More software developers than ever are relying on generative A.I. as part of their workflows. However, a new report suggests they’re using this technology in ways that might surprise you.
CodeSignal recently surveyed 1,000 developers worldwide about their use of A.I. coding assistant tools. Some 81 percent of respondents said they relied on such tools; CodeSignal’s resulting report breaks down the most popular use-cases:
“The most common use of A.I. coding assistant tools isn’t actually for writing, commenting, or debugging code: it’s for learning,” the report added. “Over three-quarters of developers who use A.I.-powered coding assistants use them to learn new skills or knowledge. This stands in contrast to early studies of these tools from Stack Overflow, GitHub, and Google, which focus on the benefits for developers’ productivity.”
Some 91 percent of developers reported utilizing ChatGPT as their generative A.I. tool of choice, well ahead of GitHub Copilot (33 percent) and Google’s Bard (21 percent). Some 49 percent said they used these tools daily, while another 39 percent used them weekly (10 percent indicated they did so every few weeks).
If you’re totally new to generative A.I., a growing number of courses online can educate you about this game-changing technology. For example, Google offers the following online tutorials, which include videos, quizzes, and short lessons:
- Generative AI, explained
- Introduction to Generative AI
- Introduction to Large Language Models
- Generative AI Fundamentals Skill Badge
- What is Generative AI Studio?
- Introduction to Generative AI Studio
- Introduction to Image Generation
- Introduction to Responsible AI
- Responsible AI: Applying AI Principles with Google Cloud
Online learning portals such as Coursera also offer courses from the likes of DeepLearning.AI, IBM, Vanderbilt University, and other institutions. As you learn, keep in mind that generative A.I. (like all kinds of tech) has its upsides and downsides; for example, you may want to double-check any and all code output to ensure everything is correct.
“Generative AI holds enormous potential to create new capabilities and value for enterprise,” reads a handy generative A.I. explainer released last year by IBM. “However, it also can introduce new risks, be they legal, financial or reputational. Many generative models, including those powering ChatGPT, can spout information that sounds authoritative but isn’t true (sometimes called ‘hallucinations’) or is objectionable and biased. Generative models can also inadvertently ingest information that’s personal or copyrighted in their training data and output it later, creating unique challenges for privacy and intellectual property laws.”
As you learn more about A.I., also remember that mastering this nascent technology can translate into a pay boost: a recent study by Amazon Web Services (AWS) and Access Partnership found that employers “are willing to pay an average of 47 percent more for IT workers with A.I. skills.” But even if you don’t want to become an A.I. expert, recognizing how A.I. tools could change your company’s workflows is essential.