Data Privacy Day: Celebrating at Private AI

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What does privacy mean to us at Private AI? As a tech company whose purpose it is to enhance privacy, we are acutely aware of the value tension between businesses needing access to data to build amazing tools and the privacy interests of individual consumers. The privacy laws that have been enacted all over the world have always been attuned to the need to strike a balance between business interests and privacy interests. While it was first about information flow across borders to facilitate international trade, today, the value of data itself has dramatically increased as it is required for the development of prediction software, chatbots, voice assistance programs, and so much more. 

Celebrating Privacy Laws

Privacy laws are certainly not new. Particularly in Europe, privacy laws governing the public and private sector have been in place for half a century. After all, Data Privacy Day was established in 2006 in celebration of the signing into force of Convention 108, the first legally binding international treaty on data protection from 1981. But so much has changed since then. In a digital world where so much of our lives is documented online and the business model of some of the most highly valued companies crucially depends on access to our personal data, the acuity of both the business and the privacy interest has intensified. As a result, the legislators of many countries around the world are in a hurry to catch up and put protections in place that, while enabling businesses to make use of our data to provide services we depend on during the day, allow us all to sleep soundly at night.

The development of laws and regulations around the world since 1981 is commendable. The generally accepted openness principle (i.e., the requirement for companies to create a privacy policy which explains how they collect and manage data) that has been enacted in virtually all privacy laws today is a great example of clear action items businesses can take away from the laws and implement, if not on their own then with the help of a privacy consultant or lawyer who would draft an appropriate privacy policy and advise on the procedures that need to be put in place to handle complaints and grant access to the personal information. 

The details of the privacy policy will depend on the particularities of each business, but under Article 13 GDPR, businesses should set out, if applicable:

  • – Identity and contact details of the data controller;
  • – Contact details of the data protection officer;
  • – The purpose and legal basis for the processing of the data;
  • – The legitimate interests pursued by the controller;
  • – Recipients or categories of recipients of the data;
  • – The intention to transfer the data across borders, and if so, whether the transferee jurisdiction is deemed to be providing adequate protection as determined by the Commissioner;
  • – The retention period, or the factors with reference to which the period will be determined;
  • – The right to request access, rectification, erasure, a restriction of processing, and portability;
  • – The right to withdraw consent;
  • – The right to lodge a complaint with a supervisory authority;
  • – Whether the provision of personal data is a statutory or contractual requirement, or a requirement necessary to enter into a contract, as well as whether the data subject is obliged to provide the personal data and of the possible consequences of failure to provide such data;
  • – Whether automated decision-making will be engaged in, meaningful information about the logic involved, as well as the significance and the envisaged consequences for the data subject.

This helps consumers to make an informed decision about what data usage they want to agree to and it provides, at least in theory, an effective way to take recourse if consumers feel their data was subjected to a use they hadn’t consented to. 

Acknowledging the Task at Hand

Privacy laws of course go further than requiring businesses to craft and publish a privacy policy. Businesses must also take measures to protect the data they are in control of. What remains notoriously unclear is how to reach the standard of protection required by the law from a technical perspective. An example is the de-identification of personal information. It sounds fairly straightforward to strip data of direct and indirect personal identifiers, but if you just turn your mind to the fact that in order to do that you first need to determine where every piece of personal information on a particular individual is in your system, things are suddenly no longer straightforward at all. You may take in personal information through websites, mail and email, from contractors, call centres, chatbots, etc., and it may be stored on computers, laptops, mobile devices, flash drives, disks, digital copiers, in your filing cabinet, and so on. The data may be in a structured form, but for many companies lots of it will likely be unstructured data, which is that much more difficult to properly de-identify, let alone anonymize. Furthermore, depending on the sensitivity of the data, different measures may need to be taken to safeguard it properly. 

Celebrating Private AI

Private AI can help with the task of identifying what personal information you have in your system. What is more, we have developed products that automatically identify and redact the personally identifiable information to aid compliance with many privacy laws, including the GDPR. 

Try if you can beat it! Click on the portions of the text that you think is personal information:

Identify the PII
Click the words within the text below that you think are Personally Identifiable Information (PII). Correct answers will turn green and be replaced with a PII marker. Incorrect answers will turn red. Good luck!

Agent: Hello Ming Xiao, thank you for calling. Could you confirm your credit card number please?

Customer: Sure, it’s 9834 3243 4356 oh wait sorry no 4365, 1246.

Agent: Thank you. And could you confirm your date of birth, please?

Customer: August 29th 1932. I’m turning 89 today!

Agent: Happy Birthday, Ming Xiao! And what are the three numbers at the back of your card?

Customer: 873

Agent: And your credit card expiration date?

Customer: oh nine twenty-four

Agent: So to confirm, your last transaction was on August 28 at Harbord Bakery for 45 dollars and eighty two cents?

Customer: Yes, that’s right near where I live on Harbord. My aunt actually has benign hematology and went to the Royal Victoria Hospital on Harbord too.

Agent: Sorry to hear that Ming Xiao. But looking at your account here I don't think there was a fraud.


Check out our
online demo with your own example text!

Conclusion

At Private AI, we take Data Privacy Day as an opportunity to celebrate how far we have come since 1981 in terms of the legislative protections of privacy interests that balance the equally important business interest in collecting and using personal data. We also celebrate what technology can do to help with the difficult implementation of the laws on a technical level, and our own contributions to the empowerment of businesses to responsibly handle personal data. We hope that ahead of us lies a world where we can enjoy all the comfort the digital age has to offer without having to fear identity theft, profiling, and the collapse of our democracies. To realize this hope, we need to find a way that we can trust the organizations we share our data with. This vision motivates us to build products that keep data safe and businesses compliant.

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Rappel

Testé sur un ensemble de données composé de données conversationnelles désordonnées contenant des informations de santé sensibles. Téléchargez notre livre blanc pour plus de détails, ainsi que nos performances en termes d’exactitude et de score F1, ou contactez-nous pour obtenir une copie du code d’évaluation.

99.5%+ Accuracy

Number quoted is the number of PII words missed as a fraction of total number of words. Computed on a 268 thousand word internal test dataset, comprising data from over 50 different sources, including web scrapes, emails and ASR transcripts.

Please contact us for a copy of the code used to compute these metrics, try it yourself here, or download our whitepaper.