Unconscious gender bias in the Google algorithm

Curated on Posted on by Stefaan Verhulst

Interview in Metode with Londa Schiebinger, director of Gendered Innovations: “We were interested, because the methods of sex and gender analysis are not in the university curriculum, yet it is very important. The first thing our group did was to develop those methods and we present twelve methods on the website. We knew it would be very important to create case studies or concrete examples where sex and gender analysis added something new to the research. One of my favorite examples is machine translation. If you look at Google Translate, which is the main one in the United States – SYSTRAN is the main one in Europe – we found that it defaults the masculine pronoun. So does SYSTRAN. If I put an article about myself into Google Translate, it defaults to «he said» instead of «she said». So, in an article of one of my visits to Spain, it defaults to «he thinks, he says…» and, occasionally, «it wrote». We wondered why this happened and we found out, because Google Translate works on an algorithm, the problem is that «he said» appears on the web four times more than «she said», so the machine gets it right if it chooses «he said». Because the algorithm is just set up for that. But, anyway, we found that there was a huge change in English language from 1968 to the current time, and the proportion of «he said» and «she said» changed from 4-to-1 to 2-to-1. But, still, the translation does not take this into account. So we went to Google and we said «Hey, what is going on?» and they said «Oh, wow, we didn’t know, we had no idea!». So what we recognized is that there is an unconscious gender bias in the Google algorithm. They did not intend to do this at all, so now there are a lot of people who are trying to fix it….

How can you fix that?

Oh, well, this is the thing! …I think algorithms in general are a problem because if there is any kind of unconscious bias in the data, the algorithm just returns that to you. So even though Google has policies, company policies, to support gender equality, they had an unconscious bias in their product and they do not mean to. Now that they know about it, they can try to fix it….(More)”

Rules for a Flat World – Why Humans Invented Law and How to Reinvent It for a Complex Global Economy

Curated on Posted on by Stefaan Verhulst

Book by Gillian Hadfield: “… picks up where New York Times columnist Thomas Friedman left off in his influential 2005 book, The World is Flat. Friedman was focused on the infrastructure of communications and technology-the new web-based platform that allows business to follow the hunt for lower costs, higher value and greater efficiency around the planet seemingly oblivious to the boundaries of nation states. Hadfield peels back this technological platform to look at the ‘structure that lies beneath’—our legal infrastructure, the platform of rules about who can do what, when and how. Often taken for granted, economic growth throughout human history has depended at least as much on the evolution of new systems of rules to support ever-more complex modes of cooperation and trade as it has on technological innovation. When Google rolled out YouTube in over one hundred countries around the globe simultaneously, for example, it faced not only the challenges of technology but also the staggering problem of how to build success in the context of a bewildering and often conflicting patchwork of nation-state-based laws and legal systems affecting every aspect of the business-contract, copyright, encryption, censorship, advertising and more. Google is not alone. A study presented at the World Economic Forum in Davos in 2011 found that for global firms, the number one challenge of the modern economy is increasing complexity, and the number one source of complexity is law. Today, even our startups, the engines of economic growth, are global from Day One.

Put simply, the law and legal methods on which we currently rely have failed to evolve along with technology. They are increasingly unable to cope with the speed, complexity, and constant border-crossing of our new globally inter-connected environment. Our current legal systems are still rooted in the politics-based nation state platform on which the industrial revolution was built. Hadfield argues that even though these systems supported fantastic growth over the past two centuries, today they are too slow, costly, cumbersome and localized to support the exponential rise in economic complexity they fostered. …

The answer to our troubles with law, however, is not the one critics usually reach for—to have less of it. Recognizing that law provides critical infrastructure for the cooperation and collaboration on which economic growth is built is the first step, Hadfield argues, to building a legal environment that does more of what we need it to do and less of what we don’t. …(More)”

What Communication Can Contribute to Data Studies: Three Lenses on Communication and Data

Curated on Posted on by Stefaan Verhulst

Andrew Schrock at the International Journal of Communication: “We are awash in predictions about our data-driven future. Enthusiasts believe big data imposes new ways of knowing, while critics worry it will enable powerful regimes of institutional control. This debate has been of keen interest to communication scholars. To encourage conceptual clarity, this article draws on communication scholarship to suggest three lenses for data epistemologies. I review the common social scientific perspective of communication as data. A data as discourse lens interrogates the meanings that data carries. Communication around data describes moments where data are constructed. By employing multiple perspectives, we might understand how data operate as a complex structure of dominance….(More)”

Troopers Use ‘Big Data’ to Predict Crash Sites

Curated on Posted on by Stefaan Verhulst

Jenni Bergal at Pew Charitable Trusts: “As Tennessee Highway Patrol Sgt. Anthony Griffin patrolled an area near Murfreesboro one morning in January 2014, he gave a young woman a ticket for driving her Geo Prizm without wearing a seat belt.

