Report on Algorithmic Risk Assessment Tools in the U.S. Criminal Justice System


Press release: “The Partnership on AI (PAI) has today published a report gathering the views of the multidisciplinary artificial intelligence and machine learning research and ethics community which documents the serious shortcomings of algorithmic risk assessment tools in the U.S. criminal justice system. These kinds of AI tools for deciding on whether to detain or release defendants are in widespread use around the United States, and some legislatures have begun to mandate their use. Lessons drawn from the U.S. context have widespread applicability in other jurisdictions, too, as the international policymaking community considers the deployment of similar tools.

While criminal justice risk assessment tools are often simpler than the deep neural networks used in many modern artificial intelligence systems, they are basic forms of AI. As such, they present a paradigmatic example of the high-stakes social and ethical consequences of automated AI decision-making….

Across the report, challenges to using these tools fell broadly into three primary categories:

  1. Concerns about the accuracy, bias, and validity in the tools themselves
    • Although the use of these tools is in part motivated by the desire to mitigate existing human fallibility in the criminal justice system, this report suggests that it is a serious misunderstanding to view tools as objective or neutral simply because they are based on data.
  2. Issues with the interface between the tools and the humans who interact with them
    • In addition to technical concerns, these tools must be held to high standards of interpretability and explainability to ensure that users (including judges, lawyers, and clerks, among others) can understand how the tools’ predictions are reached and make reasonable decisions based on these predictions.
  3. Questions of governance, transparency, and accountability
    • To the extent that such systems are adapted to make life-changing decisions, tools and decision-makers who specify, mandate, and deploy them must meet high standards of transparency and accountability.

This report highlights some of the key challenges with the use of risk assessment tools for criminal justice applications. It also raises some deep philosophical and procedural issues which may not be easy to resolve. Surfacing and addressing those concerns will require ongoing research and collaboration between policymakers, the AI research community, civil society groups, and affected communities, as well as new types of data collection and transparency. It is PAI’s mission to spur and facilitate these conversations and to produce research to bridge such gaps….(More)”

AI & Global Governance: Robots Will Not Only Wage Future Wars but also Future Peace


Daanish Masood & Martin Waehlisch at the United Nations University: “At the United Nations, we have been exploring completely different scenarios for AI: its potential to be used for the noble purposes of peace and security. This could revolutionize the way of how we prevent and solve conflicts globally.

Two of the most promising areas are Machine Learning and Natural Language Processing. Machine Learning involves computer algorithms detecting patterns from data to learn how to make predictions and recommendations. Natural Language Processing involves computers learning to understand human languages.

At the UN Secretariat, our chief concern is with how these emerging technologies can be deployed for the good of humanity to de-escalate violence and increase international stability.

This endeavor has admirable precedent. During the Cold War, computer scientists used multilayered simulations to predict the scale and potential outcome of the arms race between the East and the West.

Since then, governments and international agencies have increasingly used computational models and advanced Machine Learning to try to understand recurrent conflict patterns and forecast moments of state fragility.

But two things have transformed the scope for progress in this field.

The first is the sheer volume of data now available from what people say and do online. The second is the game-changing growth in computational capacity that allows us to crunch unprecedented, inconceivable quantities data with relative speed and ease.

So how can this help the United Nations build peace? Three ways come to mind.

Firstly, overcoming cultural and language barriers. By teaching computers to understand human language and the nuances of dialects, not only can we better link up what people write on social media to local contexts of conflict, we can also more methodically follow what people say on radio and TV. As part of the UN’s early warning efforts, this can help us detect hate speech in a place where the potential for conflict is high. This is crucial because the UN often works in countries where internet coverage is low, and where the spoken languages may not be well understood by many of its international staff.

Natural Language Processing algorithms can help to track and improve understanding of local debates, which might well be blind spots for the international community. If we combine such methods with Machine Learning chatbots, the UN could conduct large-scale digital focus groups with thousands in real-time, enabling different demographic segments in a country to voice their views on, say, a proposed peace deal – instantly testing public support, and indicating the chances of sustainability.

