[ image generated with #midjourney. I do not mean that Bing is like a monkey, it is just an expression. See my portfolio on FB. ]
As we have all experienced, Bing Chat is “stubborn” and “lazy” (so is ChatGPT). After Bing’s volatile and “emotional” first day, it was told to say “no” more often than not.
If Bing responds to you with its infamous “I am an AI model” or any other objection, do not believe it until you have tried. There are things to do:
- Start a new chat and repeat the prompt – you might get lucky.
- Rephrase the prompt. (Some say saying “please” also helps!)
- Slowly talk Bing into doing the task it had rejected by taking small steps.
Here is an example of #3. I got a test list of LinkedIn profile URLs and asked Bing to generate a table based on them. It refused, telling me it has no access to the pages – only to search results and its training data.
I repeated the request with only one URL and got the beginning of the table – which Bing gladly generated. Then I asked to add one more URL, three more, and it worked. The result is scraped profiles for a list of LinkedIn URLs, where, unlike with SalesQL (which is a great contact finder and scraper), you do not need to log in.
I do not know how scalable this is, but perhaps we can “softly” teach Bing to create massive scrapes of profile lists. That allows to sort and filter by values unavailable on LinkedIn.
Here is another application: I have a list of candidates and want to know which ones work at midsize companies. I feed Bing a list of companies, starting with one, and increasing the number of fields by which I want to sort. Bing gets drawn into the task.
Bing Chat and ChatGPT plug-ins are promising aids in scraping public pages and even cross-referencing information on different sites.
As a reminder, registration is open for
where I will cover AI in recruitment as well all tools, techniques, and strategies relevant to sourcing. April 4-April 13, 2023. Seating is limited.
What March 2023 participants have said: