Article by Stefaan Verhulst: “…In what follows, we offer five thoughts on how to advance Data Driven Philanthropy. These are operational strategies, specific steps that philanthropic organisations can take in order to harness the potential of data for the public good. At its broadest level, then, this article is about data stewardship in the 21st century. We seek to define how philanthropic organisations can be responsible custodians of data assets, both theirs and those of society at large. Fulfilling this role of data stewardship is a critical mission for the philanthropic sector and one of the most important roles it can play in helping to ensure that our ongoing process of digital transformation is more fair, inclusive, and aligned with the broader public interest…(More)”.
How tracking animal movement may save the planet
Article by Matthew Ponsford: “Researchers have been dreaming of an Internet of Animals. They’re getting closer to monitoring 100,000 creatures—and revealing hidden facets of our shared world….There was something strange about the way the sharks were moving between the islands of the Bahamas.
Tiger sharks tend to hug the shoreline, explains marine biologist Austin Gallagher, but when he began tagging the 1,000-pound animals with satellite transmitters in 2016, he discovered that these predators turned away from it, toward two ancient underwater hills made of sand and coral fragments that stretch out 300 miles toward Cuba. They were spending a lot of time “crisscrossing, making highly tortuous, convoluted movements” to be near them, Gallagher says.
It wasn’t immediately clear what attracted sharks to the area: while satellite images clearly showed the subsea terrain, they didn’t pick up anything out of the ordinary. It was only when Gallagher and his colleagues attached 360-degree cameras to the animals that they were able to confirm what they were so drawn to: vast, previously unseen seagrass meadows—a biodiverse habitat that offered a smorgasbord of prey.
The discovery did more than solve a minor mystery of animal behavior. Using the data they gathered from the sharks, the researchers were able to map an expanse of seagrass stretching across 93,000 square kilometers of Caribbean seabed—extending the total known global seagrass coverage by more than 40%, according to a study Gallagher’s team published in 2022. This revelation could have huge implications for efforts to protect threatened marine ecosystems—seagrass meadows are a nursery for one-fifth of key fish stocks and habitats for endangered marine species—and also for all of us above the waves, as seagrasses can capture carbon up to 35 times faster than tropical rainforests.
Animals have long been able to offer unique insights about the natural world around us, acting as organic sensors picking up phenomena that remain invisible to humans. More than 100 years ago, leeches signaled storms ahead by slithering out of the water; canaries warned of looming catastrophe in coal mines until the 1980s; and mollusks that close when exposed to toxic substances are still used to trigger alarms in municipal water systems in Minneapolis and Poland…(More)”.
Situating Data Sets: Making Public Data Actionable for Housing Justice
Paper by Anh-Ton Tran et al: “Activists, governments and academics regularly advocate for more open data. But how is data made open, and for whom is it made useful and usable? In this paper, we investigate and describe the work of making eviction data open to tenant organizers. We do this through an ethnographic description of ongoing work with a local housing activist organization. This work combines observation, direct participation in data work, and creating media artifacts, specifically digital maps. Our interpretation is grounded in D’Ignazio and Klein’s Data Feminism, emphasizing standpoint theory. Through our analysis and discussion, we highlight how shifting positionalities from data intermediaries to data accomplices affects the design of data sets and maps. We provide HCI scholars with three design implications when situating data for grassroots organizers: becoming a domain beginner, striving for data actionability, and evaluating our design artifacts by the social relations they sustain rather than just their technical efficacy…(More)”.
The U.S. Census Is Wrong on Purpose
Blog by David Friedman: “This is a story about data manipulation. But it begins in a small Nebraska town called Monowi that has only one resident, 90 year old Elsie Eiler.
The sign says “Monowi 1,” from Google Street View.
There used to be more people in Monowi. But little by little, the other residents of Monowi left or died. That’s what happened to Elsie’s own family — her children grew up and moved out and her husband passed away in 2004, leaving her as the sole resident. Now she votes for herself for Mayor, and pays herself taxes. Her husband Rudy’s old book collection became the town library, with Elsie as librarian.
But despite what you might imagine, Elsie is far from lonely. She runs a tavern that’s been in her family for 50 years, and has plenty of regulars from the town next door who come by every day to dine and chat.
I first read about Elsie more than 10 years ago. At the time, it wasn’t as well known a story but Elsie has since gotten a lot of coverage and become a bit of a minor celebrity. Now and then I still come across a new article, including a lovely photo essay in the New York Times and a short video on the BBC Travel site.