Secondly, anticipating the deeper drivers of conflict. We could combine new imaging techniques – whether satellites or drones – with automation. For instance, many parts of the world are experiencing severe groundwater withdrawal and water aquifer depletion. Water scarcity, in turn, drives conflicts and undermines stability in post-conflict environments, where violence around water access becomes more likely, along with large movements of people leaving newly arid areas.

One of the best predictors of water depletion is land subsidence or sinking, which can be measured by satellite and drone imagery. By combining these imaging techniques with Machine Learning, the UN can work in partnership with governments and local communities to anticipate future water conflicts and begin working proactively to reduce their likelihood.

Thirdly, advancing decision making. In the work of peace and security, it is surprising how many consequential decisions are still made solely on the basis of intuition.

Yet complex decisions often need to navigate conflicting goals and undiscovered options, against a landscape of limited information and political preference. This is where we can use Deep Learning – where a network can absorb huge amounts of public data and test it against real-world examples on which it is trained while applying with probabilistic modeling. This mathematical approach can help us to generate models of our uncertain, dynamic world with limited data.

With better data, we can eventually make better predictions to guide complex decisions. Future senior peace envoys charged with mediating a conflict would benefit from such advances to stress test elements of a peace agreement. Of course, human decision-making will remain crucial, but would be informed by more evidence-driven robust analytical tools….(More)”.

Politics and Technology in the Post-Truth Era


Book edited by Anna Visvizi and Miltiadis D. Lytras: “Advances in information and communication technology (ICT) have directly impacted the way in which politics operates today. Bringing together research on Europe, the US, South America, the Middle East, Asia and Africa, this book examines the relationship between ICT and politics in a global perspective.

Technological innovations such as big data, data mining, sentiment analysis, cognitive computing, artificial intelligence, virtual reality, augmented reality, social media and blockchain technology are reshaping the way ICT intersects with politics and in this collection contributors examine these developments, demonstrating their impact on the political landscape. Chapters examine topics such as cyberwarfare and propaganda, post-Soviet space, Snowden, US national security, e-government, GDPR, democratization in Africa and internet freedom.


Providing an overview of new research on the emerging relationship between the promise and potential inherent in ICT and its impact on politics, this edited collection will prove an invaluable text for students, researchers and practitioners working in the fields of Politics, International Relations and Computer Science…..(More)”

LAPD moving away data-driven crime programs over potential racial bias


Mark Puente in The Los Angeles Times: “The Los Angeles Police Department pioneered the controversial use of data to pinpoint crime hot spots and track violent offenders.

Complex algorithms and vast databases were supposed to revolutionize crime fighting, making policing more efficient as number-crunching computers helped to position scarce resources.

But critics long complained about inherent bias in the data — gathered by officers — that underpinned the tools.

They claimed a partial victory when LAPD Chief Michel Moore announced he would end one highly touted program intended to identify and monitor violent criminals. On Tuesday, the department’s civilian oversight panel raised questions about whether another program, aimed at reducing property crime, also disproportionately targets black and Latino communities.

Members of the Police Commission demanded more information about how the agency plans to overhaul a data program that helps predict where and when crimes will likely occur. One questioned why the program couldn’t be suspended.

“There is very limited information” on the program’s impact, Commissioner Shane Murphy Goldsmith said.

The action came as so-called predictive policing— using search tools, point scores and other methods — is under increasing scrutiny by privacy and civil liberties groups that say the tactics result in heavier policing of black and Latino communities. The argument was underscored at Tuesday’s commission meeting when several UCLA academics cast doubt on the research behind crime modeling and predictive policing….(More)”.

Introducing the Contractual Wheel of Data Collaboration


Blog by Andrew Young and Stefaan Verhulst: “Earlier this year we launched the Contracts for Data Collaboration (C4DC) initiative — an open collaborative with charter members from The GovLab, UN SDSN Thematic Research Network on Data and Statistics (TReNDS), University of Washington and the World Economic Forum. C4DC seeks to address the inefficiencies of developing contractual agreements for public-private data collaboration by informing and guiding those seeking to establish a data collaborative by developing and making available a shared repository of relevant contractual clauses taken from existing legal agreements. Today TReNDS published “Partnerships Founded on Trust,” a brief capturing some initial findings from the C4DC initiative.

