Category: Artificial intelligence

Introduction

“The development of full artificial intelligence could spell the end of the human race” says Stephen Hawking, a significant figure in the field of Cosmology, Artificial Intelligence (AI) and theoretical physics (Cellan-Jones, 2014, para 1). But today in the modern AI world which is mostly known by many, as the fourth industrial revolution, the AI researchers refute and under-value Stephen Hawkings intimidating predictions. They keep themselves blind over the facts that AI brings forth more threats than benefits to individuals and societies. According to Rouse (2019), Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning and self-correction (para.1). This essay’s main concern goes on how an increase involvement of AI will impact individuals, organizations, and labor workforce in China. The problems which AI carries with itself in China are, increased rate of unemployment and immeasurable amount of funds being continuously invested in it. It will also look forward to different solutions to tackle these problems, including government providing subsidies to unemployed people and upgrading the educational system in China in order to confront the rapid technological changes. And in the end, it evaluates these solutions and finds one highly recommended solution.

Situation

AI is now rapidly changing the face of businesses and multinational organizations in more than 75 developed countries including China, which is currently the second country after United States leading in AI development (citation). International Monetary Fund reports that ‘Asia holds 65% of the worldwide responsibility for employing manufacturing robots where China accounts for 50% of Asia’s total industrial robot usage’ (Danmeng & Jia, 2018, para.5). China is already facing unemployment problems with over ‘50 million citizens currently unemployed’ (Trading Economics, 2019), mainly due to its enormous population with highest population rate of ‘1.393 billion people’ (Countryeconomy, 2018, para.1), and it is estimated to reach up to ‘1.433 billion people by the end of 2019’ (WorldOMeters, 2019, para.1). China is currently one of the countries, with most foreign Multi-National Company (MNC’s) factories running in it due to its inexpensive land, therefore, MNC companies with enormous funds adds more profit by minimizing their cost of production by replacing labors with robots. Apple Inc. in Eastern China has found that ‘Autonomous machines in China costs 130,000 yen per year ($19,000) which is equivalent to the cost of multiple workers doing the same job within a shorter amount of time’ (Danmeng & Jia, 2018, para.5). CEIC (2019) estimated that “On average, the monthly income of a middle-class citizen in China stands around US$330.” In addition, CEIC (2019) also reports that “China’s Labor Force Participation dropped to 68.72% by December 2018.” Due to an unpleasant wage rate and unfair work pressure, Chinese labors passion for work also disappears every year, making them directly dependent on Chinese government for financial Aids. As result of poor wage given to employees and firms maximization of profit by replacing human workforce with automated machines, the nuisance of unemployment continues to grow with an unstoppable rate.

Problems

AI bring forward multiple barriers and problems with its daily upgradation and improvement which mainly includes high unemployment rate and lofty cost of starting AI firms. Firstly, Danmeng and Jia (2018, para.4) states that “30-40% of the labors has been replaced with AI machines over the past three years”; their research makes it very specific that every year China has been witnessing an immense decline in unemployment rate with advanced AI. According to Ren (2018), 2.3 million employees working in industrial sector are either going to lose their jobs or more than half of them will be reassigned to new jobs before 2027 due to disruptive AI technologies. (para.1). “Chinese scholars and psychologists treat the situations of unemployed people as Post-Traumatic Stress Disorder (PSTD)” (Yang, 2019, para.3). This extreme downward unemployment rate has brought up significant consequences which includes rage, stress and depression due to poverty amongst unemployed. Yang (2019) also points out that social anger and unrest are also some of the emotional problems caused due to unemployment (para.2). Additionally, Yang (2019) also states that besides psychological suffering, unemployment has also been responsible for many physical problems like headaches, stomach ache and hair loss (para.3). Unemployment holds the middle and low-class citizens of China in a severe health condition which also decreases the nations productivity growth.

Secondly, China must be aware of the exorbitant amount of money invested in AI firms which effects the economy of China directly and indirectly. According to Barhat (2018) “Investors poured $4.2 billion into more than 200 Chinese A.I. companies between 2012 and 2017” (para.1). Following this, Barhat (2018) also reports that, an addition of $1 trillion is going to be invested to build and upgrade their AI industry within the next 30 years. Chinese investors are on a constant run in the flight for the latest technology in AI industry, with apparently more than $1.42 trillion invested and to be invested funds, which leads to more imbalance in their economy, which then leads to corruption and deceit amongst government heads. According to Distinguished Fellow and & Adjunct Professor at Carnegie Mellon University’s College of Engineering, Vivek Wadhwa, ‘Governments can’t make innovation by throwing money at AI firms, this will only lead to more corruption and bureaucracy’ (Barhat, 2018, para.11). Therefore, investing boundless amount of money in AI can easily destroy an economy of a nation by bringing almost irreversible imbalance in high, middle and low-class citizens of China.

Solution

There are limited solutions available to be addressed in order to tackle with the problem of AI related unemployment. Governments and Ministry of Education plays an important role in introducing new laws and policies as a solution to fight against this consequence in China. Firstly, government can start providing subsidies like UBI Policy and introduce more public jobs. Subsidies should be provided by the government to the unemployed in order to motivate them to start working again. According to Arthur (2016), “Universal Basic Income (UBI) is a payment made to all adult individuals that allows people to meet their basic needs. It is made without any work or activity test” (para.1). Government can introduce the UBI policy in China to improve the financial status of the middle and low-class citizens for a reasonably short-term. This policy encourages the citizens to get their self-esteem back and motivate them to start working again. “UBI takes the weight off the unemployed citizens shoulders by ensuring that everyone has enough money in their pocket for survival and also helps to keep money flowing through the economy, particularly after tens of millions of jobs have been disappeared” (Stollery, 2018, para.12). The Chinese government can also start providing public jobs to the unemployed to decrease unemployment rate. According to CompTIA (2019), “U.S. economy added 75,000 jobs in May 2019” (para.10). China can launch public organizations to promote and employ low-class citizens in public job for their survival and to balance the nation’s economic too.

Secondly, China’s Ministry of Education can directly bring an impact on the future of work by confronting present students with rapid and immense technological changes. According to McKinsey Global Institute report ‘around 40 to 160 million women worldwide may need to change their profession by 2030, which will often be replaced by high-skilled roles’ (Press, 2019, para.3). Most of the occupations which requires least qualifications are evidently getting and going to be replaced with AI robots and other automated machines. This predicted situation then leaves behind only those jobs which demands higher skills and talents. CompTIA (2019) state that over 89900 software and application developers, 25000 computer user support specialists, 22100 computer systems engineers and architects, 20100 computer system analysts and 17600 IT project managers were required by companies worldwide only during the month of May 2019 (para.11). Therefore, Ministry of Education can adapt present students with future intense technological competition by increasing the education level in schools and colleges through upgrading educational systems and hiring highly qualified teachers and mentors.

