Since the dawn of the dot-com era, more and more business models have come to rely on convincing customers that there is indeed such a thing as a free lunch.
Wise people know that isn’t true. “Free” nowadays just means you don’t pay with your money; you pay with your life. At least, that is, some of the details about yourself, your life, and your behavior, so that the data can be collected, analyzed, bought, sold, squeezed for intelligence, shaken for loose change, (stolen by cyberattackers), and fed into ever-more sophisticated technology to motor “data-driven” business initiatives. This isn’t necessarily sinister; organizations may use personal data on customers to provide better service, more customized healthcare. And for some industries, trading data is the main way to sustain themselves, as people get out of the habit of spending actual money on things like music and news. Businesses are required to maintain some personal data on employees and may monitor those employees’ behavior to improve productivity, and also worker safety, or employee wellness. Data is so helpful, that businesses collect it about everything.
The end result is a culture of surveillance.
Even when well-intentioned, data collection can be very dangerous — both to the individual and to the business taking stewardship of it.
Consumers and employees alike are waking up to these realities and want their privacy back; regulators are stepping in with tighter oversight and steeper punishments. And many forward-thinking organizations and innovative IT leaders are taking privacy rights seriously, recognizing that protecting the privacy of their consumers and employees is an important part of maintaining their trust.
But where to start?
A look at most organizations’ data stores would show a messy, tangle of poorly governed datasets growing out of control. Lots of the data your organization collects it probably doesn’t need, never uses, doesn’t even know that it has. It’s eating up storage space, and is an accident waiting to happen. An appetizing target for a cyberattacker; a costly violation for a regulatory auditor; an uncomfortable situation when law enforcement brings a discovery request; a public relations embarrassment that causes the organization to lose the trust of customers or employees. All of the above, or worse.
So what do IT leaders do?
- How can you maintain the privacy of data in storage, in transit, and (trickiest of all) in compute? And do so at scale, in a collaborative, work-from-anywhere world?
- How can you do “privacy by design” from the start?
- How bad are the potential fines for regulatory violations, and what new regulations are coming next?
- Is the value of data worth the risk?
This week we’re devoting coverage to all the various complications of having data privacy survive in a data-driven world, and shining light on the tools and technologies that can enhance privacy while continuing business.
Here’s what’s coming this week:
Privacy Debate for 2023: Can Data Collection Persist As Is?, by Joao-Pierre S. Ruth — More layers of state and federal regulation on data privacy loom on the horizon, with political agendas and business needs also adding tension to the mix.
Trusted Execution Environments Make Computing More Private, by Samuel Greengard — Trusted execution environments are changing the face of cloud computing — and they will have an even bigger impact in the months and years ahead.
What Do the Multimillion-Dollar Google Settlement, Meta Fine Mean for Data Privacy?, by Carrie Pallardy — Google agreed to pay a significant amount in a settlement for violating consumer privacy laws. Could this settlement and Meta’s latest fine be the beginning of a new future for data privacy?
(from Network Computing) Data Privacy and Protection in the Age of Cloud, by Sal Salamone — With more data on more cloud platforms being subject to increasingly stringent regulations, traditional approaches to protecting data fall short.
Data Strategy: Synthetic Data and Other Tech for AI’s Next Phase, by Jessica Davis — Forrester’s Data Strategy & Insights event will offer insights to help you take your machine learning and artificial intelligence initiatives to the next phase.
Coming Up Next:
Stealth Data Collection Threatens Employee Privacy, by John Edwards
Secretly and quietly, often without enterprise knowledge or permission, cybersecurity and monitoring tools are scooping up an array of sensitive employee data.
How Should Data Brokers and Credit Bureaus Be Protecting Your Data?, by Richard Pallardy
The largest stewards of personally identifiable information have poor cybersecurity records. What have they learned from previous breaches?
Data Clean Rooms: Enabling Analytics, Protecting Privacy, by Jessica Davis
Data clean rooms offer a way for organizations to collaborate with and share data in a protected environment that preserves privacy and governance. Here’s why they are on the rise now.
The Top Five Data Privacy Penalties post-GDPR, by Carlo Massimo
From California to China and the country that fined itself, here are the five most interesting data privacy penalties of 2021-22.
How to Build Privacy-By-Design Into Customer Experience, by Pam Baker
The predatory nature of data collection is spiking demand for data privacy protection as part of the customer experience. Are you ready to deliver that?
Exploring End-to-End Encrypted Messaging and the Enterprise, by Carrie Pallardy
Data clean rooms offer a way for organizations to collaborate with and share data in a protected environment that preserves privacy and governance. Here’s why they are on the rise now.
The Companies Leading Privacy-Enabling Tech, by Nathan Eddy
Selecting a data privacy management vendor requires organizations to carefully consider their specific needs, and the level of help they need to meet compliance requirements.
Is the Hassle of Sharing Data Worth the Value it Creates?, by Lydia Clougherty Jones
Data sharing is essential to generate enterprise and customer value, but it requires a focused approach and culture of responsible data and technology use.
