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Sturgeon Says UK PM May Nudging Scotland Towards Second Referendum

U.S. News

Speculation about a possible second Scottish secession vote has increased in the last week with media reports suggesting nationalists were preparing to call for a referendum as early as next month to coincide with Prime Minister Theresa May's plan to formally trigger Britain's exit from the European Union.


Nudging people to court

Science

New York City issues hundreds of thousands of summonses and misdemeanor arrests each year, highly concentrated in the city's poorer and minority communities ([ 1 ][1], [ 2 ][2]). On page 682 of this issue, Fishbane et al. ([ 3 ][3]) report that about 40% of the summonses (issued usually for infractions or violations that are classified below misdemeanors) issued in New York City in 2015 resulted in a failure to appear (“FTA”) in court, which (usually) results in an arrest warrant and a host of collateral consequences ([ 4 ][4], [ 5 ][5]). To increase the likelihood that a person issued a summons shows up to the mandatory court date, Fishbane et al. experimented with a number of different behavioral “nudges,” such as summons form redesign and texting different types of reminders to defendants. They found that all of these interventions decreased the FTA rate. It would be a positive step if other jurisdictions adopted these reforms. However, if the authors are correct that their study shows that FTAs are not exclusively caused by “choosing” not to appear in court, what role will that have in efforts to reform our massive and punitive criminal legal system? Predicting behavior is distinct from understanding motives. Fishbane et al. suggest that the research design can adjudicate between two different motives for identical behavior: contempt for one's legal obligations versus lack of knowledge about one's legal obligations. This may be a mere framing device for the authors' true interest—perhaps simply establishing the existence of a treatment effect and estimating its magnitude. But behavioral economics infrequently so limits its explanatory ambitions. Rather, it aspires to illuminate underlying causal mechanisms by reference to general psychological principles. What makes such topics interesting, yet difficult, is that observed behavioral propensities are usually compatible with multiple psychological explanations [e.g., ([ 6 ][6])]. Although the evidence that the “nudge” treatments produce causal effects seems fairly straightforward, the authors' preferred explanation of the effect is less clear. What the authors present as opposing hypotheses do not seem to be mutually exclusive. The hypothesis the authors seem interested in refuting—that the high FTA rate for summonses is explained by defendants “deciding to skip court”—might capture many mental states. One such mental state might be “To hell with criminal court,” where someone is aware of the specifics of their court obligations and would be intent on noncompliance irrespective of more information about how to comply or the consequences of failure. Another might be “I can't afford to go to court today,” where someone is aware of the specifics of their court date, but does not attend because they made a rational calculation that the benefits of nonappearance outweigh the costs (e.g., the opportunity costs of competing obligations to work or child care). But one can “choose” not to attend court even while being unaware of the specifics of the obligation simply by “choosing” not to look at the information. Versions of this could include: “I realize this summons means I am supposed to go to court at some time, somewhere. But I feel hopeless and disillusioned from repeated injustice in the criminal legal system and I am tuned out,” or “I am overwhelmed and busy trying to manage so many life obligations with so few resources, I never got around to this one.” From my years studying and working in New York City's criminal courts, these seem especially plausible. But these do not seem conceptually exclusive of the authors' preferred hypothesis: “insufficient awareness” of legal obligations. What I find more interesting, as a lawyer, sociologist, and reform advocate, is what these opposing theses say about how we think we must approach the politics of criminal legal reform. The hypotheses reflect our cultural assumptions: Either the people summonsed by the state—largely low-income Black and brown residents—are deserving of compassion or leniency because they are oblivious, or they are undeserving because they are obstinate. But they are not excused on the same terms many of us frequently invoke: We are busy, our time and resources are overtaxed, and we sometimes fail to discharge some of our obligations because we are just emotionally overwhelmed. Unfortunately, the largely low-income and minority communities where summons enforcement is concentrated have had all too many encounters with the state's penal authority. Most recognize that the little piece of paper the police officer hands them represents another mandatory encounter with the state's coercive arm. The fact that it is confusing or mentally taxing to pin down the logistical details of how exactly to comply is distinct from the claim that one is not “aware” that the state has issued a sanction-backed demand to do so. To live in poverty and in highly policed neighborhoods in America is to be constantly subjected to such demands—from police, courts, welfare agencies, child services, landlords—and to hear a persistent message that one's failure to successfully perform is proof of one's unfitness for concern and respect in our polity. At the height of “Broken Windows” policing in New York City around 2010, almost three-quarters of summonses and half of misdemeanor arrests resulted in some kind of dismissal, most of them “earned” because defendants did community service, agreed to a temporary marking on their record, or just appeared in court until the prosecution was willing to dismiss charges ([ 2 ][2], [ 7 ][7]). Many New York City prosecutors hold “clean slate” events where anyone with an outstanding summons warrant can have it dismissed