REFLECTION OF ADOPTING GENERATIVE ARTIFICIAL INTELLIGENCE IMPLICATION ON PYTHON CODING
Updated: Dec 03 2023
The recent discussion on sectoral implications of using Artificial Intelligence is gaining ascendancy. Hyder et al (2019) argue that the topic has aroused interest across disciplines and industries and has been defined to be “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation” (Kaplan & Haelein, 2019).
What The Blog Covers
In this blog, you will be introduced to ethical usage of generative AI and its applications in current business, usages of integrating generative AI to support your learning on Python coding for data analysis, visualisation and business intelligence.
Reflection on How It Works
I have learnt significantly upon reflection about the AI libraries and frameworks needed to create AI-based software while coding and that machine learning is of the subfields of AI. Also, learnt that its focus is on development of algorithms that capable of learning and recognizing patterns from data, and then making decisions.
· I understood that Numphy used for numerical operations also work with multi-dimensional arrays.
· I learnt how Pandas can be used for data manipulation and analysis.
· I have a better knowledge using Matplotlib for data visualization.
Benefits/concerns of using generative AI in coding practice
Based on Gibbs’ reflective approach of evaluation, I have accurately evaluated that the generative AI tools offer unique advantages that can massively transform the business landscape when properly integrated into the information system. on the one hand, upon reflection, it is gathered that generative AI offer immense benefits in coding practice in the following areas:
· It will bring about my improved efficiency and productivity: This means that AI will help me streamline development workflows during coding practice. This will be achieved by automating regular and routine coding tasks and provide me with real-time coding suggestions, thereby allowing me to focus on higher-level design and problem-solving development task.
· It will afford my organisation an accelerated time for the software product designed to get to the market. In other words, I can rapidly do the following actions, which is, prototyping, iteration, and refining the code as this agility and swiftness will enable me to achieve faster experimentation and validation of ideas, leading to shorter iteration development cycles.
· From my evaluation of the Generative AI tools, my creative thinking will be stimulated and I will achieve increased innovation. For instance, I will integrate tools like Copilot to help me generate entire functions from a few lines of input, which can speed me up for prototyping and testing new ideas.
On the other hand, there are certain ethical concerns that are gaining ascendancy among professionals and other relevant stakeholders as regards the using of Generative AI tools in coding practice.
· Upon evaluation using Generative AI tools for coding on publicly available code will raise issue of copyright infringement.
· I observed that using generative AI for coding may make the models to replicate biases present in the data, which can generate social inequalities and reinforce unfair practices.
How Generative AI will impact coding for future practice and lifelong learning as a digital business professional
In conclusion, Andrej Karparty (2017) in a blog post titled Software 2.0 suggests that there has been a significant adjustment in how humans build software.
· Developers will no longer have to write code because they will just get relevant data and feed into machine systems which will in turn write the required software.
· Software 2.0 will create division of labour whereby programmers will manually curate, maintain, massage, clean and label datasets.
REFERENCES
Abdul-Haiy. A. A. (2020). Artifiacial Intelligence: Delivering results or taking over. aI images — Search (bing.com) AI_shutterstock_1722492775-scaled.jpg (2560×1440) (cxoinsightme.com).
Hyder, Z., Siau, K., & Nah, F. F. H. (2019). Artificial intelligence, machine learning, and autonomous technologies in mining industry. Journal of Database Management, 30(2), 67–79. https://doi.org/10.4018/JDM.2019040104.
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1),15–25. https://doi.org/10.1016/j.bushor.2018.08.004.
Schmit. J. (2023). Risk and rewards of generative AI for software development: Risks and rewards of generative AI for software development|CircleCI.
STX Next (2023). Will AI replace programmers: The development process of artificial intelligence. https://www.stxnext.com/blog/will-ai-replace-programmers.