AI isn’t going anywhere, there’s no “AI bubble burst” coming that will slow down growth. The early 2000s tech crash won’t repeat here. That said, there is a bubble bursting for some startups whose business models are being displaced by rapid AI advancement, but that’s another conversation entirely.
All that to say: gaining deeper skills, certifications, or formal education around the intersection of AI, data privacy, and ethics is a smart move.
My advice: complement your governance and ethics learning with some hands-on technical skills. For example, learn a bit of Python so you can do basic data analytics. You don’t need to become a data scientist, but knowing how to write a simple data query or understand a data pipeline will help you speak the same language as the technical teams.
Also, get comfortable with the technical basics of AI. You don’t need to build models, but understanding how they work (and where they can fail) will make you far more credible in governance and policy conversations.
There are a ton of great (and free) options to learn: OpenAI, DeepLearning.AI, Google, and others all have entry-level or certification courses, and YouTube is also a great option to learn about new technology. Google’s foundational AI courses are free, with certifications costing around $100. OpenAI recently started offering learning paths for developers and educators, and they’ll likely expand into broader AI literacy training soon.
If you can blend the rigor of a Master of Legal Studies with practical AI and data literacy, you’ll be positioning yourself in a space that’s going to be in very high demand for years to come.
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