AI: ARTIFICIAL INTELLIGENCE

Scientists have developed a new ‘mind reading’ artificial intelligence system that can decode complex human thoughts just by measuring brain activity. The AI system indicates that the mind’s building blocks for constructing complex thoughts are formed by the brain’s various sub-systems and are not word-based.

What is Artificial Intelligence? 

 Artificial Intelligence (AI) is the ability of machines to learn and reason through analogy, analyse, interpret information, recognise speech, visual perception and take decisions. In other words, AI is application of human intelligence by the machines. Artificial Intelligence is an intelligence displayed by machines. It is a division of computer science which deals with making machines or computers as intelligent as human beings. The term Artificial Intelligence was devised in 1956 by John McCarthy. It is a recreation of human intelligence processes such as the acquisition of information and rules for using the information, reasoning, and self-correction by machines, particularly computer systems.

• Back in 1956, scholars gathered at Dartmouth College to begin considering how to build computers that could improve themselves and take on problems that only humans could handle. That’s still a workable definition of artificial intelligence.
• In 2012, a team led by Geoffrey Hinton at the University of Toronto proved that a system using a brain-like neural network could “learn” to recognize images. That same year, a team at Google led by Andrew Ng taught a computer system to recognize cats in YouTube videos without ever being taught what a cat was.
• Since then, computers have made enormous strides in vision, speech and complex game analysis. One AI system recently beat the world’s top player of the ancient board game Go.

Different types of Artificial Intelligence.

§  Algorithm- machine performs a programmed/ algorithmic function.  Algorithms are used for data processing, calculations and automated reasoning. 

§  Machine learning- machine’s ability to perform with partial programming. Machines like computers can analyze and interpret information and derive logical inferences. 

§  Narrow Artificial Intelligence- machine is programmed for single set of task and it keeps executing it. Apple’s Siri or Microsoft’s Cortana fall in this category where they are designed to answer the questions they understand. 

§  General Artificial Intelligence- machine imitates human cognitive actions and is able to improve its learning abilities. This kind of AI, also known as strong AI or super-intelligence can surpass human intelligence.

§  Bot- The programme that enables the machine to perform automated tasks like adding a reminder or appointment to the calendar. 

Artificial Intelligence  in everyday life

AI is everywhere and many of us do not notice its presence, but AI has become part of our daily life. Here are a few examples:

•       Smartphones: It’s in the name. The phone has now become smart, thanks to AI – from detecting your fingerprint to suggesting apps; from auto-correcting your words to autofilling your forms. AI in the form of algorithms has made it possible for this gadget to simplify our lives.
•        Google Search: Many of us cannot imagine our lives without Google. But did you know that Google search too uses AI? How else do you think it auto-completes sentences based on your previous searches and gives you personalised results?
•        Siri, Cortana, Google Assistant: These are all virtual personal assistants that are forever present to help you out. All you need to do is call out to them and they are there at your service. They use algorithms and speech recognition to understand and respond.
•       Video Games: Yes, video games too use AI to make your gaming experience extraordinary. Imagine while playing you plan an attack but before you execute it, your enemy (the computer) counters it with its move. That’s because of AI.
•       YouTube, Netflix and Ecommerce sites: Do you see those recommended videos and products popping up on screen as soon as you log in using your ID? They appear because of AI. Complex algorithms track your searches and purchases and help the site come up with recommended products or videos based on them.
•       Facebook: We all use Facebook, and based on Artificial Intelligence, it brings back your memories from the same day several years back. It also posts those sponsored links on your newsfeed based on your searches online and your clicks within Facebook. Also, notice how it suggests tagging people automatically? It does that through a complex nine-layer deep neural network with more than 120 parameters. It has a 97 per cent accuracy rate. That’s also AI.
•       Other examples of Artificial Intelligence that we may not come across in our everyday lives are:
•       Smart Cars: Ever heard of Tesla? This car that has already hit the American roads has a feature that allows the car to self-drive.
•       With the help of AI using predictive capabilities, Tesla can be turned to auto-pilot mode. It also receives updates to better the experience.
•      Amazon’s Echo with Alexa: This new speaker brought out by Amazon comes with the virtual personal assistant, Alexa.
•       Alexa responds to you just like Siri and other assistants and communicates with you through the speaker.
•       Robots: Robotics is an evolving field that has been capturing the minds of several people. It is also a field that uses AI to help robots take command and respond to their human counterparts. From Kiva to Xiaodu to Hub, robots are being developed by several intelligent humans.

Applications 

§  Some of the major applications are seen in the creation of machines or robots that can perform human tasks without errors like autonomous, driverless cars that can prevent accidents due to human errors. As they don’t require breaks like humans, they provide higher levels of productivity in lesser time than humans.  

§  Artificial Intelligence also finds extensive and significant application in the medical science. Robots can perform complex surgeries with precision, record the huge amount of information that can be used for individualised treatments, evolved research works etc.  

