Insight about AI is a Promise or Risk for Developers

The idea of “artificial intelligence” goes back thousands of years to ancient philosophers considering questions of life and death. In ancient times, inventors made things called “automatons” which were mechanical and moved independently of human intervention.

One of the earliest records of an automaton comes from 400 BCE and refers to a mechanical pigeon created by a friend of the philosopher Plato. In the early 1900s. Some creators even made some versions of what we now call “robots”. This range of time was when the interest in AI really came ahead. Alan Turing published his work “Computer Machinery and Intelligence”, which experts used to measure computer intelligence. The term “artificial intelligence” was coined and came into popular use at that time.

The time between when the phrase “artificial intelligence” was created and the 1980s was a period of both rapid growth and struggle for AI research. Leads to that some similar inventions on Notable dates include


Computing Machinery and Intelligence

Alan Turing published "Computing Machinery and Intelligence"  Introducing the Turing test and opening the doors to what would be known as AI. The Turing Test is a widely used measure of a machine's ability to demonstrate human-like intelligence. He proposed that the “Turing test is used to determine whether or not a computer(machine) can think intelligently like humans”.


AI research

John McCarthy created LISP (an acronym for List Processing), the first programming language for "AI research", which is still in popular use to this day.As one of the earliest programming languages, Lisp pioneered many ideas in computer science, including tree data structures automatic storage management, dynamic typing, conditionals, higher-order functions, recursion, the self-hosting compiler and the read–eval–print loop.The name LISP derives from "LISt Processor" Linked lists are one of Lisp's major data structures and Lisp source code is made of lists.


Machine Learning

Arthur Samuel created the term “machine learning” when making a speech about teaching machines to play chess better than the humans who programmed them. The Samuel Checkers-playing Program was among the world's first successful self-learning programs and as such a very early demonstration of the fundamental concept of artificial intelligence (AI).


AI boom

Most of the 1980s showed a period of rapid growth and interest in AI, labeled as the “AI boom.” This came from both breakthroughs in research and additional government funding to support the researchers. That brings us to the most recent developments in AI, up to the present day.


Neural Network

Two researchers from Google (Jeff Dean and Andrew Ng) trained a neural network to recognize cats by showing unlabeled images and no background information. To enter the image data into the model during training, we first must load an image from the disk and transform it into an array of bytes. The training program then feeds this byte array together with the label “cat” or “dog” into the neural network to learn if it is a cat or a dog.


AI and ML

AI and ML are on the front lines of the fight against the COVID-19 pandemic. Researchers are using AI and ML tools to predict the spread of the virus, to do virtual drug testing to find potential treatments among existing drugs and to design potential vaccines. Robotics even plays a role, in the use of social connectivity robots to help residents of nursing homes stay in touch with loved ones during the quarantine.



OpenAI developed DALL-E, which can process and understand images enough to produce accurate captions, moving AI one step closer to understanding the visual world. DALL·E, DALL·E 2 and DALL·E 3 are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions, called "prompts".



OpenAI announced the GPT-4 multimodal LLM that receives both text and image prompts. Elon Musk, Steve Wozniak and thousands more signatories urged a six-month pause on training "AI systems more powerful than GPT-4". GPT-4 is more creative and collaborative than ever before. It can generate, edit and iterate with users on creative and technical writing tasks, such as composing songs, writing screenplays or learning a user’s writing style.

















Evolution of AI

AI is a machine’s ability to perform cognitive functions or a robot controlled by a computer to do tasks that are usually done by human minds, such as perceiving, reasoning, learning, interacting with an environment, problem-solving and even exercising creativity.

Artificial intelligence allows machines to model or even improve upon, the capabilities of the human mind. And from the development of self-driving cars to the proliferation of generative AI tools like ChatGPT and Google’s Bard, AI is increasingly becoming part of our everyday life — and companies across every industry are investing in it.

