Stefaan Verhulst

Paper by Małgorzata Śmietanka, Hirsh Pithadia and Philip Treleaven: “Federated learning is a pioneering privacy-preserving data technology and also a new machine learning model trained on distributed data sets.

Companies collect huge amounts of historic and real-time data to drive their business and collaborate with other organisations. However, data privacy is becoming increasingly important because of regulations (e.g. EU GDPR) and the need to protect their sensitive and personal data. Companies need to manage data access: firstly within their organizations (so they can control staff access), and secondly protecting raw data when collaborating with third parties. What is more, companies are increasingly looking to ‘monetize’ the data they’ve collected. However, under new legislations, utilising data by different organization is becoming increasingly difficult (Yu, 2016).

Federated learning pioneered by Google is the emerging privacy- preserving data technology and also a new class of distributed machine learning models. This paper discusses federated learning as a solution for privacy-preserving data access and distributed machine learning applied to distributed data sets. It also presents a privacy-preserving federated learning infrastructure….(More)”.

About: “The criminal legal system is a maze of laws, language, and unwritten rules that lawyers are trained to maneuver to represent defendants.

However, according to the Bureau of Justice Statistics, only 27% of county public defender’s offices meet national caseload recommendations for cases per attorney, meaning that most public defenders are overworked, leaving their clients underrepresented.

Defendants must complete an estimated 200 discrete tasks during their legal proceeding. This leaves them overwhelmed, lost, and profoundly disadvantaged while attempting to navigate the system….

We have… created a product that acts as the trusted advisor for defendants and their families as they navigate the criminal legal system. We aim to deliver valuable and relevant legal information (but not legal advice) to the user in plain language, empowering them to advocate for themselves and proactively plan for the future and access social services if necessary. The user is also encouraged to give feedback on their experience at each step of the process in the hope that this can be used to improve the system….(More)”

Report by David Autor, David Mindell and Elisabeth Reynolds for the MIT Future of Work Task Force: “The world now stands on the cusp of a technological revolution in artificial intelligence and robotics that may prove as transformative for economic growth and human potential as were electrification, mass production, and electronic telecommunications in their eras. New and emerging technologies will raise aggregate economic output and boost the wealth of nations. Will these developments enable people to attain higher living standards, better working conditions, greater economic security, and improved health and longevity? The answers to these questions are not predetermined. They depend upon the institutions, investments, and policies that we deploy to harness the opportunities and confront the challenges posed by this new era.

How can we move beyond unhelpful prognostications about the supposed end of work and toward insights that will enable policymakers, businesses, and people to better navigate the disruptions that are coming and underway? What lessons should we take from previous epochs of rapid technological change? How is it different this time? And how can we strengthen institutions, make investments, and forge policies to ensure that the labor market of the 21st century enables workers to contribute and succeed?

To help answer these questions, and to provide a framework for the Task Force’s efforts over the next year, this report examines several aspects of the interaction between work and technology….(More)”.

Louise Guillot and Elisa Braun at Politico: “Emmanuel Macron asked 150 ordinary people to help figure out France’s green policies — and now this citizens’ convention is turning into a political problem for the French president.

The Citizens’ Convention on Climate was aimed at calming tensions in the wake of the Yellow Jackets protest movement — which was sparked by a climate tax on fuel — and showing that Macron wasn’t an out-of-touch elitist.

After nine months of deliberations, the convention came up with 149 proposals to slash greenhouse gas emissions this summer. The government has to put some of these measures before the parliament for them to become binding, and a bill is due to be presented in December.

But that’s too slow for many of the convention’s members, who feel the government is back-pedalling on some of the ideas and that Macron has poked fun at them.

Muriel Raulic, a member of the convention, accused Macron of using the body to greenwash his administration.

She supports a moratorium on 5G high-speed mobile technology, which has created some health and environmental fears. Macron has dismissed proponents of the ban as “Amish” — a Christian sect suspicious of technology.

The 150 members wrote an open letter to Macron in mid-October, complaining about a lack of “clear and defined support from the executive, whose positions sometimes appear contradictory,” and to “openly hostile communications” from “certain professional actors.”

Some gathered late last month before the National Assembly to complain they felt used and treated like “guinea pigs” by politicians. In June, they created an association to oversee what the government is doing with their proposals. 

…The government denied it is using the convention to greenwash itself….(More)”.

Blog by the Annie E. Casey Foundation: “Advanced data analytics are deeply embedded in the operations of public and private institutions and shape the opportunities available to youth and families. Whether these tools benefit or harm communities depends on their design, use and oversight, according to a report from the Annie E. Casey Foundation.