A Google search reveals many, many similar articles that all tell more or less the same story.
But then suddenly in 2021, there was a new wrinkle: According to the just-published 2020 U.S. Census data, Monowi now had 2 residents, doubling its population.
This came as a surprise to Elsie, who told a local newspaper, “Then someone’s been hiding from me, and there’s nowhere to live but my house.”
It turns out that nobody new had actually moved to Monowi without Elsie realizing. And the census bureau didn’t make a mistake. They intentionally changed the census data, adding one resident.
Why would they do that? Well, it turns out the census bureau sometimes moves residents around on paper in order to protect people’s privacy.
Full census data is only made available 72 years after the census takes place, in accordance with the creatively-named “72 year rule.” Until then, it is only available as aggregated data with individual identifiers removed. Still, if the population of a town is small enough, and census data for that town indicates, for example, that there is just one 90 year old woman and she lives alone, someone could conceivably figure out who that individual is.
So the census bureau sometimes moves people around to create noise in the data that makes that sort of identification a little bit harder…(More)”.
Are Evidence-Based Medicine and Public Health Incompatible?
Essay by Michael Schulson: “It’s a familiar pandemic story: In September 2020, Angela McLean and John Edmunds found themselves sitting in the same Zoom meeting, listening to a discussion they didn’t like.
At some point during the meeting, McLean — professor of mathematical biology at the Oxford University, dame commander of the Order of the British Empire, fellow of the Royal Society of London, and then-chief scientific adviser to the United Kingdom’s Ministry of Defense — sent Edmunds a message on WhatsApp.
“Who is this fuckwitt?” she asked.
The message was evidently referring to Carl Heneghan, director of the Center for Evidence-Based Medicine at Oxford. He was on Zoom that day, along with McLean and Edmunds and two other experts, to advise the British prime minister on the Covid-19 pandemic.
Their disagreement — recently made public as part of a British government inquiry into the Covid-19 response — is one small chapter in a long-running clash between two schools of thought within the world of health care.
McLean and Edmunds are experts in infectious disease modeling; they build elaborate simulations of pandemics, which they use to predict how infections will spread and how best to slow them down. Often, during the Covid-19 pandemic, such models were used alongside other forms of evidence to urge more restrictions to slow the spread of the disease. Heneghan, meanwhile, is a prominent figure in the world of evidence-based medicine, or EBM. The movement aims to help doctors draw on the best available evidence when making decisions and advising patients. Over the past 30 years, EBM has transformed the practice of medicine worldwide.
Whether it can transform the practice of public health — which focuses not on individuals, but on keeping the broader community healthy — is a thornier question…(More)”.
Air Canada chatbot promised a discount. Now the airline has to pay it
Article by Kyle Melnick: “After his grandmother died in Ontario a few years ago, British Columbia resident Jake Moffatt visited Air Canada’s website to book a flight for the funeral. He received assistance from a chatbot, which told him the airline offered reduced rates for passengers booking last-minute travel due to tragedies.
Moffatt bought a nearly $600 ticket for a next-day flight after the chatbot said he would get some of his money back under the airline’s bereavement policy as long as he applied within 90 days, according to a recent civil-resolutions tribunal decision.
But when Moffatt later attempted to receive the discount, he learned that the chatbot had been wrong. Air Canada only awarded bereavement fees if the request had been submitted before a flight. The airline later argued the chatbot wasa separate legal entity “responsible for its own actions,” the decision said.
Moffatt filed a claim with the Canadian tribunal, which ruled Wednesday that Air Canada owed Moffatt more than $600 in damages and tribunal fees after failing to provide “reasonable care.”
As companies have added artificial intelligence-powered chatbots to their websites in hopes of providing faster service, the Air Canada dispute sheds light on issues associated with the growing technology and how courts could approach questions of accountability. The Canadian tribunal in this case came down on the side of the customer, ruling that Air Canada did not ensure its chatbot was accurate…(More)”
Community views on the secondary use of general practice data: Findings from a mixed-methods study
Paper by Annette J. Braunack-Mayer et al: “General practice data, particularly when combined with hospital and other health service data through data linkage, are increasingly being used for quality assurance, evaluation, health service planning and research.Using general practice data is particularly important in countries where general practitioners (GPs) are the first and principal source of health care for most people.