Evaluation

Artificial Intelligence has been increasingly developed since 2010 with the aim of bringing ease in work industry with both pros and cons attached to the idea from every aspect of life. Evidently, AI’s effect on future of work, is a very broad and complex situation which undoubtedly requires multiple approaches by governments and ministries in order to minimize its negative impacts on both individuals and society. Firstly, implementation of subsidy policy by government would be a financial support to unemployed people in short run. According to Brown (2015), many countries like Australia, Austria, France, Germany, Poland Sweden and UK has been witnessing the success of subsidy programs implemented (para.7). However, this approach requires huge amount of funds for a long period of time to aid 2.3 million unemployed low-class citizens, which can lead to economic imbalance or it can even crash China’s economy in worst case scenarios. Furthermore, it also increase laziness and procrastination to those who are not willing to work but are still applicable to access governmental subsidies due to their unemployment status. Secondly, Chinese government can provide numerous public sector jobs to their below average class citizens. This opportunity keeps them busy with work and helps them earn adequate income for living and covering their daily expense for survival. In addition to that, Caponi (2017) state that, increasing public sector jobs also assists in decreasing the unemployment rate (para.1). Regardless of work opportunities and adequate income, public jobs can lead to loss of creativity and poor IQ among below average class people, which leaves them far behind from the daily necessary education. Additionally, Caponi (2017) reported that, by promoting and offering more public jobs, overall productivity of an economy can face a downward trend. Lastly, Ministry of Education can have an impact directly on current and future consequences with AI related work by increasing the level of education in high schools and colleges. C. Yi, a professor at the Tianjin University of Finance and Economics reports that Ministry of Education must reform China’s education system that will be able to train students to develop skills needed in the future and adapt themselves to new AI based jobs (Global Times, 2018, para.18). This initiative taken by ministry of education brings multiple advantages. One of the advantages of upgrading educational system is that it leads to an increase in creativity. This initiative can also bring down the unemployment rate significantly, which then supports nations economic growth on a long run. On the other hand, this process will be time consuming and requires huge amounts of funds. All the different solutions emphasized has positive as well as negative outcomes. However, the best course of action would be initiatives to be taken by ministry of education like increasing education level in secondary and high schools to prepare students for rapid technological changes. Evidently, Ministry of Education plays a significant role in challenging the upcoming consequences of AI in the near coming future.

Conclusion

To conclude, Artificial Intelligence and its effect on future of work is a huge, and entirely complex concern which will bring a vast change to the future of work. AI’s growth can have a massive negative impact on individuals and societies in China, which includes high unemployment rate and lofty amount of money invested in AI companies manufacturing process. This essay suggests three overall solutions which includes introduction of subsidy policy, addition of public jobs in the economy by the government and upgradation of educational system by ministry of education. After evaluating these solutions, it highly recommends that ministry of education must change educational system not only because it confronts students with rapid technological changes, but it also increases young peers’ creativity. This also helps economy grow in the long term by minimizing the unemployment rate in the future.

References

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2. Barhat, V. (2018). China is determined to steal A.I. crown from US and nothing, not even a trade war, wil stop it. Retrieved from https://www.cnbc.com/2018/05/04/china-aims-to-steal-us-a-i-crown-and-not-even-trade-war-will-stop-it.html
3. Brown, A. (2015). Can hiring subsidies benefit the unemployed?. Retrieved from https://wol.iza.org/articles/can-hiring-subsidies-benefit-unemployed/long
4. Caponi, V. (2017). The effects of public sector employment on the economy. Retrieved from https://wol.iza.org/articles/effects-of-public-sector-employment-on-economy/long
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10. Global Times. (2018). AI to affect 70% of occupations as robotics complement China’s shrinking labor force. Retrieved from http://en.people.cn/n3/2018/0917/c90000-9500920.html
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12. Ren, D. (2018). 2.3 million – the number of jobs that could be lost to artificial intelligence in China’s financial sectors by 2027. Retrieved from https://www.scmp.com/business/companies/article/2139685/23-million-number-jobs-could-be-lost-artificial-intelligence
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14. Stollery, B. (2018). Universal Basic Income is an inevitable part of our automated future. Retrieved from https://medium.com/age-of-awareness/universal-basic-income-is-an-inevitable-part-of-our-automated-future-3cc181d4778d
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17. Yang, G. (2019). Unemployment and mental health in China. Retrieved from https://theasiadialogue.com/2019/04/15/unemployment-and-mental-health-in-china/

First of all let’s look at some facts that we have managed to accomplished with digital technology. We have improved magnificially in medical technology by creating vaccines and antibiotics for as many sickness that could of possibly be deadly in the past. Also if not because of Alexander Graham Bell creating the very first telephone we wouldn’t of seen a drastic change of how our communication has changed, such as having Mobile cell phones to call friends and family members also by having the new popular apps such as Snapchat, Instagrams and Twitter and so on. Although technology won’t stop improving anytime soon, in present time we are starting to see that most people are starting to get frightened with the realization that one day we will have Artificial Robots walking upon us in the streets and being our next door neighbors. What most people are mostly getting worried about is that having too much technology will affect the mind of our children by the way they think, concentrate and read. Personally I would have too disagree that digital technology is making us dumber, if anything its improving our way of thinking, increasing our brain intelligence and way we invents things.

Our way of thinking has been improving as long as before our first ancestors started to walk this earth, with them inventing the fire so they wouldn’t of been eating raw foods and also, so they could keep warm due to the cruel winters they faced, they also created tools, so they could defend themselves when other tribes came too attack them but most importantly they made the tools so they would be able to hunt more easily. Most importantly they created something in which we always wear at all times, which is clothes, they created clothes with the fur of the animals that they killed so they never let anything go to waste from the animal. At the same time there are still people who don’t seem too care about this and just seem to care on how digital technology is changing the way we think. For example, the number one thing most people have complained about has been about television is Changing our way we think and act. Too explain this Brooke Gladstone and Josh Neufeld in “ The Influencing Machines” say “ study after study has found strong links between excessive T.V exposure and childhood obesity, smoking and sexual activity” (325). What I think they both are talking about is that watching way too much t.v can affect our minds and the way that we act and this seems too have a mental block in our way we say things. No matter what the occasion is, watching television shouldn’t change the way we do things, since in the 1920’s when the television was barely starting too become popular and until now that pretty much everyone in the United States has about two too three televisions in their homes. Not only that it has also been proven that watching television can calm down the mind and lower stress. So precisely having a calm minds means better grab of information and better storing of information.

Which brings me to my second topic, about how digital technology is actually increasing our brain intelligence. One of the most compelling evidence there is that thanks to the advancing of internet connection it has actually made scholars life more easier due to the fact that it has helped them find sources quicker than what it would of taken people back in the day, days upon weeks to find in books. According to Nicholas Carr “the web has been godsend to me as a writer research that once required days in the stacks or periodical rooms of libraries can now be done in minutes” ( 314). Carr speaks his way of how he once used to find his information in the libraries but, as soon as internet was created all the information that he worked so hard to find he could easily find it in mere seconds. In Carr’s view “ a few google searches, some quick clicks on hyperlinks, and I got the telltale fact or pithy quote I was after” (314). This quote that Carr speaks about is powerful because it has a positive and negative effect, one being that he hates the fact that having advanced technology is causing him not too obtain the information as he once did when he read a book in the other hand it’s a great form to find data much more efficiency.

In the continuation to the invention of the internet and television, brings me to the the last topic which having technology is an has been one of the best inventions ever created. Technology can be a friend an or an enemy because everything you do with it depends on you. For example, the right way to use it would be to do work and too get as much information you need, the reason I say this is because my little nephew first toy was a tablet he was aware what it was knowing how to unlock it and turn it off. Personally I was a little skeptical that my brother would buy this for his son and a couple of years later he was already learning the alphabet, sea creatures, land creature an so on. This has brought to my attention that he was just gaining more intelligence every single day and someday he would invent things that would help mankind. Of course lets not forget the bad choices which means you are constantly just browsing Facebook, Instagram, Snapchat or any other type of Social media when you need to complete very important assignment for school, a resume for a Job or anything else in particular. The best invention has been created by those who know what too exactly they are looking more and searching for.

