Flawed Humans, Flawed Justice


Adam Benforado in the New York Times  on using …”lessons from behavioral science to make police and courts more fair…. WHAT would it take to achieve true criminal justice in America?

Imagine that we got rid of all of the cops who cracked racist jokes and prosecutors blinded by a thirst for power. Imagine that we cleansed our courtrooms of lying witnesses and foolish jurors. Imagine that we removed every judge who thought the law should bend to her own personal agenda and every sadistic prison guard.

We would certainly feel just then. But we would be wrong.

We would still have unarmed kids shot in the back and innocent men and women sentenced to death. We would still have unequal treatment, disregarded rights and profound mistreatment.

The reason is simple and almost entirely overlooked: Our legal system is based on an inaccurate model of human behavior. Until recently, we had no way of understanding what was driving people’s thoughts, perceptions and actions in the criminal arena. So, we built our institutions on what we had: untested assumptions about what deceit looks like, how memories work and when punishment is merited.

But we now have tools — from experimental methods and data collection approaches to brain-imaging technologies — that provide an incredible opportunity to establish a new and robust foundation.

Our justice system must be reconstructed upon scientific fact. We can start by acknowledging what the data says about the fundamental flaws in our current legal processes and structures.

Consider the evidence that we treat as nearly unassailable proof of guilt at trial — an unwavering eyewitness, a suspect’s signed confession or a forensic match to the crime scene.

While we charge tens of thousands of people with crimes each year after they are identified in police lineups, research shows that eyewitnesses chose an innocent person roughly one-third of the time. Our memories can fail us because we’re frightened. They can be altered by the word choice of a detective. They can be corrupted by previously seeing someone’s image on a social media site.

Picking out lying suspects from their body language is ineffective. And trying then to gain a confession by exaggerating the strength of the evidence and playing down the seriousness of the offense can encourage people to admit to terrible things they didn’t do.

Even seemingly objective forensic analysis is far from incorruptible. Recent data shows that fingerprint — and even DNA — matches are significantly more likely when the forensic expert is aware that the sample comes from someone the police believe is guilty.

With the aid of psychology, we see there’s a whole host of seemingly extraneous forces influencing behavior and producing systematic distortions. But they remain hidden because they don’t fit into our familiar legal narratives.

We assume that the specific text of the law is critical to whether someone is convicted of rape, but research shows that the details of the criminal code — whether it includes a “force” requirement or excuses a “reasonably mistaken” belief in consent — can be irrelevant. What matters are the backgrounds and identifies of the jurors.

When a black teenager is shot by a police officer, we expect to find a bigot at the trigger.

But studies suggest that implicit bias, rather than explicit racism, is behind many recent tragedies. Indeed, simulator experiments show that the biggest danger posed to young African-American men may not be hate-filled cops, but well-intentioned police officers exposed to pervasive, damaging stereotypes that link the concepts of blackness and violence.

Likewise, Americans have been sold a myth that there are two kinds of judges — umpires and activists — and that being unbiased is a choice that a person makes. But the truth is that all judges are swayed by countless forces beyond their conscious awareness or control. It should have no impact on your case, for instance, whether your parole hearing is scheduled first thing in the morning or right before lunch, but when scientists looked at real parole boards, they found that judges were far more likely to grant petitions at the beginning of the day than they were midmorning.

The choice of where to place the camera in an interrogation room may seem immaterial, yet experiments show that it can affect whether a confession is determined to be coerced. When people watch a recording with the camera behind the detective, they are far more likely to find that the confession was voluntary than when watching the interactions from the perspective of the suspect.

With such challenges to our criminal justice system, what can possibly be done? The good news is that an evidence-based approach also illuminates the path forward.

Once we have clear data that something causes a bias, we can then figure out how to remove that influence. …(More)

The death of data science – and rise of the citizen scientist


Ben Rossi at Information Age: “The notion of data science was born from the recent idea that if you have enough data, you don’t need much (if any) science to divine the truth and foretell the future – as opposed to the long-established rigours of statistical or actuarial science, which most times require painstaking efforts and substantial time to produce their version of ‘the truth’. …. Rather than embracing this untested and, perhaps, doomed form of science, and aimlessly searching for unicorns (also known as data scientists) to pay vast sums to, many organisations are now embracing the idea of making everyone data and analytics literate.

