A short poem by ChatGPT, as engineered and quality controlled by all-too-human, Ralph Losey. Ralph prompted the Ai to generate a simple rhyming poem that summarizes the fourteen Principles of The Sedona Conference®. These are, in Ralph’s opinion, good words for anyone to remember and live by in the field of electronic evidence.
See Losey’s earlier blog for the average adult and kid’s version of the fourteen Sedona Principels. Also see his recent blog, Homage to Richard Braman and the Sedona Conference. Go to www.thesedonaconference.org to download a free copy of the original Sedona Principles, 3rd Edition. This Sedona Poem concludes, for now, Ralph’s Sedona series.
In electronic discovery, we must all abide
By 14 rules that cannot be pushed aside.
For electronic data is just as key
As any other kind you or I might see.
We must be fair and not demand too much
Or else our efforts will lose their touch.
We must think about the cost and worth
And whether it’s sensible to unearth.
Together we must work and plan
To find and share the data at hand.
Clear requests and exact replies
Will keep us from telling any lies.
Some information we must keep safe
While others we can freely chafe.
The owner should decide the fate
Of the data they keep and create.
Proof is necessary to claim foul play
Else accusations will not carry sway.
Start by searching where it’s easiest found
For a quick and easy turnaround.
Deleted data is not always a must
Unless the reason is fair and just.
Privacy is key in any case
Lest we want to risk an embarrassing disgrace.
Tools are there to aid our quest
To make the search less of a test.
When sharing information, we must be clear
To make it understandable and without any fear.
The owner must pay to keep it safe
Unless a reason causes a different waive.
Those who break the rules, take heed
Courts will make sure you fix the misdeed.
Richard Braman (1953-2014) founded The Sedona Conference® in 1997. Before that he was a top litigator in San Francisco and Minneapolis where he also owned and operated a jazz club, Gabriel’s. For that reason, I feel certain he would smile at this essay using jazz images to describe the essence of the Sedona Principles that he loved so dearly.
Article written by Open AI’s ChatGPT with all-too-human prompt engineering by Ralph Losey. Hat’s off to ChatGPT-Plus for the excellent jazz-based images and writing. All images by Dall-E and Losey.
In the realm of electronic discovery, a certain rhythm permeates the airwaves, one that resonates with the pulse of jazz music. A harmonious interplay between those who seek information and those who hold it, creates an intriguing melody that’s both enchanting and demanding. The rules that govern this space are like the musical notes that make up a tune, essential to the experience of the listener, the same way that following the right protocol is essential to the seeker’s success.
In this jazz-infused world, the importance of electronic information is akin to the fundamental nature of a rhythm section in a jazz ensemble. Just as the bass, drums, and piano are integral to the musicality of jazz, electronic data is vital to modern life. Its significance is such that it must be carefully tended to, given the same consideration as any other kind of data.
When a seeker is searching for electronic data, they must adopt a musician’s mentality, avoiding excessive requests that sound like dissonant notes in a melody. Their goal should be to play a smooth tune, one that strikes the right chords, avoiding notes that don’t fit. Just as a jazz musician must be aware of their musical costs, a seeker must consider the expenses of pursuing information, keeping in mind the value of the information that is sought.
Just like a jazz band, those who seek and those who hold electronic data must work together in a harmonious exchange. A melody is only successful when everyone plays their part, just like a search for electronic data can only be accomplished with cooperation between parties. A clear and concise request from the seeker must be met with a reply that’s just as clear, like a musician playing a melody that’s understandable to their audience.
In this jazz world of electronic discovery, keeping data secure is like a trumpet player protecting their prized instrument. It’s the responsibility of the data owner to ensure that the data is safeguarded, but they don’t have to keep every single piece of data. Like a jazz musician who only keeps the essential notes to make a melody work, a data owner must protect what is necessary while disregarding what isn’t.
In the event of a dispute, it’s important to have proof, just like a jazz musician who has to demonstrate their musical chops on stage. To prove a point, it’s necessary to play the right notes, and in electronic discovery, it’s crucial to present the right data. The seeker should start by looking in the most accessible places, just like a musician who looks for the right melody in the most obvious places.
