As we are increasingly aware, the ethical Duty of Technology Competence requires lawyers to keep abreast of “changes in the law and its practice, including the benefits and risks associated with relevant technology.” To date, 35 states have adopted the duty.
In a previous post, I highlighted the risks of blindly relying on algorithmic results (relevant technology) as a potential violation of the Duty of Technology Competence. We now have case law from Canada focusing on the benefits of using algorithmic results to perform legal research. In fact, this case law may be interpreted as requiring the use of algorithmic results when ethically performing legal research.
In spring 2017, I briefly discussed the issues with scholarship impact factor in law as a response to a recommendation by a law professor to create a rankings methodology based on Google Scholar citation.
Now US News is trying to get in the game of creating a ranking of law faculty by scholarship impact factor using Hein publication metrics. US News is asking each law school for the names and other details of its fall 2018 full-time tenured and tenure-track faculty. US News plans to link the names of each individual law school's faculty to citations and publications that were published in the previous five years and are available in HeinOnline.
Earlier this week, the folks at The Algorithm asked "what is AI, exactly?" The answer is reproduced below.
The question may seem basic, but the answer is kind of complicated. In the broadest sense, AI refers to machines that can learn, reason, and act for themselves. They can make their own decisions when faced with new situations, in the same way that humans and animals can. As it currently stands, the vast majority of the AI advancements and applications you hear about refer to a category of algorithms known as machine learning. These algorithms use statistics to find patterns in massive amounts of data. They then use those patterns to make predictions on things like what shows you might like on Netflix, what you’re saying when you speak to Alexa, or whether you have cancer based on your MRI. Machine learning, and its subset deep learning (basically mac…