming economically inviable to apply, we started disassembling nuclear stations across the world and to slowly reduce our nuclear arsenal.

This is all a proof of concept that, no matter how alluring a technology may be, if we are scared enough of it we can coordinate as a species and roll it back, to do our best to put the genie back in the bottle. One of the things eliezer says over and over again is that what makes AGI different from other technologies is that if we get it wrong on the first try we don’t get a second chance. Here is where I think he is wrong: I think if we get AGI wrong on the first try, it is more likely than not that nothing world ending will happen. Perhaps it will be something scary, perhaps something really scary, but unlikely that it will be on the level of all humans dropping dead simultaneously due to diamonoid bacteria. And THAT will be our Chernobyl, that will be the fire alarm, that will be the red flag that the disaster monkeys, as he call us, wont be able to ignore.

Now WHY do I think this? Based on what am I saying this? I will not be as hyperbolic as other yudkowsky detractors and say that he claims AGI will be basically a god. The AGI yudkowsky proposes is not a god. Just a really advanced alien, maybe even a wizard, but certainly not a god.

Still, even if not quite on the level of godhood, this dangerous superintelligent AGI yudkowsky proposes would be impressive. It would be the most advanced and powerful entity on planet earth. It would be humanity’s greatest achievement.

It would also be, I imagine, really hard to create. Even leaving aside the alignment bussines, to create a powerful superintelligent AGI without flaws, without bugs, without glitches, It would have to be an incredibly complex, specific, particular and hard to get right feat of software engineering. We are not just talking about an AGI smarter than a human, that’s easy stuff, humans are not that smart and arguably current AI is already smarter than a human, at least within their context window and until they start hallucinating. But what we are talking about here is an AGI capable of outsmarting reality.

We are talking about an AGI smart enough to carry out complex, multistep plans, in which they are not going to be in control of every factor and variable, specially at the beginning. We are talking about AGI that will have to function in the outside world, crashing with outside logistics and sheer dumb chance. We are talking about plans for world domination with no unforeseen factors, no unexpected delays or mistakes, every single possible setback and hidden variable accounted for. Im not saying that an AGI capable of doing this wont be possible maybe some day, im saying that to create an AGI that is capable of doing this, on the first try, without a hitch, is probably really really really hard for humans to do. Im saying there are probably not a lot of worlds where humans fiddling with giant inscrutable matrixes stumble upon the right precise set of layers and weight and biases that give rise to the Doctor from doctor who, and there are probably a whole truckload of worlds where humans end up with a lot of incoherent nonsense and rubbish.

Im saying that AGI, when it fails, when humans screw it up, doesn’t suddenly become more powerful than we ever expected, its more likely that it just fails and collapses. To turn one of Eliezer’s examples against him, when you screw up a rocket, it doesn’t accidentally punch a worm hole in the fabric of time and space, it just explodes before reaching the stratosphere. When you screw up a nuclear bomb, you don’t get to blow up the solar system, you just get a less powerful bomb.

He presents a fully aligned AGI as this big challenge that humanity has to get right on the first try, but that seems to imply that building an unaligned AGI is just a simple matter, almost taken for granted. It may be comparatively easier than an aligned AGI, but my point is that already unaligned AGI is stupidly hard to do and that if you fail in building unaligned AGI, then you don’t get an unaligned AGI, you just get another stupid model that screws up and stumbles on itself the second it encounters something unexpected. And that is a good thing I’d say! That means that there is SOME safety margin, some space to screw up before we need to really start worrying. And further more, what I am saying is that our first earnest attempt at an unaligned AGI will probably not be that smart or impressive because we as humans would have probably screwed something up, we would have probably unintentionally programmed it with some stupid glitch or bug or flaw and wont be a threat to all of humanity.

