The Inevitability of AI Law & Policy: Preparing Government for the Era of Autonomous Machines

Curated on Posted on by Stefaan Verhulst

Public Knowledge: “Today, we’re happy to announce our newest white paper, “The Inevitability of AI Law & Policy: Preparing Government for the Era of Autonomous Machines,” by Public Knowledge General Counsel Ryan Clough. The paper argues that the rapid and pervasive rise of artificial intelligence risks exploiting the most marginalized and vulnerable in our society. To mitigate these harms, Clough advocates for a new federal authority to help the U.S. government implement fair and equitable AI. Such an authority should provide the rest of the government with the expertise and experience needed to achieve five goals crucial to building ethical AI systems:

  • Boosting sector-specific regulators and confronting overarching policy challenges raised by AI;
  • Protecting public values in government procurement and implementation of AI;
  • Attracting AI practitioners to civil service, and building durable and centralized AI expertise within government;
  • Identifying major gaps in the laws and regulatory frameworks that govern AI; and
  • Coordinating strategies and priorities for international AI governance.

“Any individual can be misjudged and mistreated by artificial intelligence,” Clough explains, “but the record to date indicates that it is significantly more likely to happen to the less powerful, who also have less recourse to do anything about it.” The paper argues that a new federal authority is the best way to meet the profound and novel challenges AI poses for us all….(More)”.

Open Data Exposed

Curated on Posted on by Stefaan Verhulst

Book by Bastiaan van Loenen, Glenn Vancauwenberghe, Joep Crompvoets and Lorenzo Dalla Corte: “This book is about open data, i.e. data that does not have any barriers in the (re)use. Open data aims to optimize access, sharing and using data from a technical, legal, financial, and intellectual perspective.

Data increasingly determines the way people live their lives today. Nowadays, we cannot imagine a life without real-time traffic information about our route to work, information of the daily news or information about the local weather. At the same time, citizens themselves now are constantly generating and sharing data and information via many different devices and social media systems. Especially for governments, collection, management, exchange, and use of data and information have always been key tasks, since data is both the primary input to and output of government activities. Also for businesses, non-profit organizations, researchers and various other actors, data and information are essential….(More)”.

Positive deviance, big data, and development: A systematic literature review

Curated on Posted on by Stefaan Verhulst

Paper by Basma Albanna and Richard Heeks: “Positive deviance is a growing approach in international development that identifies those within a population who are outperforming their peers in some way, eg, children in low‐income families who are well nourished when those around them are not. Analysing and then disseminating the behaviours and other factors underpinning positive deviance are demonstrably effective in delivering development results.

However, positive deviance faces a number of challenges that are restricting its diffusion. In this paper, using a systematic literature review, we analyse the current state of positive deviance and the potential for big data to address the challenges facing positive deviance. From this, we evaluate the promise of “big data‐based positive deviance”: This would analyse typical sources of big data in developing countries—mobile phone records, social media, remote sensing data, etc—to identify both positive deviants and the factors underpinning their superior performance.

While big data cannot solve all the challenges facing positive deviance as a development tool, they could reduce time, cost, and effort; identify positive deviants in new or better ways; and enable positive deviance to break out of its current preoccupation with public health into domains such as agriculture, education, and urban planning. In turn, positive deviance could provide a new and systematic basis for extracting real‐world development impacts from big data…(More)”.

Algorithmic Government: Automating Public Services and Supporting Civil Servants in using Data Science Technologies

Curated on Posted on by Stefaan Verhulst

Zeynep Engin and Philip Treleaven in the Computer Journal:  “The data science technologies of artificial intelligence (AI), Internet of Things (IoT), big data and behavioral/predictive analytics, and blockchain are poised to revolutionize government and create a new generation of GovTech start-ups. The impact from the ‘smartification’ of public services and the national infrastructure will be much more significant in comparison to any other sector given government’s function and importance to every institution and individual.

Potential GovTech systems include Chatbots and intelligent assistants for public engagement, Robo-advisors to support civil servants, real-time management of the national infrastructure using IoT and blockchain, automated compliance/regulation, public records securely stored in blockchain distributed ledgers, online judicial and dispute resolution systems, and laws/statutes encoded as blockchain smart contracts. Government is potentially the major ‘client’ and also ‘public champion’ for these new data technologies. This review paper uses our simple taxonomy of government services to provide an overview of data science automation being deployed by governments world-wide. The goal of this review paper is to encourage the Computer Science community to engage with government to develop these new systems to transform public services and support the work of civil servants….(More)”.

The Public Mapping Project: How Public Participation Can Revolutionize Redistricting

Curated on Posted on by Stefaan Verhulst

Book by Micah Altman and Michael P. McDonald: “… unveil the Public Mapping Project, which developed DistrictBuilder, an open-source software redistricting application designed to give the public transparent, accessible, and easy-to-use online mapping tools. As they show, the goal is for all citizens to have access to the same information that legislators use when drawing congressional maps—and use that data to create maps of their own….(More)”.

Statistics Canada promises more detailed portrait of Canadians with fewer surveys

Curated on Posted on by Stefaan Verhulst

Bill Curry at The Globe and Mail: “Canadians are increasingly shunning phone surveys, but they could still be providing Statistics Canada with valuable data each time they flush the toilet or flash their debit card.

The national statistics agency laid out an ambitious plan Thursday to overhaul the way it collects and reports on issues ranging from cannabis and opioid use to market-moving information on unemployment and economic growth.

