Data Governance and Policy in Africa


This open access book edited by Bitange Ndemo, Njuguna Ndung’u, Scholastica Odhiambo and Abebe Shimeles: “…examines data governance and its implications for policymaking in Africa. Bringing together economists, lawyers, statisticians, and technology experts, it assesses gaps in both the availability and use of existing data across the continent, and argues that data creation, management and governance need to improve if private and public sectors are to reap the benefits of big data and digital technologies. It also considers lessons from across the globe to assess principles, norms and practices that can guide the development of data governance in Africa….(More)”.

The Early History of Counting


Essay by Keith Houston: “Figuring out when humans began to count systematically, with purpose, is not easy. Our first real clues are a handful of curious, carved bones dating from the final few millennia of the three-​million-​year expanse of the Old Stone Age, or Paleolithic era. Those bones are humanity’s first pocket calculators: For the prehistoric humans who carved them, they were mathematical notebooks and counting aids rolled into one. For the anthropologists who unearthed them thousands of years later, they were proof that our ability to count had manifested itself no later than 40,000 years ago.

In 1973, while excavating a cave in the Lebombo Mountains, near South Africa’s border with Swaziland, Peter Beaumont found a small, broken bone with twenty-​nine notches carved across it. The so-​called Border Cave had been known to archaeologists since 1934, but the discovery during World War II of skeletal remains dating to the Middle Stone Age heralded a site of rare importance. It was not until Beaumont’s dig in the 1970s, however, that the cave gave up its most significant treasure: the earliest known tally stick, in the form of a notched, three-​inch long baboon fibula.

On the face of it, the numerical instrument known as the tally stick is exceedingly mundane. Used since before recorded history—​still used, in fact, by some cultures—​to mark the passing days, or to account for goods or monies given or received, most tally sticks are no more than wooden rods incised with notches along their length. They help their users to count, to remember, and to transfer ownership. All of which is reminiscent of writing, except that writing did not arrive until a scant 5,000 years ago—​and so, when the Lebombo bone was determined to be some 42,000 years old, it instantly became one of the most intriguing archaeological artifacts ever found. Not only does it put a date on when Homo sapiens started counting, it also marks the point at which we began to delegate our memories to external devices, thereby unburdening our minds so that they might be used for something else instead. Writing in 1776, the German historian Justus Möser knew nothing of the Lebombo bone, but his musings on tally sticks in general are strikingly apposite:

The notched tally stick itself testifies to the intelligence of our ancestors. No invention is simpler and yet more significant than this…(More)”.

What if You Knew What You Were Missing on Social Media?


Article by Julia Angwin: “Social media can feel like a giant newsstand, with more choices than any newsstand ever. It contains news not only from journalism outlets, but also from your grandma, your friends, celebrities and people in countries you have never visited. It is a bountiful feast.

But so often you don’t get to pick from the buffet. On most social media platforms, algorithms use your behavior to narrow in on the posts you are shown. If you send a celebrity’s post to a friend but breeze past your grandma’s, it may display more posts like the celebrity’s in your feed. Even when you choose which accounts to follow, the algorithm still decides which posts to show you and which to bury.

There are a lot of problems with this model. There is the possibility of being trapped in filter bubbles, where we see only news that confirms our existing beliefs. There are rabbit holes, where algorithms can push people toward more extreme content. And there are engagement-driven algorithms that often reward content that is outrageous or horrifying.

Yet not one of those problems is as damaging as the problem of who controls the algorithms. Never has the power to control public discourse been so completely in the hands of a few profit-seeking corporations with no requirements to serve the public good.

Elon Musk’s takeover of Twitter, which he renamed X, has shown what can happen when an individual pushes a political agenda by controlling a social media company.

Since Mr. Musk bought the platform, he has repeatedly declared that he wants to defeat the “woke mind virus” — which he has struggled to define but largely seems to mean Democratic and progressive policies. He has reinstated accounts that were banned because of the white supremacist and antisemitic views they espoused. He has banned journalists and activists. He has promoted far-right figures such as Tucker Carlson and Andrew Tate, who were kicked off other platforms. He has changed the rules so that users can pay to have some posts boosted by the algorithm, and has purportedly changed the algorithm to boost his own posts. The result, as Charlie Warzel said in The Atlantic, is that the platform is now a “far-right social network” that “advances the interests, prejudices and conspiracy theories of the right wing of American politics.”

The Twitter takeover has been a public reckoning with algorithmic control, but any tech company could do something similar. To prevent those who would hijack algorithms for power, we need a pro-choice movement for algorithms. We, the users, should be able to decide what we read at the newsstand…(More)”.