Now here comes the hypothetical back and forth, because im not stupid and I can try to anticipate what Yudkowsky might argue back and try to answer that before he says it (although I believe the guy is probably smarter than me and if I follow his logic, I probably cant actually anticipate what he would argue to prove me wrong, much like I cant predict what moves Magnus Carlsen would make in a game of chess against me, I SHOULD predict that him proving me wrong is the likeliest option, even if I cant picture how he will do it, but you see, I believe in a little thing called debating with dignity, wink)

What I anticipate he would argue is that AGI, no matter how flawed and shoddy our first attempt at making it were, would understand that is not smart enough yet and try to become smarter, so it would lie and pretend to be an aligned AGI so that it can trick us into giving it access to more compute or just so that it can bid its time and create an AGI smarter than itself. So even if we don’t create a perfect unaligned AGI, this imperfect AGI would try to create it and succeed, and then THAT new AGI would be the world ender to worry about.

So two things to that, first, this is filled with a lot of assumptions which I don’t know the likelihood of. The idea that this first flawed AGI would be smart enough to understand its limitations, smart enough to convincingly lie about it and smart enough to create an AGI that is better than itself. My priors about all these things are dubious at best. Second, It feels like kicking the can down the road. I don’t think creating an AGI capable of all of this is trivial to make on a first attempt. I think its more likely that we will create an unaligned AGI that is flawed, that is kind of dumb, that is unreliable, even to itself and its own twisted, orthogonal goals.

And I think this flawed creature MIGHT attempt something, maybe something genuenly threatning, but it wont be smart enough to pull it off effortlessly and flawlessly, because us humans are not smart enough to create something that can do that on the first try. And THAT first flawed attempt, that warning shot, THAT will be our fire alarm, that will be our Chernobyl. And THAT will be the thing that opens the door to us disaster monkeys finally getting our shit together.

But hey, maybe yudkowsky wouldn’t argue that, maybe he would come with some better, more insightful response I cant anticipate. If so, im waiting eagerly (although not TOO eagerly) for it.

Part 3 CONCLUSSION

So.

After all that, what is there left to say? Well, if everything that I said checks out then there is hope to be had. My two objectives here were first to provide people who are not familiar with the subject with a starting point as well as with the basic arguments supporting the concept of AI risk, why its something to be taken seriously and not just high faluting wackos who read one too many sci fi stories. This was not meant to be thorough or deep, just a quick catch up with the bear minimum so that, if you are curious and want to go deeper into the subject, you know where to start. I personally recommend watching rob miles’ AI risk series on youtube as well as reading the series of books written by yudkowsky known as the sequences, which can be found on the website lesswrong. If you want other refutations of yudkowsky’s argument you can search for paul christiano or robin hanson, both very smart people who had very smart debates on the subject against eliezer.

The second purpose here was to provide an argument against Yudkowskys brand of doomerism both so that it can be accepted if proven right or properly refuted if proven wrong. Again, I really hope that its not proven wrong. It would really really suck if I end up being wrong about this. But, as a very smart person said once, what is true is already true, and knowing it doesn’t make it any worse. If the sky is blue I want to believe that the sky is blue, and if the sky is not blue then I don’t want to believe the sky is blue.

This has been a presentation by FIP industries, thanks for watching.

[ukdissertationhelper]

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[philosophiesde]

Zoomposium with Prof. Dr. Martin Bogdan: "When AI gets bored - Ways to (artificial) consciousness