The Contractual Wheel of Data Collaboration [beta]

The Contractual Wheel of Data Collaboration [beta] — Stefaan G. Verhulst and Andrew Young, The GovLab

As part of the C4DC effort, and to support Data Stewards in the private sector and decision-makers in the public and civil sectors seeking to establish Data Collaboratives, The GovLab developed the Contractual Wheel of Data Collaboration [beta]. The Wheel seeks to capture key elements involved in data collaboration while demystifying contracts and moving beyond the type of legalese that can create confusion and barriers to experimentation.

The Wheel was developed based on an assessment of existing legal agreements, engagement with The GovLab-facilitated Data Stewards Network, and analysis of the key elements of our Data Collaboratives Methodology. It features 22 legal considerations organized across 6 operational categories that can act as a checklist for the development of a legal agreement between parties participating in a Data Collaborative:…(More)”.

How nudge theory is ageing well


Julian Baggini at the Financial Times: “A decade ago, Cass Sunstein and Richard Thaler’s book Nudge was on the desk of every serious politician and policy wonk. Its central thesis was alluringly simple: by changing the environment in which we make decisions — the “choice architecture” — people could be encouraged to do things that were good for them and for society without governments compelling them to do anything.

The idea hit the liberal sweet-spot, promising maximum social impact for minimal interference with personal freedom. In 2010, Britain’s government set up its Behavioural Insights Team — popularly known as the “nudge unit” — to put these ideas into practice.

Around the world, others followed. Sunstein is justly proud that 10m poor American children now get free breakfast and lunch during the academic year as a result of just one such intervention making enrolment for free school meals automatic.

Ten years on, Sunstein has produced two new books to win over the unconverted and boost the faith of true believers. One, On Freedom, is a tiny, commuter-friendly pamphlet between hard covers. The other, Trusting Nudges, co-authored with the behavioural economist Lucia A Reisch, is a short, thoughtful, measured and important analysis of what citizens actually think about nudging and why that matters — albeit with the dry, academic furniture of endless tables, footnotes and technical appendices.

Despite the stylistic gulf between them, the two books are best read together as a response to those who would like to give nudges the nudge, claiming that they are covert, manipulative, an insult to human agency and place too much trust in governments and too little on human reason. Not only that, but for all the hype, nudges only work at the margins, delivering relatively minor results without having any major impact on poverty, inequity or inequality.

On Freedom economically and elegantly takes apart the accusation that nudges undermine liberty. Sunstein rightly points out that a nudge is only a nudge by definition if it leaves the nudged able to choose otherwise. For example, the system adopted by several jurisdictions to put people on organ donation registers by default carries with it the right to opt out. Nor are the best nudges covert.

There may not be a sign at the canteen telling you that healthy foods have been put at the front because that’s where you’re more likely to choose them but organisations that adopt this as a policy can and should do so openly. Sunstein’s most important argument is that “we cannot wish choice architecture away”: something has to be on the supermarket shelves that people tend to take more from, something has to be the default for benefit claims. The question is not whether we nudge but how we do so: with forethought or without….(More)”

San Francisco teams up with Uber, location tracker on 911 call responses


Gwendolyn Wu at San Francisco Chronicle: “In an effort to shorten emergency response times in San Francisco, the city announced on Monday that it is now using location data from RapidSOS, a New York-based public safety tech company, and ride-hailing company Uber to improve location coordinates generated from 911 calls.

An increasing amount of emergency calls are made from cell phones, said Michelle Cahn, RapidSOS’s director of community engagement. The new technology should allow emergency responders to narrow down the location of such callers and replace existing 911 technology that was built for landlines and tied to home addresses.

Cell phone location data currently given to dispatchers when they receive a 911 call can be vague, especially if the person can’t articulate their exact location, according to the Department of Emergency Management.

