AI Coding with ChatGPT (and others)

Artificial intelligence (AI) has been changing many job functions and industries over the last decade, and software development is no exception. While many thought jobs such as truck operator, factory employee, and cashier would be among the first to be replaced by automation, most people probably did not add software engineer to that list. Yet, several AI and machine learning (ML) tools, including OpenAI, ChatGPT, GPT-3, and GitHub CoPilot, are currently used for development by thousands of software engineers. Most of these technologies rely on tons of data to train their models, and most are continually being updated with fresh data. For instance, ChatGPT is a language model that can produce text that resembles human speech because it was trained on an enormous text corpus. Similar to this, GitHub CoPilot helps developers with their coding projects by using information from the GitHub code repository to make suggestions.

With any new technology, there are inherent risks and limitations to be aware of. I'll go over some of these drawbacks and risks associated with AI coding technologies in this post, including both developed and presently in use tools. I will also look at the possible benefits and drawbacks of new AI coding tools, as well as how they may affect the tech industry and the employment outlook for software engineers.

These AI coding tools do have some restrictions, regardless how convenient they are. Stack Overflow recently blocked posts created by AI, citing worries about incorrect information. This emphasizes the need for caution while utilizing these tools because AI-generated code might not always be trustworthy. Additionally, it's possible that AI-generated code fragments won't always work with bigger systems, which can cause issues and inconsistencies.

I've personally utilized a few AI coding tools as a software engineer, including ChatGPT and GitHub CoPilot. Although these tools can be useful and save time by delivering responses to coding questions right away, they are not without their disadvantages. The AI-generated code snippets may contain errors and false assumptions, which may cause issues later on. As a result, it's crucial to use these technologies responsibly and avoid becoming overly dependent on them.

Concerns about ethics are also raised by the rise of AI in coding. It is crucial to think about the possible effects of AI use as it becomes more common in sectors like tech and medical. The employment of AI in coding, for instance, may result in job losses and a decline in the demand for human programmers. In addition, there are worries that AI could bring bias into systems, which could have detrimental effects.

While it's true that for hundreds of years automation has been modifying and replacing job roles, it's also vital to remember that these adjustments always result in the creation of new jobs. For instance, when computers were initially invented, they took the place of specific occupations like calculators and typists. However, the development of computers has spawned entirely new sectors of the economy, including computer programming.

Similar to this, if AI coding tools become more prevalent, the role of coders may change from writing code to overseeing these tools. The ability to control and supervise the use of these tools will require that coders acquire new abilities as they become more sophisticated and capable of producing code. This could involve activities like checking the accuracy and bias-freeness of AI-generated code's output and debugging any potential problems.

The employment landscape for software engineers may alter as a result of the adoption of AI coding tools, but new opportunities are also expected to be generated. The usage of AI coding tools may result in the development of new professions and sectors, such as AI management and AI governance, similar to the historical instances of computers.

Overall, it is crucial to keep in mind that automation has always been a driving force in the economy, creating new opportunities and spurring growth, even though the use of AI coding tools may result in certain changes in the employment market. The same is expected to be true for AI coding tools, as they will not only increase productivity but also open up new learning and skill-building opportunities for software engineers.

In conclusion, AI coding is a quickly developing discipline with a wide range of possible advantages, but it also carries a number of hazards and restrictions. Software development will incorporate AI as it develops and is able to evaluate vast code repositories and systems. However, since AI-generated code might not always be trustworthy, it is crucial to utilize caution and these technologies sensibly. Additionally, it is important to think about and handle the ethical concerns of AI in coding.