Can A.I. really become sentient?

Written by Youtube / mygreatlearning.com / PSI editor on June 23, 2022. Posted in Current News

The short answer to What is Artificial Intelligence is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.

A layman with a fleeting understanding of technology would link it to robots. They’d say Artificial Intelligence is a terminator like-figure that can act and think on its own.

If you ask about artificial intelligence to an AI researcher, (s)he would say that it’s a set of algorithms that can produce results without having to be explicitly instructed to do so.The intelligence demonstrated by machines is known as Artificial Intelligence.

Artificial Intelligence has grown to be very popular in today’s world. It is the simulation of natural intelligence in machines that are programmed to learn and mimic the actions of humans. These machines are able to learn with experience and perform human-like tasks.

As technologies such as AI continue to grow, they will have a great impact on our quality of life. It’s but natural that everyone today wants to connect with AI technology somehow, may it be as an end-user or pursuing a career in Artificial Intelligence.

What is Artificial Intelligence? – Definition

• An intelligent entity created by humans.
• Capable of performing tasks intelligently without being explicitly instructed.
• Capable of thinking and acting rationally and humanely.

How do we measure if Artificial Intelligence is acting like a human?

Even if we reach that state where an AI can behave as a human does, how can we be sure it can continue to behave that way? We can base the human-likeness of an AI entity with the:

• Turing Test
• The Cognitive Modelling Approach
• The Law of Thought Approach
• The Rational Agent Approach

Let’s take a detailed look at how these approaches perform:

What is the Turing Test in Artificial Intelligence?

The basis of the Turing Test is that the Artificial Intelligence entity should be able to hold a conversation with a human agent. The human agent ideally should not able to conclude that they are talking to an Artificial Intelligence. To achieve these ends, the AI needs to possess these qualities:

• Natural Language Processing to communicate successfully.
• Knowledge Representation to act as its memory.
• Automated Reasoning to use the stored information to answer questions and draw new conclusions.
• Machine Learning to detect patterns and adapt to new circumstances.

Cognitive Modelling Approach

As the name suggests, this approach tries to build an Artificial Intelligence model based on Human Cognition. To distil the essence of the human mind, there are 3 approaches:

• Introspection: observing our thoughts, and building a model based on that
• Psychological Experiments: conducting experiments on humans and  observing their behaviour
• Brain Imaging: Using MRI to observe how the brain functions in different scenarios and replicating that through code.

The Laws of Thought Approach

The Laws of Thought are a large list of logical statements that govern the operation of our mind. The same laws can be codified and applied to artificial intelligence algorithms. The issues with this approach, because solving a problem in principle (strictly according to the laws of thought) and solving them in practice can be quite different, requiring contextual nuances to apply. Also, there are some actions that we take without being 100 percent certain of an outcome that an algorithm might not be able to replicate if there are too many parameters.

The Rational Agent Approach

A rational agent acts to achieve the best possible outcome in its present circumstances.

According to the Laws of Thought approach, an entity must behave according to the logical statements. But there are some instances, where there is no logical right thing to do, with multiple outcomes involving different outcomes and corresponding compromises. The rational agent approach tries to make the best possible choice in the current circumstances. It means that it’s a much more dynamic and adaptable agent.

Now that we understand how Artificial Intelligence can be designed to act like a human, let’s take a look at how these systems are built.

How does Artificial Intelligence (AI) Work?

Building an AI system is a careful process of reverse-engineering human traits and capabilities in a machine, and using its computational prowess to surpass what we are capable of.
To understand How Artificial Intelligence actually works, one needs to deep dive into the various sub-domains of Artificial Intelligence and understand how those domains could be applied to the various fields of the industry. You can also take up an artificial intelligence course that will help you gain a comprehensive understanding.

• Machine Learning : ML teaches a machine how to make inferences and decisions based on past experience. It identifies patterns, analyses past data to infer the meaning of these data points to reach a possible conclusion without having to involve human experience. This automation to reach conclusions by evaluating data, saves a human time for businesses and helps them make a better decision. To learn basic concepts you can enrol for free machine learning course for beginners.
• Deep Learning : Deep Learning is an ML technique. It teaches a machine to process inputs through layers in order to classify, infer and predict the outcome.
• Neural Networks : Neural Networks work on similar principles to Human Neural cells. They are a series of algorithms that captures the relationship between various underlying variables and processes the data as a human brain does.
• Natural Language Processing: NLP is a science of reading, understanding, and interpreting a language by a machine. Once a machine understands what the user intends to communicate, it responds accordingly.
• Computer Vision: Computer vision algorithms try to understand an image by breaking down an image and studying different parts of the object. This helps the machine classify and learn from a set of images, to make a better output decision based on previous observations.
• Cognitive Computing : Cognitive computing algorithms try to mimic a human brain by analysing text/speech/images/objects in a manner that a human does and tries to give the desired output. Also, take up applications of artificial intelligence course for free.