Four Principles to Make Advanced Data Analytics Work for Children and Families examines the growing field of advanced data analytics and offers guidance to steer the use of big data in social programs and policy….

The Foundation report identifies four principles — complete with examples and recommendations — to help steer the growing field of data science in the right direction.

Four Principles for Data Tools

1. Expand opportunity for children and families. Most established uses of advanced analytics in education, social services and criminal justice focus on problems facing youth and families. Promising uses of advanced analytics go beyond mitigating harm and help to identify so-called odds beaters and new opportunities for youth.
   • Example: The Children’s Data Network at the University of Southern California is helping the state’s departments of education and social services explore why some students succeed despite negative experiences and what protective factors merit more investment.
   • Recommendation: Government and its philanthropic partners need to test if novel data science applications can create new insights and when it’s best to apply them.
      
2. Provide transparency and evidence. Advanced analytical tools must earn and maintain a social license to operate. The public has a right to know what decisions these tools are informing or automating, how they have been independently validated, and who is accountable for answering and addressing concerns about how they work.
   • Recommendations: Local and state task forces can be excellent laboratories for testing how to engage youth and communities in discussions about advanced analytics applications and the policy frameworks needed to regulate their use. In addition, public and private funders should avoid supporting private algorithms whose design and performance are shielded by trade secrecy claims. Instead, they should fund and promote efforts to develop, evaluate and adapt transparent and effective models.
      
3. Empower communities. The field of advanced data analytics often treats children and families as clients, patients and consumers. Put to better use, these same tools can help elucidate and reform the systems acting upon children and families. For this shift to occur, institutions must focus analyses and risk assessments on structural barriers to opportunity rather than individual profiles.
   • Recommendation: In debates about the use of data science, greater investment is needed to amplify the voices of youth and their communities.
      
4. Promote equitable outcomes. Useful advanced analytics tools should promote more equitable outcomes for historically disadvantaged groups. New investments in advanced analytics are only worthwhile if they aim to correct the well-documented bias embedded in existing models.
   • Recommendations: Advanced analytical tools should only be introduced when they reduce the opportunity deficit for disadvantaged groups — a move that will take organizing and advocacy to establish and new policy development to institutionalize. Philanthropy and government also have roles to play in helping communities test and improve tools and examples that already exist….(More)”.

Book by Juan Enriquez: “Most people have a strong sense of right and wrong, and they aren’t shy about expressing their opinions. But when we take a polarizing stand on something we regard as an eternal truth, we often forget that ethics evolve over time. Many shifts in the right versus wrong pendulum are driven by advances in technology. Our great-grandparents might be shocked by in vitro fertilization; our great-grandchildren might be shocked by the messiness of pregnancy, childbirth, and unedited genes. In Right/Wrong, Juan Enriquez reflects on what happens to our ethics as technology makes the once unimaginable a commonplace occurrence.

Evolving technology changes ethics. Enriquez points out that, contrary to common wisdom, technology often enables more ethical behaviors. Technology challenges old beliefs and upends institutions that do not grow and change. With wit and compassion, Enriquez takes on a series of technology-influenced ethical dilemmas, from sexual liberation to climate change to the “immortality” of mistakes on social media. (“Facebook, Twitter, Instagram, and Google are electronic tattoos.”) He cautions us to judge those who “should have known better,” given today’s vantage point, with less fury and more compassion. We need a quality often absent in today’s charged debates: humility. Judge those in the past as we hope to be judged in the future….(More)”.

Paper by David Le Blanc: “This paper briefly takes stock of two decades of e-participation initiatives based on a limited review of the academic literature. The purpose of the paper is to complement the results of the e-government Survey 2020/ As such, the emphasis is on aspects that the e-government survey (based on analysis of e-government portals and on quantitative indicators) does not capture directly. Among those are the challenges faced by e-participation initiatives and key areas of attention for governments.

The paper maps the field of e-participation and related activities, as well as its relationships with other governance concepts. Areas of recent development in terms of e-participation applications are briefly reviewed. The paper selectively highlights conclusions from the literature on different participation tools, as well as a list of key problematic areas for policy makers. The paper concludes that while e-participation platforms using new technologies have spread rapidly in developed countries in the first decade of the 2000s and in developing countries during the last 10 years, it is not clear that their multiplication has translated into broader or deeper citizen participation. Beyond reasons related to technology access and digital skills, factors such as lack of understanding of citizens’ motivations to participate and the reluctance of public institutions to genuinely share agenda-setting and decision-making power seem to play an important role in the observed limited progress….(More)’

Essay by Meg King and Aaron Shull: “Policy makers around the world are leaning on historical analogies to try to predict how artificial intelligence, or AI — which, ironically, is itself a prediction technology — will develop. They are searching for clues to inform and create appropriate policies to help foster innovation while addressing possible security risks. Much in the way that electrical power completely changed our world more than a century ago — transforming every industry from transportation to health care to manufacturing — AI’s power could effect similar, if not even greater, disruption.