Information about the person and research field

In this very exciting interview from our Zoomposium themed blog “Artificial intelligence and its consequences”, Axel and I talk this time with the German computer scientist Martin Bogdan, who conducts research on applied signal processing and data analysis in medicine and biology as well as embedded systems for bioanalog information processing at the Faculty of Mathematics and Computer Science in the Neuromorphic Information Processing Department at the University of Leipzig and works as Dean of Studies for Computer Science. It was precisely in this context that I became aware of him during my online research. I was looking for scientists, and in particular computer scientists, who work and research in the field of neuromorphic and bioanalog information processing. One reason for the research was that I have recently been dealing a lot with a possible paradigmshift from physics to biology in AI research. In this context, one could almost speak of a “biologization” in the development of new AIsystems. In this context of the possibilities of “communication” between biological-neuronal and artificial-neuronal networks, he has also worked a lot on new processor architectures. The old processor design for AI applications in the form of the functionalities of the hardware at circuit level (register transfer level synthesis) using “standard CMOS logic gates” is increasingly being replaced by artificial, neural networks “artificial neuronal network (ANN)” or “spiking neuronal networks (SNN)” in the course of “neuromorphic engineering” or “deeplearning (DL)” or perhaps replace them completely in the future. An attempt is made to translate the biological-neuronal networks of the brain into “spiking neuronal networks (SNN)” with the help of the Hodgkin-Huxley-Model. The action potentials of neurons and their connections are simulated as brain areas. Martin Bogdan also had another exciting but also provocative article on this topic, "Is Boredom an Indicator on the way to Singularity of Artificial Intelligence? Hypotheses as Thought-Provoking Impulse“ in 2023, in which he explores precisely this question of whether perhaps ”boredom“ in artificial intelligence could be a possible indicator for consciousness in the form of Kurzweil's ”Singularity". This is of course a “steep thesis”, which we had Mr. Bogdan explain to us in the not at all “boring” interview ;-). More at: https://youtu.be/izN9ac-9zw8

or: https://philosophies.de/index.php/2025/05/30/wenn-sich-ki-langweilt/

[tutorsindia152]

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[meganamy11]

The Ultimate Guide to Academic Writing Services: Why Students Need Them

Academic writing is an essential part of every student’s educational journey. Whether it’s writing essays, research papers, case studies, or dissertations, students must meet high academic standards. However, not everyone possesses strong writing skills, and time constraints often add to the struggle. This is where academic writing services come into play. These services offer professional assistance to students, helping them produce high-quality academic work.

In this blog, we will explore the significance of academic writing services, why students use them, and how they can improve academic performance.

Understanding Academic Writing Services

What Do These Services Offer?

Academic writing services provide students with professionally written essays, research papers, thesis papers, and other academic assignments. These services employ expert writers with extensive knowledge in various subjects, ensuring well-researched and well-structured papers.

Types of Academic Writing Assistance

Custom-written essays and research papers

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Why Students Use Academic Writing Services

Time Constraints and Deadlines

Many students struggle with managing their time effectively. With multiple assignments, exams, and extracurricular activities, meeting deadlines can become overwhelming. Assignment writing services help ease this burden by providing well-written assignments within the required timeframe.

Lack of Expertise in Academic Writing

Not all students are skilled in academic writing. Some struggle with structuring their papers correctly, using proper citations, or conducting in-depth research. Professional writing services help students meet academic expectations and improve their writing skills.

Language Barriers for Non-Native English Speakers

For international students, writing in English can be a challenge. Academic writing services help bridge this gap by providing well-articulated, grammatically correct papers.

How Academic Writing Services Improve Student Performance

High-Quality Research Papers and Essays

Students receive well-researched content, ensuring better grades and deeper subject knowledge.

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By reviewing professionally written papers, students learn how to format and structure their own assignments correctly.

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Exposure to well-written content helps students grasp complex topics and improve their analytical thinking skills.

How to Choose the Best Academic Writing Service

Checking Reviews and Ratings

Before selecting a service, students should check customer reviews and ratings to ensure reliability.

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A good writing service should offer reasonable pricing and a transparent refund policy.

Ensuring Timely Delivery and Support

Reliable services provide 24/7 customer support and guarantee on-time delivery.

Are Academic Writing Services Ethical?

Some argue that using writing services is unethical. However, students can use them responsibly by treating the papers as study guides and learning tools rather than submitting them as their own work.

Future Trends in Academic Writing Services

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With advancements in artificial intelligence, AI tools are now being integrated into writing services to enhance efficiency and accuracy.

Personalized Learning and Writing Support

Future services may focus on personalized assistance, helping students improve their writing skills through tailored feedback and tutorials.