How humans and thinking are not separatable, like computers and innovation not avoidable. How the wheel creates a revolution in agriculture, now AI creating complex construction projects for the robot-enabled assembly lines of today makes the possibility that machines might someday acquire human intelligence and strike out on their own.

Related to the article in Times of India, a recent study has concluded that there are more users of computer over 64 million lives in urban India, nearly 87% of people use the machine not just for professional work but for more for surfing, personal work and study or research work from these we can clearly understand machines and smart machines getting just an ordinary part of our lives and culture. So, it is not just humans, computers and other devices also now acquiring more skills and perception.

Machine learning is a subset of AI, which enables the machine to automatically learn from data, improve performance from past experiences and make predictions. Machine learning contains a set of algorithms that work on a huge amount of data. Data is fed to these algorithms to train them and based on training, they build the model & perform a specific task. The volume and complexity of data that is now being generated, too vast for humans to reasonably reckon with, has increased the potential of machine learning, as well as the need for it.

On the way, Generative AI is a form of machine learning that can produce text, video, images and other types of content. ChatGPT, DALL-E and Bard are examples of generative AI applications that produce text or images based on user-given prompts or dialogue.

Artificial intelligence started to be applied to real-world problems—which has serious implications for the business world. By using artificial intelligence, companies have the potential to make business more efficient and profitable. But ultimately, the value of artificial intelligence isn’t in the systems themselves but in how companies use those systems to assist humans in different following fields...

Healthcare and Diseases: AI in healthcare may also utilize data to forecast which patients would benefit from a specific treatment, resulting in a highly tailored strategy that saves time and money. It is also able to assist in minimizing the effects of the significant shortage of skilled clinical professionals by taking over some of the diagnostic tasks that are traditionally performed by humans.

Buying and Selling: One of the most common and well-known applications of machine learning in everyday life is recommender systems. Predicting customer behaviour continues to remain popular, as businesses use AI to recommend the best things to their customers. Search engines, e-commerce websites, entertainment platforms and a variety of web and mobile apps all make use of these systems. Previous purchases, item views, clicks and contextual data like location, language, device and browsing history are often used to make these recommendations.

Security and Fraud: AI may be used to improve cybersecurity in a proactive and predictable manner. It may be used to analyse millions of files and assaults to figure out what makes them tick. Companies can prevent future attacks by understanding mathematical DNA. In banking, machine learning may be used to create super-accurate predictive maintenance models that can recognize and prioritize all types of potential fraudulent actions.

Information Technology: Widespread AI applications have already changed the way that users interact with the world. ChatGPT is an example of text-to-text generative AI essentially, an AI-powered chatbot trained to interact with users via natural language dialogue. Users can ask ChatGPT questions, engage in back-and-forth conversation and prompt it to compose text in different styles or genres, such as poems, essays, stories or recipes, among others

Now let’s back jump to our main question “How is AI Replacing Humans in many working areas”. Unlike the human brain, which can handle multiple tasks at once, computers must “think” linearly to achieve this intelligence. Despite this limitation, there are many areas in which AI has already advanced beyond human intelligence. where artificial neural networks have proven that they can go above and beyond the limits of human intelligence. Following that Some fields in which AI raises its hands are…

Image and Object Recognition e.g.: capsule networks created by Geoffrey Hinton

Speech Generation and Recognition e.g.: Google released WaveNet and Baidu launched Deep Speech

Imitation of Art and Style e.g.: is an example of a company-created application that has used deep learning techniques to learn hundreds of distinctive styles.

Predictions e.g.: an example of machine intelligence that provides far more accurate predictions than humans would be Google’s Project Sunroof.

Data Entry AI-powered machines can perform data entry tasks faster and more accurately than humans.

Customer Service AI chatbots and voice assistants can handle routine customer service queries, reducing the need for human interaction.

Proofreaders and Translators Grammarly is a good example of such a tool. You can translate your writing into hundreds of other languages thanks to AI tools like DeepL and Google Translate.

