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AI Res Art Res

The Era of AI-Generated Art and Authorship Rights

art and AI
Generated by Dezgo

Written by Isabel Cheng on Digilah (Student Tech Research)

My Bio:

Hello, I am Isabel. I am a rising junior in high school at Stamford American International School (SAIS). As AI-generated art rapidly gains popularity and advances, questions such as its ownership, copyright, and how it applies to existing intellectual property frameworks arise. Hence, I want to explore the different perspectives toward AI-generated art and how that should be applied to the law with my research article below.

Section 1: Understanding AI-Generated Art

If you are familiar with the concept of Artificial Intelligence (AI), you know that they are algorithm models that programmers train on extensive databases. They analyze vast amounts of data fed to them and learn patterns so they know how to respond to act. However, the technology itself cannot think on its own or create original ideas.

Likewise, AI-generated artworks are created through machine learning models. The databases of images and artworks they are fed with are often without the permission of their owners. With that said, how is AI-generated art affecting the artistic landscape, and where does this technology stand in terms of authorship and the legal status of AI as a creator?

Section 2: Popular Generative AI Websites

Let’s talk about some of the most popular AI generative websites. First off, is Midjourney. Launched in early 2022, it is one of the most recognized AI image/art generators. Though it has a $10-20 USD monthly subscription fee, it is known for giving the best quality pictures fast, which has attracted a substantial user base.

Midjourney Showcase Page (Source: Midjourney Feed)

Leonardo AI, also launched in 2022, has a relatively beginner-friendly interface along with refined tools for paying professionals too. Its free version operates on a token system that resets on a daily basis, allowing users to generate images based on prompts. It produces images relatively well based on the prompts, and compared to Midjourney, it is more customizable because it has a larger variety of style options.

Leonardo AI Home Page (Source: Leonardo AI)

Ideogram, another AI generator that is gaining traction, also caters to a wide audience. It has a range of pricing plans catering to users of different needs. It has a free version where you are allowed up to 10 prompts a day. Its consistent performance in text-to-image generation makes it a reliable choice for many users.

Ideogram Explore Page (Source: Ideogram AI)

Dalle-E 3 is another popular image-generative AI in the market, particularly in AI artworks like drawings and paintings. Though it is still not fully developed, you can access it via ChatGPT Plus.

Notably, Dall-E 3 is one of the few AI image generators that states explicitly on its website that it is designed to refuse requests for images mimicking living artists’ styles. They also allow creators to opt their art out of future training of their image generation models.

However, challenges remain in ensuring artists receive recognition. Is a fake death certificate enough to make Dall-E 3 accept requests for mimicking a living artist’s style? What about the artists who are unaware that their work is being used to train AI models?

With that said, let us dive into the growing concerns about the unauthorized usage of artists’ art styles to train image-generating models.

Dall-E 3 Index Page (Source: OpenAI)

Section 3: Artist Recognition and Copyright Challenges in the Age of AI

Since 2023, the advent of AI generation tools has prompted many to be curious and experiment with them. This includes artists, and an increasing number of them are utilizing these tools to enhance their own work, with some feeding their own artworks into AI systems, so that after inputting a prompt, they are able to produce a new piece of art in their own unique style, all in a matter of minutes.

One wouldn’t exist without the other, and this raises questions about the relationship between traditional and AI-generated art.

In Singapore, the Copyright Act protects original creative work. The owner who made an original art piece is usually automatically given a copyright, and they are granted the right to reproduce, distribute, and display the work.

 However, when it comes to work generated by AI, a critical question arises: Does the creator of the AI, the user of the AI, the work of artists who trained the AI, or the AI itself hold the copyright? The existing framework primarily addresses human authorship, leaving a grey area for AI-generated work.

As of now, the Singapore law does not explicitly recognize AI as the creator, which complicates ownership and copyright claims to their generated artwork.  

Furthermore, Singapore’s legal system emphasizes that copyright protection is only given if the work is original. Since AI-generated art is often trained on databases with existing art, it raises questions about whether the art it generates meets the originality requirement. This could limit the ability of artists to claim copyright over AI-generated work that they incorporate their style or elements into.

As Singapore and countries around the world navigate these complexities, there is a growing consensus that intellectual property laws need to be updated to better fit the world today. Policymakers and legal experts should work together with artists and AI experts to shape a new legal landscape that protects creativity and authorship rights in this new age of AI.