Whether it is the “next electricity” or not, one fact all can agree on is that AI is not a thing in itself. Most authors contributing to this essay series focus on the concept that AI is a general-purpose technology — or GPT — that will enable many applications across a variety of sectors. While AI applications are expected to have a significantly positive impact on our lives, those same applications will also likely be abused or manipulated by bad actors. Setting rules at both the national and the international level — in careful consultation with industry — will be crucial for ensuring that AI offers new capabilities and efficiencies safely.

Situating this discussion, though, requires a look back, in order to determine where we may be going. While AI is not new — Marvin Minsky developed what is widely believed to be the first neural network learning machine in the early 1950s — its scale, scope, speed of adoption and potential use cases today highlight a number of new challenges. There are now many ominous signs pointing to extreme danger should AI be deployed in an unchecked manner, particularly in military applications, as well as worrying trends in the commercial context related to potential discrimination, undermining of privacy, and upended traditional employment structures and economic models….(More)”

Paper by Elizabether Seger and Mark Briers: “The current COVID-19 pandemic and the accompanying ‘infodemic’ clearly illustrate that access to reliable information is crucial to coordinating a timely crisis response in democratic societies. Inaccurate information and the muzzling of important information sources have degraded trust in health authorities and slowed public response to the crisis. Misinformation about ineffective cures, the origins and malicious spread of COVID-19, unverified treatment discoveries, and the efficacy of face coverings have increased the difficulty of coordinating a unified public response during the crisis. 

In a recent report, researchers at the Cambridge Centre for the Study of Existential Risk (CSER) in collaboration with The Alan Turing Institute and the Defence Science and Technology Laboratory (Dstl) workshopped an array of hypothetical crisis scenarios to investigate social and technological factors that interfere with well-informed decision-making and timely collective action in democratic societies.

Crisis scenarios

Crisis scenarios are useful tools for appraising threats and vulnerabilities to systems of information production, dissemination, and evaluation. Factors influencing how robust a society is to such threats and vulnerabilities are not always obvious when life is relatively tranquil but are often highlighted under the stress of a crisis. 

CSER and Dstl workshop organisers, together with workshop participants (a diverse group of professionals interested in topics related to [mis/dis]information, information technology, and crisis response), co-developed and explored six hypothetical crisis scenarios and complex challenges:

• Global health crisis
• Character assassination
• State fake news campaign
• Economic collapse
• Xenophobic ethnic cleansing
• Epistemic babble, where the ability for the general population to tell the difference between truth and fiction (presented as truth) is lost

We analysed each scenario to identify various interest groups and actors, to pinpoint vulnerabilities in systems of information production and exchange, and to visualise how the system might be interfered with. We also considered interventions that could help bolster the society against threats to informed decision-making.

The systems map below is an example from workshop scenario 1: Global health crisis. The map shows how adversarial actors (red) and groups working to mitigate the crisis (blue) interact, impact each other’s actions, and influence the general public and other interest groups (green) such as those affected by the health crisis. 

Systems maps help visualise vulnerabilities in both red and blue actor systems, which, in turn, helps identify areas where intervention (yellow) is possible to help mitigate the crisis….(More)“

Book by Brian W. Kernighan: “Numbers are often intimidating, confusing, and even deliberately deceptive—especially when they are really big. The media loves to report on millions, billions, and trillions, but frequently makes basic mistakes or presents such numbers in misleading ways. And misunderstanding numbers can have serious consequences, since they can deceive us in many of our most important decisions, including how to vote, what to buy, and whether to make a financial investment. In this short, accessible, enlightening, and entertaining book, leading computer scientist Brian Kernighan teaches anyone—even diehard math-phobes—how to demystify the numbers that assault us every day.

With examples drawn from a rich variety of sources, including journalism, advertising, and politics, Kernighan demonstrates how numbers can mislead and misrepresent. In chapters covering big numbers, units, dimensions, and more, he lays bare everything from deceptive graphs to speciously precise numbers. And he shows how anyone—using a few basic ideas and lots of shortcuts—can easily learn to recognize common mistakes, determine whether numbers are credible, and make their own sensible estimates when needed.

Giving you the simple tools you need to avoid being fooled by dubious numbers, Millions, Billions, Zillions is an essential survival guide for a world drowning in big—and often bad—data….(More)”.