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The impact is likely to be greatest in areas, including criminal justice and appellate decision-making, where “equitable justice,” or discretionary moral judgment, is frequently considered paramount.

By offering efficiency and at least an appearance of impartiality, AI adjudication will both foster and benefit from a turn toward “codified justice,” an adjudicatory paradigm that favors standardization above discretion.

The single most promising response is for the government to play a greater role in structuring the emerging market for AI justice, but auspicious reform proposals would borrow several interrelated approaches.

High Court confirms enforceability of jurisdiction clause agreed electronically by “click-wrapping”

A recent survey of regional data protection authorities in Germany has revealed 75 cases of reported personal data breaches since the GDPR came into effect on 25 May 2018.

Germany differs from Ireland as the responsibility for monitoring and ensuring compliance with the GDPR and national data protection laws is delegated to each of the 16 German states, with each state possessing its own authority.

The highest fines have been reported in the Baden-Wurttemberg region (€203, 000 across seven cases), Rhineland-Palatinate region (€124,000 across nine cases) and Berlin (€105,600 across eighteen cases).

Should Artificial Intelligence Practice Law?

Morgan Stanley reduced its legal staff and now uses AI to perform 360,000 hours of contract review in seconds and a number of legal services can conduct legal research (e.g., Ross Intelligence), perform contract analysis (e.g., Kira Systems, LawGeex, and help develop legal arguments in litigation (e.g., Case Text).

With machine learning, you provide the computer with a model that can learn what a cat looks like and then let the computer review millions of cat (and non-cat) pictures, stimulating the model when it correctly discerns a cat, and correcting it when it doesn’t properly identify a cat.

The upshot is that the computer develops a probabilistic model of what a cat looks like, such as “if it has pointy ears, is furry, and has eyes that can penetrate your soul, there is a 95 percent chance that it is a cat.” And there is room for error.

If a lawyer applies legal reasoning to identifying cat pictures, that lawyer will become well versed in the legal requirements as to what pictorial elements (when taken together) make up a cat picture.

The lawyer will then look at a proposed cat picture and review each of the elements in the picture as it relates to each of the legally cited elements that make up a cat and come up with a statement like, “Because the picture shows an entity with pointy ears, fur, and soul-penetrating eyes, this leads to the conclusion that this is a picture of a cat.” In machine learning, the room for error does not lie in the probability of the correctness of the legally cited cat elements to the proposed cat picture.

Legal A.I. - Where it Stands Today

Antoine Blondeau is the co-founder and managing partner at Alpha Intelligence Capital. This video was filmed for ZegalCon 2018.

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