Do conscious AIs need to have the capacity to feel pain?

Do conscious AIs need to have the capacity to feel pain?

How can we be sure that the AI feels pain? The “pain reaction” can be sensor-activated tape. When somebody touches a robot in a certain way. It can say, “It hurts”. This same reaction is possible to create. Using a tape recorder and an electric switch. That means the AI can have multiple reactions that mimic human reactions. So if the bot car has certain sensors and somebody kicks it, that system can say. “Please, don’t kick me”. 

Do the AI need to feel pain? That’s a good question, because if we want to create artificial superintelligence, we need to create a machine with consciousness. And that is very dangerous and difficult. Researchers and philosophers don’t agree on what consciousness is or what it entails to be you. Consciousness is being you, but how does that thing form? We say that some part of consciousness is the sum of information that our senses send to the brain. But that’s the first thing that we agree on. 

The second thing is that consciousness is the thing that is connected to memory. Our experience modeling our way to react to something. But the thing that we see the world as being at the middle of is a mystery. This thing is consciousness. But how does that thing form? We can make machines that can mimic feelings very easily. When somebody presses the robot’s hand with a certain power. That launches a reaction. Where the robot says, “This hurts”. The fact is that a similar reaction is possible to create.

By using a scale and a cassette recorder. When certain pressure impacts the scale. The hand presses the power switch. That conducts electricity to the recorder that plays the message to people. This thing means that. Robots that mimic pain are easy to make. But if we want to make a conscious robot, we must realize one thing. The robot can mimic human reactions very easily. If the robot is left behind, it can say, “Please don’t leave me”. Or, when somebody kicks the robot's shin, it can say, “This hurts”. 

In that case. Reaction is like reflexes. When something happens and there is a match in the system memories, that activates a reaction. If some merchandise’s weight is higher. Than a certain level. The robot can report that the merchandise is too heavy. The human-shaped robot requires the scales because it may carry too heavy things. Or presses too strongly. That breaks the robot or merchandise. 

The robot can use its own touch sensor that activates that reaction. Or the surveillance cameras can send that information to a robot. Those reactions are preprogrammed reactions. For a certain situation. Reactions are like tapes that certain actions activate. This doesn’t require deep consciousness. 

These kinds of reactions don’t mean that the robot really fears that situation. Another thing is that. If somebody tries to shut down the AI. There can be a program that only authorized persons can perform that operation. The system can only transform to use a secondary power line. That means the AI can refuse to shut down its main unit, even if it's not conscious. Consciousness makes AI dangerous. A creature with consciousness protects itself. That is only one way to see those things. The AI doesn’t need consciousness to refuse to shut itself down. And that means. It’s hard to state. If the system is conscious. Or if the system just follows reactions that were programmed into it. 

Why is it so hard to order Tacos from AI?

 Why is it so hard to order Tacos from AI?

When we see cases where companies like Taco Bell fail in their plans to replace human workers with AI, we might ask what went wrong. The answer is simple: the AI didn’t understand when somebody asked something. And then somebody asks, Why does AI understand better when a professor or military leader says something than in other cases. Where does a regular person ask something? The answer is that those first two cases speak using literary language. Regular people speak using dialects. And that is hard for the AI.

When AI translates speech, it uses a speech-to-text application. This application transforms spoken words into a form. That algorithms understand. “Understanding” means that the system searches the algorithm. There is a match for those words or commands. That match is like a trigger that activates an action. That the algorithm controls.

If a person uses dialects, there must be their own algorithm or trigger for those dialect words. This means that the fuzzy logic that the AI uses. Is the sum of the precise logic. The fuzzy logic means that there are multiple triggers that the system can activate. So every dialect requires its own trigger. Or in other cases, there must be a translation protocol that transforms dialect words into literal words.

And then that system transmits the translated words to the trigger that activates the action. The AI has problems in cases where somebody has speech defects. Or they use something else. Than the official dialects. In those cases, there is no match in triggers. This is one of the biggest problems. For large language models. LLM.

When the AI takes command, it follows a certain line. First, it must search keywords like “draw an elephant for me”. The system finds the word “draw”, which means. The system transfers the mission to an algorithm or module that handles graphics. Then the system searches for images. Where there are elephants. The system creates its own version of those images. It connects those images using certain parameters. And that means the image that AI creates is the average of the images that the AI uses. The AI must understand the words that it gets.

https://futurism.com/taco-bells-ai-drive-thru

Artificial bacteria are the biggest hope and the biggest threat.

