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The US-driven and NGO-mediated prosecutorial approach to address trafficking prioritizes efforts to convict the accused and foregrounds victim-witness testimony as the central piece of evidence to do so. Though training rescued women to testify against alleged traffickers is thus a key component of donor-driven NGOs’ efforts, the author’s ethnographic research revealed that this is a rare occurrence. This chapter explores the multiple and complex reasons why most rescued women don’t testify, by situating them in the broader Indian sociolegal context. In juxtaposition, it tracks the case of a trafficked woman, Sunaina Das, who testified for the prosecution in a New Delhi trial court, to also explore the constellation of factors that lead some women to testify and the challenges they face. It follows Sunaina’s encounters with the Indian criminal justice system and the support she received from both NGOs and Indian legal actors. Finally, it explores how an NGO-led training session for Indian judges impacted her case. Through these contributions, this chapter challenges prevalent assumptions in global anti-trafficking campaigns about the victimhood of Global South sex workers, about criminal justice necessarily benefiting trafficked sex workers, and about the Indian criminal justice system necessarily lacking the ability to address sex trafficking.
Faced with the trajectory of legal systems today, policymakers can now contend with perhaps the most critical choice of our times. Will they continue down the road to the end of law, or will they renew its role? Will they choose the legal family that is most appropriate for their constituents, or will they let the gravitational pull toward the privatization of disputes decide for them? One might claim that the obfuscated role of law – especially in the pre-filing family – might as well be replaced by AI-based decision-making. Indeed, we show that the pre-filing family may be the most conducive to AI-based dispute resolution. However, one might choose to look at the changes that legal systems have undergone in recent decades as a mark of flexibility within legal systems – and potential for growth. As of today, the underlying motive for change has all too frequently been saving time and money for the legal systems themselves. However, if this underlying motive is moderated and retuned to respond to the needs of the individual litigant, changes of a different nature are possible. We analyze changes that can lead to human-centered design, and the harnessing of AI toward that goal.
Chapter 2 focuses on voir dire, or the questioning of prospective jurors. The traditional view is that this stage is supposed to enable judges and lawyers to determine which prospective jurors are biased and need to be removed and which are unbiased and can serve on the jury. The transformation view is that voir dire has little value as a means of finding jurors who have subtle biases, but it has a lot of value in helping to transform citizens into impartial jurors. Other than in extreme cases of bias, there is little evidence that the kind of biases that everyone has can or should be identified during voir dire. Instead, voir dire really begins the process of helping prospective jurors to put aside their private concerns, to understand the need to manage their own biases, and to see themselves as part of a group endeavor. There is often a moment when prospective jurors stop formulating their excuses and start thinking about serving. At that moment, a transformation begins in earnest. This chapter also describes how voir dire can be reformed to bring about the transformation of citizens into jurors even more effectively than current practice does.
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