An AI Model Tested In The Ukraine War Is Helping Assess Damage From The Hawaii Wildfires


Article by Irene Benedicto: “On August 7, 2023, the day before the Maui wildfires started in Hawaii, a constellation of earth-observing satellites took multiple pictures of the island at noon, local time. Everything was quiet, still. The next day, at the same, the same satellites captured images of fires consuming the island. Planet, a San Francisco-based company that owns the largest fleet of satellites taking pictures of the Earth daily, provided this raw imagery to Microsoft engineers, who used it to train an AI model designed to analyze the impact of disasters. Comparing before and after the fire photographs, the AI model created maps that highlighted the most devastated areas of the island.

With this information, the Red Cross rearranged its work on the field that same day to respond to the most urgent priorities first, helping evacuate thousands of people who’ve been affected by one of the deadliest fires in over a century. The Hawaii wildfires have already killed over a hundred people, a hundred more remain missing and at least 11,000 people have been displaced. The relief efforts are ongoing 10 days after the start of the fire, which burned over 3,200 acres. Hawaii Governor Josh Green estimated the recovery efforts could cost $6 billion.

Planet and Microsoft AI were able to pull and analyze the satellite imagery so quickly because they’d struggled to do so the last time they deployed their system: during the Ukraine war. The successful response in Maui is the result of a year and a half of building a new AI tool that corrected fundamental flaws in the previous system, which didn’t accurately recognize collapsed buildings in a background of concrete.

“When Ukraine happened, all the AI models failed miserably,” Juan Lavista, chief scientist at Microsoft AI, told Forbes.

The problem was that the company’s previous AI models were mainly trained with natural disasters in the U.S. and Africa. But devastation doesn’t look the same when it is caused by war and in an Eastern European city. “We learned that having one single model that would adapt to every single place on earth was likely impossible,” Lavista said…(More)”.

What is the value of data? A review of empirical methods


Paper by Diane Coyle and Annabel Manley: “With the growing use of digital technologies, data have become core to many organizations’ decisions, with its value widely acknowledged across public and private sectors. Yet few comprehensive empirical approaches to establishing the value of data exist, and there is no consensus about which methods should be applied to specific data types or purposes. This paper examines a range of data valuation methodologies proposed in the existing literature. We propose a typology linking methods to different data types and purposes…(More)”.

Driving Excellence in Official Statistics: Unleashing the Potential of Comprehensive Digital Data Governance


Paper by Hossein Hassani and Steve McFeely: “With the ubiquitous use of digital technologies and the consequent data deluge, official statistics faces new challenges and opportunities. In this context, strengthening official statistics through effective data governance will be crucial to ensure reliability, quality, and access to data. This paper presents a comprehensive framework for digital data governance for official statistics, addressing key components, such as data collection and management, processing and analysis, data sharing and dissemination, as well as privacy and ethical considerations. The framework integrates principles of data governance into digital statistical processes, enabling statistical organizations to navigate the complexities of the digital environment. Drawing on case studies and best practices, the paper highlights successful implementations of digital data governance in official statistics. The paper concludes by discussing future trends and directions, including emerging technologies and opportunities for advancing digital data governance…(More)”.

The Urgent Need to Reimagine Data Consent


Article by Stefaan G. Verhulst, Laura Sandor & Julia Stamm: “Recognizing the significant benefits that can arise from the use and reuse of data to tackle contemporary challenges such as migration, it is worth exploring new approaches to collect and utilize data that empower individuals and communities, granting them the ability to determine how their data can be utilized for various personal, community, and societal causes. This need is not specific to migrants alone. It applies to various regions, populations, and fields, ranging from public health and education to urban mobility. There is a pressing demand to involve communities, often already vulnerable, to establish responsible access to their data that aligns with their expectations, while simultaneously serving the greater public good.

We believe the answer lies through a reimagination of the concept of consent. Traditionally, consent has been the tool of choice to secure agency and individual rights, but that concept, we would suggest, is no longer sufficient to today’s era of datafication. Instead, we should strive to establish a new standard of social license. Here, we’ll define what we mean by a social license and outline some of the limitations of consent (as it is typically defined and practiced today). Then we’ll describe one possible means of securing social license—through participatory decision -making…(More)”.

How data-savvy cities can tackle growing ethical considerations


Bloomberg Cities Network: “Technology for collecting, combining, and analyzing data is moving quickly, putting cities in a good position to use data to innovate in how they solve problems. However, it also places a responsibility on them to do so in a manner that does not undermine public trust. 