 Artificial bacteria are the biggest hope and the biggest threat. 

Artificial bacteria are not. Like natural bacteria.  

DNA and mRNA are tools that can rewrite a cell's genetic code. That means the cell changes its shape and then starts to make different things than the original cells. The ability to program cells is an opportunity. And threat. The ability to remove hereditary diseases from the human body. The problem is that the same technology allows researchers to make  more perfect lifeforms. Than natural organisms. Artificial life normally means bacteria. Created using genetic reprogramming. In that case, the DNA bits will be collected and connected into the new form. That allows researchers to create bacteria that create antibiotics and spider silk, which is the strongest material in nature. 

Bacteria can be reprogrammed to search and destroy cancer cells. And probably, genetically engineered cells can form tissues for the bioprinters. Reprogrammed bacteria can also make it possible to create a large mass of things like skin. In that case, bacteria are on the nutrient platform, and the system just changes the DNA in their nucleus. Theoretically is possible to create anaerobic bacteria. That releases oxygen into blood vessels. That kind of anaerobic, biological oxygen synthesis is one of the most fascinating things in biotechnology. 

The ability to create artificial bacteria allows researchers to create new types of biological weapons. The same thing. That allows bacteria to search and destroy cancer cells. Allows weaponized bacteria to find things. Like neural structures or the blood vessel wall. And then attack those vital tissues. That kind of bacteria is very dangerous. There is a possibility. The bacteria themselves copy the targeted person’s cell antigens into themselves. And another dangerous thing is that. Those bacteria can destroy themselves after a certain time. When we think about the perfect, artificial organisms, we must realize that those organisms can turn the “Alien” movie monsters into reality. 

There can be infectious bacteria that can create things. Like the HIV virus at the same time. That allows those bacteria to destroy the immune defense at the same time. Here, we must remember that artificial bacteria are made. Connecting DNA bits together.  It is not like natural bacteria. That means those bacteria can make things. That is not possible for natural bacteria. 

Researchers can create artificial organisms, and the same technology that makes bacteria resistant to poisons can turn them resistant to antibiotics. When we think about aliens, we might think of a very complicated lifeform. from outer space. The fact is that the term “alien” means something non-natural. Biolaboratory can create aliens that nothing can resist. Those aliens are not like humans; they are microscopic organisms. Those creatures can be a fast-increasing bacterial population. Those bacteria can look like hospital bacteria. 

The thing that protects us against immune-resistant super bacteria is their complicated form. Their population will not increase fast enough to it can cause problems outside the hospitals. Natural bacteria destroy those organisms very fast. The biggest threat is the super bacteria that can increase their population too fast. If antibiotics cannot destroy those bacteria. They can cause problems. 

https://futurism.com/scientists-synthetic-lifeform-syn57

Images: Futurism.com

Black Hawk down in Colombia.

  Black Hawk down in Colombia. 

https://defence-blog.com/colombian-black-hawk-shot-down-by-drone/

Colombian criminals or rebels shot down Black Hawk helicopter, and that is a great warning that drones cause very big threats to rotary-wing aircraft. That means the warfare. But also, police work reaches a new level. The drone can cause a threat to helicopters and aircraft. And that means also criminals can cause a threat to SWAT and other police units using drones. The helicopter that criminals shot down was used by paramilitary police. 

And also, criminal organizations can attack each other using drones. That means the role of helicopters must be re-estimated immediately. The drug cartels have money to buy technology. And they also follow the Ukraine war. Cartel bosses have billions of dollars, and drones are multipurpose tools in the hands of those super gangsters. 

Drones can carry drugs over the borders, and they can carry drugs and weapons to prisons. Drones can also carry weapons over the borders, and that means they are perfect tools for smugglers and other gangs. A drone is a cheap system that can be used in reconnaissance missions. Those systems can eavesdrop on people’s homes. And they are effective tools to observe areas. Criminals have the same needs as the police and the military. 

Drones can cause damage or even destroy large aircraft. The drone swarm can be released from the containers. The system opens the container’s roof and releases drones when the vehicle is at a certain point. The truck driver must not have an idea. That some drones are hidden in a container. The drone can search the target independently using an AI-based search and destroy protocol. When the container is at a certain point. The system releases drones automatically. Those containers can also be on trains or on ship decks. Or those carrier vehicles can also be dropped from a cargo plane. Remote-controlled systems can also carry those things. 