Section 4: Protecting Artists – Tools and Views

Artists are increasingly turning to AI-generative-art poisoning software such as Nightshade, Glaze, Have I Been Trained, and more to protect their work from being used in unauthorized AI training.

These tools allow creators to alter the pixels of their artworks that are imperceptibly different from human eyes but will get picked up by machine learning algorithms and act as a poisoned data sample, resulting in deformed outputs from AI models.

Glaze More Info Page (Source: The University of Chicago)

However, the development of all these poisoning tools is not perfect, and most end up compromising the quality of the artwork. Additionally, some artists view the anti-poisoning software as another unnecessary step, given that another training model could come out to invalidate this approach.

Furthermore, another perspective on AI-generated art is that there is no difference between AI learning and an artist. Most artists take inspiration from other artists anyway and make their own art as a derivative of that.

AI needs artists, but if you look at human history, modern art is built upon thousands and thousands of years of art from different cultures across the globe. Artists need artists too, suggesting that AI could be seen as an extension of this creative process.

Contrary to that though, another valid argument is the idea that AI art is theft? It’s a common consensus that it takes at least 10,000 hours to learn a new skill. Most artists invest years practicing and honing their craft, while all companies do is download datasets of millions of artworks and use them to train their algorithm models.

With that, the models can then make combinations from what they “learned” and instantly generate pieces, often profiting from it through consumers without having done anything artistic themselves.

This situation is unfair to artists, as no human can feasibly digest billions of images and create amalgamations of all of them in seconds. This could lead to a culture of complacency, ultimately stifling creativity and innovation. It is concerning to consider that all “new” and “original” art could end in the next few years if lawmakers do not adequately protect artists’ rights.

However, a lot of this issue involves how AI interacts with the current intellectual copyright laws, further driving the need for policymakers to amend them.

As previously noted, law and legal experts should work together with artists and AI experts to consider adding something like an AI Commission system or requiring AI developers to get permission/credit from artists whose art is used in training datasets.

Conclusion

In conclusion, the rise of AI-generated art is both an opportunity and a challenge for artists and the legal system. Especially with the evolution of AI technology, education, and awareness are crucial for both artists and lawmakers to navigate this new landscape.

Legal frameworks need to reform and adapt so that artists, AI, AI creators, and users get fair recognition for their contributions. As we move forward, it becomes clearer that the ambiguity surrounding artistic authorship around the world has to be changed, fostering an environment where creativity can thrive alongside technological advancement.

References

https://docs.midjourney.com/docs/plans https://leonardo.ai/

https://ideogram.ai/t/explore

https://www.midjourney.com/showcase

https://openai.com/about

https://openai.com/index/dall-e-3

https://glaze.cs.uchicago.edu

https://dezgo.com/text2image/sdxl

https://lawgazette.com.sg/feature/generative-ai

https://www.channelnewsasia.com/singapore/ai-art-copyright-law-artificial-intelligence-authorship-originality-3339396#:~:text=In%20Singapore%2C%20the%20law%20holds,concerns%20around%20protecting%20their%20work.

Most asked questions

Which are the commonly used AI-generative-art poisoning softwares?

Artists are increasingly turning to AI-generative-art poisoning software such as Nightshade, Glaze, Have I Been Trained, and more to protect their work from being used in unauthorized AI training.

How can I access Dalle-E 3?

Dalle-E 3 is a popular image-generative AI in the market. Though it is still not fully developed, you can access it via ChatGPT Plus.

Most searched queries

Midjourney

Ideogram

Leonardo AI

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Categories
AI Res Med Res

Beyond Diagnosis: The XAI Era in Healthcare

XAI

Written by Steve Shi on Digilah (Student Tech Research)

My Bio:

I am a 1st year student at Nanyang Technological University (NTU). Through this article, I aim to discuss the integration of Explainable Artificial Intelligence (XAI) in healthcare to address transparency concerns in AI decision-making. Delving into the world of XAI, the ability to explain and interpret the decisions made by AI algorithms could bridge the gap between technological advancements and the human touch in healthcare.

Introduction:

In recent years, the integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare has surged rapidly, presenting revolutionary opportunities for improving diagnostics, drug discovery, and patient outcomes. However, the escalating reliance on complex AI systems has raised concerns about transparency, accountability, and the interpretability of decision-making processes.

In response to these challenges, Explainable Artificial Intelligence (XAI) has emerged as a key player in making AI systems more transparent and understandable, particularly in the critical realm of healthcare.

