Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions-like taxation, justice, and child protection-are now commonplace. How might designers support such human values? We interviewed 27 public sector machine learning practitioners across 5 OECD countries regarding challenges understanding and imbuing public values into their work. The results suggest a disconnect between organisational and institutional realities, constraints and needs, and those addressed by current research into usable, transparent and 'discrimination-aware' machine learning-absences likely to undermine practical initiatives unless addressed. We see design opportunities in this disconnect, such as in supporting the tracking of concept drift in secondary data sources, and in building usable transparency tools to identify risks and incorporate domain knowledge, aimed both at managers and at the 'street-level bureaucrats' on the frontlines of public service. We conclude by outlining ethical challenges and future directions for collaboration in these high-stakes applications.

https://dl.acm.org/doi/pdf/10.1145/3173574.3174014

Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of th...

Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data:

by Viktor Mayer‐Schonberger, Princeton, NJ, Princeton University Press, 2009, 237 pp., US$24.95 (hardback), ISBN 978‐0‐691‐13861‐9 Viktor Mayer‐Schonberger is the director of the Information and In...

Delete: The virtue of forgetting in the digital age

As research on algorithms and their impact proliferates, so do calls for scrutiny/accountability of algorithms. A systematic review of the work that has been done in the field of 'algorithmic accountability' has so far been lacking. This contribution puts forth such a systematic review, following the PRISMA statement. 242 English articles from the period 2008 up to and including 2018 were collected and extracted from Web of Science and SCOPUS, using a recursive query design coupled with computational methods. The 242 articles were prioritized and ordered using affinity mapping, resulting in 93 'core articles' which are presented in this contribution. The recursive search strategy made it possible to look beyond the term 'algorithmic accountability'. That is, the query also included terms closely connected to the theme (e.g. ethics and AI, regulation of algorithms). This approach allows for a perspective not just from critical algorithm studies, but an interdisciplinary overview drawing on material from data studies to law, and from computer science to governance studies. To structure the material, Bovens's widely accepted definition of accountability serves as a focal point. The material is analyzed on the five points Bovens identified as integral to accountability: its arguments on (1) the actor, (2) the forum, (3) the relationship between the two, (3) the content and criteria of the account, and finally (5) the consequences which may result from the account. The review makes three contributions. First, an integration of accountability theory in the algorithmic accountability discussion. Second, a cross-sectoral overview of the that same discussion viewed in light of accountability theory which pays extra attention to accountability risks in algorithmic systems. Lastly, it provides a definition of algorithmic accountability based on accountability theory and algorithmic accountability literature.

What to account for when accounting for algorithms: a systematic literature review on algorithmic accountability

We turn on the lights in our house from a desk in an office miles away. Our refrigerator alerts us to buy milk on the way home. A package of cookies on the supermarket shelf suggests that we buy it, based on past purchases. The cookies themselves are on the shelf because of a "smart" supply chain. When we get home, the thermostat has already adjusted the temperature so that it's toasty or bracing, whichever we prefer. This is the Internet of Things -- a networked world of connected devices, objects, and people. In this book, Samuel Greengard offers a guided tour through this emerging world and how it will change the way we live and work. Greengard explains that the Internet of Things (IoT) is still in its early stages. Smart phones, cloud computing, RFID (radio-frequency identification) technology, sensors, and miniaturization are converging to make possible a new generation of embedded and immersive technology. Greengard traces the origins of the IoT from the early days of personal computers and the Internet and examines how it creates the conceptual and practical framework for a connected world. He explores the industrial Internet and machine-to-machine communication, the basis for smart manufacturing and end-to-end supply chain visibility; the growing array of smart consumer devices and services -- from Fitbit fitness wristbands to mobile apps for banking; the practical and technical challenges of building the IoT; and the risks of a connected world, including a widening digital divide and threats to privacy and security. Finally, he considers the long-term impact of the IoT on society, narrating an eye-opening "Day in the Life" of IoT connections circa 2025.

The Internet of Things

Big Data and security policies:: Towards a framework for regulating the phases of analytics and use of Big Data

Exploring the Boundaries of Big Data

Europa is straks een krimpend continent. Hebben we daarom meer arbeidsmigranten nodig? En voegen zij zich als vanzelf in onze economie en samenleving? Of zijn de deuren al te ver opengezet? In betere banen gaat in de vraag hoe het arbeidsmigratiebeleid nu en in de toekomst vorm moet krijgen, in Nederland en de Europese Unie. Een aantal internationaal gerenommeerde wetenschappers analyseert de Europese arbeidsmigratie van vandaag en doordrenkt de uitdagingen voor morgen. Dit boek maakt duidelijk dat migratie een ander gezicht heeft gekregen. De meeste migranten die nu naar Nederland komen zij Europeanen, vaak uit Midden- en Oost-Europa. Sommigen blijven voorgoed anderen keren terug. Ook verwelkomt Nederland steeds meer hoger opgeleiden, regelmatig van buiten Europa. Door open grenzen is migratiebeleid vooral arbeidsmarktbeleid geworden.Voor beter arbeidsmigratiebeleid is inzicht noodzakelijk in de toekomstige structuur van de arbeidsmarkt in een globaliserende economie. Alleen dan kan arbeidsmigratie beter worden afgewogen tegen andere alternatieven. Is investeren in scholing te verkiezen boven buitenlandse werknemers? Bovendien: willen er straks nog wel mensen naar Nederland komen? Bij een ander gezicht van migratie hoort tenslotte een ander integratiebeleid. Daarbij mag van overheid en werkgevers meer worden verwacht. En bovenal van Brussel.

Making Migration Work : The future of labour migration in the European Union

Hoe ongelijk is Nederland? Een verkenning van de ontwikkeling en gevolgen van economische ongelijkheid

Big Data-toepassingen bieden vele kansen voor opsporing en surveillance. Ze maken snelle en precieze reconstructies van misdaden mogelijk, evenals gerichte inspecties en het realtime volgen van ontwikkelingen bij crisissituaties. Tegelijkertijd ontstaan er nieuwe risico’s voor burgers, op het gebied van privacy, discriminatie en de vrije meningsuiting. Aan de horizon dreigt (semi-)automatische besluitvorming, waarbij de uitkomsten van data-analyses sturend zijn voor het handelen van veiligheidsorganisaties. De WRR analyseert in dit rapport hoe de Nederlandse overheid Big Data kan gebruiken en richt zich daarbij specifiek op het veiligheidsdomein. Big Data kan volgens de raad uitsluitend vruchten afwerpen als de huidige wet-en regelgeving wordt versterkt om fundamentele rechten en vrijheden te waarborgen. Hiertoe moet de aandacht worden verlegd van het reguleren van het verzamelen van data - het zwaartepunt in de huidige juridische kaders - naar de regulering van en het toezicht op de fases van de analyse en het gebruik van Big Data. Voor de vrijheid en de veiligheid van de burgers doen zich in deze twee fasen van Big Data-processen de grootste kansen en de grootste risico’s voor.

Erik Schrijvers

Papers

Big Data and security policies:: Towards a framework for regulating the phases of analytics and use of Big Data

Exploring the Boundaries of Big Data

Making Migration Work : The future of labour migration in the European Union

Hoe ongelijk is Nederland? Een verkenning van de ontwikkeling en gevolgen van economische ongelijkheid

Big Data in een vrije en veilige samenleving