The Consequences of Generative AI
2023 was a huge success for Generative AI and just AI in general. With the rise of ChatGPT, Google Bard, and other AI tools, society is now leaning more towards automation than ever before. However, this warrants a lot of concern from critics, while others are completely defending it. It is time to look at both sides of the story and gauge just how impactful generative AI is and whether this impact is positive or negative.
Productivity
As with any technological revolution in the past, critics will often question how worker productivity is affected. Does the new technology do enough to alleviate some of the labor being put on workers? And, is it sustainable and cost-effective? In the case of generative AI, everything is checked. According to McKinsey & Company, 2.6 to 4.4 trillion dollars could be added to the global economy per year in the 63 test cases they used. These cases were mainly in the IT support, consulting, and customer support fields. These fields were able to thrive under generative AI because their productivity went up. To quantify this, The Nielsen Norman Group writes that with AI, agents can handle up to 13.8% more inquiries per hour than their counterparts who didn’t use AI. Additionally, in the business sector, those who used AI could write 58% more business documents per hour. Finally, the biggest growth of them all, programmers who use AI reportedly code 126% more projects per week. Productivity has skyrocketed since the advent of generative AI and there is no foreseeable end to how much we can boost productivity.
The Stock Market
While productivity was positively affected by generative AI, the stock market could see some negatives. After all, the stock market is built on trust, and once that trust is gone, it’s hard and sometimes impossible to get back that trust. With AI being so new, trust is just not something many people have with AI. In an article by OpenGrowth, AI can lack adaptability when it comes to volatile market trends, and sudden inflations/deflations. Not only that, but AI has to be trained with data from the past and sometimes this data can be inaccurate. Sometimes stocks can spike in a matter of a day or two(like Volkswagon in 2008) and can even plummet in a day or two(like META platforms in 2022). We also have to take into account cyberattacks and cybersecurity with AI. After all, the average data breach from 2022 cost about 4.35 million dollars, which was a 2.6% rise from 2021’s average cyberattack cost. All these factors make the stock market a dangerous zone for AI. Before generative AI can be used in the stock market, one must be in a position where they are ready for cyberattacks and in a position where they place full trust in the AI.
Jobs
Similar to productivity, jobs will be positively impacted by generative AI. In another report by McKinsey & Company, 30% of hours worked at an American job by 2030 will be automated and most of it will be made up of generative AI. For partial or complete automation of a workplace, generative AI is essential. If generative AI isn’t used in American workplaces, that means that only 21.5% of hours worked would be automated whereas with generative AI, it would be close to 30% of all hours. Contrary to popular belief however, this automation doesn’t mean a complete elimination of jobs, but rather it means that workers will have to put in less time and energy in the workplace to achieve the same results as they would have without AI. However, this is all theoretical and there is one more question that will fill in the puzzle here. Will people actually adopt generative AI in the workplace and will employers spend money on AI in the beta stage? The answer is actually a surprising yes. In fact, according to Cision, 71% of employers have some idea of employees using generative AI in everyday work. 56% of people use generative AI on a daily basis too, making them better over time at using it. Not only that, it was found that 86% of those who responded to the survey likened the skills of generative AI to that of a worker. 45% said that generative AI had skills comparable to an experienced worker, 31% said it had skills comparable to a novice worker, and 10% said it had skills comparable to an expert worker. Overall the satisfaction score for generative AI was higher than expected.
Conclusion
While the present state of AI might look interesting and optimistic, it is important to note that the future of AI is merely speculation and predictions based on historical data. Not only that, generative AI is only in its early infancy stage and it hasn’t even been a year since the revolutionary generative AI, ChatGPT, was unveiled. More research, more time, and more money have to be spent in order for a more concrete version of generative AI to exist. There is also heavy backlash surrounding this topic. For example, according to the New York Times, Goldman Sachs released a report on how AI could actually harm workers' lives, the worker hierarchy, and much more. They also state how it could displace many people in smaller companies while those in bigger companies could see more benefits. It states that generative AI would create a wide social and economic inequality, one that hasn’t been seen in all of history. Not only that, a lot of the research presented in this article on the internet has not taken into consideration what happens when generative AI escapes the human realm and gains consciousness. It also doesn’t take into account the mass protests this could cause the misinformation spread throughout the world from AI. Overall, it is important to be cautious when talking about AI and to remain optimistic about its future.