Although there is broad public support for the secondary use of health data, there are good reasons to question whether this support extends to general practice settings. GP–patient relationships may be very personal and longstanding and the general practice health record can capture a large amount of information about patients. There is also the potential for multiple angles on patients’ lives: GPs often care for, or at least record information about, more than one generation of a family. These factors combine to amplify patients’ and GPs’ concerns about sharing patient data….
Adams et al. have developed a model of social licence, specifically in the context of sharing administrative data for health research, based on an analysis of the social licence literature and founded on two principal elements: trust and legitimacy.In this model, trust is founded on research enterprises being perceived as reliable and responsive, including in relation to privacy and security of information, and having regard to the community’s interests and well-being.
Transparency and accountability measures may be used to demonstrate trustworthiness and, as a consequence, to generate trust. Transparency involves a level of openness about the way data are handled and used as well as about the nature and outcomes of the research. Adams et al. note that lack of transparency can undermine trust. They also note that the quality of public engagement is important and that simply providing information is not sufficient. While this is one element of transparency, other elements such as accountability and collaboration are also part of the trusting, reflexive relationship necessary to establish and support social licence.
The second principal element, legitimacy, is founded on research enterprises conforming to the legal, cultural and social norms of society and, again, acting in the best interests of the community. In diverse communities with a range of views and interests, it is necessary to develop a broad consensus on what amounts to the common good through deliberative and collaborative processes.
Social licence cannot be assumed. It must be built through public discussion and engagement to avoid undermining the relationship of trust with health care providers and confidence in the confidentiality of health information…(More)”
Data, Privacy Laws and Firm Production: Evidence from the GDPR
Paper by Mert Demirer, Diego J. Jiménez Hernández, Dean Li & Sida Peng: “By regulating how firms collect, store, and use data, privacy laws may change the role of data in production and alter firm demand for information technology inputs. We study how firms respond to privacy laws in the context of the EU’s General Data Protection Regulation (GDPR) by using seven years of data from a large global cloud-computing provider. Our difference-in-difference estimates indicate that, in response to the GDPR, EU firms decreased data storage by 26% and data processing by 15% relative to comparable US firms, becoming less “data-intensive.” To estimate the costs of the GDPR for firms, we propose and estimate a production function where data and computation serve as inputs to the production of “information.” We find that data and computation are strong complements in production and that firm responses are consistent with the GDPR, representing a 20% increase in the cost of data on average. Variation in the firm-level effects of the GDPR and industry-level exposure to data, however, drives significant heterogeneity in our estimates of the impact of the GDPR on production costs…(More)”
University of Michigan Sells Recordings of Study Groups and Office Hours to Train AI
Article by Joseph Cox: “The University of Michigan is selling hours of audio recordings of study groups, office hours, lectures, and more to outside third-parties for tens of thousands of dollars for the purpose of training large language models (LLMs). 404 Media has downloaded a sample of the data, which includes a one hour and 20 minute long audio recording of what appears to be a lecture.
The news highlights how some LLMs may ultimately be trained on data with an unclear level of consent from the source subjects. ..(More)”.
Could AI Speak on Behalf of Future Humans?
Article by Konstantin Scheuermann & Angela Aristidou : “An enduring societal challenge the world over is a “perspective deficit” in collective decision-making. Whether within a single business, at the local community level, or the international level, some perspectives are not (adequately) heard and may not receive fair and inclusive representation during collective decision-making discussions and procedures. Most notably, future generations of humans and aspects of the natural environment may be deeply affected by present-day collective decisions. Yet, they are often “voiceless” as they cannot advocate for their interests.
Today, as we witness the rapid integration of artificial intelligence (AI) systems into the everyday fabric of our societies, we recognize the potential in some AI systems to surface and/or amplify the perspectives of these previously voiceless stakeholders. Some classes of AI systems, notably Generative AI (e.g., ChatGPT, Llama, Gemini), are capable of acting as the proxy of the previously unheard by generating multi-modal outputs (audio, video, and text).
We refer to these outputs collectively here as “AI Voice,” signifying that the previously unheard in decision-making scenarios gain opportunities to express their interests—in other words, voice—through the human-friendly outputs of these AI systems. AI Voice, however, cannot realize its promise without first challenging how voice is given and withheld in our collective decision-making processes and how the new technology may and does unsettle the status quo. There is also an important distinction between the “right to voice” and the “right to decide” when considering the roles AI Voice may assume—ranging from a passive facilitator to an active collaborator. This is one highly promising and feasible possibility for how to leverage AI to create a more equitable collective future, but to do so responsibly will require careful strategy and much further conversation…(More)”.