As Gen AI tools become increasingly crucial for driving innovation and efficiency, I'm curious about your approach to managing concerns around proprietary data while embracing the benefits of these tools. How do you strike a balance between leveraging Gen AI technologies and mitigating the risks of sharing proprietary information?
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Chief Information Security Officer in Healthcare and Biotecha year ago
I would suggest implementing a CASB solution and start tracking your user's behaviour and take action as per the data
0: 'No gen ai' - your people will use it anyway and you'll probably be opening yourself up to data leaks
1: 'use it if you want, with these rules' - Your people have their own accounts with chatgpt (or other) directly , you might say no copying confidential data in, but it will likely happen.
2: 'internally deployed chatbot' - You deploy a llm in your own tenant and control data privacy at the system level. Eliminate the need to use chatGPT or other, because they can access a free model by their company. lower risk of data leaks
3: bespoke tuning on top of internally hosted models - the gold nugget, get responses specific to your enterprise data, full controls over privacy, very unlikely to have accidental data leaks because your users wont need to copy paste data into a chatbot, as your enterprise bot already had access to the data in question.