In conclusion, people will not lose the way they think just because they believe technology will take over one day. In reality this is just a beginning of a new era due to the fact that more youngsters will become smarter and will continue to push forward too make the world a better place. Not only that brain intelligence will also increase which means more people will be in college and graduation rates will increase and too top it all of more invention will come our way

Works Cited

1. Graff,Gerald Cathy Birkenstein and Russel Durst They Say, I Say. With Readings 3rd edition, Norton, 2015.
2. Carr, Nicholas “Is Google Making Us Stupid” They Say, I Say, edited by Gerald Graff. PP 313-329
3. Gladstone, Brooke and Neufeld, Josh “ The Influencing Machines” They Say, I Say edited by Gerald Graff. PP 330-339
4. Thompson, Clive “ Smarter than You Think: How Technology Is Changing Our Minds For The Better” They Say, I Say, edited by Gerald Graff. PP 340-360

When people think of the world, people automatically think of tech. Our future will no longer be on paper and pencil, but everything will be technologically advanced. We all know these now, just like 200 years ago our ancestors dreamt of tall buildings and remote communication devices. The world doesn’t wait, it advances. Artificial intelligence is already something that is a big part in the world we live in. Artificial intelligence is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. Overall it is a machine that will perform and do everything that a human brain can do. It is made up of cognitive computing, computer vision, machine learning, neural networks, deep learning, natural language processing.

The connection between AI and social media is how social media is a form of AI. Social media uses AI technology to analyze user behavior, mental state, and physical context. For instance, for the sites like instagram, tiktok and facebook you are exposed to things that you find relatable to. On instagram everything on your feed is things that you like. You will rarely find 34eanything that you don’t find interesting on it. Tiktok for you page is the same; it loads up videos that relate to and the content you watch. For facebook you get ads that connect to you. Now you might wonder, how do they know what I like. Well that’s where AI comes in, it tracks and follows what you like and do and gives you personalized recommendations, collecting and most probably selling your data to other sites at the same time. Websites and apps are continuously collecting broad swaths of data on their users often without them being aware of it, or of how or where their personal information is being used or stored.

Social media has a big hand in human rights as well. For example as mentioned before people post and use their social media platforms to share news. This also violates and clashes with rights of people. It may limit their privacy and expose them, because posts do not have to be approved before it becomes available to the whole world. Privacy is only one of the many rights that are violated through the use of social media. In recent days, people post many different allegations on other people and are believed by most without any trial and proof. Since most social media platforms are used by teenagers who do not all have the necessary knowledge about copyright laws, pictures, videos and art are often shared without crediting the creator.

Research states that the consequences that social media and AI have on human rights is how the technologies have gotten overtaken by using techniques from AI to express the center elements of social media applications, specifically search, collection, observation, predictions, sifting, recommenders, scorers, content age, and asset portion. Not only that but the risks it provides are the following: manipulation of individuals or groups, diminishing variety that creates biased views and distortion of reality, constraints on communication and freedom of expression, threats to privacy and data protection rights, social discrimination, violation of intellectual property rights, impact on the human brain and cognitive capacity, and algorithmic power over human behavior and development. In fact Advocates for Human Rights note that “increasingly, information and images that first came to light through social media have been used to fuel momentum for independent investigations.” New forms of AI also make it difficult to predict the main harm it will do, and as stated before for example, from manipulation of audio and video content such as deep-fakes, highly persuasive bargaining/sales agents, accurate lie detection or context-sensitive micro-targeting of content. In recent years social media has also been a platform to spread disinformation. Propaganda was always a big thing forever. Before it was in newspapers, and articles, and now they are used in social media. Not only that but even in elections it is presented, the misuse of cyber.

The pros that social media and AI have on human rights is how different approaches to improve AI on social media has been proposed. Many hope to change the problematic situation dealing with social media violating human rights with machine learning. Big Data analytics have also been enhanced by rapidly improving AI capabilities in pattern matching, increasingly delivering societal level impacts, rendering individual consent an even less effective mechanism for governing negative consequences of data processing. Government officials are also holding requirements to trusting AI to handle such as non-discrimination, respect for privacy, robustness, and safety are already subject to existing regulation or are well aligned with commercial company requirements. Many people also state how technology already delivers many benefits. Some of the benefits being its value for human rights and development is enormous. It helps connect and communicate around the globe, and empowers, informs and investigates. It can be used and sorted into communications, satellite imagery and data streams to directly defend and promote human rights. Others also state how human rights, social media, and human rights have been key successes in the use of these tools for documentation and advocacy in the past decade, including greater participation, more documentation, and growth of new fields around citizen evidence and fact-findings. People also want to use Machine learning for tracking illegal wildlife trade on social media.

Artificial intelligence has been one of the most valuable tools in technology. It deals with a lot of things, one of which was mentioned human rights and social media. They build off of each other and at the end all connect. The effects of human rights social media on artificial intelligence is still an ongoing process. It has its negative and positive effects. Since the world in a few years will be run by AI, with no human taking lead they are trying to make amends to the problems while also extracting from it as for the bad effects. Some cons just can’t be changed or solidified, or people yet have to come with solutions. Even though there are different sides dealing with the same topic, articles have different viewpoints and there is a middle ground for the articles as they all want the best for what the future beholds.

I’m super excited to talk to you today about the present and future of artificial intelligence. Whenever there’s a buzzword and a complex subject matter it’s usually good to start with a definition but it’s actually a little tricky because the definition of artificial intelligence seems to be constantly moving.

We are in the world now where research has actually shifted largely from playing games, which is still an important area and can feature some things – things that we didn’t used to consider as that much of high intelligence. Just understanding spoken words seems relatively simple. We can all do it but that was actually a hard problem until 2010 when deep learning changed it and is able to make much more progress on this and now we don’t call it AI anymore. It’s just Siri. It’s just a speech recognition software but that was a really hard problem that we weren’t able to solve and there’s still some tricky issues in research in it.

Another area where deep learning has made a huge amount of progress in recent years is computer vision, namely image classification. One of the most important ideas of recent years in the AI is to have so-called end-to-end trainable models where we take in raw input for instance, the pixels of an image and want to predict a final output for instance is there a cat or a dog or house or clock in that image and so as we put that raw input the pixels into these models they keep trying to learn more and more complex representations. As they start looking at the pixels the first layer might only identify simple edges and blobs which actually turns out to also have good correlation to the early visual cortex in the human brain but then as they go to the next layer they combine these blobs and colors and edges to more complex textures and then as they go further and deeper into these different layers they’ll identify object parts and eventually combine those object parts to identify full objects. Now we’ve actually been able to combine in computer vision even with some language processing and we can do quite amazing things.

In the medical field particular oncology this is a small start-up that actually is automating blood cell counting so you can make very small pricking your finger and you can count blood cells. People actually sit there and for each blood sample count how many red or white blood cells they are now that you can make this much cheaper. You can identify infections and help patients with leukemia and so on.

In general I think radiology will also have a huge impact with AI the problem with radiology is that we need a lot of trained data because unlike in a blood scan or pathology scan you’re looking for a thousand different things that could be wrong. In a head CT scan and it will take us a while before we could automate that entire process so for a very long time AI will work together with radiologists to improve that process and in fact we already know that we can identify certain things that can very quickly kill you. So for instance a stroke or a so called intracranial hemorrhage, brain bleeds, those we can identify very quickly and then without knowing all the other things that might be wrong in a head CT scan we can put those to the top of the queue in an emergency room setting and that can already save lives.

Now we talked about computer vision and speech recognition as two successes of AI. There are actually still some areas that we’re struggling with and that is motor control. In deep learning there are some active areas of research that we still work on and one of them is text summarization. It’s actually a really tricky problem. In a model that exists in the past can only generate at most a sentence coherently. What’s fascinating here is the summarization algorithm learned to some cases copy and paste particular words, sometimes entire phrases but sometimes it also picks and chooses which words to pick from which area of the longer document. In order to generate the summary in many cases actually generates coherent longer document summarized summaries and this still remains an open research problem.

