Why AI cannot solve complex coding problems
AI has become a prominent technology in recent years with the rise of ChatGPT and the development of AI bots. Although AI has become revolutionary, it is still very young and isn’t yet sophisticated enough to effectively develop accurate and complex code. There are many limitations with current AI technology, such as reliability, creativity, and some legality issues. However, with developments on the rise and AI being used outside of coding for other general purposes, it won’t be long before improvements will be made to coding AIs. Our current AIs provide some benefits, such as being used as a tool to help beginner developers learn and much more. AI has become more relevant than ever, and its direction could lead to more significant developments. However, for now, AI remains unreliable and uncertain.
Why AI is unreliable for coding
Artificial intelligence is plagued with numerous problems that hinder it from creating effective and reliable code. Many questions have been raised about the legal and ethical aspects of AI. Furthermore, with AI using open-source code and algorithms, it fails to replicate the creativity and complexity of coding. Put, AI just isn’t sophisticated enough yet.
Reliance on AI may not accommodate all coding problems
AI has become a tool for many uses, with developing code being just one of the many things it can do. However, many downsides come with using language models when it comes to coding. For example, developers that use OpenAI Codex have reported a low accuracy of 36% when it comes to producing coding solutions. This bot is specialized in code and still isn’t sophisticated enough to answer complex coding problems. In addition, developers who use AI generally have to spend most of their time reviewing and testing the generated solutions. This makes it time-consuming and, in most cases, slower than simply writing code manually.
There are legal and ethical questions when using AI code bots
Using AI code for work or personal use can raise many legal and ethical questions regarding copying and plagiarism. AI bots extensively use open-source code to learn and write their solutions. GitHub’s coding platform states, “Copilot now writes 40% of code”. With millions of users on their site, this could prove harmful by potentially causing unintentional copying or plagiarism. It’s also unrealistic to assume everyone will use AI solutions in good faith. Using AI code may potentially spark up issues with copyright infringement as not all code AI uses to learn is open source. Organizations such as the Software Freedom Conservancy have condemned the use of AI coding for this very reason.
Complex problems are too intricate for AI to break down
There are many things that coding bots need to improve in order to write complex code. First of all, AI is too dependent on the data and algorithms that it collects to write reliable code. As a result, code being written by AI would be inaccurate or biased to the problem they are given. Such as with ChatGPT, it won’t always produce the right answer and, at the same time, be bland and unoriginal while doing so. This also brings up how uncreative coding bots are. One of the biggest qualities of coding is the ability to break down problems and find creative solutions. With AI relying heavily on open-source code and algorithms, using AI-written code isn’t useful for problem-solving difficult issues.
The Future of AI
Although current AI models struggle with the more challenging aspects of coding, this may only be the case for a while. As more and more data is given to AI models and technology improves, there may be a day when most coding is done not by humans but by machines.
Current Limitations
The limitations of AI are primarily centered around how models learn, that is, through massive sets of data from many sources. This means that the code being used for AI models to learn can be faulty and contribute to the unreliability of the code produced, especially at higher levels.
Innovation in the works
More recent developments in artificial intelligence and language models have seen the combination of different models. This means that soon, models like Chat-GPT will be able to respond to text and images (including videos). Furthermore, AI models can learn how to play games, move mechanical arms, and more. Refining these incredible discoveries could reshape many fields in our world.
Another innovation on the horizon is recent developments surrounding neural networks. Neural networks are a machine learning method (how sites like YouTube or Netflix know what shows to recommend you)partly inspired by how real human brains work. Recently, a physical neural network made of the nanowire was shown to adapt ‘on the fly’. This could address one of the significant issues with current AI models, their prolonged training phase and overall inability to learn from user input instantaneously. This could mean that experienced software engineers could ‘coach’ AI and have it adapt in real time so that other users would benefit from a more knowledgeable model.
What Does This Mean for the Future of Coding?
Using AI to assist with coding may only be marginally better than writing it alone. With the possibility of errors and biased data, experienced programmers could find it to be more of a hindrance than a help. However, due to the ever-evolving nature of AI and machine learning, a future where AI can code just as well, if not better than most programmers, may be on the horizon.
How AI can be beneficial
Though artificial intelligence is still limited due to the technology being introduced recently, it still has various practical applications for the everyday person. Furthermore, due to the versatility of modern language models, it is very easy to use AI to automate or assist with many niche tasks.
The general usage of AI
Artificial intelligence is used in many ways and has become one of our most used pieces of technology over the past few years. An example of a typical usage of AI is Google Translate, allowing people to transcribe a language into a different one. Another example is Google Lens with its visual recognition, giving users the ability to upload a picture and be shown results similar to the image posted. Virtual assistants, such as Alexa or Siri, respond to the user’s voices and present the information necessary to answer the question. A more recent example would be image generation, allowing users to write a prompt and having artificial intelligence generate an image related to that prompt.
One type of artificial intelligence that is widely known to many is chatbots. Coursera, an online learning platform, writes: “Artificial intelligence refers to computer systems capable of performing complex tasks that historically only a human could do.” In other words, it is a piece of software that can replicate human conversations and can reason, answer, make decisions, and learn from the user interacting with said bot. Millions of people use chatbots to get help with problems, and oftentimes the bot will come up with a response gathered from either sources on the internet or a pre-written script.
Not only are chatbots beneficial to everyday people, but they also provide advantages for companies. According to Forbes, an American business magazine, chatbots can help businesses by lessening the need for real customer support workers. They can help consumers easily find products or services by asking chatbots, who can be available almost all the time.
AI can be used to help beginner developers.
Since software engineers create artificial intelligence, these bots are capable of helping those who are also in the computer science field by assisting with the more mundane parts of the coding process.
ZDNet states that artificial intelligence can offer suggestions to the code, speed up development time by predicting software behavior and auto-completion, and update and optimize the code. While these may sound good on paper, AI can sometimes be incorrect and could lead to more problems than solutions for the more adept programmer. However, it can serve as a great foundation for the inexperienced to get started.
Artificial intelligence is also skilled at finding bugs in code and proposing solutions to fix them. One such example of a chatbot that can find bugs and is widely known and used is ChatGPT.
As stated on the website that runs this software, OpenAI, ChatGPT is trained to follow a given instruction and provide a response in return. ChatGPT provides code debugging, which can be suitable for beginning developers who might need assistance with their code but cannot find their specific problem online.
Conclusion
While the allure of using artificial intelligence to automate or assist with code has been present almost since its inception, some caution should be given before entirely relying on AI to write complex code, especially for serious software development. The reason for this hesitancy is that as it stands, AI needs to be more reliable due to its inability to adapt quickly and its potential to give solutions that are flat-out wrong.
However, all hope is still possible regarding the potential for AI coding as innovation continues to improve the practicality and adaptability of language models. Furthermore, despite its current unreliability at high levels, basic code can be written with the help of AI, which allows non-coders to get their foot in the door when it comes to software development and learning how to code. The future is bright for artificial intelligence, but we have to weather the current era of unreliability as this young technology continues to improve.