There is one bigger threat than the Cuban Missile Crisis. That is that. The Russians will position a Club-K container missile system in the USA territory.

There was sometimes suspicion that Russians or Chinese wanted to make the tactical missile carriers. Looks like civilian container carriers. In the worst case, the Club-K, the container missile system, will be positioned in the USA. And then the remote operators launch those missiles from those containers. 

The system would be similar to Club-K, which uses long-range cruise missiles. But those tactical systems use some tactical missiles similar to HiMARS. Those remote-controlled trucks can travel near the military targets. And then shoot their missiles at the targets. This kind of system can be hidden in the targeted country, and then satellites can activate the missile launcher. This kind of system can be the biggest threat that the U.S. government can imagine. 

https://defence-blog.com/colombian-black-hawk-shot-down-by-drone/

https://www.globalsecurity.org/military/world/russia/club.htm

https://www.twz.com/air/colombian-black-hawk-downed-by-drone-is-a-glimpse-of-whats-to-come

Quantum dots can help address the challenges of quantum networks.

 Quantum dots can help address the challenges of quantum networks. 

"Quantum Cryptography with quantum dot-based compact and high-rate single-photon nano-devices. Credit: Lars Luder " (ScitechDaily, Scientists Crack a 40-Year Puzzle in Unbreakable Encryption)

"For decades, scientists thought unbreakable quantum encryption required flawless light sources, a nearly impossible feat. But a team has flipped the script using tiny engineered “quantum dots” and clever new protocols." ScitechDaily, Scientists Crack a 40-Year Puzzle in Unbreakable Encryption)

"By making imperfect light behave more securely, they proved that encrypted messages can travel farther and more safely than ever before. Real-world tests have shown that their method outperforms even the best current systems, bringing practical, affordable quantum-safe communication a significant step closer." (ScitechDaily, Scientists Crack a 40-Year Puzzle in Unbreakable Encryption)

Theoretically, a quantum network is an easy thing to create. The system must only create the quantum channel, or “electromagnetic wormhole” between two objects. And send a photon in that network. The security in a quantum network forms because information is stored in the photon’s particle form. If something touches that photon, this destroys information. Actually, it reorders information in a form that the system cannot use. In a quantum network, a photon is like a ring that is around the superstring. The laser ray will protect that system. 

This thing makes quantum communication ultra-secure. The system can store data in the qubits that are photon or some other particle’s superpositions. It can also send so-called empty photons in the track. This increases the security. But the system should control the entanglements, internal and external superpositions, and data transportation channels. 

*************************************'

The next part of the text is straight borrowed from ScitechDaily.com

For four decades, the holy grail of quantum key distribution (QKD) — the science of creating unbreakable encryption using quantum mechanics — has hinged on one elusive requirement: perfectly engineered single-photon sources. These are tiny light sources that can emit one particle of light (photon) at a time. But in practice, building such devices with absolute precision has proven extremely difficult and expensive.

To work around that, the field has relied heavily on lasers, which are easier to produce but not ideal. These lasers send faint pulses of light that contain a small, but unpredictable, number of photons — a compromise that limits both security and the distance over which data can be safely transmitted, as a smart eavesdropper can “steal” the information bits that are encoded simultaneously on more than one photon.

Research team flipped the script. Instead of waiting for perfect photon sources, they developed two new protocols that work with what we have now — sub-Poissonian photon sources based on quantum dots, which are tiny semiconductor particles that behave like artificial atoms.

By dynamically engineering the optical behavior of these quantum dots and pairing them with nanoantennas, the team was able to tweak how the photons are emitted. This fine-tuning allowed them to suggest and demonstrate two advanced encryption strategies:

1)A truncated decoy state protocol: A new version of a widely used quantum encryption approach, tailored for imperfect single photon sources, that weeds out potential hacking attempts due to multi-photon events.

2) A heralded purification protocol: A new method that dramatically improves signal security by “filtering” the excess photons in real time, ensuring that only true single photon bits are recorded.

In simulations and lab experiments, these techniques outperformed even the best versions of traditional laser-based QKD methods — extending the distance over which a secure key can be exchanged by more than 3 decibels, a substantial leap in the field.