AI power language capabilities will allow us to improve our communication in the next couple of years where we talk in one language and we listen in another one coming live at the other end. We can improve access to information. In fact, we’ll be able to automate most of the basic human needs like food, we can automate farming with computer vision and some simpler robotic control, and we can build houses automatically and so on.

As human intelligence and productivity gets enhanced it will lead us to a future where we can focus on unique and creative tasks and those kinds of tasks that require empathy and where we care for each other and we can basically automate a lot of the boring treachery that is out there.

Artificial Intelligence (AI) is the simulation of human intelligence and computation in machines, especially computer systems. These such processes include learning, reasoning and self-correction. There is AI all around us, from self-driving vehicles to virtual personal assistants on mobile devices such as Apple’s Siri.

A.I can be categorized into two different groups: weak AI and strong AI.

Weak AI are systems that are designed for specific tasks. They are able to sense things similar to what they know and classify them accordingly. This presents a human-like experience however this is just a simulation. The AI may not understand your commands but follows an algorithms in order to respond to your requests. A very good example of a weak AI is Apple’s Siri, which has the Internet behind it serving as a powerful database. Siri seems very intelligent, as it is able to hold a conversation with actual people, even giving sarcastic remarks and a few jokes, but actually operates in a very narrow, predefined manner.

Strong A.I on the other hand can be described as a machine that could fool a human into thinking it is also human. Strong A.I are machines that are capable of experiencing consciousness. They are perceived to have human cognitive abilities. When a strong AI is presented with a problem, it proceeds to find a solution without human intervention.

In 1980, philosopher John Searle published an argument in the journal The Behavioural and Brain Sciences that has now become one of the most well known arguments and thought experiments in recent philosophy. The argument entails an individual seated in a room. The room is completely sealed except for a little slot that allows for messages to enter and exit the room. The individual in the room speaks only English and no other language. The individual is provided with a book with Chinese characters and responses to such characters and instructions on what to do. Someone slips a message in Chinese into the room and the individual must create a response using the book and the instructions without knowing any Chinese whatsoever. The individual is capable of producing a string of characters that reply to the Chinese message and henceforth, fooling the individual outside. The person outside is lead to believe the individual inside the room is Chinese even when they are not.

The Chinese room argument plays a significant role in the computer science community. Searle’s experiment is created in an effort to argue against strong AI. Searle says “The point of the argument is this: if the man in the room does not understand Chinese on the basis of implementing the appropriate program for understanding Chinese then neither does any other digital computer solely on that basis because no computer, qua computer, has anything the man does not have.”

Similar to a computer, the individual in the room follows a set of instructions to reply to the individual outside. He does not know what he is saying or what the messages mean however, he is capable of fooling the individual outside that he speaks fluent Chinese. This is directly related to computers such that strong AI may seem like it has knowledge however, it is merely following a set of instructions provided. To the outsider user, strong AI may be seen to have cognitive thinking skills and the ability to understand what it is being asked to do however, like the individual inside the Chinese room, it does not understand its request and only provides a response to the task by following the set of instructions it has been asked to do.

In the original BBS article, Searle identified and discussed several responses to the argument that he had come across in giving the argument in talks at various places. As a result, these early responses have received the most attention in subsequent discussion. There are seven main responses to the Chinese argument: the systems reply, the virtual mind reply, the robot reply, the brain simulator reply, the other minds reply, the intuition reply.

The Systems Reply argues that the man inside the room does not understand any Chinese whatsoever however, replies continue. The man is just a part of the larger system. Hence, the man can be described as the CPU, the book with Chinese characters and the instructions being the database. These make up the larger system. The Virtual Mind Reply argues whether understanding is created, not necessarily in the mind of the individual inside the room. The Virtual Mind Reply holds that a running system may create new, virtual, entities that are distinct from both the system as a whole, as well as from the sub-systems such as the CPU or operator.

The Robot Reply argues that we put a digital computer in a robot body, with sensors, such as video cameras and microphones, and add effectors, such as wheels to move around with, and arms with which to manipulate things in the world. Such a robot—a computer with a body—could do what a child does, learn by seeing and doing. The Robot Reply holds that such a digital computer in a robot body, freed from the room, could attach meanings to symbols and actually understand natural language.

The Brain Simulator Reply argues that the program implemented by the computer or the person in the room does not represent information that we have about the world but simulates the actual sequence of neuron firings at the synapses of a Chinese speaker when he understands Chinese and gives answers to them. Surely then, we would have to say that the machine or the room understood Chinese or else we would also have to deny that native Chinese speakers understood Chinese since at the level of the synapses there would be no difference between the program of the computer and the program of the Chinese brain.

The Other Minds Reply argues that the behaviour of the room mimics anyone else who actually understands Chinese. Since the room is behaving in this way, it should be credited with understanding Chinese too.

The Intuition Reply argues that the Chinese room argument depends on the assumption that certain things such as the man in the room or the computer are incapable of thinking or having understanding. Henceforth, they are incapable of learning Chinese.

From the expansive world of technological reality delivering Artificial Intelligence (AI) to the truth of fading humanity killing Emotional Intelligence (EI), we need to respond to the ways in which the millennial’s world is shape-shifting, and what lies ahead. Formal education is not enhancing the learner’s ability to live a good life, have peace with oneself and others, and become a worthy member of society. Linking education with commercial objectives, we are only educating the left side of the head and not the heart.

A couple of years ago an unique experimental self driving car was released on New Jersy roads, that was not coded or programmed by engineers. The car sensors were connected to a huge network of artificial neurons that processed data and delivered command to the brake, steering wheel and other sub-system. This car was developed by chip maker NVidea, did not need any human intervention. With this technology, referred to as deep learning, artificial is advancing to a level where systems become so intelligent that they surpass human capabilities and comprehension. If this happens as physicist Stephen Hawkins has anticipated “A supper intelligent AI will be extremely good at accomplishing its goals, and if those goals aren’t aligned with ours, we were in trouble.”

Elon Musk seems to agree. In a YouTube video on the subject he sounds an alarm bell: “if AI becomes smarter than a person, what do we do and what jobs will we have? Will AI take over our world? How worried should the human race be? As per the World Economic Forum report published in 2016, about five million jobs will be lost to robots and automation by 2020. These predictions may come to pass. But let’s look at the man-machine debate more objectively. It’s true that super-computers such as Waston can process data, recognise patterns and thereby learn by itself at a faster rate than a human brain. But such machine learning capabilities which are integral to AI require massive amount of data.

Who creates this data? Most often than not, especially in Greenfield areas, humans are the original creators. If there is no data, there is no AI. How does AI learn? It teaches itself by repetition, logical progression and sequencing that enables it to decipher higher level patterns at lightning speeds for problem solving and decision making. By that token, AI has phenomenal power to substitute repetitive tasks that require sequential logic.

A recent survey of AI is likely to transform the workplace confirms this proposition. Decision makers in India indicated some of the jobs that could be outsourced to AI powered to digital assistants: writing and responding to e-mails, entering timesheets, scheduling calendars and some routine accounting, billing and HR tasks. Though AI can process billions of data points to arrive at an efficient decision in a blink of an eye, the contextual, emotional and intuitive aspects of the decision making still remains the prerogative of the human race. In fields that need creativity and out of the box thinking, human judgement will be hard to replace.

The perspective offered so far pitches man and machine in two different camps, with the debate focusing on who will reign supreme. But recent developments in the field suggest it doesn’t have to be that way. There can be a third side. The merging of man-machine to create a powerful combined force. Elon Musk has already founded a company called Neuralink, which is in process of discovering and developing devices that can connect to the brain. Ray Kurzwell, a futurist and Google’s AI guru, believes the world is experiencing one of the most peaceful times in history since World War – II. While hunger rates are lower than what they were in past, technology has lifted millions out of poverty and made it possible for three billion people to have smartphones.

