Data Privacy
データプライバシー
As an ML engineer, I see firsthand how data powers the systems we build — and how easily the people behind that data can be forgotten. Data privacy isn't just a compliance checkbox. It's a question of respect.
Every model trained, every pipeline deployed, every feature engineered starts with someone's information. I believe we have a responsibility to treat that data with care — to minimize collection, to be transparent about usage, and to give people meaningful control over their own information.
Things I care about
- ▹Data minimization — collect only what you need
- ▹Transparency in ML systems and training data provenance
- ▹Right to deletion and meaningful user consent
- ▹Privacy-preserving ML techniques (federated learning, differential privacy)
- ▹Fighting the normalization of surveillance capitalism
More thoughts on this topic coming soon in the blog section. This is something I want to write more about.