This leads me to what my column is really meant to focus on: the rise of the citizen scientist. 

The citizen scientist is not a new idea, having seen action in the space and earth sciences world for decades now, and has really come into its own as we enter the age of open data.

Cometh the hour

Given the exponential growth of open data initiatives across the world – the UK remains the leader, but has growing competition from all locations – the need for citizen scientists is now paramount. 

As governments open up vast repositories of new data of every type, the opportunity for these same governments (and commercial interests) to leverage the passion, skills and collective know-how of citizen scientists to help garner deeper insights into the scientific and civic challenges of the day is substantial. 

They can then take this knowledge and the collective energy of the citizen scientist community to develop common solution sets and applications to meet the needs of all their constituencies without expending much in terms of financial resources or suffering substantial development time lags. 

This can be a windfall of benefits for every level or type of government found around the world. The use of citizen scientists to tackle so-called ‘grand challenge’ problems has been a driving force behind many governments’ commitment to and investment in open data to date. 

There are so many challenges in governing today that it would be foolish not to employ these very capable resources to help tackle them. 

The benefits manifested from this approach are substantial and well proven. Many are well articulated in the open data success stories to date. 

Additionally, you only need to attend a local ‘hack fest’ to see how engaged citizen scientists can be of any age, gender and race, and feel the sense of community that these events foster as everyone focuses on the challenges at hand and works diligently to surmount them using very creative approaches. 

As open data becomes pervasive in use and matures in respect to the breadth and richness of the data sets being curated, the benefits returned to both government and its constituents will be manifold. 

The catalyst to realising these benefits and achieving return on investment will be the role of citizen scientists, which are not going to be statisticians, actuaries or so-called data gurus, but ordinary people with a passion for science and learning and a desire to contribute to solving the many grand challenges facing society at large….(More)

Policy Practice and Digital Science


New book edited by Janssen, Marijn, Wimmer, Maria A., and Deljoo, Ameneh: “The explosive growth in data, computational power, and social media creates new opportunities for innovating the processes and solutions of Information and communications technology (ICT) based policy-making and research. To take advantage of these developments in the digital world, new approaches, concepts, instruments and methods are needed to navigate the societal and computational complexity. This requires extensive interdisciplinary knowledge of public administration, policy analyses, information systems, complex systems and computer science. This book provides the foundation for this new interdisciplinary field, in which various traditional disciplines are blending. Both policy makers, executors and those in charge of policy implementations acknowledge that ICT is becoming more important and is changing the policy-making process, resulting in a next generation policy-making based on ICT support. Web 2.0 and even Web 3.0 point to the specific applications of social networks, semantically enriched and linked data, whereas policy-making has also to do with the use of the vast amount of data, predictions and forecasts, and improving the outcomes of policy-making, which is confronted with an increasing complexity and uncertainty of the outcomes. The field of policy-making is changing and driven by developments like open data, computational methods for processing data, opining mining, simulation and visualization of rich data sets, all combined with public engagement, social media and participatory tools….(More)”

Social Dimensions of Privacy


New book edited by Dorota Mokrosinska and Beate Roessler: “Written by a select international group of leading privacy scholars, Social Dimensions of Privacy endorses and develops an innovative approach to privacy. By debating topical privacy cases in their specific research areas, the contributors explore the new privacy-sensitive areas: legal scholars and political theorists discuss the European and American approaches to privacy regulation; sociologists explore new forms of surveillance and privacy on social network sites; and philosophers revisit feminist critiques of privacy, discuss markets in personal data, issues of privacy in health care and democratic politics. The broad interdisciplinary character of the volume will be of interest to readers from a variety of scientific disciplines who are concerned with privacy and data protection issues.

