I’m excited to share a press release from GW Law School announcing our new GW Center for Law and Technology. Through the Center, we’re building out our privacy and tech curriculum and activities. Recently, we have done the following:
Here are some notable books on privacy and security from 2023. To see a more comprehensive list of nonfiction works about privacy and security for all years, Professor Paul Schwartz and I maintain a resource page on Nonfiction Privacy + Security Books.
Hideyuki (“Yuki”) Matsumi (Vrije Universiteit Brussel) and I have significantly revised our essay, AI, Algorithms, and Awful Humans, forthcoming 92 Fordham Law Review (2024). It will be part of a Fordham Law Review symposium, The New AI: The Legal and Ethical Implications of ChatGPT and Other Emerging Technologies. In response to great feedback, we have made many refinements and changes to our arguments. The essay is short (just 18 pages), and it’s a quick fun read.
The essay argues that various arguments about human versus machine decision-making fail to account for several important considerations regarding how humans and machines decide. You can download the article for free on SSRN. We welcome feedback.
Here’s the abstract:
A profound shift is occurring in the way many decisions are made, with machines taking greater roles in the decision-making process. Two arguments are often advanced to justify the increasing use of automation and algorithms in decisions. The “Awful Human Argument” asserts that human decision-making is often awful and that machines can decide better than humans. Another argument, the “Better Together Argument,” posits that machines can augment and improve human decision-making. These arguments exert a powerful influence on law and policy.
In this Essay, we contend that in the context of making decisions about humans, these arguments are far too optimistic. We argue that machine and human decision-making are not readily compatible, making the integration of human and machine decision-making extremely complicated.
It is wrong to view machines as deciding like humans do, but better because they are supposedly cleansed of bias. Machines decide fundamentally differently, and bias often persists. These differences are especially pronounced when decisions have a moral or value judgment or involve human lives and behavior. Making decisions about humans involves special emotional and moral considerations that algorithms are not yet prepared to make – and might never be able to make.
Automated decisions often rely too much on quantifiable data to the exclusion of qualitative data, resulting in a change to the nature of the decision itself. Whereas certain matters might be readily reducible to quantifiable data, such as the weather, human lives are far more complex. Human and machine decision-making often don’t mix well. Humans often perform badly when reviewing algorithmic output.
We contend that algorithmic decision-making is being relied upon too eagerly and with insufficient skepticism. For decisions about humans, there are important considerations that must be better appreciated before these decisions are delegated in whole or in part to machines.
Click the button to download the essay draft for free.
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I am delighted to announce that the new 8th edition of my casebook, INFORMATION PRIVACY LAW, with Professor Paul Schwartz is out in print! This is a very special edition, as this year marks the 20th anniversary of the casebook.
More information about the book is at the Information Privacy Law casebook website. You can order a review copy of the book on Aspen’s site. Here’s the new table of contents. The ISBN is 9798886143355.
It has been a long journey since the first edition in 2003. I was fortunate to have Richard Mixter as my editor at Aspen. He believed in this project since the beginning. But it took quite a lot of work making the case for Aspen to publish the casebook, as there were only a handful of privacy courses at the time. Aspen ultimately decided to print the book as a special softcover.
In case you missed my recent webinar with Anu Bradford, you can watch the replay here. We discussed her new book, Digital Empires: The Global Battle to Regulate Technology (Oxford 2023).
Here’s my new cartoon about how many tech companies extol innovation, yet seem to lose that innovative spirit when it comes to regulation. With the right incentives, it’s amazing how tech companies can rise to the challenge. They can certainly innovate to address regulatory demands; instead, they often send in lobbyists to pout and complain or to block laws. It would be better for companies to try to innovate for regulation rather than fight it. Policymakers might look to use some carrots rather than just sticks. Positive incentives can help steer tech companies to address regulatory concerns.
Watch the video of my short lightning talk for a segment in a privacy conference put on by the Privacy Commissioner of Bermuda. The topic I was asked to speak on is “what data protection is not.” You can watch the video here.
In case you weren’t able to make it to my recent webinar with Jared Coseglia (TRU Staffing Partners), you can watch the replay here. We had a great discussion about strategies for entering the privacy field.
Here’s my latest cartoon – for Halloween. This cartoon is inspired by many companies now starting to use their users’ data to train their AI algorithms. Recently, Elon Musk’s X (formerly Twitter) changed its privacy notice to indicate that it would start using user data for AI training. As the famous saying goes, “If you’re not paying for the product, you are the product.”
Some other Halloween cartoons:
NOTE: This post was originally part of my special newsletter on LinkedIn – Privacy+Tech Insights. This is a different newsletter from my weekly newsletter. My LinkedIn newsletters are more infrequent and typically involve a more focused analysis of a particular issue.
A quiet revolution has been going on with personal and sensitive data. There have been many notable developments. In the past few years, we’ve witnessed the triumph of the EU approach to defining personal data and to designating special protections for sensitive data.
We’ve seen a growing recognition in the law that:
These are significant developments, yet oddly, they haven’t made headline news.