He thinks the human race is at an evolutionary inflection point where man and machine will become one in the near future. Instead of being in separate camps and humanity living in existential fear of whether AI will take over our world, he believes “Robots will go inside our brain and connect to our neocortex by the year 2029.”

Abstract

We have tried to give a short summary of what intelligence is, and then we have compared the key components which separate the human intelligence versus the artificial one. Different examples of contemporary AI agents have helped us illustrate the pace in which the field is being developed. Parallel to this development, many risks have appeared concerning the future of human civilization. We have also tried to present a solution to the addressed issue, based on our research in this field.

Introduction

The definition of intelligence

Intelligence has been defined in many ways including: the capacity of logic, understanding, self-awareness, learning, emotional knowledge, reasoning, planning, creativity and problem solving. More generally, it can be described as the ability to perceive or infer information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context.

AI (breviation for Artificial Intelligence) – a very recent subject in science, goes even deeper towards this particular phenomenon. Besides studying the human intellect, AI also aims to construct computational machinery capable of human-like or even beyond (human-like) rationality and behavior.

The definitions that were coined to define artificial intelligence are divided in four groups:

Thinking Humanly, Acting Humanly, Thinking Rationally and Acting Rationally. See picture below for popular definitions on these groups.

Comparison between HI and AI

Main comparison between HI and AI

The principle of how human intelligence works is very similar to the artificial intelligence one. In humans information is transmitted by electrical signals along neurons’ axon. The neuron is the basic working unit of the brain. It is a specialized cell designed to transmit information to other nerve cells, muscle or gland cells. In Artificial Intelligence a similar way of processing information is called the ANN (Artificial Neural Network), which is based on artificial neurons, modelled by the type found in humans.

The ability for humans to learn relies on work of large network of areas in the cerebral cortex which supports our ability to learn and consciously remember everyday facts. AI agents on the other hand have a different way of learning their tasks. Below we have listed the types of machine learning:

Supervised machine learning – With this method the machine can learn from activity in past events and then produce new data. This works with given labeled data which then get processed and predict an output in the future. In the final phase the end result compares with the intended output in order to fix errors.

Unsupervised machine learning – In contrast to the previous example, the machine in this case is given unlabeled sets of data. It cannot provide an intended output, but it can create meaningful structures from unspecified information. (ex. Pictures, Video, Audio etc.)

Semi-supervised machine learning – This method is a cross between supervised and unsupervised machine learning. For this method both unlabeled and labeled sets of data are given, with the labeled ones serving as a training for how the machine will process the unlabeled ones for future predicaments.

Reinforcement machine learning algorithms – With this method the machine interacts with its environment by taking action and discovering whether the result is a failure or success. Through trial and error the machine optimizes it’s path of dealing with the specific task. This is reinforced by rewarding the machine when it performs well, also known as a reinforcement signal.

Comparison of HI vs AI divided in five different fields

Energy Efficiency Comparison. The human brain requires 25 Watts to function, whereas a typical machine uses 2 Watts for its learning mechanism.

Universal Comparison. Humans usually learn how to manage hundreds of different skills during their lifetime, whereas AI is usually designed to perform a few amount of tasks.

Multitasking Comparison. Human worker works on multiple responsibilities, whereas the time needed to teach a system on each and every responsibility is considerably high.

Decision Making Comparison. Humans have the ability to learn decision making from experienced scenarios. Even the most advanced robots hardly compete in mobility with a six-year old child, after sixty years of research and development of the field.

State Comparison. The human brain is analogue, whereas computers are digital.

AI Agents

We are providing our paper with two examples of Artificial Intelligence development in the last decade, to help describe the position in which the field finds itself today.

AlphaGo

AlphaGo, developed by Google DeepMind, is the first computer to have won against a professional player of the abstract strategy board game Go, thus earning the title as the best player in the world.

Using only the search tree method to win a game in Go, is practically impossible, because there are 10 to the power of 170 possible configurations of the board. To tackle this problem, the developers of AlphaGo combined MCTS (Monte Carlo tree search) with deep neural networks, which function with different layers containing millions of neuron-like connections. AlphaGo played a vast number of strong amateur games in order to have a better understanding on how human reasoning works, then it played against different versions of itself, learning by trial and error in order to improve the gameplay. We earlier defined this method as reinforcement learning.

In 2015, AlphaGo beat Lee Sedol in Go, in a five-game match winning four games and losing one, marking the first case in which AI won against a professional human player of the game. It’s successor AlphaGo master beat Ke Jie in 2017, the number one player in the world, thus being awarded as a professional 9-dan Go player by the Chinese Weiqi Association.

After the match between AlphaGo and Ke Jie, Google Deepmind retired AlphaGo in order to continue studying the AI field. Later on they announced AlphaGo Zero, which ran without human data, beating AlphaGo in a 100-0 winning streak. It achieved the level of AlphaGo Master in 21 days and surpassed all the older versions within 40 days. DeepMind even developed an appropriated version of the AlphaGo Zero algorithm, the AlphaZero, which in a timespan of 24 hours, became the best player of chess, shogi and Go, and a 3-day version of AlphaGo in each case.

Sophia – the robot

Sophia is a social robot that uses artificial intelligence to see people, understand conversation and form relationships.

It can crack jokes, make facial expressions and seemingly understands what’s going on around it . It can learn from one experience and apply that knowledge to new situations, as humans do. Sophia’s software can be broken down in three configurations:

• A research platform for the team’s AI research. Sophia doesn’t have witty pre-written responses here, but can answer simple questions like “Who are you looking at?” or “Is the door open or shut?”
• A speech reciting robot. Goertzel ( the CTO of Hanson Robotics), says that Sophia can be preloaded with text that it will speak and then use machine learning to match facial expressions and pauses to the text.
• A robotic chatbot. Sophia also sometimes runs a dialogue system, where it can look at people, listen to what they say and choose a pre-written response based on what the person said and other factors gathered from the internet like the crypto currency price.

For the last configuration Goertzel says “She is piecing together phrases in a contextually appropriate way, but she doesn’t understand everything she’s saying.”

Conclusion

The potential occurrence of future risks by the development of AI

These Artificial Intelligence entities which we have described, serve as an illustration of how fast the field is developing. This pace has raised a numerous amount of questions and concerns for future well-being of humans. Many influential contemporary scientists and entrepreneurs i.e multidisciplinary businessman and engineer Elon Musk or the late theoretical physicist Stephen Hawking, have ranked AI as the biggest risk that the human civilization might face. The problem arises greatly if the Superintelligent hypothetical agent will come in existence. The definition of Superintelligence states that an AI agent will exceed human intelligence and will dominate across all tasks. This concept is believed to happen since human cognition is evolutionary mechanical system and therefore can be emulated on synthetic materials. If evolutionary algorithms will take place in the formation of this intelligence agent, that means that the machine will be able to improve itself over and over again with a faster pace compared to the time which natural evolution happened to humans. Another factor of greater dominance is the “body” of AI agents. They are not made out of organic matter and is prior to survive on significantly less resources. An example of risk would be the hijacking of internet by an AI attacker, which would be able to post fake news, manipulate situations and wage wars between people.

A possible solution and AI contributions in humanity

The solution that we are presenting towards these matters suggest that AI scientists should carefully develop machines and robots only to be able to live in a healthy symbiosis with them, to aid the human evolution in other forms and improvement of abilities. There are many fields in which AI is currently delivering a positive contribution for humanity for example:

Medicine

Medical Artificial Intelligence (AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. AI has the capability of detecting meaningful relationships in data sit and has been widely used in many clinical situations to diagnose, treat and predict the results.