In the healthcare sector, where high level of precision, reliability, and accountability are demanded, traditional AI systems are often viewed as “black boxes,” as the internal workings and processes that lead to a particular output or decision are not easily understandable or interpretable by humans, raising doubts about their decision-making processes.

In healthcare applications where lives are at stake, the lack of transparency in AI decision-making processes can lead to critical implications. This concern is addressed by XAI by providing insights into how AI systems arrive at their decisions, offering a level of transparency that is essential for fostering trust and collaboration between AI and healthcare professionals. In addition, XAI goes a step further by offering transparent explanations for medical diagnoses, unravelling the intricacies of drug discovery processes, and demystifying the decision-making landscape in clinical settings.

Figure 1: Healthcare Professional & AI

Medical Diagnosis:

One of the primary applications of XAI in healthcare is in medical diagnosis. AI systems are increasingly utilised to analyse medical images such as X-rays, CT scans, and MRIs to aid in disease detection.

However, the opacity of these systems raises questions about their accuracy and reliability. XAI steps in by generating explanations for the decisions made by AI algorithms, enabling medical professionals to verify and understand the reasoning behind the proposed diagnoses.

This transparency not only enhances the trustworthiness of the AI system but also facilitates collaboration, leading to more accurate diagnoses and improved patient outcomes.

Figure 2: Overall Pipeline of medical XAI application[1]

Drug Discovery and Development:

The drug discovery and development process are areas where XAI is poised to make a significant impact. AI systems play a crucial role in sifting through vast datasets to identify potential drug candidates for various diseases.

However, the lack of transparency in these systems makes it challenging for researchers to comprehend how a specific drug candidate was identified. XAI addresses this by providing clear explanations for the decisions made by the AI system.

This transparency empowers researchers to understand the underlying mechanisms and rationale for the drug discovery process, ultimately leading to the development of more effective and targeted treatments. The result is a streamlined drug development process that saves time and resources.

Figure 3: Illustration of AI model used in the lab[2]

Improving Patient Outcomes and Reducing Healthcare Costs:

Predicting health risks and optimizing treatment plans are vital aspects of healthcare that benefit from AI systems. XAI plays a crucial role in this context by offering transparency and understanding.

By providing clear explanations for the predictions made by AI systems, clinicians can comprehend the reasoning behind a particular decision or recommendation, enhancing clinical confidence, promote the widespread implementation of AI-based clinical decision support systems, and ultimately result in improved patient outcomes and better healthcare delivery. [3]Healthcare professionals can also make informed decisions and interventions, contributing to early disease detection, preventive measures, and ultimately, improved patient outcomes.

Additionally, the transparency afforded by XAI can contribute to reducing healthcare costs by enabling more efficient resource allocation and strategic decision-making.

Challenges in Implementing XAI in Healthcare:

While the potential benefits of XAI in healthcare are immense, implementation comes with its set of challenges. As AI systems become more complex, finding the right balance between simplicity and accuracy, is essential to ensure that the transparency offered by XAI does not compromise the reliability of AI systems.

Additionally, standardisation and guidelines for implementing XAI in healthcare[4] are also needed to guarantee the transparency and reliability of the AI systems. Furthermore, ensuring that explanations align with human models is an also ongoing area of research.

The Future of XAI in Healthcare:

As the integration of AI in healthcare continues to evolve, the role of XAI becomes increasingly pivotal. Its potential to enhance transparency, trust, and collaboration between humans and AI systems has far-reaching implications for the industry.

Ongoing research and development in XAI will likely address current challenges and contribute to the standardisation of practices in healthcare. The future holds promise for XAI to revolutionise healthcare practices, ensuring that the benefits of AI are harnessed responsibly and ethically for the betterment of patient care.

Conclusion:

Explainable Artificial Intelligence is on the verge of transforming the landscape of healthcare. From enhancing the interpretability of medical diagnoses and drug discovery processes to improving patient outcomes and addressing ethical concerns, XAI stands as a beacon of transparency in the realm of AI applications.

The integration of XAI in healthcare promises a future where AI systems work seamlessly with healthcare professionals, leading to more accurate diagnoses, efficient drug development, and ultimately, improved healthcare for all. As the journey of XAI in healthcare progresses, it is essential to continue refining its implementation, ensuring that transparency and accountability remain at the forefront of technological advancements in the pursuit of a healthier future.

