Today, we are faced with technological advancements that were unimaginable just a few years ago. The emergence of chatGPT and other software capable of creating documentation, unique images, and videos raises questions about the future of professional tasks. In 2017, economists contemplated different economic possibilities based on the speed of technological development and society’s ability to adapt to these changes. Under these conditions, they envisioned three distinct scenarios:
- Technology develops rapidly, and society manages to keep up: This is the most optimistic scenario. Technology progresses quickly, eliminating numerous simple and complex tasks while creating new markets and jobs. Society adapts rapidly and learns to perform the new tasks associated with these emerging jobs. This is also the most desirable scenario as technological development offers advantages in combating climate change, poverty, and inequality.
- Technology develops rapidly, but we fail to adapt: Technology advances swiftly, leading to exceptional economic growth, but also competition among organizations seeking to leverage this technology for increased profits. By always striving to do more, it is possible for human capabilities to reach their limits, leading companies to phase out human involvement that slows them down. This scenario is not ideal due to the inequality it can generate between the elites who retain their jobs and those who cannot compete with machine capabilities. It can also create a gap between technologically developed countries and those that are not.
- Technology develops too slowly: This is the status quo scenario. Technology continues to progress at its current pace, and society faces no challenges in adapting to new technologies. However, this is also not an ideal scenario as technological development can provide solutions to pressing problems such as the energy crisis, climate crisis, or even a future pandemic more significant than Covid-19.
The Rise of Generative AI
Generative AI, such as chatGPT, generates content using an immense database. By harnessing this database, AI recognizes common elements and trends, enabling it to “create” new content. This greatly facilitates tasks such as research, integrating research into documentation, simple programming code creation, text correction, and the production of unique images or videos.
However, chatGPT is not “intelligent” in the sense that it can use logic to arrive at conclusions. It succeeds because a human has already done so somewhere on the Internet. ChatGPT can provide us with this information quickly and easily. However, the Internet is also filled with false or invented information, whether intentionally or inadvertently. I myself have noticed that during certain searches, when I asked ChatGPT for references, it invented those references since the referenced articles did not exist at all.
We have also observed that it is easy to deceive ChatGPT and obtain false answers. For example, someone convinced ChatGPT that 1+1 equals 3 because their wife said so and she was always right.
Conclusion
What does the future of work look like after the arrival of technologies like chatGPT? Well, it’s hard to say. Generative AI can easily replace content generation tasks, simplifying the processes of information research and synthesis. This could also lead to the elimination of jobs that require specific data entry into documentation. However, these are tasks that could already be simplified through features included in software like Word or Excel but are not yet widely utilized. Therefore, it is unlikely that chatGPT will replace us in the workplace, but it will certainly facilitate our tasks, helping us to produce and learn faster than before.