AI-assisted robotic surgery

Robot assisted surgery is considered “minimally invasive” so patients won’t need to heal from large incisions. Via artificial intelligence, robots can use data from past operations to inform new surgical techniques. The positive results are indeed promising. A robot was used on a eye surgery for the first time, and the most advanced surgical robot, the Da Vinci allows doctors to perform complex procedures with greater control than conventional approaches. Heart surgeons are assisted Heartlander, a miniature robot, that enters a small incision on the chest to perform mapping and therapy over the surface of the heart.

Virtual nursing assistance

From interacting with patients to directing patients to the most effective care setting, virtual nursing assistance could save the healthcare industry $20 billion annually. Since virtual nurses are available 24/7, the can answer questions, monitor patients and provide quick answers. Most applications of virtual nursing assistance today allow for more regular communications between patients and care providers between office visits to prevent hospital readmission or unnecessary hospital visits.

Image analysis

Currently, image analysis is very time consuming for human providers, but an MIT-led research team developed a machine learning algorithm that can analyze 3D scans up to 1000 times faster than what is possible today. This near real-time assessment can provide critical input for surgeons who are operating. It is also hoped that AI can help improve the next generation of radiology tools that don’t rely on tissue samples. Additionally, AI image analysis could support remote areas that don’t have easy access to healthcare providers and even make telemedicine more effective as patients can use their camera phones to send in pics of rashes, cuts or bruises to determine what care is necessary. When saving minutes can mean saving lives, AI and machine learning can be transformative not only for healthcare but for every single patient.

Education

AI has had many applications in educations systems. It helps teachers fill the gaps in administrative works and lets them be more efficient contribution in human capabilities where AI cannot perform well, thus creating a symbiosis which offers a more advanced tuition in schools and universities. Students profit from AI as well, gaining help in areas which they are lacking, extracurricular activities, getting tested for a better differentiation in their professional aspect and also receiving feedback from tests in interactive platforms.

Economy

AI offers different solutions for occurring problems in the field of business as well. For example it can:

• Predict the vulnerability of a specific software and prevent external attacks for days even weeks ahead. AI performs in cybersecurity much more efficiently than a firewall or an AV data because of its ability to work automatically without prior knowledge or pre-programming to find and exterminate anomalies.
• AI can be used to reduce energy usage and costs for large industries. It has already been used to reduce costs for drills, natural gas transportation and refining of energy sources such are oils or petroleum.
• Customer responses have been given as input for AI agents and in return they have inferred structures containing qualities and attributes that correlate with the response rate and the engagement of individuals in the matter. Intelligent chatbots and conversational interfaces have been built to provide information for customers. Advancements in deep learning algorithms and methods are especially (Wikipedia, 2018) (Stuard Russell, 2009)

References

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For quite some time, specialists have worried about the unforeseen impacts of artificial intelligence (AI) on humanity. Warning perspectives on the possible frightening future extend throughout all means of communication. Generally, these tragic predictions have brought up the need for a more ethical execution of artificial intelligence; that some way or another designers should make AI systems with a feeling of morals. Some specialists say we can fabricate our future man-made robots to differentiate good from bad, always act legitimately all by itself, and even help real people in trouble.

However, not only this prospective seems to be still many years away, but there are also a lot of doubts regarding how, if even possible, we will be able to achieve this degree of engineering understanding. What is more important right now, is to take a look at our current AI systems and how they are fabricating their moral choices in everyday circumstances.

Training ethics to AI is extremely difficult since it’s even hard for humans to agree on what’s morally correct. When in ethical problems, people generally depend on gut feeling, robots, on the other hand, need exact and factual measurements.

Three practices to start creating more moral AI:

• Develop ethical principles as explicit computable guidelines.
• Gather plenty of data on human’s ethics (millions of people).
• Being more honest about AI’s ethical measurements.

AI technology is already changing our lives in several aspects such as health, security, and education. However, no matter how smart AI may become, its ways of thinking and processing information will always be different from a real human. This should make us reflect on the ethical aspects of the development of AI, especially on the convenience of giving these machines total autonomy. If (Terminator-like) gone wrong, this could be a threat to society and even humanity as a whole.

It currently looks like there are more proposed rules than actual laws set up for AI. However, as it becomes more and more important in our daily lives, experts anticipate the adoption of AI guidelines in the near future.

AI has already proven to have several benefits for businesses, governments, healthcare systems, consumers, researchers, and many others. It is expected that the advances and developments of the coming years will allow AI to achieve new functions and improve many of the tasks that we already do today, giving them complete autonomy to choose, like the now common self-driving cars. That’s why we need to focus on nurturing AI with universal principles of respect, freedom, and equality.

If even in a society, we all have different worldviews and perspectives and it is extremely complicated to find common ground on what is morally correct, for a robot who needs exact metrics and information, it is extraordinarily harder. It is imperative that we start focusing on making artificial intelligence ethical before it’s too late.

The Evolution of Technology and the Rise of Artificial Intelligence

In a world where technology plays a significant role in individual lives, technology focuses on the latest inventions and devices designed to make people daily activities easier, faster and more convenient. Technology have 4 ages, first is the electromechanical age which is designed in 183’s which mainly focus on the beginning of telecommunications. Second is the pre mechanical age in 3bc to 145 ad which focus on the age of information technology. Third is the mechanical age back in 145 to 184 where it is the era of mechanical age when we first start to see connections between our current technology and its ancestors. This explodes the interest of many people with this area. The last age is electronic age in 194 to present which basically what we currently live in. Come to think of it, do we people know what really happen back then? How our technologies evolve so fast? How people cope with this evolution? And how this technology can affects us? Basically, history of invention of tools and techniques and is similar to the other sides of history.

The Foundations and Advancements in AI: From Turing to Modern Applications

The term came from the Greek word techne which means art and craft. It was first used to describe applied arts but now it is used to describe the advancement and changes around us. It starts with the beginning of life on earth, and goes until the founding of early modern technologies, such as computer and nuclear power. We often think about technology as the latest innovation: the smart phone, the 3D printer, the VR headset. It’s only by taking a longer view, however, that we can understand its entwining with our species’ existence. For technology is more than a computer, cars or gadgets. It is the entirety of human-made artifacts that extend and amplify our grasp of the world. As the philosopher Hannah Arendt put it in 1958, we have in recent centuries developed a science “that considers the nature of the Earth from the viewpoint of the Universe”. Yet in doing so we have paradoxically trained ourselves to ignore the most important lesson of all: our co-evolution with technology. In this paper we will mainly focus in artificial intelligence and if it is a threat to humanity or not. The term artificial intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage. During the Second World War, noted British computer scientist Alan Turing worked to crack the ‘Enigma’ code which was used by German forces to send messages securely. Alan Turing and his team created the Bombe machine that was used to decipher Enigma’s messages. The Enigma and Bombe Machines laid the foundations for Machine Learning. According to Turing, a machine that could converse with humans without the humans knowing that it is a machine would win the “imitation game” and could be said to be “intelligent”. Early AI research in the 1950s explored topics like problem solving and symbolic methods. In the 1960s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities. For somehow they taught it will transform the world.