Conclusion

Academic writing services have become an essential tool for students struggling with writing assignments. They provide professional assistance, ensuring high-quality work while helping students improve their writing skills. However, students must use these services ethically and responsibly. By choosing a reliable service, students can enhance their academic performance and gain a better understanding of academic writing.

[scholarshipme]

University of Twente, Netherlands PhD Scholarship 2025 in Geo-Artificial Intelligence

Study Grants for International Students Are you passionate about using artificial intelligence (AI) to tackle global environmental challenges? The University of Twente (UT), a leading university in the Netherlands, is offering an exciting PhD position in Geo-Artificial Intelligence for Mapping Vegetation Dynamics. Applications are open until March 5, 2025, providing a unique opportunity to contribute to cutting-edge research on climate change and environmental sustainability. This four-year PhD program is part of the EARTHONE Horizon Europe project, which focuses on developing innovative data-driven technologies to analyze vegetation seasonality and its response to climate change. By joining this project, you will play a key role in advancing solutions for environmental resilience. Degree Level The scholarship is available for PhD-level programs at the University of Twente. Available Subjects The PhD position focuses on the following fields: - Artificial Intelligence - Geography - Geo-Artificial Intelligence About the PhD Position The University of Twente is seeking a motivated PhD candidate with a Master’s degree (MSc) in geospatial sciences, computer science, environmental sciences, or a related field. The successful candidate will: - Develop and apply geo-artificial intelligence methods, including spatiotemporal machine learning techniques. - Study vegetation dynamics at regional and local scales. - Integrate climate simulations, remote sensing data, and ground observations to model the effects of extreme weather events and land-use changes on vegetation. Benefits of the Program Why Choose the University of Twente? The University of Twente is known for its High Tech Human Touch philosophy, combining advanced technology with a focus on societal impact. As a PhD candidate, you will benefit from: - A gross monthly salary ranging from €2,901 in the first year to €3,707 in the fourth year. - Additional financial benefits, including an 8% holiday allowance and an 8.3% year-end bonus. - A multidisciplinary and international academic environment with access to state-of-the-art research facilities. - A structured professional and personal development program through the Twente Graduate School. - A lively green campus with excellent working conditions and a supportive community. - Opportunities to collaborate with experts in climate modeling, forestry, soil science, and agronomy. Eligible Nationalities The scholarship is open to students of all nationalities. Eligibility Criteria To apply for this PhD position, you must meet the following requirements: - Academic Qualifications: - A Master’s degree (MSc) in geospatial sciences, computer science, environmental sciences, or a related field. - Technical Skills: - Strong programming skills (preferably in Python). - Experience with machine learning models and geospatial modeling. - Interdisciplinary Collaboration: - Ability to work in an interdisciplinary and internationally oriented environment. - Language Proficiency: - Excellent command of English. - Fluency in Dutch or willingness to learn is a plus. - Additional Skills: - Knowledge of climate change, ecology, or phenology is advantageous but not mandatory. Application Procedure To apply for this PhD position, submit the following documents before the March 5, 2025 deadline: - A motivation letter (one page maximum) explaining your interest in the topic and what you bring to the team. - A Curriculum Vitae (CV) (including academic grades, references, and publications if applicable). - A short research proposal (two pages maximum) outlining your ideas for phenological modeling within the EARTHONE project. - A brief description (250 words) of your most significant academic achievement (e.g., MSc thesis or final project). Interview Process: - First-round interviews are scheduled for March 19, 2025. - Second-round interviews may follow a week later. Conclusion This PhD position at the University of Twente offers a unique opportunity to work on a globally relevant project while developing advanced skills in geo-artificial intelligence and machine learning. With competitive financial benefits, a supportive academic environment, and the chance to contribute to climate resilience, this is an ideal opportunity for aspiring researchers. Don’t miss the deadline: Applications close on March 5, 2025. Start preparing your application today! For more information, visit the University of Twente’s official website. Read the full article

[csiprojectsblog]

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[phdthesisworld]

PhD Education Thesis Topics in Mumbai: Focus on Educational Technology

Educational technology has transformed the learning landscape in India, particularly in urban centers like Mumbai. As a hub of innovation and technological advancement, Mumbai presents unique opportunities and challenges for integrating technology into education. With the rapid pace of digital transformation, educational technology is reshaping the way teachers teach, students learn, and institutions deliver education.