without adjudication or paying a fine. The entire logic of low-level enforcement is less about showing up to court for the purpose of adjudicating the underlying accusation than it is about showing up to court for the purpose of demonstrating that one has undertaken a cost to perform a responsibility. I would respectfully disagree with the authors' assertion that our nation's punitive penal policies are “built on an assumption that people intentionally weigh the costs and benefits” of illegal conduct. I would say they are built on the assumption that the people targeted by such policies—largely people of color and impoverished people—are undeserving of full and equal membership in our political community absent a positive showing of worthiness. Consider the evidence presented by Fishbane et al. in which MTurk participants responded to information about hypothetical “failures to take a required action,” such as paying bills, turning in educational paperwork, and making a required criminal court appearance (i.e., FTA). Compared to most other domains, respondents rated court FTAs as less likely attributable to “forgetting” and more likely to be “intentional.” And respondents were least supportive of “nudges” in the criminal justice domain. These findings might just be ascriptions of blameworthiness. When people are asked how likely it is that a criminal defendant “intentionally and deliberately decided to skip their appointment,” they might be reporting how likely they think it is that this person is as culpable as “intentionally deciding” to skip, whether or not the person actually knew when and where the appointment was or remembered its occasion ([ 8 ][8]). Similarly, respondents' expression of preferences for punitive measures over “nudges” in response to court FTAs does not necessarily mean they believe one is more efficacious than the other in the criminal justice domain. It might well reflect their political moral judgments that people who miss court, irrespective of the reasons, deserve punishments and not nudges. This is especially likely given evidence that whenever you ask someone about their attitudes toward crime, they are often also expressing their attitudes toward race ([ 9 ][9], [ 10 ][10]). Although it would be positive if many jurisdictions would adopt the practices described by Fishbane et al. , changing the approach to penal and welfare policy in our country will require interventions that are much more radical than cost-neutral behavioral nudges that everyone can agree on. 1. [↵][11]New York City does not collect racial identification data on the summons form. Data on misdemeanor arrests show that about 80% of fingerprintable misdemeanor arrests in recent years are of Black or Hispanic individuals. See ([ 2 ][2]). 2. [↵][12]1. I. Kohler-Hausmann , Misdemeanorland: Criminal Courts and Social Control in an Age of Broken Windows Policing (Princeton Univ. Press, 2018). 3. [↵][13]1. A. Fishbane et al ., Science 370, eabb6591 (2020). [OpenUrl][14][Abstract/FREE Full Text][15] 4. [↵][16]The FTA rate for misdemeanor arrests (including “desk appearance ticket” arrests) is substantially lower than 40%, with about half of those returning voluntarily within 30 days of the missed court date. See data from ([ 5 ][5]). 5. [↵][17]New York City Criminal Justice Agency, CJA Annual Report of 2017 (pp. 19, 36–38); . 6. [↵][18]1. D. Gal, 2. D. D. Rucker , J. Consum. Psychol. 28, 497 (2018). [OpenUrl][19][CrossRef][20][PubMed][21] 7. [↵][22]1. P. Chauhan et al ., The Summons Report: Trends in the Issuance and Disposition of Summonses in New York City 2003–2013; [www.jjay.cuny.edu/sites/default/files/news/Summons\_Report\_DRAFT\_4\_24\_2015\_v8.pdf][23]. 8. [↵][24]This elision is what is behind much of criminal law doctrine on “willful ignorance,” where courts and juries find defendants guilty because they believe choosing not to know under certain circumstances is just as culpable as knowing. 9. [↵][25]1. R. C. Hetey, 2. J. L. Eberhardt , Psychol. Sci. 25, 1949 (2014). [OpenUrl][26][CrossRef][20][PubMed][21] 10. [↵][27]This is analogous to a situation where people responding to the question “Do workers who are late for work because of childcare problems deserve to be fired?” might also be expressing beliefs about women in the workforce. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: #ref-9 [10]: #ref-10 [11]: #xref-ref-1-1 "View reference 1 in text" [12]: #xref-ref-2-1 "View reference 2 in text" [13]: #xref-ref-3-1 "View reference 3 in text" [14]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DFishbane%26rft.auinit1%253DA.%26rft.volume%253D370%26rft.issue%253D6517%26rft.spage%253Deabb6591%26rft.epage%253Deabb6591%26rft.atitle%253DBehavioral%2Bnudges%2Breduce%2Bfailure%2Bto%2Bappear%2Bfor%2Bcourt%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.abb6591%26rft_id%253Dinfo%253Apmid%252F33033154%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [15]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjE3OiIzNzAvNjUxNy9lYWJiNjU5MSI7czo0OiJhdG9tIjtzOjIyOiIvc2NpLzM3MC82NTE3LzY1OC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [16]: #xref-ref-4-1 "View reference 4 in text" [17]: #xref-ref-5-1 "View reference 5 in text" [18]: #xref-ref-6-1 "View reference 6 in text" [19]: {openurl}?query=rft.jtitle%253DJ.%2BConsum.%2BPsychol.%26rft_id%253Dinfo%253Adoi%252F10.1177%252F0956797614540307%26rft_id%253Dinfo%253Apmid%252F25097060%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [20]: /lookup/external-ref?access_num=10.1177/0956797614540307&link_type=DOI [21]: /lookup/external-ref?access_num=25097060&link_type=MED&atom=%2Fsci%2F370%2F6517%2F658.atom [22]: #xref-ref-7-1 "View reference 7 in text" [23]: http://www.jjay.cuny.edu/sites/default/files/news/Summons_Report_DRAFT_4_24_2015_v8.pdf [24]: #xref-ref-8-1 "View reference 8 in text" [25]: #xref-ref-9-1 "View reference 9 in text" [26]: {openurl}?query=rft.jtitle%253DPsychol.%2BSci.%26rft_id%253Dinfo%253Adoi%252F10.1177%252F0956797614540307%26rft_id%253Dinfo%253Apmid%252F25097060%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [27]: #xref-ref-10-1 "View reference 10 in text"


Will Democracy Survive Big Data and Artificial Intelligence?