References:

Göllner, S. (2022, August 11). State of the art of Explainable AI in Healthcare in 2022. Medium.

State of the art of Explainable AI in Healthcare in 2022 | by Sabrina Göllner | Medium

Zitnik, M. (n.d.). Research directions. Zitnik Lab.

https://zitniklab.hms.harvard.edu/research

Giuste, F. et al. Explainable artificial intelligence methods in combating pandemics: A systematic review. In IEEE Rev. Biomed. Eng. 16, 5–21. 

https://doi.org/10.1109/RBME.2022.3185953 (2022).

Jin, W., Li, X., Fatehi, M., & Hamarneh, G. (2023). Guidelines and evaluation of clinical explainable AI in medical image analysis. Medical Image Analysis, 84, 102684.

https://doi.org/10.1016/j.media.2022.102684

Most asked questions

What is the role of XAI in medical diagnosis?

XAI steps in by generating explanations for the decisions made by AI algorithms, enabling medical professionals to verify and understand the reasoning behind the proposed diagnoses.

What are the key benefits of integrating XAI into healthcare practices?

Integrating XAI fosters trust and collaboration, leading to accurate diagnoses, streamlined drug development and better patient outcomes.

Most searched queries

Magnetic Resonance Imaging (MRI)

Computed Tomography (CT) scan

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Categories
Ad Res AI Res

AI transforms advertising industry Dynamics

Generative AI

Written by Diem-Quynh Do on Digilah (Tech Thought Leadership).

My Bio:

Hi, I am Quynh. I am currently a 3rd year Communication Studies major at Nanyang Technological University. Back in my first year of university, generative AI was largely an unknown topic. Fast forward to the present, it is the central point of every discussion about the use of technology in communication and media. Witnessing this swift change is the motivation for me to reflect on my experience with these tools and ponder the question: Is generative AI the future of my industry?

Read my research article below:

Generative AI (Gen AI) took center stage as the prominent buzzword of 2023. This technology revolutionized every single industry for its capacity to quickly generate various types of content including text, images, audio, and more. Its extraordinary capacities led to significant workforce changes and stood behind some of the major layoffs in the past year. That said, how is Gen AI transforming the advertising landscape, and where does it stand in an industry where it does what it does best – generating text and images?

The buzz around Generative AI

Gen AI first existed in the ’60s century in the form of chatbots. However, it was not until recent years that they became widely accessible and adopted by internet users worldwide. While Gen AI can assist all sectors in their day-to-day tasks, the implication of the current technology, which is to generate various types of media, remains the most relevant in the advertising industry.

In their original forms, text generators stand as a revolutionary tool for communication specialists and advertisers with their ability to churn out ad copy and refine written pieces in no time. Image generators are also widely utilized and proven to be a cost-effective and time-efficient alternative.

But the potential of Gen AI does not stop there. Big players in the tech industries are also bringing generative AI into their products. Adobe Photoshop, the household name for all professional creatives, introduced their AI-powered Generative Fill in early 2023. This feature was widely celebrated, as it helps to significantly reduce the time spent on creating and editing media assets.

 Adobe Photoshop Generative Fill (Source: Adobe Support)

Canva, catering to non-professionals, also incorporated AI to swiftly assist users in discovering templates along with the AI image generator and other capabilities.

Canva’s Magic Studio, powered by AI (Source: Canva)

Google also introduced a new Gen AI tool for their Google Performance Max partners. This innovative tool will aid advertisers in asset creation, ad copy generation, and more.

Google’s AI-powered ads tool (Source: Google)

These tech giants saw a trend in advertisers’ habits: a desire for tools that facilitate swift content creation, allowing more time for other meaningful tasks. It is also a strategic move to cut the budget on outsourcing designers and writers and produce content in-house with the help of AI.

The confined box of AI tools

While Gen AI exhibits extraordinary capabilities, it fundamentally remains a product crafted by humans and acquires knowledge through the datasets fed into the system. Therefore, its generating capacity is limited by what is available in the training dataset.

A prominent example is a trend that blew up on TikTok. Taking advantage of the new image-generative feature of ChatGPT, users create prompts that ask AI to generate different sets of images. All went well until a user took a step further and asked ChatGPT to generate an image of a hamburger without cheese. To our surprise, AI failed at this simple task despite the creator’s effort to rephrase and work around the instruction.