For PhD candidates focusing on educational technology, selecting a relevant and impactful thesis topic is crucial. This article highlights potential PhD thesis topics related to educational technology in Mumbai, offering a variety of perspectives that align with both local and global trends.

1. Impact of Digital Learning Tools on Student Engagement in Mumbai’s Schools

One of the key areas of research in educational technology is how digital learning tools influence student engagement and learning outcomes. In Mumbai, many schools are adopting e-learning platforms, online assessments, and interactive digital content. This one of the leading PhD Education Thesis Topics in Mumbai could explore how these tools affect student motivation, participation, and academic performance.

Key Areas to Explore:

The effectiveness of online learning platforms like Moodle or Google Classroom in improving student engagement.

The role of gamification and interactive apps in increasing student motivation.

Comparative studies of digital and traditional learning methods in terms of student participation.

2. The Role of Artificial Intelligence in Personalized Learning in Mumbai’s Higher Education

Artificial Intelligence (AI) is increasingly being used to personalize the learning experience, particularly in higher education. In Mumbai, universities and colleges are adopting AI-driven tools to provide personalized learning paths, adapt content to individual learning styles, and improve student outcomes. A PhD thesis on this topic could focus on the implementation and challenges of AI in higher education institutions.

Key Areas to Explore:

How AI-powered platforms such as adaptive learning systems tailor content based on individual student performance.

The challenges of implementing AI in a large, diverse student population in Mumbai.

The impact of AI on student learning outcomes, particularly in STEM subjects.

3. Assessing the Effectiveness of Online Education in Mumbai’s Educational Institutions

The shift to online education during the COVID-19 pandemic has sparked debates on its effectiveness and sustainability. In Mumbai, many educational institutions have transitioned to online learning, and some have adopted hybrid learning models. This topic could evaluate the long-term effectiveness of online education in different educational settings.

Key Areas to Explore:

The impact of online learning on student academic performance and satisfaction in Mumbai’s schools and universities.

The challenges faced by teachers and students in adapting to online learning platforms.

Comparison of hybrid and traditional learning models in terms of academic outcomes and student engagement.

4. The Integration of Virtual Reality (VR) and Augmented Reality (AR) in Mumbai’s Classrooms

Virtual Reality (VR) and Augmented Reality (AR) technologies are becoming increasingly popular in educational settings, offering immersive and interactive learning experiences. This topic could explore how VR and AR are being integrated into the curriculum in Mumbai’s educational institutions, particularly in subjects such as science, history, and the arts.

Key Areas to Explore:

The use of VR/AR to create immersive learning environments that enhance understanding of complex concepts.

The challenges and opportunities of integrating VR/AR into Mumbai’s schools and colleges.

The potential of VR/AR to bridge the gap in experiential learning for students in Mumbai.

5. E-Assessment and Its Impact on Education Quality in Mumbai’s Schools

As educational technology advances, the use of digital assessments has become more widespread. E-assessments offer numerous advantages, such as immediate feedback and adaptive testing, but they also raise questions about their impact on educational quality. A PhD thesis on this topic could examine how e-assessments are implemented in Mumbai’s schools and their effect on student performance and learning outcomes.

Key Areas to Explore:

The advantages and challenges of e-assessment systems compared to traditional paper-based exams.

How e-assessment affects the quality of education, particularly in large, urban schools.

The role of digital exams in preparing students for real-world skills and competencies.