(ScitechDaily, Scientists Crack a 40-Year Puzzle in Unbreakable Encryption)

************************************

The superstring is like a wire that aims those photons into receivers. The problem is how to make a practical solution for that model. 

The problem with quantum communication is simple. The quantum system used for communication must be fully controlled. The system can use photons to transport information. But the problem is that the photons must be counted. The light source that can send single photons is not very easy to make. This is why researchers use lasers that send an indefinite number of photons. Because the number of photons changes every time the laser sends data, this makes the quantum system difficult to create. If researchers don’t know all parts of the system, they cannot control it. 

The solution to the problem can be quantum dots. In that kind of system. Information travels between superpositioned and entangled photons or other quantum dots. That can be the solution to the problem. How to transmit information in the quantum network. Quantum entanglement is one kind of resonance. In that case, the system transmits oscillations through the quantum fiber from the transmitter to the receiver. This method is not as secure as the photonic-based system. If somebody touches the fiber, it destroys information. 

Another problem is how to send the decryption key in the quantum system. Without that key, the system cannot decrypt data that is stored in the information carriers. Data is stored in the particles’ internal superpositions if it is transported in a quantum channel. This means that the data is transported in a structure that we can call a tower. The tower has floors, which are qubit states. The receiver must know what states are used in the data transportation. 

https://scitechdaily.com/scientists-crack-a-40-year-puzzle-in-unbreakable-encryption/

https://en.wikipedia.org/wiki/Quantum_key_distribution

Superficialism is a big threat to people.

 Superficialism is a big threat to people. 

If you let AI make decisions for you, blame yourself. Who is responsible, if we offer our free will and ability to criticize some machine? When we follow the orders that the machine gives, we offer our free will to the machine.

The Internet and modern society favor superficial people. People who deliver their ability to think to some machines. When we process the information we receive, we might ask ourselves if we truly think and process that data? Or do we simply click the homepage, search for about three seconds, and then move to another homepage? Do we even read more than some titles from homepages? Can you, or I, draw some conclusions using those titles? And then, do we move to some more interesting homepages? When we search for things on the net. We can search only for homepages that please us. That is one way to see things. 

If we just follow the instructions that the AI gives. We give leadership to the machine. If we never ask why AI makes something, we lose our way to introduce criticism. If we just follow orders and be quiet, that means nobody even knows that we have some different opinions. We can think what we want, but the thing is, how can we share those opinions with other people? 

When people are worrying about things like reading books, we must dare to ask one thing. When did you go to the library? And lend some books?  When your boss said to you that you can keep a couple of hours free to go to the library and search for information in those books? Or do we lend books that we can fill shelves? Using books? Or do we really open those books and then concentrate on those things? And when we spent our lunch break discussing books that we read? The decision is ours. Maybe we read books. Maybe we read texts from computer screens. But if we want to share our opinions with other people. There is always something more interesting. 

There are two ways to think about things. 

1) We can notice that something has happened. 

2) We can notice that something has happened, and then ask why that thing happens. 

We must realize that people always lead governments and nations. When somebody talks about value-based realism, we should ask: 

Whose values? Whose realism? Or, who describes our values and realism? Or things that we tell outside as values and realism? Are those things serving only the majority? And when we defend some minorities, we must realize that those things can also serve something. We can use things like racism as an excuse to kick our competitors. So, when something comes to the newspapers and their headlines, we must ask ourselves, why did that thing become so important, just in that moment?

Things like sports and some lone island survivor reality TV are more interesting than some ideas that some writer introduced a long time ago. When we sit at our desks in our workplace. We must be quiet so that we don’t disturb other people. So we just sit, look at the screen, and be careful not to disturb our workmates. Is that the environment where it is easy to share opinions and offer analytical thoughts to people? 

But otherwise, why can’t we tell our opinions to other people? That is the thing that. We must realize, before we introduce some criticism. If we just sit and look at things. That might look something. We cannot accept; we can follow two routes. We can sit quietly, and then other people say that we have nothing to say. We can share our opinions with other people. When we face social media, we must understand one thing. Many people misuse that tool. They introduce opinions that we cannot understand or accept. And we have our free will. We can read things that we know are false. We can remove that false information by closing social media accounts. Follow the official media. 

