ChatGPT is a new Artificial Intelligence technology and we discuss how this is useful as a research and productivity tool. Susan and Scott chat with Emal Bariali, the Founder of BA Blocks, who has been researching ChatGPT for use by business analysis professionals. Emal has published several ChatGPT videos on his RU-vid channel (see link below).
As a high-level primer, GPT stands for Generative Pre-trained Transformer. It is a type of Large Language Model (LLM) artificial intelligence tool. We don’t focus on the technology in this discussion, we focus on the implications and usefulness of this artificial intelligence technology.
During our discussion, we demonstrate a simple example of using OpenAI’s ChatGPT tool. The example is exploring what menu items and policies to include when building a website. The results provide lists of items and a brief description of each.
There are a number of useful functions ChatGPT can perform:
- Knowledge gathering and research to perform discovery work quickly and efficiently
- Summarize the transcript of a meeting
- Building creative output such as a social media calendar and title ideas (even poems and song lyrics!)
- Writing code such as SQL
- Productivity tools: Microsoft and Google are working to include Large Language Models (LLMs) in their productivity suites to perform mundane or repetitive tasks. This will provide the ability to use this functionality to address low-value work and free up more time. Susan describes “shallow work” versus “deep work”, where LLMs can help with the shallow work. Some examples of how the ChatGPT type of functions will work in productivity suites are:
- Draft an email based on available data (meeting transcripts, files, emails, etc.)
- Generate a presentation (including photos it has access to)
- Pull meaning from a spreadsheet of data
Some limitations of ChatGPT are it can’t create new ideas, it could be plagiarising, it can’t read body language, it doesn’t understand organizational culture, etc. There are some risks of using ChatGPT as it can generate results that aren’t accurate. It requires diligence to ensure the results are used appropriately.
Emal suggests making sure you’re clear on the prompts you ask to get more accurate results and look at the results critically to review it well.
RESOURCES:
Emal’s RU-vid Channel with ChatGPT demos - / @bablocks
Cornell University Study - GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models arxiv.org/abs/2303.10130
Productivity Tools:
- Microsoft 365 Copilot Info - • Introducing Microsoft ...
- AI and Google Workspace Info - • A new era for AI and G...
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#chatgpt #AI #businessanalysis
23 июл 2024