AI as Humanity’s Existential Threat: Concerns and Arguments

Speaking at mit in 214, he called artificial intelligence humanity’s “biggest existential threat” and compared it to “summoning the demon”. Upon reading that statement the writers agree that artificial intelligence is a threat to humanity. It is about building machines that can think and act intelligently and includes tools such as Google’s search algorithms or the machines that make self-driving cars possible. While most current applications are used to impact humankind positively, any powerful tool can be wielded for harmful purposes when it falls into the wrong hands. Today, people have achieved applied AI, AI that performs a narrow task such as facial recognition, natural language processing or internet searches. Ultimately, experts in the field are working towards artificial general intelligence, where systems can handle any task that intelligent humans could perform, and most likely beat us at each of them. Definitely it is a threat to humanity; it is poised to disrupt our world. Having invasion of privacy and social grading it is now possible to track and analyze an individual’s every move online as well as when they are going about their daily business. Cameras are nearly everywhere, and facial recognition algorithms know who you are. AI machines are like other human beings in terms of their capacities for decision and action. They cannot be compared to other machines as the degree of independence that AI technologies have is much more complex. AI is an attempt to reproduce super intelligent humans. It chooses one aspect of human beings, namely the intelligence, and artificially magnifies it to an extent that allows the machine to do things far better than humans can.

The Double-Edged Sword of AI: Benefits and Risks

AI is associated with superlative memory, calculative power, decision-making capacity, high speeds of action, etc. These machines thus become super-beings, and a society filled with many super-beings is a recipe for disaster. AI machines are a mirror to our desire for immortality and the absence of human weaknesses. Most importantly, the AI has not been used to get rid of poverty, to have a more equitable distribution of wealth, or to make people more content with what they have. Instead, they will primarily be dictated by profit for the companies that make them. With intelligent machines enabling high-level cognitive processes like thinking, perceiving, learning, problem-solving and decision making, coupled with advances in data collection and aggregation, analytics and computer processing power, AI presents opportunities to complement and supplement human intelligence and enrich the way people live and work. On the other hand, some of the leading scientists and thinkers have warned about ‘technological singularity’. Technological singularity refers to the belief that ordinary humans will someday be overtaken by artificially intelligent machines or cognitively enhanced biological intelligence, or both. You’ve seen a lot of science fiction movies about the negative impacts of Artificial Intelligence (Ai) and its benefits too but there will always be negative consequences along with the good. Humans are now beyond genius. It’s power that ultimately alters people’s lives. Artificial intelligence in daily tasks may generate laziness on the part of humans. If people have lost 95% of all their jobs in the world to robots, would we prefer to be substituted by a robot or another Artificial intelligence? That’s the human problem, we like the easy way. On the other side, there’s a disadvantages of Artificial Intelligence. One of these are, the kind of technologies are expensive to made and costly if there’s any problem or need to fix on machines. It is also expensive to implement some technologies or machines. Second, all human will be independent to machine that will result to human dependency on their lives. Most of the people want an easily life and mostly and instant life. Third, the rate of unemployed people will increase because of the machines works instead of human power. It will also result to poverty, and besides it is the rights of people to have a decent job especially those people who studied in particular field. Overusing and abusing the machine shows how humans are dependent to work on their own, this shows how people will not use their minds, abilities, and creativity anymore to produce or provide different things. And lastly, it can probably replace human from doing in particular workplace. By this situation, we will not recognize as a great worker because most of the people will have more trust to machines rather than humans.

Debating AI’s Future: Threat or Boon to Humanity?

In the counter view part when you understand the deeper view of artificial intelligence would this thought crossed your mind? “Artificial intelligence is made by human why will it be a threat to humanity if human made it?” The threat is not in the technology but in the humans who use such technology. For example, guns don’t kill, only people do. It should be remembered here that technology is as useful as it can be harmful. Technology will always be under our control and so we can literally pull the plug when we want. From paper to the telegraph, from steam engines to computers, human beings have always feared new technology. Yet, we know from history that we have always embraced technology eventually, to make our life better, easier. There’s no reason to believe that our future with AI will be any different. Healthcare and medicine become affordable and accessible with AI taking centre stage in telemedicine and quick diagnosis. Water and energy networks become accessible and widely usable when AI can mediate the use of different sources. Even though it can be a threat to the people around it, it still have an advantages especially to those field in community that really need some innovated materials in order to develop and improve the things around them. Some of the advantages that artificial intelligence has are first; obviously it can help the way of living of humanity. Especially in human labor, there are a lot of areas in workplace that can help to do precisely, accurately and fast the work of laborer. This kind of innovation is necessary to all agricultural field because with the help of Artificial Intelligence it can be done easily and fast because AI can work 24/7. Second, it can definitely enrich the flow of economy. These technologies helps country to develop and improve their lives to be more modernized. The progress of economy will probably increase and if possible it can have partnership to other country. And lastly, it can be program with specific skill that the machine can do, so that it can perform better and less errors. This kind of innovation can help to ease the human errors especially in a dangerous field.

All of these readings boil down to power, because people tend to believe science basically because it is science, everything in earth is science that it goes down to manipulation. As for evidences, Lewis was not anti-science, but was opposed to ‘Scientism’, which may be defined as the ‘wrong-headed belief that modern science supplies the only reliable method of knowledge about the world and also that scientists should be the ones to dictate public policy and even our moral and religious beliefs simply on the basis of their scientific expertise.’ There was a similar relation between science and culture when Lewis lived to our own. Then as now, there were: claims that science provides a view that refutes the traditional religious view. Claims that someone is anti-science if they are skeptical of certain claims made in the name of science. Claims that public policy should be guided or controlled by an elite class of scientific experts. Science as power is the most dangerous aspect of science’s similarity to magic, which threatens the future of civilization itself. The critical difference between science and magic is that science ‘works’. In discussing the tendency of science towards reductionism, Lewis noted that: ‘As soon as we take the final step of reducing our own species to the level of mere nature, the whole process is stultified. By treating human beings as the products of blind non-rational forces, scientific reductionism eliminates man as a rational moral agent. Man’s final conquest has proved to be the abolition of man.’Reductionism opens the door to the manipulation of human beings, with no effective limit on such manipulation because scientism undermines the authority of the ethical principles needed to justify those limits. Lewis demonstrates this in his science fiction trilogy. It is interesting to note that during World War 2, Lewis wrote not about the dangers of fascism or communism but about the danger of scientism. Scientism is the belief that the sciences have no boundaries and will, in the end, be able to explain everything in the universe. Scientism can, like religious literalism, become its own ideology.

Conclusion: The Power of AI and the Responsibility of Humanity

“The development of full artificial intelligence could spell the end of the human race” Stephen hawking. It is believed that the purely intelligent creatures, whether people or machines are bad for humanity. On the other hand, AI, by itself, will not destroy humanity. Whether we use AI to augment ourselves, create new species, or use it to destroy lives and what we’ve built is entirely in our hands at least for now. No matter how dangerous AI might be for humanity, it’s clear that there’s no slowing down the pace of progress. Regardless of how many deponents come out against AI, there’s no way to stop its advancement. Future discussions will help in directing AI for good rather than bad, but no matter what happens, there’s certainly no stopping the wheels of progress as they slowly grind forward. Some of people see that it will save humanity, but most of people see that it will destroy humanity. If we look around, we seem to embrace the change being brought by the technologies but we must ensure that even though we adopt those technologies, we will not abuse these machines and use those technologies in a proper way that no one will be harm. The application of being responsible of all humanity are important, we can think of a way that people will improve their lives with their own hands and not only by the power of technologies. Artificial Intelligence can destroy human if we let it happen and if it goes into wrong hand and wrong application. In a future where benefits and risks are ‘incalculable’, it will be how humans choose to use the technology that decides whether it’s good or bad. To harness the power and benefits of machine learning we need to decide what we want machines to ‘learn’ and/or do, and what questions we want them to answer. It is clearly important that controls and goals for AI are set, and that a lot more empirical work needs to be done to gain a better understanding of how goal systems in AI should be built, and what values the machines should have. It is to ensure that we anticipate any negative health and safety consequences, assess the risks, and share this knowledge to benefit the future working world. In terms of reliability emotionally we might feel more comfortable with a human behind the wheel but I suspect studies reveal the machine is more reliable in terms of performance metrics. If over-reliance is placed on technology people could become disconnected from the process. They may cease to understand how things work become de-skilled or fail to appreciate how bad things are when they go wrong. The future is yet to be unknown but one thing is for sure human should be the most intelligent thing in this world and human should be aware of the data and information that you are sharing because once you have shared something it is impossible to bring it back.