To help local governments deal with these issues, the London Office of Technology and Innovation, or LOTI, has a set of recommendations for data ethics capabilities in local government. One of those recommendations—for cities that are mature in their work in this area—is to hire a dedicated data ethicist.

LOTI exists to support dozens of local boroughs across London in their collective efforts to tackle big challenges. As part of that mission, LOTI hired Sam Nutt to serve as a data ethicist that local leaders can call on. The move reflected the reality that most local councils don’t have the capacity to have their own data ethicist on staff and it put LOTI in a position to experiment, learn, and share out lessons learned from the approach.

Nutt’s role provides a potential framework other cities looking to hire data ethicists can build on. His position is based on job specifications for data ethicists published by the UK government. He says his work falls into three general areas. First, he helps local councils work through ethical questions surrounding individual data projects. Second, he helps them develop more high-level policies, such as the Borough of Camden’s Data Charter. And third, he provides guidance on how to engage staff, residents, and stakeholders around the implications of using technology, including research on what’s new in the field. 

As an example of the kinds of ethical issues that he consults on, Nutt cites repairs in publicly subsidized housing. Local leaders are interested in using algorithms to help them prioritize use of scarce maintenance resources. But doing so raises questions about what criteria should be used to bump one resident’s needs above another’s. 

“If you prioritize, for example, the likelihood of a resident making a complaint, you may be baking in an existing social inequality, because some communities do not feel as empowered to make complaints as others,” Nutt says. “So it’s thinking through what the ethical considerations might be in terms of choices of data and how you use it, and giving advice to prevent potential biases from creeping in.” 

Nutt acknowledges that most cities are too resource constrained to hire a staff data ethicist. What matters most, he says, is that local governments create mechanisms for ensuring that ethical considerations of their choices with data and technology are considered. “The solution will never be that everyone has to hire a data ethicist,” Nutt says. “The solution is really to build ethics into your default ways of working with data.”

Stefaan Verhulst agrees. “The question for government is: Is ethics a position? A function? Or an institutional responsibility?” says Verhulst, Co-Founder of The GovLab and Director of its Data Program. The key is “to figure out how we institutionalize this in a meaningful way so that we can always check the pulse and get rapid input with regard to the social license for doing certain kinds of things.”

As the data capabilities of local governments grow, it’s also important to empower all individuals working in government to understand ethical considerations within the work they’re doing, and to have clear guidelines and codes of conduct they can follow. LOTI’s data ethics recommendations note that hiring a data ethicist should not be an organization’s first step, in part because “it risks delegating ethics to a single individual when it should be in the domain of anyone using or managing data.”

Training staff is a big part of the equation. “It’s about making the culture of government sensitive to these issues,” Verhulst says, so “that people are aware.”..(More)”.

The Ethics of Sharing: Privacy, Data, and Common Goods


Paper by Sille Obelitz Søe & Jens-Erik Mai: “Given the concerns about big tech’s hoarding of data, creation of profiles, mining of data, and extrapolation of new knowledge from their data warehouses, there is a need and interest in devising policies and regulations that better shape big tech’s influence on people and their lives. One such proposal is to create data commons. In this paper, we examine the idea of data commons as well as the concept of sharing in relation to the concept of personal data. We argue that personal data are different in nature from the objects of classical commons wherefore the logic of “sharing is caring” is flawed. We, therefore, develop an ethics of sharing taking privacy into account as well as the idea that sometimes the right thing to do is not sharing. This ethics of sharing is based in a proposal to conceptualize data commons as MacIntyrean practices and Wittgensteinian forms of life…(More)”.

Public Sector Use of Private Sector Personal Data: Towards Best Practices


Paper by Teresa Scassa: “Governments increasingly turn to the private sector as a source of data for various purposes. In some cases, the data that they seek to use is personal data. The public sector use of private sector personal data raises several important law and public policy concerns. These include the legal authority for such uses; privacy and data protection; ethics; transparency; and human rights. Governments that use private sector personal data without attending to the issues that such use raises may breach existing laws, which in some cases may not be well-adapted to evolving data practices. They also risk undermining public trust.

This paper uses two quite different recent examples from Canada where the use of private sector personal data by public sector actors caused considerable backlash and led to public hearings and complaints to the Privacy Commissioner. The examples are used to tease out the complex and interwoven law and policy issues. In some cases, the examples reveal issues that are particular to the evolving data society and that are not well addressed by current law or practice. The paper identifies key issues and important gaps and makes recommendations to address these. Although the examples discussed are Canadian and depend to some extent on Canadian law and institutions, the practices at issue are ones that are increasingly used around the world, and many of the issues raised are broadly relevant…(More)”.