It seems like it was just yesterday that ChatGPT was the fresh new breakthrough piece of technology, ready to revolutionize the way we work, play, and learn, when in fact, the world’s first chatbot, Eliza the psychotherapist, was released in 1966.

From then to the release of ChatGPT, and more recently the breakout of OpenAI, computer science and related AI innovation has been progressing at a rapid pace. Though they have drawbacks, with their versatility and high potential ceiling, these advancements and the multitude of other uses of AI have revolutionized various industries and have impacted and will continue to impact, improve, and offer many benefits and opportunities to the lives of many.

How is AI used in a positive way?

AI has many uses in technology and software development. Though it’s still a very new form of technology, it has revolutionized the way that human employees engage with their work.

One significant contribution of generative AI in tech and software development is its ability to handle tedious and time-consuming tasks, allowing human workers to focus on the more complex, creative, and intellectually demanding aspects of their roles.This includes tasks such as analysis and planning, where AI algorithms can process vast amounts of data quickly and provide valuable insights for decision-making.

Generative AI also helps greatly in the development process of software. Not only can it generate enhanced code and automate and auto-complete more repetitive code, its use of natural language processing (NLP) acts as a bridge between the language of machines and humans, translating high-level, worded specifications into neat code snippets. Reducing the higher levels of human error that come with typing out code line by line on one’s own not only enhances the overall quality of the software but allows for a lowered workload and increased efficiency of developers.

But what if AI steals my job?

If your job falls into a category of being very repetitive and easily automated, it could be at a greater risk of being reallocated to AI. “Job stealing” by technology has been happening since new technology was created. For example, less than 300 years ago, there was a role in society where people knocked on windows with sticks at the same time every day — a human alarm clock, before the mainstream use of the mechanical alarm clock. Since then, many jobs have been stolen, such as those of messengers on bikes at the turn of the 20th century, when telegraphs were commercialized. And this will be a perpetually repeating cycle until humanity stops creating new technology. According to many, we are in the middle of a fourth industrial revolution and job loss is inevitable, as is job creation. People who operate these new, complex systems — overseers of large-scale machine-to-machine content creators who pioneer the new era of the technology and design industries, and even specialists in less technological fields such as ethics and sustainability — bring in a new scope to the way that AI should be used in our society.

Throughout a phase in humanity with such fast development, Saadia Zahidi, managing director at the World Economic Forum, states that the “robot revolution” will create nearly 100 million new jobs. In fact, with the increasing prevalence of AI and the intertwining of physical and digital worlds, it is logical to think that the need for “humanness” will grow in value — the market will gravitate toward the unique touch of human creativity and empathy. As AI takes on more routine tasks and optimizes processes, the distinctive qualities of human intuition, emotion, and nuanced decision-making become increasingly precious. As the roles of machines in the workforce change, the role that human workers play will too, with a high adeptness in soft skills such as people managing and critical thinking becoming more important in many jobs. Many labor-intensive skills will change, with 55% of the workforce to require extra training in the near future to adequately adapt to working alongside AI technology. Thus, while the rise of AI in the workforce may lead to job displacement and necessitate additional training for many, it promises not only new employment and innovation opportunities in an evolving, technologising society, but a newfound value for the unique quality of humanness that distinguishes man from machine.

The biases of AI

If you cast your eyes to a field of grass that is less green, due to the newness of AI both as a form of technology and as a new concept altogether, there have been many discussions about the ethical issues surrounding it. Never before has there been a form of technology that generates content and mimics a human-like decision-making structure, possessing the potential to impact society on such a broad scale, prompting profound questions about responsibility, accountability, and the ethical implications of its deployment.

Generative AI uses neural networks to identify trends and patterns in large, “training” datasets. But, just as a discerning artist infuses their creations with their intention and purpose, the output of generative AI is only as unbiased and insightful as the data it learns from. The technology, while powerful, is not immune to the inherent biases present in the data it processes. This issue becomes particularly prominent as datasets are likely to contain less or more inaccurate data of already marginalized groups or people. For instance, AI resources such as computer-aided diagnosis systems in the medical field are found to be more likely to disadvantage women and Black people, which perpetuates the cycle of racial disparities in medical care. AI predictive policing tools, which are designed to optimize law enforcement efforts, have faced heavy criticism for reinforcing existing biases in law enforcement, with historic data of locations of crimes used as training data, leading to increased racial profiling and discriminatory outcomes, especially in communities of color.