Introduction

Starting from Turing test in 1950, Artificial Intelligence has been brought on public notice for decades. It flourished and stagnated over times in the past, which followed Gartner hype cycle. However, because of the development of big data, machine learning and deep learning technology, Artificial Intelligence returns back to the stage again in the 21st century, and play a growing role in all aspects. Millions of consumers interact with AI directly or indirectly on a day-to-day basis via virtual assistants, facial-recognition technology, mapping applications and a host of other software (Divine, 2019).

History and development

When talking about Artificial Intelligence, robots jump into most people’s mind first. However, robots are just one kind of applications of Artificial Intelligence. Artificial Intelligence has a broad definition and refers to all intelligence demonstrated by machines. Therefore, Artificial Intelligence evolve into three new terms: Artificial Narrow Intelligence, Artificial General Intelligence and Artificial Superintelligence.

Artificial Narrow Intelligence, which is also known as Weak AI, is the Artificial Intelligence that implements a limited part of mind of focused on one narrow task. Artificial General Intelligence, which is also referred to strong AI, is the intelligence of a machine that can understand or learn any intellectual task that a human being can. Artificial Superintelligence usually means a hypothetical system that possesses intelligence far surpassing that of the brightest and most talented human minds. However, most of the Artificial Intelligence we talk about nowadays are Artificial Narrow Intelligence.

By the 1950s, a British polymath Alan Turing suggested that if humans use available information as well as reason in order to solve problems and make decisions, so do machines (Anyoha, 2017). Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. By text-only channel such as a computer keyboard and screen, if the evaluator cannot reliably tell the machine from the human, the machine is said to have passed the test.

Five years later, Allen Newell, Cliff Shaw, and Herbert Simon presented their proof of Turing’s concept at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI) hosted by John McCarthy and Marvin Minsky in 1956 (Anyoha, 2017). Although the conference fell short of McCarthy’s expectations, Artificial intelligence was still founded as an academic discipline since then and John McCarthy therefore was honored as one of the “founding fathers” of Artificial Intelligence.

From 1957 to 1974, AI flourished. Computers could store more information and became faster, cheaper, and more accessible. Machine learning algorithms also improved and people got better at knowing which algorithm to apply to their problem (Anyoha, 2017). However, the limitations of hardware came soon: computers did not have enough storage to require computations. The development of AI stagnated for the following several years until “deep learning” techniques and “expert systems” were popularized in the 1980’s.

AI techniques did not gain enough growth in the late 80’s and early 90’s limited by technology and funds. During the 1990s and 2000s, many of the landmark goals of artificial intelligence had been achieved. In 1997, reigning world chess champion and grand master Gary Kasparov was defeated by IBM’s Deep Blue, a chess playing computer program. This highly publicized match was the first time a reigning world chess champion loss to a computer and served as a huge step towards an artificially intelligent decision making program. In the same year, speech recognition software, developed by Dragon Systems, was implemented on Windows. This was another great step forward (Anyoha, 2017).

Today, we are living in the age of big data. Artificial Intelligence applications are everywhere.

Risk and ethical issues

The development demonstrates how AI is transforming many walks of human existence. The increasing penetration of AI and autonomous devices into many aspects of life is altering basic operations and decision-making within organizations, and improving efficiency and response times (West, 2018). However, these developments may also raise potential disruption on issues of cyber/ data security, labor market patterns, AI consciousness and other ethical issues.

Security

From the macroscopic point of view, cybersecurity was identified as a particularly fertile area for AI-enabled vulnerabilities. By feeing disinformation to AI surveillance system, adversaries could attack national security and military secrecy unnoticedly.

From the microscopic point of view, it is now possible to track and analyze an individual’s every move online. Cameras are nearly everywhere, and facial recognition algorithms know who you are (Marr, 2018). Google has nearly everything you have searched about in your browser history and Facebook knows all your connections and how you interact with them. Credit bureau has all your financial information history. How could all these companies keep your data safe without leaking out? The key to getting the most out of AI is having a “data-friendly ecosystem with unified standards and cross-platform sharing” (West, 2018). The models created by a machine learning system can generate unfair outputs, even if trained on accurate data. How could people be treated equally and fairly based on the data collected by machines? Machines and data could not be the only procedure to finish the decision-making. Human must be involved.

Labor and employment

In light of recent successes in the field of machine learning and robotics, it seems there is only a matter of time until even complicated jobs requiring high intelligence could be comprehensively taken over by machines. Since machines are cheaper and faster, technological progress will widen the income gap even further and may lead to falling incomes and rising unemployment in large segments of the population (Mannino, 2015). How to guarantee workers’ income will be a tough problem to solve when developing AI technology rapidly for the future government.

AI consciousness

A well know HBO television series Westworld caught public eyes in 2016. In an unspecified time in the future, the theme park Westworld, allows guests to experience the American Old West in an environment populated by ‘hosts’, androids programmed to fulfill the guests’ every desire. The hosts repeat their multi-day narratives anew each cycle. At the beginning of each new cycle, each host has its memories of the previous period erased. This continues hundreds or thousands of times until the host is decommissioned or repurposed for use in other narratives. Things change until a small group of hosts have retained memories of their past ‘lives’ and are learning from their experiences as they gradually start to achieve sentience. This television series is a good and thought-provoking beginning of AI consciousness: what will happen if machines have their own thoughts, feelings and self-awareness? Will they become unexpected automated weapon against human beings when they start to think about themselves? Since we still have a long way to go to achieve Artificial Superintelligence, but what happened in Westworld may not wait unile the distant future. As machine intelligence continues to advance, we need to walk the line between progress and risk management really carefully.

Standard and Regulations

In The Ethics of Artificial Intelligence, both AI theorist Eliezer Yudkowsky and philosopher Nick Bostrom have suggested four principles which should guide the construction of new AIs: 1) the functioning of an AI should be comprehensible and 2) its actions should be basically predictable. Both of these criteria must be met within a time frame that enables the responsible experts to react in time and veto control in case of a possible failure. In addition, 3) AIs should be impervious to manipulation, and in case an accident still occurs, 4) the responsibilities should be clearly determined (Mannino, 2015).

Social and organizational

Those countries which have more advanced AI technologies will benefit more from technological progress and widen the gap between those without up-to-date technologies.

Network externalities and potential lock-in effects

According to U.S.News, the 10 best Artificial Intelligence companies are Nvidia Corp., Alphabet, Salesforce, Amazon.com, Microsoft Corp., Baidu, Intel Corp., Twilio, Facebook, and Tencent (Divine, 2019). Although Artificial Intelligence technology is not dominated by one leading company, it is obvious that all of the best Artificial Intelligence companies are from China and the United States and all of the US companies are from Silicon Valley and Seattle.

There is no doubt that most of these companies develop Artificial Intelligence technology because of network externalities. For example, Alphabet is the parent company of Google and several former Google Subsidiaries. Google searching engine ranking algorithms could be more and more precise when there are more and more people searching for the similar questions in Google, which also applies to Baidu. Another classic example would be shopping on Amazon. As more and more people shop various goods, it would be more precise and easier for Amazon to recommend related stuff after one purchase to “tempt” customers to spend more money.

It is becoming a winner-takes-all market but since we are still in the Artificial Narrow Intelligence era, there are way more to develop and explore. Therefore lock-in effects won’t be happened in a short period of time.