About four hours later, Griffin was dispatched to help out at the scene of a major accident a few miles away. A car had veered off the road, sailed over a bridge, struck a utility pole and landed in a frozen pond. When Griffin went to question the driver, who appeared uninjured, he was shocked to find it was the same woman he had ticketed earlier.

She told him she had been wearing her seat belt only because he had given her a ticket. She believed it had saved her life. And if it hadn’t been for new crash prediction software his agency was using, Griffin said he wouldn’t have been in that spot to issue her the ticket.

“I’m in my 21st year of law enforcement and I’ve never come across anything where I could see the fruit of my work in this fashion,” said Griffin, who is now a lieutenant. “It was amazing.”

As more and more states use “big data” for everything from catching fraudsters to reducing heath care costs, some highway patrols are tapping it to predict where serious or fatal traffic accidents are likely to take place so they can try to prevent them….

Indiana State Police decided to take a different approach, and are making their predictive crash analytics program available to the public, as well as troopers.

A color-coded Daily Crash Prediction map, which went online in November, pulls together data that includes crash reports from every police agency in the state dating to 2004, daily traffic volume, historical weather information and the dates of major holidays, said First Sgt. Rob Simpson….(More)”

Crowdsourced Science: Sociotechnical Epistemology in the e-Research Paradigm

Curated on Posted on by Stefaan Verhulst

Paper by David Watson and Luciano Floridi: “Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how information and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research….(More)”

Best Government Emerging Technologies

Curated on Posted on by Stefaan Verhulst

Report released at the World Government Summit (Dubai): “… the “Best Government Emerging Technologies” recognises governments that are experimenting with emerging technologies to provide government services more e ciently, e ectively and have proven results showing how they have created greater public value and transformed people›s lives.

For this purpose, the Prime Minister’s Office has joined forces with Indra to analyse and identify 29 Emerging Technologies, grouped in 9 categories that include technologies such as Artificial Intelligence, Blockchain, Cloud Computing, Robotics & Space, Smart Platforms, amongst other.

Wherever possible, case studies have been analysed as example of the use of the technology in public bodies and government, taking into account that some of these technologies may not have been implemented yet in the public sector and therefore have not a ected the lives of citizens. e analysis comprises 73 international case studies from 32 di erent countries.

is document represents an executive summary of the analysis ndings, incorporating a brief description of the main Emerging Technologies where the selected cutting-edge digital technologies are introduced, followed by a number of examples of international case studies in which governments and public bodies have implemented these technologies….

Screen Shot 2017-02-13 at 4.35.40 PM(More)

The chaos of South Africa’s taxi system is being tackled with open data

Curated on Posted on by Stefaan Verhulst

Lynsey Chutel at Quartz: “On any given day in South Africa’s cities the daily commute can be chaotic and unpredictable. A new open source data platform hopes to bring some order to that—or at least help others get it right.

Contributing to that chaos is a formal public transportation system that is inadequate for a growing urban population and an informal transportation network that whizzes through the streets unregulated. Where Is My Transport has done something unique by finally bringing these two systems together on one map.

Where Is My Transport has mapped Cape Town’s transport systems to create an integrated system, incorporating train, bus and minibus taxi routes. This last one is especially difficult, because the thousands of minibuses that ferry most South Africans are notoriously difficult to pin down.

Minibus taxis seat about 15 people and turn any corner into a bus stop, often halting traffic. They travel within neighborhoods and across the country and are the most affordable means of transport for the majority of South Africans. But they are also often unsafe vehicles, at times involved in horrific road accidents.

Devin De Vries, one of the platform’s co-founders, says he was inspired by the Digital Matatus project in Nairobi. The South African platform differs, however, in that it provides open source information for others who think they may have a solution to South Africa’s troubled public transportation system.

“Transport is a complex ecosystem, and we don’t think any one company will solve it, De Vries told Quartz. “That’s why we made our platform open and hope that many endpoints—apps, websites, et cetera—will draw on the data so people can access it.”

This could lead to trip planning apps like Moovit or Transit for African commuters, or help cities better map their public transportation system, De Vries hopes…(More)”

The Innovation-Friendly Organization

Curated on Posted on by Stefaan Verhulst

Book by Anna Simpson: “This book explores five cultural traits – Diversity, Integrity, Curiosity, Reflection, and Connection – that encourage the birth and successful development of new ideas, and shows how organizations that are serious about innovation can embrace them.

Innovation – the driver of change and resilience – It is totally dependent on culture, the social environment which shapes how ideas emerge and evolve. Ideas need to breathe, and culture determines the quality of the air. If it’s stuffy and lacks flow, then no idea, however brilliant, will live long enough to fulfil its potential.

Creating these innovation-friendly conditions is one of the key challenges facing organizations today, and one that is especially difficult for them – focused as they are on efficiency and control. Innovation, Anna Simpson argues, begins with diversity of thought and attitude: the opposite of conformity and standardisation.