And then we face a thing. Maybe we disagree with the opinions or things that official media shares. Maybe we have better knowledge than the reporter, but then how can we say that to people who read those  articles? Maybe we should write that in newspaper opinion pieces. But what if they don’t publish that thing? Journalists are also human. That means the journalist has their background, opinions, and other things. That always affects people's way of thinking and writing. When we use AI, we forget. That AI uses datasets. Collected by humans. Humans make decisions about what the AI should give and what it should not give to people who use it. 

Thinking is not enough. We must have the ability to say something. If we just sit and look at the music videos, we must realize that people never see our opinions. That is enough for people like Kim Jong-Un. People can have their opinions. But they must follow the regime. They are not allowed to say or write things that are against the regime. So, does the regime somehow deny Western people the way to introduce critical opinions in public media? We remember that critical workers were gifted to the company. People celebrated those people as heroes. 

But then we might ask, how critical are those employees really? Did they criticize their henchmen or their leaders? Today, we say that social media kills that kind of criticism. Where employees say that they see something that is right, using evidence-based arguments. Criticism without justification is not  effective way to effect. If there is no evidence. That kind of criticism is easy to knock out. But when we want to introduce criticism, we must remember that it’s easier to criticize a henchman using authority than to give critical feedback to the superior. 

AI doesn’t make U-turns.

 AI doesn’t make U-turns. 

   

We don’t always make our best move. That means we don’t always choose the fastest way to travel between two points. We simply might like another route. We might like things that we see while we travel some other, slower route. And that is inhumane. The AI always predicts that we choose the fastest and most economical route. AI thinks that we don’t look at things like old houses. AI always predicts that we travel to some other place using the fastest route. It believes that we want to make journeys in the shortest time possible. It doesn’t think that somebody chooses a longer route, because that person wants to improve fitness. 

And that is the thing that differs AI from us. 

The difference between the human and AI approach to playing games like chess is this. The AI never plays anything for fun. Or the AI will never “kill time” with games. When humans play chess, sometimes we just move pieces on the chessboard and think of other things. AI always “thinks” that we play games to win. Not just to kill time, when we wait for things like a weekly meeting. This is one of the differences between AI and humans. When AI tries to predict things like interactions in nature. It makes things better than humans. The reason for that is simple. Everything that happens in nature happens in a linear way. When action happens. A reaction follows that action. When snow starts to fall on the slopes, that action continues until the avalanche reaches the bottom of the valley. The avalanche follows the laws of nature. It will not change its mind and start to travel backwards. 

And that is the difference between avalanches and humans. Humans can change minds. When a human starts to walk across the street, that doesn’t mean that the human will go to the other side of that street.  Humans can change their minds and make a U-turn. This is the thing. That makes human nature unpredictable. And that is one thing that evolution is made for: protecting species. And that makes humans difficult prey. When some animals hunted humans. We can run to the thing that seems like a dead end. And then put their spears against attacking animals. This way of making something unpredictable. Makes it hard to predict human behavior. 

AI follows the same marks as human psychologists when they try to read humans’ feelings. The ability to use special sensors to see how blood pressure and adrenaline levels rise. If the AI doesn’t have those sensors, it must follow body language. And the way a person speaks. In those cases, the sensor systems that the AI can use. Mean as much as AI itself. If the AI can use lie detectors. It is not very hard to make an algorithm that uncovers lies.  In that case, sensors mean more than an algorithm. 

When we see cases where somebody cheats people who serve as royal guards, we know that thing makes those people angry. Those people, with ultimate strength, can hide that emotion. We might be very angry. But in some cases. We don’t tell this to other people. Animals never hide their emotions. When human turns angry against a superior force. That means humans might not attack. Humans can flee from the field and wait for a better moment to strike. That is one of the things that makes us the ultimate species. 

Let’s go back to the chess game. The algorithm predicts that we always make the best move. And this is the algorithm’s ultimate strength. And that is the algorithm’s ultimate weakness. We might think of cases where a boxer faces many practice opponents. That boxer can win all of them easily. But then in the title fight, the opponent knocks out our boxer. In that case, we forget that. Some boxers can lose their training matches because they bet on that opponent. This means the training opponent can lose matches that nobody sees. But when there is a kind of meaning. That a person can fight differently. This is the thing that AI doesn’t always understand. Humans can save their best moves for the places where those moves mean something. So, we can think about different things than what we make.