But putting one’s rights into the hands of an algorithm as a solution to insufficient or inequitable legal representation is ethically worrisome, legal experts warned.
). The chatbot will exist on the defendant’s phone as a regular app, absorbing audio through the device’s microphone, and dictating legal arguments through the glasses.
Nonetheless, Browder sees his company’s new experiment as an opportunity to reconceptualize how legal services could be democratized with AI. Like any AI, GPT-3 needs to be trained properly. DoNotPay’s law school for bots looks like mock trials run by team members at the company’s Silicon Valley headquarters in Palo Alto. The algorithms are nourished on datasets of legal documents from publicly available court records and DoNotPay’s own roster of 2.75 million cases, according to Browder, dating back to its conception in 2015.
“There is a risk that the systemic bias that already exists in the legal system will be exacerbated by relying on systems that reflect those biases,” she said. “So, you kind of have a loop, where it never gets better, because the system is already not perfect.” Similarly, not all legal cases are public, and the algorithm may only be trained on a subset restricted by specific dates or geography—which can distort the bot’s accuracy, Smuha added.
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