According to four senior Statscan officials, the agency is in the midst of a major transformation as it adapts to a world of big data collected by other government agencies as well as private sector actors such as banks, cellphone companies and digital-based companies like Uber.

At its core, the shift means the agency will become less reliant on traditional phone surveys or having businesses fill out forms to report their sales data. Instead, Statscan is reaching agreements with other government departments and private companies in order to gain access to their raw data, such as point-of-sale information. According to agency officials, such arrangements reduce the reporting paperwork faced by businesses while creating the potential for Statscan to produce faster and more reliable information.

Key releases such as labour statistics or reporting on economic growth could come out sooner, reducing the lag time between the end of a quarter and reporting on results. Officials said economic data that is released quarterly could shift to monthly reporting. The greater access to raw data sources will also allow for more localized reporting at the neighbourhood level….(More)”.

The Role of Management in Open Data Initiatives in Local Governments: Opening the Organizational Black Box

Curated on Posted on by Stefaan Verhulst

Paper by Mila Gasco-Hernandez and  Jose Ramon Gil-Garcia: “Previous studies have infrequently addressed the dynamic interactions among social, technical, and organizational variables in open government data initiatives. In addition, organization level models have neglected to explain the role of management in decision-making processes about technology and data. This article contributes to addressing this gap in the literature by analyzing the complex relationships between open government data characteristics and the organizations and institutions in which they are embedded.

We systematically compare the open data inception and implementation processes, as well as their main results, in three Spanish local governments (Gava and Rubi in Catalonia and Gijon in Asturias) by using a model that combines the technology enactment framework with some specific constructs and relationships from the process model of computing change. Our resulting model is able to identify and explain the significant role of management in shaping and mediating different interactions, but also acknowledges the importance of organizational level variables and the context in which the open data initiative is taking place…(More)”.

Surveillance Studies: A Reader

Curated on Posted on by Stefaan Verhulst

Book edited by Torin Monahan and David Murakami Wood: “Surveillance is everywhere: in workplaces monitoring the performance of employees, social media sites tracking clicks and uploads, financial institutions logging transactions, advertisers amassing fine-grained data on customers, and security agencies siphoning up everyone’s telecommunications activities. Surveillance practices-although often hidden-have come to define the way modern institutions operate. Because of the growing awareness of the central role of surveillance in shaping power relations and knowledge across social and cultural contexts, scholars from many different academic disciplines have been drawn to “surveillance studies,” which in recent years has solidified as a major field of study.

Torin Monahan and David Murakami Wood’s Surveillance Studies is a broad-ranging reader that provides a comprehensive overview of the dynamic field. In fifteen sections, the book features selections from key historical and theoretical texts, samples of the best empirical research done on surveillance, introductions to debates about privacy and power, and cutting-edge treatments of art, film, and literature. While the disciplinary perspectives and foci of scholars in surveillance studies may be diverse, there is coherence and agreement about core concepts, ideas, and texts. This reader outlines these core dimensions and highlights various differences and tensions. In addition to a thorough introduction that maps the development of the field, the volume offers helpful editorial remarks for each section and brief prologues that frame the included excerpts. …(More)”.

Rationality and politics of algorithms. Will the promise of big data survive the dynamics of public decision making?

Curated on Posted on by Stefaan Verhulst

Paper by H.G. (Haiko)van der Voort et al: “Big data promises to transform public decision-making for the better by making it more responsive to actual needs and policy effects. However, much recent work on big data in public decision-making assumes a rational view of decision-making, which has been much criticized in the public administration debate.

In this paper, we apply this view, and a more political one, to the context of big data and offer a qualitative study. We question the impact of big data on decision-making, realizing that big data – including its new methods and functions – must inevitably encounter existing political and managerial institutions. By studying two illustrative cases of big data use processes, we explore how these two worlds meet. Specifically, we look at the interaction between data analysts and decision makers.

In this we distinguish between a rational view and a political view, and between an information logic and a decision logic. We find that big data provides ample opportunities for both analysts and decision makers to do a better job, but this doesn’t necessarily imply better decision-making, because big data also provides opportunities for actors to pursue their own interests. Big data enables both data analysts and decision makers to act as autonomous agents rather than as links in a functional chain. Therefore, big data’s impact cannot be interpreted only in terms of its functional promise; it must also be acknowledged as a phenomenon set to impact our policymaking institutions, including their legitimacy….(More)”.

Declaration on Ethics and Data Protection in Artifical Intelligence

Curated on Posted on by Stefaan Verhulst

Declaration: “…The 40th International Conference of Data Protection and Privacy Commissioners considers that any creation, development and use of artificial intelligence systems shall fully respect human rights, particularly the rights to the protection of personal data and to privacy, as well as human dignity, non-discrimination and fundamental values, and shall provide solutions to allow individuals to maintain control and understanding of artificial intelligence systems.

The Conference therefore endorses the following guiding principles, as its core values to preserve human rights in the development of artificial intelligence:

  1. Artificial intelligence and machine learning technologies should be designed, developed and used in respect of fundamental human rights and in accordance with the fairness principle, in particular by:
  2. Considering individuals’ reasonable expectations by ensuring that the use of artificial intelligence systems remains consistent with their original purposes, and that the data are used in a way that is not incompatible with the original purpose of their collection,
  3. taking into consideration not only the impact that the use of artificial intelligence may have on the individual, but also the collective impact on groups and on society at large,
  4. ensuring that artificial intelligence systems are developed in a way that facilitates human development and does not obstruct or endanger it, thus recognizing the need for delineation and boundaries on certain uses,…(More)