  • Takes an innovative approach to privacy which focuses on the social dimensions and value of privacy in contrast to the value of privacy for individuals
  • Addresses readers from a variety of disciplines, including law, philosophy, media studies, gender studies and political science
  • Addresses new privacy-sensitive areas triggered by recent technological developments (More)”

New ODI research shows open data reaching every sector of UK industry


ODI: “New research has been published today (1 June) by the Open Data Institute showing that open data is reaching every sector of UK industry.

In various forms, open data is being adopted by a wide variety of businesses – small and large, new and old, from right across the country. The findings from Open data means business: UK innovation across sectors and regions draw on 270 companies with a combined turnover of £92bn and over 500k employees, identified by the ODI as using, producing or investing in open data as part of their business. The project included desk research, surveys and interviews on the companies’ experiences.

Key findings from the research include:

  • Companies using open data come from many sectors; over 46% from outside the information and communication sector. These include finance & insurance, science & technology, business administration & support, arts & entertainment, health, retail, transportation, education and energy.
  • The most popular datasets for companies aregeospatial/mapping data (57%), transport data (43%) and environment data (42%).
  • 39% of companies innovating with open data are over 10 years old, with some more than 25 years old, proving open data isn’t just for new digital startups.
  • ‘Micro-enterprises’ (businesses with fewer than 10 employees) represented 70% of survey respondents, demonstrating athriving open data startup scene. These businesses are using it to create services, products and platforms. 8% of respondents were drawn from large companies of 251 or more employees….
  • The companies surveyed listed 25 different government sources for the data they use. Notably, Ordnance Survey data was cited most frequently, by 14% of the companies. The non-government source most commonly used was OpenStreetMap, an openly licenced map of the world created by volunteers….(More)

Governing methods: policy innovation labs, design and data science in the digital governance of education


Paper by Ben Williamson in the Journal of Educational Administration and History: “Policy innovation labs are emerging knowledge actors and technical experts in the governing of education. The article offers a historical and conceptual account of the organisational form of the policy innovation lab. Policy innovation labs are characterised by specific methods and techniques of design, data science, and digitisation in public services such as education. The second half of the article details how labs promote the use of digital data analysis, evidence-based evaluation and ‘design-for-policy’ techniques as methods for the governing of education. In particular, they promote the ‘computational thinking’ associated with computer programming as a capacity required by a ‘reluctant state’ that is increasingly concerned to delegate its responsibilities to digitally enabled citizens with the ‘designerly’ capacities and technical expertise to ‘code’ solutions to public and social problems. Policy innovation labs are experimental laboratories trialling new methods within education for administering and governing the future of the state itself….(More)”

Want better science? Quit hoarding data, genetics researchers say


Nidhi Subbaraman at BetaBoston: “When Andrea Downing was 25, she got screened for the BRCA genes known to be associated with a variety of cancers, including breast cancer. Both her great-grandmother and grandmother had been diagnosed with the disease, so the results were no surprise: Downing carried the BRCA1 mutation in her genes. She learned there was a 87 percent chance she would get breast cancer during her lifetime, and 60 percent chance she would get ovarian cancer.
The revelation brought with it a dizzying range of choices. Should she get a mastectomy before the cancer showed? Should she choose to have her ovaries removed? Could she wait until after she had kids?

For the first several years after her diagnosis, Downing sought out support groups, then began booking appointments with researchers and examining the latest literature. “I’m a little different from your usual patient who tested positive,” Downing said. “I wanted to go beyond to challenge myself and understand the science of cancer.”

Then, in 2013, she chanced on was ClinVar, a research database funded by the National Institute of Health that acts as a kind of Wikipedia to catalogue scientific research on mutations in genes. It gave her a roadmap for the research associated with her variant, called C16G.

Downing typed in the letters and numbers of her mutation, and the website spit out a list of companies and labs that have studied her variant. Though much of that information was technical, she said, “the things I do understand about it are very empowering. It’s a starting point to answering questions I don’t know.”

When the database first launched, the idea was that the single repository would present a unified picture of a variant, drawing from all available research that was publicly shared by companies and research labs.