The user is asking AI to create a hamburger without cheese (Video: https://www.tiktok.com/@teddywang86/video/7315228986072681733)

The internet community went wild, with many joking about how “they said AI will take over the world”. But what is left after a good laugh is the acknowledgment that AI’s capacity is limited. As most hamburgers in the training dataset have cheese, AI faces difficulty creating one without it.

Generally, Gen AI tools’ capability is limited by specific tasks assigned to them and the quality of the data used for their training. They can only perform certain tasks or only have the knowledge up until when it was trained. Those who use Gen AI in their work must have a good understanding of the limits of this technology, use it to assist only in relevant tasks, and double-check the quality of the work.

How far is AI from us?

Just as advertising professionals must undergo training and years of experience to excel at their job, Gen AI also requires training to adapt to the specific tasks that it is assigned.  It is undoubted that with enough time and investment, Gen AI will become even better at producing results and catering to specific industries, including advertising.

But in this specific case, the learning curve might be steeper for AI than it is for humans. The supporting arguments often center around two key aspects: flexibility and originality.

Text AI generators, most prominently ChatGPT, are known for their limited flexibility in writing. While they can be instructed to adopt different styles, some users remain unsatisfied or frustrated as the result does not precisely meet their expectations.

A simple instruction to ‘energize’ a piece of text may return a copy that is oversaturated with emojis and buzzwords. The absence of ‘empathy’ in current AI technology also hinders their ability to produce written pieces that effectively address the intricacies and nuances of communication tasks.

The conversation surrounding originality often involves copyright infringement. This concern originated from the fact that third-party material might have been used in the process without permission. While referencing past artworks is a common practice in the creative industry, the added touch of human creativity somewhat mitigates these concerns.

To conclude, the fact that Gen AI does not seem to have ‘creativity’ on its own will continue to pose concerns about its range of capabilities and the originality of the product created. Yet, Gen AI remains a powerful tool that can elevate human creativity by offering new ideas and bringing in new thought dimensions.

Most asked questions

Do AI tools have a confined set of capabilities?

Does ChatGPT always give satisfactory results?

How will Gen AI help the advertising industry to evolve with time?

Most asked queries

ChatGPT

Canva

Adobe Photoshop

Copyright infringement

Generative AI

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AI Res

The Transformative Role of Artificial Intelligence in Engineering

Engineering in Collaboration with AI

Written by Amar Kumar on Digilah (Student Tech Researcher)

I am Amar Kumar, pursuing BTech in chemical engineering from IIT Guwahati. Being a first-year engineering student and a tech enthusiast, I am in awe of the drastic ways technology has and continues to shape the future of engineering. Among the most revolutionary innovations, Artificial Intelligence stands out as a transformative force that is reshaping the engineering landscape. From optimizing processes to enhancing decision-making, AI has proven to be an invaluable model in the field of engineering.

https://www.ibm.com/blog/wp-content/uploads/2023/03/What-is-Generative-AI-what-are-Foundation-Models-and-why-do-they-matter-scaled.jpg

In the engineering sector, design and simulation play a pivotal role in product development and problem-solving. AI-powered algorithms have significantly enhanced these processes, making them faster and more precise. AI can analyse large amounts of data to identify patterns, optimize designs, and stimulate real-world problems with accuracy. 

With AI-driven generative designs, engineers can now explore countless design possibilities, leading to innovative solutions that were previously difficult to comprehend. This expedites the prototyping phase and ultimately reduces time-to-market for the products.

The introduction of automated systems, such as self-driving cars and unmanned aerial vehicles (UAVs), only became possible due to advancements in AI and machine learning. Engineers in the sectors of automotive and aerospace industries are at the forefront of developing such technologies. 

By combining computer vision, sensor fusion, and decision-making algorithms, automated systems can navigate complex environments, adhere to traffic rules, and adapt to changing conditions. The potential benefits of these systems are vast, ranging from increased road safety to improved logistics and efficiency in transportation. One of the best example for this is the car Tesla of CEO Elon Musk.

AI’s influence has also extended into other sectors such as healthcare, overseeing a revolution in aspects like diagnosis, treatment, and patient care. AI algorithms can analyse large datasets to identify potential drug candidates and optimize treatment plans while AI-powered medical imaging has increased accuracy in identifying diseases, viruses, mutations and abnormalities. 