But if a dispatcher can narrow down where the emergency is happening, that increases the chance of a timely response and better result, Cahn said.

“It doesn’t matter what’s going on with the emergency if we don’t know where it is,” she said.

RapidSOS shares its location data — collected by Apple and Google for their in-house map apps — free of charge to public safety agencies. San Francisco’s 911 call center adopted the data service in September 2018.

The Federal Communications Commission estimates agencies could save as many as 10,000 lives a year if they shave a minute off response times. Federal officials issued new rules to improve wireless 911 calls in 2015, asking mobile carriers to provide more accurate locations to call centers. Carriers are required to find a way to triangulate the caller’s location within 50 meters — a much smaller radius than the eight blocks city officials were initially presented in October when the caller dialed 911…(More)”.

Trivialization and Public Opinion: Slogans, Substance, and Styles of Thought in the Age of Complexity


Book by Oldrich Bubak and Henry Jacek: “Centering on public discourse and its fundamental lapses, this book takes a unique look at key barriers to social and political advancement in the information age. Public discourse is replete with confident, easy to manage claims, intuitions, and other shortcuts; outstanding of these is trivialization, the trend to distill multifaceted dilemmas to binary choices, neglect the big picture, gloss over alternatives, or filter reality through a lens of convenience—leaving little room for nuance and hence debate.

Far from superficial, such lapses are symptoms of deeper, intrinsically connected shortcomings inviting further attention. Focusing primarily on industrialized democracies, the authors take their readers on a transdisciplinary journey into the world of trivialization, engaging as they do so the intricate issues borne of a modern environment both enabled and constrained by technology. Ultimately, the authors elaborate upon the emerging counterweights to conventional worldviews and the paradigmatic alternatives that promise to help open new avenues for progress….(More)”.

Drones to deliver medicines to 12m people in Ghana


Neil Munshi in the Financial Times: “The world’s largest drone delivery network, ferrying 150 different medicines and vaccines, as well as blood, to 2,000 clinics in remote parts of Ghana, is set to be announced on Wednesday.

The network represents a big expansion for the Silicon Valley start-up Zipline, which began delivering blood in Rwanda in 2016 using pilotless, preprogrammed aircraft. The move, along with a new agreement in Rwanda signed in December, takes the company beyond simple blood distribution to more complicated vaccine and plasma deliveries.

“What this is going to show is that you can reach every GPS co-ordinate, you can serve everybody,” said Keller Rinaudo, Zipline chief executive. “Every human in that region or country [can be] within a 15-25 minute delivery of any essential medical product — it’s a different way of thinking about universal coverage.”

Zipline will deliver vaccines for yellow fever, polio, diptheria and tetanus which are provided by the World Health Organisation’s Expanded Project on Immunisation. The WHO will also use the company’s system for future mass immunisation programmes in Ghana.

Later this year, Zipline has plans to start operations in the US, in North Carolina, and in south-east Asia. The company said it will be able to serve 100m people within a year, up from the 22m that its projects in Ghana and Rwanda will cover.

In Ghana, Zipline said health workers will receive deliveries via a parachute drop within about 30 minutes of placing their orders by text message….(More)”.

Open data promotes citizen engagement at the local level


Afua Bruce at the Hill: “The city of Los Angeles recently released three free apps for its citizens: one to report broken street lighting, one to make 311 requests and one to get early alerts about earthquakes. Though it may seem like the city is just following a trend to modernize, the apps are part of a much larger effort to spread awareness of the more than 1,100 datasets that the city has publicized for citizens to view, analyze and share. In other words, the city has officially embraced the open data movement.

In the past few years, communities across the country have realized the power of data once only available to government. Often, the conversation about data focuses on criminal justice, because the demand for this data is being met by high-profile projects like Kamala Harris’ Open Justice Initiative, which makes California criminal justice data available to the citizenry and  the Open Data Policing Project, which provides a publicly searchable database of stop, search and use-of-force data. But the possibilities for data go far beyond justice and show the possibility for use in a variety of spaces, such as efforts to preserve local wildlifetrack potholes and  understand community health trends….(More)”.