§  Developing countries like India can creatively use the technology to find unique solutions for problems related to sanitation, education, agriculture etc. AI can make things easier by weather predictions and can efficiently help in disaster management. The use of automation in the banking sector has already received positive reviews. 

§  Other than efficiency, machines have advantages over negative effects of human emotions as well. They can take more rational and logical decisions than those based on various human sentiments. 

Concerns

•      One of the major concerns is the possibility of human beings losing out on employment opportunities due to machines’ ability to perform the same tasks more efficiently. Automation has already rendered a huge number of people jobless all around the world. 
•      Unemployment due to AI could have serious impact in a country like India that will have largest working age population by 2020. IT sector, with its large number of skilled and unskilled labours, is particularly being considered to be vulnerable in this context. 
•      Another major concern is about difficulties in regulation of machines in the human society. For example how can the self driven cars that crash be held accountable for their actions? 
•      Along with the human sentiments, basic human values like morality and ethics would not exist in a machine dominated world. Such a society can lose out on factors like belongingness, warmth, brotherhood etc. 
•      AI-driven automation is leading to a resurgence of U.S. manufacturing but not manufacturing jobs. Self-driving vehicles being tested now could ultimately displace many of the almost 4 million professional truck, bus and cab drivers now working in the U.S.
•      AI is being created by a very elite few, and they have a particular way of thinking that’s not necessarily reflective of society as a whole.
• §    Prosaic use of AI will almost certainly challenge existing legal norms and regulations. When a self-driving car causes a fatal accident, or an AI-driven medical system provides an incorrect medical diagnosis, society will need rules in place for determining legal responsibility and liability.

Indian Jugad

Problem-solving is at the root of a lot of the development happening in India. As many of the issues India faces — erratic power connections, sanitation, education — are not as prevalent in the Western world, foreign companies have little incentive to address them. What this does is create a unique environment where there is plenty of opportunity for the Indian tech scene to address its problems, and that is fuelling a lot of innovation.

Possible areas for Artificial Intelligence applications in Indian conditions

·         It can complement Digital India Mission by helping in the big data analysis which is not possible without using AI.

·         Targeted delivery of services, schemes, and subsidy can be further fine-tuned.

·         Smart border surveillance and monitoring to enhance security infrastructure.

·         Weather forecasting models may become proactive and therefore preplanning for any future mishaps such as floods, droughts and therefore addressing the farming crisis, farmer’s suicide, crop losses etc.

·         By analyzing big data of road safety data and NCRB (National Crime Record Bureau) data for crimes, new policies can be formulated.

·         Disaster management can be faster and more accessible with the help of robots and intelligent machines.

·         In the counterinsurgency and patrolling operations, we often hear the loss of CRPF jawans which can be minimized by using the robotic army and lesser human personnel.

·         AI can be used to automate government processes, therefore, minimizing human interactions and maximizing transparency and accountability.

·         It can be applied to study ancient literature upon medicines and therefore help in modernizing the health care with the juxtaposition of modern machines and ancient techniques.

·         In the remotest areas where the last leg of governance is almost broken, AI can do the job. For Example: in the tribal areas and the hilly areas of the northeast.

Which is the nodal organization of the government for the research work on Artificial Intelligence (AI)?

·         Centre for artificial intelligence and robotics (CAIR), is the primary laboratory of DRDO for research and development in different areas of defense, Information and Communication Technology (ICT) and is located in Bangalore. It is involved in the Research & Development of high-quality Secure Communication, Command, and Control, and Intelligent Systems.

·         CAIR came into existence in 1986.

·         Projects: NETRA- software to intercept online communication, SECOS- Secure operating system.

What are the challenges India’s Artificial Intelligence Development is facing?

·         AI-based applications are mostly driven largely by the private sector and have been focused largely on consumer goods.

·         Public-private funding model which is a success in the United States, China, South Korea, and elsewhere may be considered good for India. Presently it is not present in India.

·         Our educational system is not updated to the modern technologies and is outdated in today’s economic environment as the nature of jobs shifts rapidly and skills become valuable and obsolete in a matter of years.

·         The debate of poverty vs. technology and where to spend the most is more likely to persist until the political class takes a higher interest in real issues than trivial ones.

Impact on Humans

Artificial intelligence systems could outperform humans in all tasks within the next 45 years, according to a new study which also suggests that all human jobs will be automated in the next 120 years.

According to a survey of over 350 artificial intelligence (AI) researchers, machines are predicted to be better than us at translating languages by 2024, writing high-school essays by 2026, driving a truck by 2027, working in retail by 2031, writing a bestselling book by 2049 and surgery by 2053.

However, there is only a five per cent chance that computers will bring about outcomes that may lead to human extinction, researchers said.

The survey, by the University of Oxford in the UK and Yale University in the US, was conducted among 352 researchers who had presented their research at the Conference on Neural Information Processing Systems or the International Conference on Machine Learning - the two major conferences in the field of AI.

However, there is little evidence that AI with human-like versatility will appear any time soon.

The survey results showed that researchers in Asia typically gave shorter time frames than those in North America - predicting that AI would outperform humans on all tasks within 30 years, compared with 74 years.