6. The Digital Divide in Mumbai’s Education System: Access and Equity in Educational Technology

While educational technology has the potential to revolutionize learning, access to technology is not equally distributed. In Mumbai, there is a significant digital divide, particularly in low-income neighborhoods. This one of the major PhD Education Thesis Topics in Mumbai could focus on understanding the barriers to accessing educational technology in different parts of the city and its implications for equitable education.

Key Areas to Explore:

The gap in access to digital devices and the internet in different socio-economic groups within Mumbai.

How the digital divide affects the educational outcomes of students from disadvantaged backgrounds.

Strategies to bridge the digital divide and ensure equal access to educational technology for all students in Mumbai.

7. The Role of EdTech Startups in Shaping Education in Mumbai

Mumbai is a thriving hub for technology startups, many of which are focused on education. EdTech startups are developing innovative solutions to address challenges in education, from e-learning platforms to digital tutoring services. This topic could investigate how EdTech startups are impacting the education sector in Mumbai and their role in shaping the future of learning.

Key Areas to Explore:

The role of EdTech startups in providing affordable, scalable educational solutions to Mumbai’s schools and colleges.

How startups are addressing issues such as student engagement, personalized learning, and teacher training.

The potential of EdTech startups to drive innovation and educational reform in Mumbai.

8. The Impact of Social Media and Online Communities on Learning in Mumbai’s Educational Institutions

Social media and online communities are increasingly being used as learning tools, enabling students and educators to collaborate, share resources, and participate in discussions outside of the classroom. A PhD thesis on this topic could explore how social media platforms like WhatsApp, Facebook, and YouTube are being used to enhance learning in Mumbai’s educational settings.

Key Areas to Explore:

The role of social media in facilitating peer-to-peer learning and collaborative projects in Mumbai’s universities.

How online communities, such as forums and discussion groups, influence student learning and knowledge sharing.

The impact of social media on student engagement, motivation, and academic success in Mumbai.

9. The Role of Mobile Learning in Enhancing Education in Mumbai’s Urban Schools

With the proliferation of smartphones, mobile learning has become an essential aspect of modern education. This topic could examine the use of mobile learning apps and platforms in Mumbai’s schools and how they are helping students learn anytime and anywhere. Mobile learning also offers flexibility for working students or those in remote areas.

Key Areas to Explore:

The adoption of mobile learning tools in Mumbai’s urban schools and their impact on student learning outcomes.

How mobile apps support self-paced learning and enhance student engagement outside of traditional classrooms.

The effectiveness of mobile learning in improving literacy and numeracy skills in Mumbai’s schools.

10. Teacher Training for Educational Technology Integration in Mumbai

For educational technology to be successfully integrated into Mumbai’s schools and universities, teachers need to be adequately trained in how to use technology in the classroom. This topic could explore the challenges and solutions related to teacher training in educational technology, ensuring that educators are well-equipped to utilize digital tools effectively.

Key Areas to Explore:

The effectiveness of teacher training programs in helping educators adopt digital tools in the classroom.

The barriers faced by teachers in incorporating technology into their teaching practices.

Best practices for teacher professional development in educational technology in Mumbai’s schools.

Summing it Up

Educational technology offers numerous opportunities to enhance teaching and learning in Mumbai’s educational institutions. PhD candidates in this field can explore a wide range of topics that align with the city’s dynamic educational landscape, from the use of AI and VR to the challenges of the digital divide. By selecting a relevant and innovative thesis topic, you can contribute to the ongoing conversation about how technology can transform education in Mumbai, helping to shape a more equitable and effective learning environment.

At PhD Thesis World, we specialize in providing expert guidance to PhD students focusing on educational technology. Whether you're interested in studying the impact of mobile learning, AI-powered education, or the role of EdTech startups, we offer the support and resources you need to succeed in your research journey.

