Blog
Sometimes we take a break from building cutting edge AI redaction models to stretch our academic muscles and write about privacy and machine learning. Check back here regularly for our musings.
Language Modelling via Learning to Rank
In the previous episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sat down with Arvid Frydenlund (PhD candidate at the University of Toronto in the Computer Science Department and Vector Institute) to discuss his latest paper Language...
What Companies Should Know About PII & Protecting It
Personally Identifiable Information (PII) is any data that can be used to identify an individual. This can be done using direct identifiers (name, social security number, etc.) which are unique to an individual, or using quasi-identifiers (date of birth, race, postal...
When the Curious Abandon Honesty: Federated Learning Is Not Private
Previously on Private AI’s speaker series CEO, Patricia Thaine, sat down with Franziska Boenisch to discuss her latest paper, ‘When the Curious Abandon Honesty: Federated Learning Is Not Private’.
MLOps & Machine Learning Deployment at Scale
In the latest episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sits down to chat about MLOps and Machine Learning Deployment at Scale with Luke de Oliveira from Twilio. Luke de Oliveira is the Director of Machine Learning at Twilio,...
9 Companies to Help You Get Your Privacy $hit Together
With the ever-growing number of global regulations, legislations, and amendments, it can be overwhelming to know where to start (or continue) your data privacy journey. Below we’ve compiled a list of 9 companies who can help you build a proactive privacy, governance,...
Deploying Transformers at Scale
Transformer networks have taken the NLP world by storm, but the sheer size of these networks presents new challenges for deployment, such as how to provide acceptable latency and unit economics.
Parameter Prediction & Training Without SGD with Prof. Graham Taylor
Previously on Private AI’s Speaker Series, our CEO Patricia Thaine sat down with data privacy law expert Carol Piovesan to talk about the legal ramifications ML teams should be aware of and what most people misunderstand about data governance. This past week on...
5 Facts You Probably Didn’t Know About Data Privacy
Data privacy, in simplest terms, is the right to control how your personal information is collected and used. Although this may seem obvious, it hasn’t always been the case. With data being generated in mass amounts daily, it’s interesting that the earliest data...
Data Protection Regulations NLP Teams should Watch for in 2022
Natural Language Processing (NLP) teams need to stay up to date with the latest data protection regulations when training their models with user data. Not only do customers continue to demand privacy, but according to the GDPR they must give positive consent for their...
Data Privacy, Law, and Cybersecurity with Carole Piovesan
Carole Piovesan discusses legal responsibilities, what companies are getting wrong with data governance, and more.
An interview with Sheila Jambekar, CPO at Plaid
GDPR compliance, privacy and engineering team collaboration, and common mistakes companies make with their data.
Talking with Dr. Ann Cavoukian, Privacy by Design inventor
Discussing developer responsibility, Bill C-11, positive consent, and the importance of Privacy by Design
Anonymized Data is Useless: Fact or Fiction
“When is anonymization useful?” is a tricky question, because the answer is highly data-type- and task-dependent.
Data Anonymization: Perspectives from a Former Skeptic
On the misleading ways journalists and industry use the term “anonymization.”
Demystifying De-identification
Understanding key tech for data protection regulation compliance
What It Really Takes to Build An AI System: It’s more complicated than many think
There’s a saying ‘the last 20% of the work takes 80% of the time’ and nowhere is that more true than AI systems.
Natural Language v. Regex: The Context wars
Regexes are highly effective in the perfect world of computer data, but unfortunately the real world is much more complicated.
Privacy Tech: Understanding Internet Security
There exists a vibrant ecosystem of specialized security tools. The sad truth is that it is almost impossible to reach 100% invulnerability. What can we do to get closer?
Customers Are Demanding Privacy
In the past three years there has been a massive wake-up in customer awareness about privacy. Many customers are now refactoring how they buy, taking their business elsewhere if they don’t trust a company’s data practices.
Liability & AI Malfunction: An AI System Developer’s Perspective
AI is rapidly being deployed around the world with few to follow. Along with the complexity of creating the technology, there remain many unanswered legal questions.