This may well be an interesting demonstration of culture at work when forming opinions about technology.

Challenge for Artificial Intelligence: Ransomware

It’s clear that the world needs better defences, and fortunately those are starting to emerge, if slowly and in patchwork fashion. When they arrive, we may have artificial intelligence to thank.

Ransomware isn’t necessary trickier or more dangerous than other malware that sneaks onto your computer, but it can be much more aggravating, and at times devastating. Most such infections don’t get in your face about taking your digital stuff away from you the way ransomware does, nor do they shake you down for hundreds of dollars or more.

Despite those risks, many people just aren’t good at keeping up with security software updates. Both recent ransomware attacks walloped those who failed to install a Windows update released a few months earlier.

Watchdog security software has its problems, too. With ransomware attack , only two of about 60 security services tested caught it at first, according to security researchers. A lot of normal applications, especially on Windows, behave like malware, and it’s hard to tell them apart.

In the early days, identifying malicious programs such as viruses involved matching their code against a database of known malware. But this technique was only as good as the database; new malware variants could easily slip through.

So security companies started characterizing malware by its behaviour. In the case of ransomware, software could look for repeated attempts to lock files by encrypting them. But that can flag ordinary computer behavior such as file compression.

Newer techniques involve looking for combinations of behaviours. For instance, a program that starts encrypting files without showing a progress bar on the screen could be flagged for surreptitious activity. But that also risks identifying harmful software too late, after some files have already been locked up.

An even better approach identifies malware using observable characteristics usually associated with malicious intent for instance, by quarantining a program disguised with a PDF icon to hide its true nature.

This sort of malware profiling wouldn’t rely on exact code matches, so it couldn’t be easily evaded. And such checks could be made well before potentially dangerous programs start running.

Machine vs. Machine

Still, two or three characteristics might not properly distinguish malware from legitimate software. But how about dozens? Or hundreds? Or even thousands?

For that, security researchers turn to machine learning, a form of artificial intelligence. The security system analyses samples of good and bad software and figures out what combination of factors is likely to be present in malware.

As it encounters new software, the system calculates the probability that it’s malware, and rejects those that score above a certain threshold. When something gets through, it’s a matter of tweaking the calculations or adjusting the threshold. Now and then, researchers see a new behaviour to teach the machine.

An arms race

On the flip side, malware writers can obtain these security tools and tweak their code to see if they can evade detection. Some websites already offer to test software against leading security systems. Eventually, malware authors may start creating their own machine-learning models to defeat security-focused artificial intelligence.

Dmitri Alperovitch, cofounder and chief technology officer at the California vendor CrowdStrike, said that even if a particular system offers 99 percent protection, “it’s just a math problem of how many times you have to deviate your attack to get that 1 percent.”

Still, security companies employing machine learning have claimed success in blocking most malware, not just ransomware. SentinelOne even offers a $1 million guarantee against ransomware; it hasn’t had to pay it yet.

A fundamental challenge

So why was ransomware still able to spread in recent weeks?

Garden-variety anti-virus software even some of the free versions can help block new forms of malware, as many are also incorporating behavioural-detection and machine-learning techniques. But such software still relies on malware databases that users aren’t typically good at keeping up to date.

Next-generation services such as CrowdStrike, SentinelOne and Cylance tend to ditch databases completely in favor of machine learning.

But these services focus on corporate customers, charging $40 to $50 a year per computer. Smaller businesses often don’t have the budget or the focus on security for that kind of protection.

And forget consumers; these security companies aren’t selling to them yet. Though Cylance plans to release a consumer version in July, it says it’ll be a tough sell at least until someone gets attacked personally or knows a friend or family member who has.

The future of Artificial Intelligence

There are endless possibilities for the application of artificial intelligence but the ethical and moral concern emanating from it cannot be brushed aside. The recent debate needs to find its way to the larger public discourse where all the stakeholders of the society can discuss and understand the possibilities that AI as a scientific innovation holds.

§  The speculations about job losses because of AI can be turned around by learning from history wherein revolutionary concepts have usually led to the creation of new set of jobs.

§  Machines cannot mimic the human brain’s ability to think uniquely and come up with new solutions to problems every time. In future also this human ability to make sense of novel situations and experiences would help in regulating AI. 

§  To preserve the significant values of humanity, a regulated application of the new technology is needed to prevent its transformation into a frankenstienian concept. 

Conclusion

Despite these threats and challenges, it would be stupid to argue that Artificial Intelligence (AI) is not the future and it’s only a matter of time that machines will replace most of the jobs. It does not mean the end of the road for humanity and we have a history of technological revolutions causing social and political changes in society. In the Early years there are bound to have some fears and challenges but so was the case with the French revolution, steam engines, industrial revolutions and most recently the computers. Nevertheless, there will be more opportunities in the fields not yet known and there will be more jobs to cater to human needs. In the case of India, Innefu is one such Artificial Intelligence (AI) based company which is still in its nascent phase but soon may challenge global companies and therefore can create AI-ecosystem in India.