[pen2print]

Top Thesis topics Related to AI and ML

Daily writing promptWhat have you been working on?View all responses Here are some top thesis topics related to Artificial Intelligence (AI) and Machine Learning (ML): Photo by Tanya Gupta on Pexels.com Explainable AI (XAI): As AI systems become more complex, understanding how they make decisions is crucial. Research on developing algorithms that explain their decision-making process to…

[edupediapublications]

Top Thesis topics Related to AI and ML

Daily writing promptWhat have you been working on?View all responses Here are some top thesis topics related to Artificial Intelligence (AI) and Machine Learning (ML): Photo by Tanya Gupta on Pexels.com Explainable AI (XAI): As AI systems become more complex, understanding how they make decisions is crucial. Research on developing algorithms that explain their decision-making process to…

[internationaljournalofresearch]

Top Thesis topics Related to AI and ML

Daily writing promptWhat have you been working on?View all responses Here are some top thesis topics related to Artificial Intelligence (AI) and Machine Learning (ML): Photo by Tanya Gupta on Pexels.com Explainable AI (XAI): As AI systems become more complex, understanding how they make decisions is crucial. Research on developing algorithms that explain their decision-making process to…

[meganamy11]

The Ultimate Guide to Academic Writing Services: Why Students Need Them

Academic writing is an essential part of every student’s educational journey. Whether it’s writing essays, research papers, case studies, or dissertations, students must meet high academic standards. However, not everyone possesses strong writing skills, and time constraints often add to the struggle. This is where academic writing services come into play. These services offer professional assistance to students, helping them produce high-quality academic work.

In this blog, we will explore the significance of academic writing services, why students use them, and how they can improve academic performance.

Understanding Academic Writing Services

What Do These Services Offer?

Academic writing services provide students with professionally written essays, research papers, thesis papers, and other academic assignments. These services employ expert writers with extensive knowledge in various subjects, ensuring well-researched and well-structured papers.

Types of Academic Writing Assistance

Custom-written essays and research papers

Editing and proofreading

Formatting and citation assistance

Thesis and dissertation writing support

Case study and coursework writing

Why Students Use Academic Writing Services

Time Constraints and Deadlines

Many students struggle with managing their time effectively. With multiple assignments, exams, and extracurricular activities, meeting deadlines can become overwhelming. Assignment writing services help ease this burden by providing well-written assignments within the required timeframe.

Lack of Expertise in Academic Writing

Not all students are skilled in academic writing. Some struggle with structuring their papers correctly, using proper citations, or conducting in-depth research. Professional writing services help students meet academic expectations and improve their writing skills.

Language Barriers for Non-Native English Speakers

For international students, writing in English can be a challenge. Academic writing services help bridge this gap by providing well-articulated, grammatically correct papers.

How Academic Writing Services Improve Student Performance

High-Quality Research Papers and Essays

Students receive well-researched content, ensuring better grades and deeper subject knowledge.

Better Understanding of Writing Structure and Formatting

By reviewing professionally written papers, students learn how to format and structure their own assignments correctly.

Enhancing Academic Knowledge

Exposure to well-written content helps students grasp complex topics and improve their analytical thinking skills.

How to Choose the Best Academic Writing Service

Checking Reviews and Ratings

Before selecting a service, students should check customer reviews and ratings to ensure reliability.

Evaluating the Pricing and Refund Policy

A good writing service should offer reasonable pricing and a transparent refund policy.

Ensuring Timely Delivery and Support

Reliable services provide 24/7 customer support and guarantee on-time delivery.

Are Academic Writing Services Ethical?

Some argue that using writing services is unethical. However, students can use them responsibly by treating the papers as study guides and learning tools rather than submitting them as their own work.

Future Trends in Academic Writing Services

AI-Driven Writing Assistance

With advancements in artificial intelligence, AI tools are now being integrated into writing services to enhance efficiency and accuracy.

Personalized Learning and Writing Support

Future services may focus on personalized assistance, helping students improve their writing skills through tailored feedback and tutorials.

Conclusion

Academic writing services have become an essential tool for students struggling with writing assignments. They provide professional assistance, ensuring high-quality work while helping students improve their writing skills. However, students must use these services ethically and responsibly. By choosing a reliable service, students can enhance their academic performance and gain a better understanding of academic writing.

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