eDiscovery Daily Blog
Understanding Blockchain and its Impact on Legal Technology, Part Four
Editor’s Note: Tom O’Connor is a nationally known consultant, speaker, and writer in the field of computerized litigation support systems. He has also been a great addition to our webinar program, participating with me on several recent webinars. Tom has also written several terrific informational overview series for CloudNine, including his most recent one, Will Lawyers Ever Embrace Technology?, which we covered as part of a webcast on November 28 of last year. Now, Tom has written another terrific overview regarding blockchain and legal technology titled Understanding Blockchain and its Impact on Legal Technology that we’re happy to share on the eDiscovery Daily blog. Enjoy! – Doug
Tom’s overview is split into six parts, so we’ll cover each part separately. Part one was last Monday, part two was last Wednesday and part three was last Friday, here’s the fourth part.
General Use Cases for Blockchain
Several actual examples may show the actual utility of blockchain.
Searching
In 2001, Microsoft researchers, Banko and Brill, released a paper Scaling to Very Very Large Corpora for Natural Language Disambiguation, which described how most work in the area of natural language processing was on small data sets of less than a million words. Error rates for algorithms such as Naive Bayes and Perceptrons were 25%, while newer memory-based algorithms achieved 19% error rates.
But as they added MORE data — not just a bit more, but orders of magnitude more — and kept the algorithms the same, then the error rates kept going down. A dataset which was three orders of magnitude larger had an error rate of less than 5%. Even more surprising, the best-performing algorithms were the simplest and always outperformed more state-of-the-art systems.
Then, in 2007, Google researchers, Halevy, Norvig and Pereira, published a paper called The Unreasonable Effectiveness of Data showing how data could be “unreasonably effective” across many AI domains. Hence, the rise of deep learning systems and the reemergence of backprop neural networks from the ’80s which are equally effective in massive datasets with more recent technologies.
So decentralized and shared control typically leads to better performing models. And since the decentralized nature of blockchains encourages data sharing, it works better whether the network is local or worldwide.
Security
Blockchain eliminates the risks that come with centralized data because it stores data across the network. Thus, it doesn’t have centralized points of vulnerability that computer hackers traditionally exploit. No more “username/password” systems, but rather encryption technology and constantly updating audit trails
A blockchain, as the name implies, is a chain of digital “blocks” that contain records of transactions. The records on a blockchain are secured through cryptography and network participants have their own private keys that are assigned to the transactions they make and act as a personal digital signature.
However, despite inherent properties that provide security, known vulnerabilities in your infrastructure can be manipulated by hackers. Any system supporting blockchain should have these capabilities at a minimum:
- Be able to prevent anyone, up to and including administrators, from accessing sensitive information
- Ability to deny illicit attempts to change data or applications within the network.
- Use highest-grade security standards to protect encryption keys
We’ll publish Part 5 – General Use Cases for Blockchain – on Wednesday.
So, what do you think? Do you understand blockchain and how it can impact the legal profession? If not, keep reading! And, as always, please share any comments you might have or if you’d like to know more about a particular topic.
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