How tracking animal movement may save the planet

Curated on Posted on by Stefaan Verhulst

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)”.

Defending democracy: The threat to the public sphere from social media

Curated on Posted on by Stefaan Verhulst

Book Review by Mark Hannam: “Habermas is a blockhead. It is simply impossible to tell what kind of damage he is still going to cause in the future”, wrote Karl Popper in 1969. The following year he added: “Most of what he says seems to me trivial; the rest seems to me mistaken”. Five decades later these Popperian conjectures have been roundly refuted. Now in his mid-nineties, Jürgen Habermas is one of the pre-eminent philosophers and public intellectuals of our time. In Germany his generation enjoyed the mercy of being born too late. In 2004, in a speech given on receipt of the Kyoto prize in arts and philosophy, he observed that “we did not have to answer for choosing the wrong side and for political errors and their dire consequences”. He came to maturity in a society that he judged complacent and insufficiently distanced from its recent past. This experience sets the context for his academic work and political interventions.

Polity has recently published two new books by Habermas, both translated by Ciaran Cronin, providing English readers access to the latest iterations of his distinctive themes and methods. He defends a capacious concept of human reason, a collaborative learning process that operates through discussions in which participants appeal only to the force of the better argument. Different kinds of discussion – about scientific facts, moral norms or aesthetic judgements – employ different standards of justification, so what counts as a valid reason depends on context, but all progress, regardless of the field, relies on our conversations following the path along which reason leads us. Habermas’s principal claim is that human reason, appropriately deployed, retains its liberating potential for the species.

His first book, The Structural Transformation of the Public Sphere (1962), traced the emergence in the eighteenth century of the public sphere. This was a functionally distinct social space, located between the privacy of civil society and the formal offices of the modern state, where citizens could engage in processes of democratic deliberation. Habermas drew attention to a range of contemporary phenomena, including the organization of opinion by political parties and the development of mass media funded by advertising, that have disrupted the possibility of widespread, well-informed political debate. Modern democracy, he argued, was increasingly characterized by the technocratic organization of interests, rather than by the open discussion of principles and values…(More)”.

Are Evidence-Based Medicine and Public Health Incompatible?

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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)”

Influencers: Looking beyond the consensus of the crowd.

Curated on Posted on by Stefaan Verhulst

Article by Wilfred M. McClay: “Those of us who take a loving interest in words—their etymological forebears, their many layers of meaning, their often-surprising histories—have a tendency to resist change. Not that we think playfulness should be proscribed—such pedantry would be a cure worse than any disease. It’s just that we are also drawn, like doting parents, into wanting to protect the language, and thus become suspicious of mysterious strangers, of the introduction of new words, and of new meanings for familiar ones.

When we find words being used in a novel way, our countenances tend to stiffen. What’s going on here? Is this a euphemism? Is there a hidden agenda here?

But there are times when the older language seems inadequate, and in fact may mislead us into thinking that the world has not changed. New signifiers may sometimes be necessary, in order to describe new things.

Such is unquestionably the case of the new/old word influencer. At first glance, it looks harmless and insignificant, a lazy and imprecise way of designating someone as influential. But the word’s use as a noun is the key to what is different and new about it. And much as I dislike the word, and dislike the phenomenon it describes, necessity seems to have dictated that such a word be created…(More)”.

To Design Cities Right, We Need to Focus on People

Curated on Posted on by Stefaan Verhulst

Article by Tim Keane: “Our work in the U.S. to make better neighborhoods, towns and cities is a hapless and obdurate mess. If you’ve attended a planning meeting anywhere, you have probably witnessed the miserable process in action—unrestrainedly selfish fighting about false choices and seemingly inane procedures. Rather than designing places for people, we see cities as a collection of mechanical problems with technical and legal solutions. We distract ourselves with the latest rebranded ideas about places—smart growth, resilient cities, complete streets, just cities, 15-minute cities, happy cities—rather than getting down to the actual work of designing the physical place. This lacks a fundamental vision. And it’s not succeeding.

Our flawed approach to city planning started a century ago. The first modern city plan was produced for Cincinnati in 1925 by the Technical Advisory Corporation, founded in 1913 by George Burdett Ford and E.P. Goodrich in New York City. New York adopted the country’s first comprehensive zoning ordinance in 1916, an effort Ford led. Not coincidentally, the advent of zoning, and then comprehensive planning, corresponded directly with the great migration of six million Black people from the South to Northern, Midwestern and Western cities. New city planning practices were a technical means to discriminate and exclude.