Two years later, the team behind the operation has published a progress report of sorts in the New England Journal of Medicine. They argue that this shared approach is working — doctors and researchers are using the database — and they are advocating for more companies and groups to join the effort to reach a more comprehensive understanding of the variants in disease genes. In particular, they’re challenging companies to be more open with their data, instead of keeping it to themselves….(More)”

Protecting Privacy in Data Release


Book by Giovanni Livraga: “This book presents a comprehensive approach to protecting sensitive information when large data collections are released by their owners. It addresses three key requirements of data privacy: the protection of data explicitly released, the protection of information not explicitly released but potentially vulnerable due to a release of other data, and the enforcement of owner-defined access restrictions to the released data. It is also the first book with a complete examination of how to enforce dynamic read and write access authorizations on released data, applicable to the emerging data outsourcing and cloud computing situations. Private companies, public organizations and final users are releasing, sharing, and disseminating their data to take reciprocal advantage of the great benefits of making their data available to others. This book weighs these benefits against the potential privacy risks. A detailed analysis of recent techniques for privacy protection in data release and case studies illustrate crucial scenarios. Protecting Privacy in Data Release targets researchers, professionals and government employees working in security and privacy. Advanced-level students in computer science and electrical engineering will also find this book useful as a secondary text or reference….(More)”

The Art of Insight in Science and Engineering: Mastering Complexity


Book by Sanjoy Mahajan: “…shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author’s fifteen years of teaching at MIT, Cambridge University, and Olin College, The Art of Insight in Science and Engineering shows us how to build insight and find understanding, giving readers tools to help them solve any problem in science and engineering.

To master complexity, we can organize it or discard it. The Art of Insight in Science and Engineeringfirst teaches the tools for organizing complexity, then distinguishes the two paths for discarding complexity: with and without loss of information. Questions and problems throughout the text help readers master and apply these groups of tools. Armed with this three-part toolchest, and without complicated mathematics, readers can estimate the flight range of birds and planes and the strength of chemical bonds, understand the physics of pianos and xylophones, and explain why skies are blue and sunsets are red. (Public access version of the book).

Big Data. Big Obstacles.


Dalton Conley et al. in the Chronicle of Higher Education: “After decades of fretting over declining response rates to traditional surveys (the mainstay of 20th-century social research), an exciting new era would appear to be dawning thanks to the rise of big data. Social contagion can be studied by scraping Twitter feeds; peer effects are tested on Facebook; long-term trends in inequality and mobility can be assessed by linking tax records across years and generations; social-psychology experiments can be run on Amazon’s Mechanical Turk service; and cultural change can be mapped by studying the rise and fall of specific Google search terms. In many ways there has been no better time to be a scholar in sociology, political science, economics, or related fields.

However, what should be an opportunity for social science is now threatened by a three-headed monster of privatization, amateurization, and Balkanization. A coordinated public effort is needed to overcome all of these obstacles.

While the availability of social-media data may obviate the problem of declining response rates, it introduces all sorts of problems with the level of access that researchers enjoy. Although some data can be culled from the web—Twitter feeds and Google searches—other data sit behind proprietary firewalls. And as individual users tune up their privacy settings, the typical university or independent researcher is increasingly locked out. Unlike federally funded studies, there is no mandate for Yahoo or Alibaba to make its data publicly available. The result, we fear, is a two-tiered system of research. Scientists working for or with big Internet companies will feast on humongous data sets—and even conduct experiments—and scholars who do not work in Silicon Valley (or Alley) will be left with proverbial scraps….

To address this triple threat of privatization, amateurization, and Balkanization, public social science needs to be bolstered for the 21st century. In the current political and economic climate, social scientists are not waiting for huge government investment like we saw during the Cold War. Instead, researchers have started to knit together disparate data sources by scraping, harmonizing, and geo­coding any and all information they can get their hands on.

Currently, many firms employ some well-trained social and behavioral scientists free to pursue their own research; likewise, some companies have programs by which scholars can apply to be in residence or work with their data extramurally. However, as Facebook states, its program is “by invitation only and requires an internal Facebook champion.” And while Google provides services like Ngram to the public, such limited efforts at data sharing are not enough for truly transparent and replicable science….(More)”