In biomedical engineering, AI-driven simulations aid in designing medical devices and prosthetics, resulting in better patient outcomes and improved quality of life.

https://elearningindustry.com/wp-content/uploads/2023/03/shutterstock_736694506.jpg

In an era of growing environmental concerns, engineers are tasked with finding sustainable solutions to pressing global challenges. AI has played a crucial role in fostering eco-friendly practices across industries. For instance, it has enabled smart energy grids that optimize energy distribution and consumption. 

AI algorithms can predict energy demand patterns, allowing for efficient allocation of resources and reducing waste. Additionally, AI is used in environmental monitoring to track air and water quality, enabling early detection of pollution and facilitating remedial actions.

As a tech enthusiast and engineering student, I am incredibly excited about the role Artificial Intelligence will play in shaping the future of engineering. From transforming design processes to enabling automated systems and promoting sustainability, AI has opened a door to new possibilities and challenges for engineers across the globe.

As technology continues to advance, it is imperative for aspiring engineers to embrace AI as a powerful tool in their arsenal. By harnessing the potential of AI responsibly, engineers can drive innovation and create a more efficient, sustainable, and technologically advanced world for   generations to come.

https://www.inteliment.com/wp-content/uploads/2021/05/44-The-Real-Skills-to-Become-an-Artificial-Intelligence-Engineer-1.jpg

Most asked questions

How is AI used in environmental monitoring?

AI is used in environmental monitoring to track air and water quality, enabling early detection of pollution and facilitating remedial actions.

How AI supports the field of biomedical engineering?

In biomedical engineering, AI-driven simulations aid in designing medical devices and prosthetics, resulting in better patient outcomes and improved quality of life.

Most searched queries

Unmanned Aerial Vehicles (UAVs)

Computer vision

Sensor fusion

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AI Res

The Human Brain VS Artificial Intelligence

Written by Sharnaya Panag on Digilah (Student Tech Research)

I am Sharnaya Panag, a graduate of O. P. Jindal Global University with a Journalism and Communication degree. I am fascinated by the hold machine and IoT has on our species, knowing that what has become of us, cannot be undone. My greatest interest is understanding and writing about our Psyche and the future we will create for ourselves.

Can mankind’s unquenchable thirst to make life easier lead to our own downfall?

It was around 5 million years ago that for the first time, the planet witnessed the breakthrough of sentient life. Nature created a species so astute, one that would never act on behalf of the will of the planet, but the will of itself.

Since Man’s inception, there has been one thing that has remained constant throughout our history. If the past has shown us one thing it is that humanity will go to great lengths to create a life of increasing comfort.

We have a very deep connection with our past, as our ancestors left behind a trail of evidence to help us decode our history. The more we read, the more it helps us to communicate with the past. 

One can take a look through manifold scriptures, some pieces of literature or even just a page out of a diary, and for a moment the reader gets to delve into the mind of somebody who lived ages before they did.

This highlights the significance of reportage, why is it so important for us to report? Not just for the present, to spread awareness, but also to leave proper documentation for the future to analyse, just as we have been doing with documents of the past, trying to connect the dots of history.

Over the course of our time, man has remained invested in breaking through to new technological advances to make everyday life easier. 

Machine was created to cut down on physical labour and for the first time, the world saw the mass production of goods in rapid time.

Fast forward to 2023, and we are now sitting in a world entirely supported by machine. The time of self-sufficiency is over. In our society, our lives wholly revolve around them for the sake of our comfort. 

Phones, laptops, cars, aeroplanes, trains, ATMs, air conditioners, and heaters, are just a few appliances we use on a daily basis, without which the lives of many would crumble.

However, the invention that completely altered the course of our evolution would be the invention of the internet. 30 years ago, on the 30th of April, 1993, the World Wide Web was made accessible to the public.

It crept its way to every nook and cranny it could and now trillion gigabytes of data are in the hands of each and every human being that can afford to access it. The overall pace picked up by humanity seemed to be quicker than ever before.

This, of course, was also not enough. Mankind is always willing to test its limits. Hence came the next chapter, the creation of an artificial body, an entity in itself. The creation of machine to decrease physical labour felt inadequate. 

Man wanted life to be effortless, we consider ourselves so superior, that we refuse to even think for ourselves, therefore the creation of Artificial Intelligence. The most popular example of this would be Chat GPT, launched on the 30th of November, 2022, an AI created to help people structure their thoughts and opinions into words not written by themselves.

Artificial Intelligence is a body that has been created to think for us. To research data, store it, assimilate it, paraphrase it, and structure it in detail in the form required by the user. Chat GPT uses web scraping as a tool using automated methods to scan websites, retrieve data and synthesize it to provide the user with a well-grounded assimilation of it. 