This first comprehensive plan also ushered in another type of dehumanization: city planning by formula. To justify widening downtown streets by cutting into sidewalks, engineers used a calculation that reflected the cost to operate an automobile in a congested area—including the cost of a human life, because crashes killed people. Engineers also calculated the value of a sidewalk through a formula based on how many people the elevators in adjoining buildings could deliver at peak times. In the end, Cincinnati’s planners recommended widening the streets for cars, which were becoming more common, by shrinking sidewalks. City planning became an engineering equation, and one focused on separating people and spreading the city out to the maximum extent possible…(More)”.

University of Michigan Sells Recordings of Study Groups and Office Hours to Train AI

Curated on Posted on by Stefaan Verhulst

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?

Curated on Posted on by Stefaan Verhulst

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)”.

Language Machinery

Curated on Posted on by Stefaan Verhulst

Essay by Richard Hughes Gibson: “… current debates about writing machines are not as fresh as they seem. As is quietly acknowledged in the footnotes of scientific papers, much of the intellectual infrastructure of today’s advances was laid decades ago. In the 1940s, the mathematician Claude Shannon demonstrated that language use could be both described by statistics and imitated with statistics, whether those statistics were in human heads or a machine’s memory. Shannon, in other words, was the first statistical language modeler, which makes ChatGPT and its ilk his distant brainchildren. Shannon never tried to build such a machine, but some astute early readers of his work recognized that computers were primed to translate his paper-and-ink experiments into a powerful new medium. In writings now discussed largely in niche scholarly and computing circles, these readers imagined—and even made preliminary sketches of—machines that would translate Shannon’s proposals into reality. These readers likewise raised questions about the meaning of such machines’ outputs and wondered what the machines revealed about our capacity to write.

The current barrage of commentary has largely neglected this backstory, and our discussions suffer for forgetting that issues that appear novel to us belong to the mid-twentieth century. Shannon and his first readers were the original residents of the headspace in which so many of us now find ourselves. Their ambitions and insights have left traces on our discourse, just as their silences and uncertainties haunt our exchanges. If writing machines constitute a “philosophical event” or a “prompt for philosophizing,” then I submit that we are already living in the event’s aftermath, which is to say, in Shannon’s aftermath. Amid the rampant speculation about a future dominated by writing machines, I propose that we turn in the other direction to listen to field reports from some of the first people to consider what it meant to read and write in Shannon’s world…(More)”.

How Health Data Integrity Can Earn Trust and Advance Health

Curated on Posted on by Stefaan Verhulst

Article by Jochen Lennerz, Nick Schneider and Karl Lauterbach: “Efforts to share health data across borders snag on legal and regulatory barriers. Before detangling the fine print, let’s agree on overarching principles.

Imagine a scenario in which Mary, an individual with a rare disease, has agreed to share her medical records for a research project aimed at finding better treatments for genetic disorders. Mary’s consent is grounded in trust that her data will be handled with the utmost care, protected from unauthorized access, and used according to her wishes. 

It may sound simple, but meeting these standards comes with myriad complications. Whose job is it to weigh the risk that Mary might be reidentified, even if her information is de-identified and stored securely? How should that assessment be done? How can data from Mary’s records be aggregated with patients from health systems in other countries, each with their own requirements for data protection and formats for record keeping? How can Mary’s wishes be respected, both in terms of what research is conducted and in returning relevant results to her?

From electronic medical records to genomic sequencing, health care providers and researchers now have an unprecedented wealth of information that could help tailor treatments to individual needs, revolutionize understanding of disease, and enhance the overall quality of health care. Data protection, privacy safeguards, and cybersecurity are all paramount for safeguarding sensitive medical information, but much of the potential that lies in this abundance of data is being lost because well-intentioned regulations have not been set up to allow for data sharing and collaboration. This stymies efforts to study rare diseases, map disease patterns, improve public health surveillance, and advance evidence-based policymaking (for instance, by comparing effectiveness of interventions across regions and demographics). Projects that could excel with enough data get bogged down in bureaucracy and uncertainty. For example, Germany now has strict data protection laws—with heavy punishment for violations—that should allow de-identified health insurance claims to be used for research within secure processing environments, but the legality of such use has been challenged…(More)”.