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Why ChatGPT won't take your Python programmer job
Is ChatGPT our new AI overlord? (No, and here’s how it can help Python devs)
Hey Grokking Python readers, and happy Thursday!
Today, machine learning and artificial intelligence (AI) are changing the face of technology and our world. AI and machine learning technologies are rapidly advancing, with considerable buzz around Microsoft’s AI-powered Bing, Google Bard, and ChatGPT.
But this week, OpenAI unveiled ChatGPT-4, an updated version of its predecessor, ChatGPT-3. ChatGPT-4 comes with exciting new features — the biggest highlight being its multimodal capabilities such as image creation.
Chatbots like ChatGPT have great potential in various industries like e-commerce, medicine, and sales. But their abilities make many people nervous, including software developers.
The common worry is, will technologies like ChatGPT take over our jobs?
Not quite. While technologies like ChatGPT can be used to boost our productivity as developers, they can't replace human judgment, or fully take our jobs.
In fact, they open up many opportunities to Python developers, too!
Let's dive in.
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How ChatGPT is changing the industry
There's no doubt that tools like ChatGPT are changing the landscape of the tech industry. Let's explore some of the ways in which they do.
Making coding more accessible
Advancements in technology have made it easier for more people to become developers throughout computer science history. Abstraction methods, such as high-level programming languages, compilers, and IDEs, have enabled engineers to write human-readable code without understanding machine code.
Additionally, the evolution of AI assistants like Github Copilot shows promise in making coding a more accessible and enjoyable experience for all. These advancements are indicative of a positive trend toward making complex technologies more approachable to a wider range of people.
Benefitting from abstraction doesn’t necessarily mean that developers would be any less skilled or knowledgeable. Similarly, not knowing how a car engine works doesn't make you a bad driver, and using autocomplete doesn't make you a bad engineer. You can still build wonderful applications while benefiting from high-level languages like Python or machine learning tools like ChatGPT.
This ability to interpret human input makes ChatGPT a valuable research tool that can provide accurate results and save you from the arduous task of scouring Google search results or StackOverflow. While it's important to verify its responses, ChatGPT can still offer helpful explanations which can aid you in learning and understanding new concepts. This benefit can significantly streamline your search for relevant knowledge while coding.
For example, you might input the following query: "I'm getting a 'ValueError: Shapes not compatible' error in TensorFlow. What does it mean, and how can I fix it?"
Having been trained on a vast array of text data, including Python code and TensorFlow documentation, ChatGPT can provide a helpful response to your query. It may explain what the error message means and suggest possible solutions. It might even offer code snippets or links to relevant documentation to help you better understand and solve the problem.
Minimizing redundancy and tedium
You can expect ChatGPT to make your coding more productive and less prone to bugs. As it is continuously updated to cater to complex requirements, you can utilize it to eliminate grunt work and speed up your productivity and testing.
In fact, over the next decade, developers will see a reduction in tedious tasks thanks to the evolution of AI assistants like ChatGPT. This could include the automation of unit tests, the generation of test cases based on parameters, the analysis of code to suggest security best practices, and the automation of QA.
Similar to how APIs simplified developers' lives, ChatGPT is expected to improve efficiency similarly. As an example, Stripe's payment processing previously required developers to write 1,000 lines of code, but now only requires a single API. With AI assistants like ChatGPT, developers can automate and simplify tedious tasks, freeing up their time for more valuable work.
Limitations of ChatGPT
While ChatGPT may seem intelligent, it is important to note that it operates based on a large set of data to generate what it determines to be the most appropriate responses. As a result, it has certain limitations.
ChatGPT can't think for you
ChatGPT is a valuable tool, but it cannot replace human judgment. Its learning models rely on content fed by developers, which can sometimes be erroneous.
For instance, regardless of what code snippet ChatGPT generates, it is crucial to exercise your own judgment to ensure that it is correct and applicable to your specific problem, as with any code snippet found on sites such as StackOverflow.
With that being said, human judgment is still required to differentiate between good and bad code. While you may receive AI assistance to write code, it will never override the value of human input. After all, AI is a man-made innovation, not the other way around. Just blindly copying and pasting code snippets from ChatGPT can have severe consequences, so exercising caution and judgment is essential.
ChatGPT is not capable of problem-solving
As a developer, you are responsible for understanding a problem, generating multiple potential solutions, and then utilizing a programming language to translate the most effective solution into code for a computer or compiler. While machine learning tools such as ChatGPT can assist in increasing coding speed, they cannot perform problem-solving tasks on your behalf.
As a developer, problem-solving is an essential skill set you need to have to succeed. This is also why machine learning tools won't have a dire impact on developer jobs.
ChatGPT won't get you hired
ChatGPT can produce a code snippet, but it is not a replacement for an entire coding interview. The major part of the interview focuses on problem-solving rather than code writing, which typically only accounts for only 5-10 minutes of a 45-minute coding interview.
You still need to ask the right questions to show your comprehension of the problem, narrate your thought process, and narrow down a solution. ChatGPT can't help you with any of this.
ChatGPT won't take our jobs
The rise of IDEs and APIs may have streamlined certain development processes, but it did not diminish the demand for skilled developers - and the same can be said for ChatGPT.
Machine learning tools can undoubtedly boost our productivity, but they cannot replace the power of human thinking and capability. As we mentioned above, these tools can be both impressively accurate and hilariously off-base, leaving humans' critical thinking and problem-solving skills irreplaceable. Furthermore, ChatGPT is not a panacea for complex issues nor a substitute for innovation. Nevertheless, these tools can help alleviate some of the tedious tasks that bog us down, freeing us up to tackle more ambitious problems — such as advancing the field of AI.
In fact, as a Python developer, there's a lot you can gain from the growth of AI technologies!
What ChatGPT means for Python developers
In the midst of the AI boom, having strong Python skills can set you apart and make you more marketable to potential employers. As big data continues to grow in importance, software developers will need to equip themselves with the right skills and knowledge to transform data into actionable business solutions and strategies.
Understanding how AI works and what it can be used for can help you harness big data to go above and beyond what traditional software development alone can provide. You can discover patterns, uncover trends, automate processes, and simplify complex tasks by leveraging AI techniques such as natural language processing (NLP), computer vision, and deep learning. With this knowledge, you can develop innovative solutions that streamline workflows, save time and resources, and ultimately provide greater value to your clients or organization.
Acquiring proficiency in Python is an essential part of that journey. Fortunately, Educative's Zero to Hero in Python for Machine Learning skill path covers everything you need to know to get started.
This skill path covers the following:
Basic Python programming concepts
Machine learning terminology
Supervised and unsupervised learning methods
Different types of algorithms
Data preprocessing, feature selection, and model evaluation
Machine learning libraries and frameworks such as NumPy and Pandas
By the end, you'll have hands-on experience using Python libraries and frameworks for machine learning.
Now over to you: Do you think ChatGPT can help you? Does AI inspire you on your Python journey — if so, how? Leave your thoughts in the comments below!
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