It also has a plug-in feature which allows it to interconnect with third-party websites. Chat GPT uses the Bing API which permits two or more computer programs to communicate and uses it to navigate through the web to gather data. It can cite every source so that the user has access to every website it went through.

Students are now using Chat GPT to write their assignments, and even people working in multinational corporations use it to assimilate data and statistics. The need has become so severe that people are now using it to write mail since formatting an e-mail has become such a task.

We are dealing with an entity beyond our understanding. A trillion gigabytes of data, endless information at the fingertips of this AI. The majesty of the human brain is undeniable, but can the brain possibly compete with an AI whose brain we can potentially attribute to the entire internet?

There is nothing stopping companies from permanently resorting to using AI to achieve profitability. The wheel is already set in motion, just in the month of July of 2022, the founder and CEO of e-commerce firm Dukaan, Suumit Shah took to X(formerly called Twitter) to announce that 90% of the customer crew of his company has been replaced by an AI chatbot.

He added that the response time has dropped from a whopping two hours to just three minutes and the cost related to customer care was brought down by 85%.

Being sentient beings, our species has evolved beyond belief. We have the privilege to read or write anything we desire in detail, and we can preserve our beliefs for future generations. The world today is obsessed with taking the easy way out because of how fast-paced society has become.

In the past writers, and documentarians from all over the globe went to great lengths to collect, assimilate, and structure data. People spent years trying to extract the information necessary, going through extensive bodies of work, scriptures, research papers, articles, books, speeches, and various other documents. 

They did this all to keep the populace aware of world events, to provide them with entertainment or even just writing for fun.

At the centre of it all remains effort, and creativity. However, now there is an entity that can produce material in a matter of seconds, in turn reducing the effort we put in to educate ourselves, leading to the inevitable culmination of creativity.

Without creativity, our credibility to commit to the task will be put to the test. Our skills may fall short in the face of Artificial Intelligence. Looking at journalism and writing as an example, will man be able to make the effort and hold on to creativity?

 

The problem is that if our mind isn’t put to work, and is given constant chances to escape effort, it will lead to the impotency of the human brain. If the students of today use interfaces as a loophole to avoid the task at hand, the pattern will spread and over the course of time, it is bound to become a habit. 

In the near future, resorting to Artificial Intelligence will become the norm, just as relying on machinery, technology, and the internet became the social norm.

The facts are displayed in front of us very clearly. Humanity must be able to spot the pattern otherwise all we can do is sit back and watch our own downfall. Companies will always vouch for their profitability and benefit. It will be difficult to hold on to reality as we know it. 

There will be no jobs left for man if we accept and allow AI to become a part of our lives and the social norm. The progress of Artificial intelligence must be put to a stop or at least slowed for the preservation of the future of upcoming generations.

Resources

https://botpress.com/blog/does-chatgpt-save-data#:~:text=So%2C%20where%20does%20ChatGPT%20get,stores%20it%20in%20its%20database.

https://cointelegraph.com/news/chatgpt-can-now-access-the-internet-with-new-openai-plugins#:~:text=Join%20us%20on%20social%20networks,introduced%20by%20its%20creator,%20OpenAI

https://www.ncbi.nlm.nih.gov/books/NBK231624/#:~:text=In%20evolutionary%20terms%2C%20if%20objective,off%20from%20the%20lesser%20apes.

https://www.ndtv.com/india-news/dukaan-ceo-replaces-90-of-customer-support-staff-with-ai-chatbot-internet-angry-4197641#pfrom-instagram

https://cointelegraph.com/news/chatgpt-can-now-access-the-internet-with-new-openai-plugins#:~:text=Join%20us%20on%20social%20networks,introduced%20by%20its%20creator,%20OpenAI.

Images

https://feeds.abplive.com/onecms/images/uploaded-images/2023/05/18/48a0f3031002ea28e4913062116ef0381684423930331324_original.jpg?impolicy=abp_cdn&imwidth=650

https://cepr.org/sites/default/files/styles/16_9_small/public/voxeu-cover-image/Hartmann_Maschinenhalle_1868_%252801%2529.jpg?itok=dxF3XNKc

https://images.inc.com/uploaded_files/image/1920×1080/getty_910319072_387225.jpg

https://miro.medium.com/v2/resize:fit:1168/0*bb87estJQdKJTiqf.jpeg

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