#artificialintelligence

"Enlightenment is man's emergence from his self-imposed immaturity. Immaturity is the inability to use one's understanding without guidance from another." The digital revolution is in full swing. How will it change our world? The amount of data we produce doubles every year. In other words: in 2016 we produced as much data as in the entire history of humankind through 2015. Every minute we produce hundreds of thousands of Google searches and Facebook posts. These contain information that reveals how we think and feel. Soon, the things around us, possibly even our clothing, also will be connected with the Internet. It is estimated that in 10 years' time there will be 150 billion networked measuring sensors, 20 times more than people on Earth. Then, the amount of data will double every 12 hours. Many companies are already trying to turn this Big Data into Big Money. Everything will become intelligent; soon we will not only have smart phones, but also smart homes, smart factories and smart cities. Should we also expect these developments to result in smart nations and a smarter planet? The field of artificial intelligence is, indeed, making breathtaking advances. In particular, it is contributing to the automation of data analysis. Artificial intelligence is no longer programmed line by line, but is now capable of learning, thereby continuously developing itself. Recently, Google's DeepMind algorithm taught itself how to win 49 Atari games. Algorithms can now recognize handwritten language and patterns almost as well as humans and even complete some tasks better than them. They are able to describe the contents of photos and videos. Today 70% of all financial transactions are performed by algorithms. News content is, in part, automatically generated. This all has radical economic consequences: in the coming 10 to 20 years around half of today's jobs will be threatened by algorithms. It can be expected that supercomputers will soon surpass human capabilities in almost all areas--somewhere between 2020 and 2060.


Will Democracy Survive Big Data and Artificial Intelligence?

#artificialintelligence

"Enlightenment is man's emergence from his self-imposed immaturity. Immaturity is the inability to use one's understanding without guidance from another." The digital revolution is in full swing. How will it change our world? The amount of data we produce doubles every year. In other words: in 2016 we produced as much data as in the entire history of humankind through 2015. Every minute we produce hundreds of thousands of Google searches and Facebook posts. These contain information that reveals how we think and feel. Soon, the things around us, possibly even our clothing, also will be connected with the Internet. It is estimated that in 10 years' time there will be 150 billion networked measuring sensors, 20 times more than people on Earth. Then, the amount of data will double every 12 hours. Many companies are already trying to turn this Big Data into Big Money. Everything will become intelligent; soon we will not only have smart phones, but also smart homes, smart factories and smart cities. Should we also expect these developments to result in smart nations and a smarter planet? The field of artificial intelligence is, indeed, making breathtaking advances. In particular, it is contributing to the automation of data analysis. Artificial intelligence is no longer programmed line by line, but is now capable of learning, thereby continuously developing itself. Recently, Google's DeepMind algorithm taught itself how to win 49 Atari games. Algorithms can now recognize handwritten language and patterns almost as well as humans and even complete some tasks better than them. They are able to describe the contents of photos and videos. Today 70% of all financial transactions are performed by algorithms. News content is, in part, automatically generated. This all has radical economic consequences: in the coming 10 to 20 years around half of today's jobs will be threatened by algorithms. It can be expected that supercomputers will soon surpass human capabilities in almost all areas--somewhere between 2020 and 2060. Experts are starting to ring alarm bells.


Constraint-Based Verification of a Mobile App Game Designed for Nudging People to Attend Cancer Screening

AAAI Conferences

In Norway, cervical cancer prevention involves the participation of as many eligible women aged 25-69 years as possible. However, reaching and inviting every eligible women to attend cervical cancer screening and HPV vaccination is difficult. Using social nudging and gamification in modern means of communication can encourage the participation of unscreened people. Simula Research Laboratory together with the Cancer Registry of Norway have developed FightHPV, a mobile app game intended to inform adolescent and eligible women about cervical cancer screening and HPV vaccination while they play and, to facilitate their further participation to prevention campaigns. However, game design and health information transfer can be hard to reconcile, as the design of each game episode is more guided by the release of information than gameplay and playing difficulty. In this paper, we propose a constraint-based model of FightHPV to evaluate the difficulty of each episode and to help the game designer in improving the player experience. This approach is relevant to facilitate social nudging of eligible women to participate to cervical cancer screening and HPV vaccination, as shown by the initial deployment of FightHPV and tests performed in focus groups. The design of this mobile app can thus be regarded as a new application case of Artificial Intelligence techniques such as gamification and constraint programming.