What are the Types of Artificial Intelligence?

Not all types of AI all the above fields simultaneously. Different Artificial Intelligence entities are built for different purposes, and that’s how they vary. AI can be classified based on Type 1 and Type 2 (Based on functionalities). Here’s a brief introduction to the first type.

3 Types of Artificial Intelligence

• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super Intelligence (ASI)

What is Artificial Narrow Intelligence (ANI)?

This is the most common form of AI that you’d find in the market now. These Artificial Intelligence systems are designed to solve one single problem and would be able to execute a single task really well. By definition, they have narrow capabilities, like recommending a product for an e-commerce user or predicting the weather. This is the only kind of Artificial Intelligence that exists today. They’re able to come close to human functioning in very specific contexts, and even surpass them in many instances, but only excelling in very controlled environments with a limited set of parameters.

What is Artificial General Intelligence (AGI)?

AGI is still a theoretical concept. It’s defined as AI which has a human-level of cognitive function, across a wide variety of domains such as language processing, image processing, computational functioning and reasoning and so on.
We’re still a long way away from building an AGI system. An AGI system would need to comprise of thousands of Artificial Narrow Intelligence systems working in tandem, communicating with each other to mimic human reasoning. Even with the most advanced computing systems and infrastructures, such as Fujitsu’s K or IBM’s Watson, it has taken them 40 minutes to simulate a single second of neuronal activity. This speaks to both the immense complexity and interconnectedness of the human brain, and to the magnitude of the challenge of building an AGI with our current resources.

What is Artificial Super Intelligence (ASI)?

We’re almost entering into science-fiction territory here, but ASI is seen as the logical progression from AGI. An Artificial Super Intelligence (ASI) system would be able to surpass all human capabilities. This would include decision making, taking rational decisions, and even includes things like making better art and building emotional relationships.

Once we achieve Artificial General Intelligence, AI systems would rapidly be able to improve their capabilities and advance into realms that we might not even have dreamed of. While the gap between AGI and ASI would be relatively narrow (some say as little as a nanosecond, because that’s how fast Artificial Intelligence would learn) the long journey ahead of us towards AGI itself makes this seem like a concept that lays far into the future.

Difference between Augmentation and AI

Strong and Weak Artificial Intelligence

Extensive research in Artificial Intelligence also divides it into two more categories, namely Strong Artificial Intelligence and Weak Artificial Intelligence. The terms were coined by John Searle in order to differentiate the performance levels in different kinds of AI machines. Here are some of the core differences between them.

What is the Purpose of Artificial Intelligence?

The purpose of Artificial Intelligence is to aid human capabilities and help us make advanced decisions with far-reaching consequences. That’s the answer from a technical standpoint. From a philosophical perspective, Artificial Intelligence has the potential to help humans live more meaningful lives devoid of hard labour, and help manage the complex web of interconnected individuals, companies, states and nations to function in a manner that’s beneficial to all of humanity.

Currently, the purpose of Artificial Intelligence is shared by all the different tools and techniques that we’ve invented over the past thousand years – to simplify human effort, and to help us make better decisions. Artificial Intelligence has also been touted as our Final Invention, a creation that would invent ground-breaking tools and services that would exponentially change how we lead our lives, by hopefully removing strife, inequality and human suffering.

That’s all in the far future though – we’re still a long way from those kinds of outcomes. Currently, Artificial Intelligence is being used mostly by companies to improve their process efficiencies, automate resource-heavy tasks, and to make business predictions based on hard data rather than gut feelings.

As all technology has come before this, the research and development costs need to be subsidised by corporations and government agencies before it becomes accessible to everyday laymen. To learn more about the purpose of artificial intelligence and where it is used, you can take up an AI course and understand the artificial intelligence course details and upskill today.

See also this video about whether Google’s AI has become sentient:

Header image: University of Alabama

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