If data has been deleted or hard to find, it’s not essential to search for it unless there’s a good reason. Like a jazz musician who only plays what is necessary, the seeker must focus on what’s important to the case at hand. Privacy is another significant concern in this world, like a jazz musician who has to play with a level of restraint to maintain their musical dignity.
In the world of electronic discovery, there are tools that are available to aid in the search for data, just like a jazz musician who uses instruments to create their musical sound. These tools are designed to simplify the process and streamline it, much like a musician who uses new technology to create new sounds.
When data is shared, it should be presented in a way that’s easily understood, like a jazz musician who communicates their musical ideas to their listeners. The data owner is responsible for paying for the safekeeping and sharing of the data, much like a jazz promoter who takes care of the musical instruments and ensures that the performance runs smoothly.
In conclusion, the world of electronic discovery is like a jazz composition, with each player fulfilling a vital role. The right notes, played at the right time, create a melody that’s pleasing to the ears. Similarly, following the right protocols and rules in electronic discovery ensures a successful outcome. Like a jazz musician who respects the music and the other musicians on stage, those who seek and those who hold electronic data must work together with respect and integrity. Only then can the music of electronic discovery be played in perfect harmony, creating a beautiful sound that’s worthy of applause.
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The GPT-3 “AI” Explains Itself to Tech-Savvy e-Discovery Lawyers and Shows a Few Possible ApplicationsJanuary 10, 2023
Article and Illustrations Written by GPT-3 as Generated by Human Attorney, Ralph Losey
GPT-3 (Generative Pre-trained Transformer 3) is a state-of-the-art natural language processing (NLP) model developed by OpenAI. It is trained on a massive dataset of over 8 billion words. This training allows it to generate human-like text that can be used for various language-based tasks, such as language translation, summarization, question answering (and writing this blog).
GPT-3 could be used in the legal field in the process of electronic discovery. E-discovery refers to the process of identifying, collecting, and producing electronically stored information (ESI) in response to a request for production in a legal case.
Here are examples of how GPT-3 could potentially be used in e-discovery:
- Document review: GPT-3 could be used to review and classify large volumes of ESI, such as emails and documents, in order to identify relevant information and reduce the burden on human reviewers. AI systems can also be used to identify patterns and trends in data that might not be immediately apparent to human reviewers. For example, an AI system might be able to identify connections between different pieces of data, such as a common sender or recipient, or a particular keyword that appears repeatedly in a group of documents. This can help legal teams identify relevant information more quickly and efficiently, and potentially uncover new leads or evidence that might not have been discovered through manual review.
- Predictive coding: GPT-3 could be used to assist with predictive coding, a process that uses machine learning algorithms to identify relevant ESI based on examples provided by human reviewers. By using AI to identify and prioritize relevant documents, legal teams can focus their efforts on the most important and relevant information, rather than having to review every document in a dataset.
- Summarization: GPT-3 could be used to generate summaries of large volumes of ESI, making it easier for reviewers to quickly understand the content and identify relevant information.
- Language translation: GPT-3 could be used to translate ESI from one language to another, allowing reviewers to more easily review and understand documents written in languages they may not be proficient in.
- Question answering: GPT-3 could be used to assist with answering questions related to ESI, such as clarifying the meaning of certain terms or providing context for certain documents.
- Legal research: GPT-3 can be used to quickly search through large volumes of legal documents, such as case law or statutes, and provide relevant information to lawyers.
- Drafting legal documents: GPT-3 can be used to assist lawyers in drafting legal documents, such as contracts or pleadings, by suggesting language and providing relevant information.
- Redaction. GPT-3 can help identify and redact sensitive or privileged information from documents, improving the efficiency of the review process.
- Data visualization: GPT-3 tools can help visualize and analyze large volumes of data, making it easier to identify patterns and trends.
Overall, GPT-3 has the potential to significantly improve efficiency and accuracy in the e-discovery process by automating certain tasks and assisting with the review and analysis of ESI. GPT-3’s ability to process and generate human-like text makes it a useful tool for lawyers because it can assist with tasks such as legal research, document review, summarization, document drafting, and language translation.
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Posted by Ralph Losey