Likewise, with ongoing pressures to deliver results before yesterday, how can organizations allow sufficient space for the seemingly aimless process of following interesting possibilities and pondering on the impact of various options?Anna Simpson shows how large organizations can adapt their culture to enable the exchange of different perspectives; to support each person to bring their whole self to their work; to embrace the aimlessness that fosters creative experimentation; to take the time to approach change with the care it deserves, and – lastly – to develop the collective strength needed to face the ultimate ‘sledgehammer test’….(More)”.

Embracing Innovation in Government Global Trends

Curated on Posted on by Stefaan Verhulst

Report by the OECD: “Innovation in government is about finding new ways to impact the lives of citizens, and new approaches to activating them as partners to shape the future together. It involves overcoming old structures and modes of thinking and embracing new technologies and ideas. The potential of innovation in government is immense; however, the challenges governments face are significant. Despite this, governments are transforming the way they work to ensure this potential is met….

Since 2014, the OECD Observatory of Public Sector Innovation (OPSI), an OECD Directorate for Public Governance and Territorial Development (GOV) initiative, has been working to identify the key issues for innovation in government and what can be done to achieve greater impact. To learn from governments on the leading edge of this field, OPSI has partnered with the Government of the United Arab Emirates (UAE) and its Mohammed Bin Rashid Centre for Government Innovation (MBRCGI) , as part of the Middle East and North Africa (MENA)-OECD Governance Programme, to conduct a global review of new ways in which governments are transforming their operations and improving the lives of their people, culminating in this report.

Through research and an open Call for Innovations, the review surfaces key trends, challenges, and success factors in innovation today, as well as examples and case studies to illustrate them and recommendations to help support innovation. This report is published in conjunction with the 2017 World Government Summit, which brings together over 100 countries to discuss innovative ways to solve the challenges facing humanity….(More)”

Big data may be reinforcing racial bias in the criminal justice system

Curated on Posted on by Stefaan Verhulst

Laurel Eckhouse at the Washington Post: “Big data has expanded to the criminal justice system. In Los Angeles, police use computerized “predictive policing” to anticipate crimes and allocate officers. In Fort Lauderdale, Fla., machine-learning algorithms are used to set bond amounts. In states across the country, data-driven estimates of the risk of recidivism are being used to set jail sentences.

Advocates say these data-driven tools remove human bias from the system, making it more fair as well as more effective. But even as they have become widespread, we have little information about exactly how they work. Few of the organizations producing them have released the data and algorithms they use to determine risk.

 We need to know more, because it’s clear that such systems face a fundamental problem: The data they rely on are collected by a criminal justice system in which race makes a big difference in the probability of arrest — even for people who behave identically. Inputs derived from biased policing will inevitably make black and Latino defendants look riskier than white defendants to a computer. As a result, data-driven decision-making risks exacerbating, rather than eliminating, racial bias in criminal justice.
Consider a judge tasked with making a decision about bail for two defendants, one black and one white. Our two defendants have behaved in exactly the same way prior to their arrest: They used drugs in the same amount, have committed the same traffic offenses, owned similar homes and took their two children to the same school every morning. But the criminal justice algorithms do not rely on all of a defendant’s prior actions to reach a bail assessment — just those actions for which he or she has been previously arrested and convicted. Because of racial biases in arrest and conviction rates, the black defendant is more likely to have a prior conviction than the white one, despite identical conduct. A risk assessment relying on racially compromised criminal-history data will unfairly rate the black defendant as riskier than the white defendant.

To make matters worse, risk-assessment tools typically evaluate their success in predicting a defendant’s dangerousness on rearrests — not on defendants’ overall behavior after release. If our two defendants return to the same neighborhood and continue their identical lives, the black defendant is more likely to be arrested. Thus, the tool will falsely appear to predict dangerousness effectively, because the entire process is circular: Racial disparities in arrests bias both the predictions and the justification for those predictions.

We know that a black person and a white person are not equally likely to be stopped by police: Evidence on New York’s stop-and-frisk policy, investigatory stops, vehicle searches and drug arrests show that black and Latino civilians are more likely to be stopped, searched and arrested than whites. In 2012, a white attorney spent days trying to get himself arrested in Brooklyn for carrying graffiti stencils and spray paint, a Class B misdemeanor. Even when police saw him tagging the City Hall gateposts, they sped past him, ignoring a crime for which 3,598 people were arrested by the New York Police Department the following year.

Before adopting risk-assessment tools in the judicial decision-making process, jurisdictions should demand that any tool being implemented undergo a thorough and independent peer-review process. We need more transparencyand better data to learn whether these risk assessments have disparate impacts on defendants of different races. Foundations and organizations developing risk-assessment tools should be willing to release the data used to build these tools to researchers to evaluate their techniques for internal racial bias and problems of statistical interpretation. Even better, with multiple sources of data, researchers could identify biases in data generated by the criminal justice system before the data is used to make decisions about liberty. Unfortunately, producers of risk-assessment tools — even nonprofit organizations — have not voluntarily released anonymized data and computational details to other researchers, as is now standard in quantitative social science research….(More)”.