Surgical Assistants Artificial intelligence (AI) and robotics advancements have opened truly revolutionary possibilities for doctors and surgeons. robotic doctors can eliminate the chances of human error in surgeries. A robot called Smart Tissue Autonomous Robot (Star) has already performed successful keyhole surgery on pigs without human assistance.

Driving Self-driving cars and delivery drones have the potential to replace jobs in transportation and logistics.

Agriculture Automated machines can monitor and manage crops more efficiently than humans, potentially replacing agricultural jobs, etc…

Thus, the above interventions of AI in the industry may lead to another serious question.

While AI has the potential to automate specific tasks and jobs, it is likely to replace humans in some areas. AI is best suited for handling repetitive, data-driven tasks and making data-driven decisions. However, human skills such as creativity, critical thinking, emotional intelligence and complex problem-solving still need to be more valuable and not easily replicated by AI.

The future of AI is more likely to involve collaboration between humans and machines, where AI augments human capabilities and enables humans to focus on higher-level tasks that require human ingenuity and expertise. It is essential to view AI as a tool that can enhance productivity and facilitate new possibilities rather than as a complete substitute for human involvement.

Well, we can never entirely predict the future. However, many leading experts talk about the possible future of AI. According to the findings of recent research, the capabilities of AI are constantly expanding. It takes a significant amount of time to develop AI systems, which is something that cannot happen in the absence of human intervention and is dependent on human intellect. Continuing this, now we have the responsibility to clarify...

AI Lacks Emotional Intelligence: Emotional intelligence is one distinguishing factor that makes humans forever relevant in the workplace. The importance of emotional intelligence in the workspace cannot be overemphasized, especially when dealing with clients A machine can't achieve such levels of human connection, regardless of how well AI machines are programmed to respond to humans, it is unlikely that humans will ever develop such a strong emotional connection with these machines. Hence, AI cannot replace humans, especially as connecting with others is vital for business growth. Some proofs are…

AI Can Only Work with Inputted Data: AI can only function based on the data it receives. Anything more than that would take on more than it can handle and machines are not built that way. Therefore, if you fear that AI may infiltrate all industries and eliminate the demand for your professional skills, you can rest assured that won't happen as AI lacks in human ability because, as already established, AI can only work with the data it receives. Hence, it cannot think up new ways, styles or patterns of doing work and is restricted to the given templates.

AI Does Not Have Soft Skills: Soft skills are a must-have for every worker in the workspace. They include teamwork, attention to detail, critical and creative thinking, effective communication and interpersonal skills, Humans are taught and required to possess these skills developing them is valuable for everyone, regardless of position. However, soft skills are alien to machines with artificial intelligence. AI cannot develop these soft skills critical to workplace development and growth.

AI Needs to Be Fact-Checked: A big problem with AI chatbots like ChatGPT is that they are often inaccurate and require fact-checking by human moderators. Granted, AI is capable of learning quickly, but it lacks common sense and is simply incapable of reasoning and contesting facts to the degree that humans can.

Summing up the AI current dynamics of as Conclusion

Finally let’s have some conclusion, many of the advantages of AI are well-known, understood and touted. And its limitations are well known too. But there are other salient features that, while not often mentioned, are worthy of our attention. AI applications can execute incredibly complicated tasks with ease. They can personalize recommendations for the next song you may enjoy Moreover, they can accomplish such tasks at levels of volume and accuracy that human experts cannot match.

At the same time, many articles have been written about humans having abilities that AI lacks. These articles often argue that humans and AI must work together since a more wide-ranging Artificial General Intelligence is not yet within reach and current AI models – which are excellent in narrow tasks – still benefit from human guidance.

So Artificial intelligence isn't something to fear. However, you must step up your game to not be replaced by AI. Upskill, stay abreast with the latest trends in your field and be innovative and creative. So, the next time you hear how artificial intelligence threatens to eliminate humans from the workforce, refer to this article and rest assured that humans will always have the upper hand over AI.

The power of human ingenuity is taking risks and betting on it.