Judicial Analytics and the Great Transformation of American Law

Predictive judicial analytics holds the promise of increasing efficiency and fairness of law. Judicial analytics can assess extra-legal factors that influence decisions. Behavioral anomalies in judicial decision-making offer an intuitive understanding of feature relevance, which can then be used for debiasing the law. A conceptual distinction between inter-judge disparities in predictions and interjudge disparities in prediction accuracy suggests another normatively relevant criterion with regards to fairness. Predictive analytics can also be used in the first step of causal inference, where the features employed in the first step are exogenous to the case. Machine learning thus offers an approach to assess bias in the law and evaluate theories about the potential consequences of legal change

Algorithmic Jim Crow

This Article contends that current immigration- and security-related vetting protocols risk promulgating an algorithmically driven form of Jim Crow. Under the “separate but equal” discrimination of a historic Jim Crow regime, state laws required mandatory separation and discrimination on the front end, while purportedly establishing equality on the back end. In contrast, an Algorithmic Jim Crow regime allows for “equal but separate” discrimination. Under Algorithmic Jim Crow, equal vetting and database screening of all citizens and noncitizens will make it appear that fairness and equality principles are preserved on the front end. Algorithmic Jim Crow, however, will enable discrimination on the back end in the form of designing, interpreting, and acting upon vetting and screening systems in ways that result in a disparate impact

The Empirical Turn In Family Law

Historically, the legal system justified family law’s rules and policies through morality, common sense, and prevailing cultural norms. In a sharp departure, and consistent with a broader trend across the legal system, empirical evidence increasingly dominates the regulation of families. There is much to celebrate in this empirical turn. Properly used, empirical evidence in family law can help the state act more effectively and efficiently, unmask prejudice, and depoliticize contentious battles. But the empirical turn also presents substantial concerns. Beyond perennial issues of the quality of empirical evidence and the ability of legal actors to use it, there are more fundamental problems: Using empirical evidence focuses attention on the outcomes of legal rules, discouraging a debate about contested and competing values. Reliance on empirical evidence overlays a veneer of neutrality on normative judgments. And uncritically adopting evidence about present conditions without interrogating the role of historical discrimination that continues to disadvantage some families can replicate that discrimination. Given the promise and peril of the empirical turn in family law, this Essay proposes a framework to guide the use of this evidence. The framework preserves space for debating multiple values and advises decisionmakers when to use empirical evidence, with particular attention to the dangers for nondominant families. The framework also recommends strengthening evidentiary gatekeeping and elevating the potential for legal scholarship to serve as a bridge from the broader research base to the courts. With this guidance in place, empirical evidence can take its rightful place as a useful but cabined tool in the legal regulation of families

Value Gaps in the Planetary Matrix of the World Community as a Limitrophe of War and Peace

The article describes the problem of spontaneous transformation of the planetary matrix of the social world, moving from the cell to the network structure, resulting not only in the changes of the world system of the planetary community, the shapes of national states are melting out gradually, the need for cosmopolitan world perception and thinking of the political elite arises, the managing processes come into the picture, hybrid planetary policy is formed, and finally, qualitatively new conflict forms and even hybrid wars appear. With the change in the planetary matrix structure, there are several fundamental changes in the life-plan of a planetary human being, since the fundamentally different segments of archetypes are activated in the world community's subconsciousness, the values-semantic substrates are mixed in the consciousness, and completely different logical schemes and algorithms of influence on a person are activated in the noosphere. At the same time, this means that in the sphere of national powers the emphasis of state policy, state regulation and public administration tends to shift from the territorial horizon into the plane of regulation of world planetary processes. This tendency also transfers the focus of their organizational efforts from the national and state levels to the political space of interstate and supra-state entities. The most intense points of relations between the actors of the modern integral process are the so-called limitrophes and frontiers

Platforms and the Fall of the Fourth Estate: Looking Beyond the First Amendment to Protect Watchdog Journalism

Journalists see the First Amendment as an amulet, and with good reason. It has long protected the Fourth Estate—an independent institutional press—in its exercise of editorial discretion to check government power. This protection helped the Fourth Estate flourish in the second half of the twentieth century and ably perform its constitutional watchdog role. But in the last two decades, the media ecology has changed. The Fourth Estate has been subsumed by a Networked Press in which journalists are joined by engineers, algorithms, audience, and other human and non-human actors in creating and distributing news. The Networked Press’s most powerful members are platforms. These platforms—companies like Facebook, Google, and Twitter—shun the media label even as they function as information gatekeepers and news editors. Their norms and values, including personalization and speed, stymie watchdog reporting. The Networked Press regime significantly threatens watchdog journalism, speech that is at the core of the press’s constitutional role. Yet, limited by the state action doctrine, the First Amendment cannot shield this speech from a threat by private actors like platforms. Today, the First Amendment is insufficient to protect a free press that can serve as a check on government tyranny. This article argues that we must look beyond the First Amendment to protect watchdog journalism from the corrosive power of platforms. It describes the limits of the First Amendment and precisely how platforms threaten watchdog journalism. It also proposes a menu of extra-constitutional options for bolstering this essential brand of speech

Machine learning in predictive analytics on judicial decision-making

Legal professionals globally are under pressure to provide ‘more for less' – not an easy challenge in the era of big data, increasingly complex regulatory and legislative frameworks and volatile financial markets. Although largely limited to information retrieval and extraction, Machine Learning applications targeted at the legal domain have to some extent become mainstream. The startup market is rife with legal technology providers with many major law firms encouraging research and development through formal legal technology incubator programs. Experienced legal professionals are expected to become technologically astute as part of their response to the ‘more for less' challenge, while legal professionals on track to enter the legal services industry are encouraged to broaden their skill sets beyond a traditional law degree. Predictive analytics applied to judicial decision-making raise interesting discussions around potential benefits to the general public, over-burdened judicial systems and legal professionals respectively. It is also associated with limitations and challenges around manual input required (in the absence of automatic extraction and prediction) and domain-specific application. While there is no ‘one size fits all' solution when considering predictive analytics across legal domains or different countries' legal systems, this dissertation aims to provide an overview of Machine Learning techniques which could be applied in further research, to start unlocking the benefits associated with predictive analytics on a greater (and hopefully local) scale