An attempt to combat these inherent biases in datasets can be seen in Google’s Generative AI software, Gemini, which had its image-generation feature removed from the platform within a month of its launch. Gemini went viral on social media for generating images of white historical figures of incorrect races, outputting racially diverse popes, as well as generating female firemen when prompted. When asked to generate images of male firemen, a set of gender-diverse images were produced instead.

Since being taken off the platform, many people have blamed the Google CEO, Sundar Pichai, for this setback, though Pichai himself was not the one who fed the data into the AI program that output these flawed and inaccurate images. So when AI does something wrong, who is liable? If a software is created that, for instance, wrongfully diagnoses a patient, convicts an innocent man, or rejects the job application of a qualified individual of a certain demographic, who should be held liable? If a software is created that produces erroneous or harmful outcomes, the question of responsibility becomes intricate and multifaceted. Is it the developer or engineer for coding the software in a way that perpetuates bias? The providers of the biased or incomplete data that is used to train the software? Organizations that use the software for not implementing adequate safeguards? Or even, such as in the case of the Google example, the CEOs and executives, for failing to enforce ethical AI practices in their organization? These questions are ever-prevalent. As a society, we must make sure we provide the right answers for ourselves and future generations.

What other generative AI is there?

Generative AI has often been used by both professionals and amateurs alike to create art: from the generation of artful images by Google’s AI tool Gemini, to a simple “Generative Fill” on Photoshop, to using AI to extend a pre-existing photo, to creating animations of 3D objects and designing characters in games and TV shows. Artists can unlock possibilities and opportunities that could not have been found without the key of AI.

For example, Jiang Guang-tao, the voice actor for the character “Vyn” in the video game “Tears of Themis,” faced a challenging situation when he was cooperating with the police during an investigation, and thus was unable to continue recording voice lines for Vyn. In a unique response, the game’s development company, HoYoverse, with the actor’s permission, utilized generative AI technology to recreate the character's voice using a database of lines recorded in the past, allowing the game developers to continue the character’s narrative seamlessly without switching voice actors, and ensuring that the character’s presence and storyline remained intact.

All in all, the uses of generative AI continue to expand and evolve, leaving an indelible mark on our society and daily lives. From enhancing productivity and efficiency in software development to fostering creativity and innovation in art and entertainment, generative AI has demonstrated its immense potential to drive positive change across various industries. AI has changed the workforce, with proficient use of generative AI leading to an all-time high in productivity and efficiency. AI has changed the way we learn and what we learn, with a growing number of students in high schools and universities learning the skills they need to succeed in a society with rapidly advancing technology. In the medical field, AI has saved lives, aiding in the early diagnosis of cardiovascular disease and cancer through its imaging analysis. As generative AI continues to advance and evolve, its impact on society and daily life will only continue to grow, with boundless potential for changing this world for the better.

Sources:

8days. (2023). Over 20 Of Hawick Lau’s Shows Could Be Deemed Unsuitable For Broadcast In China After His Voice Actor Is Arrested. [online] Available at: https://www.8days.sg/entertainment/asian/hawick-lau-voice-actor-arrested-shows-deemed-unsuitable-763136 [Accessed 23 Feb. 2024].

What is Generative AI? | NVIDIA. (2014). NVIDIA. https://www.nvidia.com/en-us/glossary/generative-ai/ (2024).

X (Formerly Twitter). https://twitter.com/mtracey/status/1760340827115553006

Carter, T. (2023, October). Workers fear AI taking their jobs, but artists say it’s already happening. Business Insider; Insider. https://www.businessinsider.com/ai-taking-jobs-fears-artists-say-already-happening-2023-10

Hiszpańska, P. (2023, August 19). Artificial Intelligence saves lives – AI is revolutionizing medicine. Billennium. https://billennium.com/artificial-intelligence-saves-lives-or-how-ai-is-revolutionizing-medicine/

Lawton, G. (2024). What is generative AI? Everything you need to know. Enterprise AI; TechTarget. https://www.techtarget.com/searchenterpriseai/definition/generative-AI

Roman, D. (2021, June 30). The future of work and the 4th Industrial Revolution - WeAreBrain. WeAreBrain. https://wearebrain.com/blog/the-future-of-work-job-market-of-tomorrow

Shine, I., & Whiting, K. (2023, May 4). The jobs most likely to be lost and created because of AI. World Economic Forum. https://www.weforum.org/agenda/2023/05/jobs-lost-created-ai-gpt/