Article by Haley Fitzpatrick, Tobias Luthe, and Birger Sevaldson: “To leverage the fullest potential of systemic design research in real-world contexts, more diverse and reflexive approaches are necessary. Especially for addressing the place-based and unpredictable nature of sustainability transformations, scholars across disciplines caution that standard research strategies and methods often fall short. While systemic design promotes concepts such as holism, plurality, and emergence, more insight is necessary for translating these ideas into practices for engaging in complex, real-world applications. Reflexivity is crucial to understanding these implications, and systemic design practice will benefit from a deeper discourse on the relationships between researchers, contexts, and methods. In this study, we offer an illustrated example of applying a diverse and reflexive systems oriented design approach that engaged three mountain communities undergoing sustainability transformations. Based on a longitudinal, comparative research project, a combination of methods from systemic design, social science, education, and embodied practices was developed and prototyped across three mountain regions: Ostana, Italy; Hemsedal, Norway; and Mammoth Lakes, California. The selection of these regions was influenced by the researchers’ varying levels of previous engagement. Reflexivity was used to explore how place-based relationships influenced the researchers’ interactions with each community. Different modes of reflexivity were used to analyze the contextual, relational, and boundary-related factors that shaped how the framing, format, and communication of each method and practice adapted over time. We discuss these findings through visualizations and narrative examples to translate abstract concepts like emergence and plurality into actionable insights. This study contributes to systemic design research by showing how a reflexive approach of weaving across different places, methods, and worldviews supports the critical facilitation processes needed to apply and advance methodological plurality in practice…(More)”
How Copyright May Destroy Our Access To The World’s Academic Knowledge
Article by Glyn Moody: “The shift from analogue to digital has had a massive impact on most aspects of life. One area where that shift has the potential for huge benefits is in the world of academic publishing. Academic papers are costly to publish and distribute on paper, but in a digital format they can be shared globally for almost no cost. That’s one of the driving forces behind the open access movement. But as Walled Culture has reported, resistance from the traditional publishing world has slowed the shift to open access, and undercut the benefits that could flow from it.
That in itself is bad news, but new research from Martin Paul Eve (available as open access) shows that the way the shift to digital has been managed by publishers brings with it a new problem. For all their flaws, analogue publications have the great virtue that they are durable: once a library has a copy, it is likely to be available for decades, if not centuries. Digital scholarly articles come with no such guarantee. The Internet is constantly in flux, with many publishers and sites closing down each year, often without notice. That’s a problem when sites holding archival copies of scholarly articles vanish, making it harder, perhaps impossible, to access important papers. Eve explored whether publishers were placing copies of the articles they published in key archives. Ideally, digital papers would be available in multiple archives to ensure resilience, but the reality is that very few publishers did this. Ars Technica has a good summary of Eve’s results:
When Eve broke down the results by publisher, less than 1 percent of the 204 publishers had put the majority of their content into multiple archives. (The cutoff was 75 percent of their content in three or more archives.) Fewer than 10 percent had put more than half their content in at least two archives. And a full third seemed to be doing no organized archiving at all.
At the individual publication level, under 60 percent were present in at least one archive, and over a quarter didn’t appear to be in any of the archives at all. (Another 14 percent were published too recently to have been archived or had incomplete records.)..(More)”.
The Unintended Consequences of Data Standardization
Article by Cathleen Clerkin: “The benefits of data standardization within the social sector—and indeed just about any industry—are multiple, important, and undeniable. Access to the same type of data over time lends the ability to track progress and increase accountability. For example, over the last 20 years, my organization, Candid, has tracked grantmaking by the largest foundations to assess changes in giving trends. The data allowed us to demonstrate philanthropy’s disinvestment in historically Black colleges and universities. Data standardization also creates opportunities for benchmarking—allowing individuals and organizations to assess how they stack up to their colleagues and competitors. Moreover, large amounts of standardized data can help predict trends in the sector. Finally—and perhaps most importantly to the social sector—data standardization invariably reduces the significant reporting burdens placed on nonprofits.
Yet, for all of its benefits, data is too often proposed as a universal cure that will allow us to unequivocally determine the success of social change programs and processes. The reality is far more complex and nuanced. Left unchecked, the unintended consequences of data standardization pose significant risks to achieving a more effective, efficient, and equitable social sector…(More)”.
EBP+: Integrating science into policy evaluation using Evidential Pluralism
Article by Joe Jones, Alexandra Trofimov, Michael Wilde & Jon Williamson: “…While the need to integrate scientific evidence in policymaking is clear, there isn’t a universally accepted framework for doing so in practice. Orthodox evidence-based approaches take Randomised Controlled Trials (RCTs) as the gold standard of evidence. Others argue that social policy issues require theory-based methods to understand the complexities of policy interventions. These divisions may only further decrease trust in science at this critical time.
EBP+ offers a broader framework within which both orthodox and theory-based methods can sit. EBP+ also provides a systematic account of how to integrate and evaluate these different types of evidence. EBP+ can offer consistency and objectivity in policy evaluation, and could yield a unified approach that increases public trust in scientifically-informed policy…
EBP+ is motivated by Evidential Pluralism, a philosophical theory of causal enquiry that has been developed over the last 15 years. Evidential Pluralism encompasses two key claims. The first, object pluralism, says that establishing that A is a cause of B (e.g., that a policy intervention causes a specific outcome) requires establishing both that A and B are appropriately correlated and that there is some mechanism which links the two and which can account for the extent of the correlation. The second claim, study pluralism, maintains that assessing whether A is a cause of B requires assessing both association studies (studies that repeatedly measure A and B, together with potential confounders, to measure their association) and mechanistic studies (studies of features of the mechanisms linking A to B), where available…(More)”.
A.I.-Generated Garbage Is Polluting Our Culture
Article by Eric Hoel: “Increasingly, mounds of synthetic A.I.-generated outputs drift across our feeds and our searches. The stakes go far beyond what’s on our screens. The entire culture is becoming affected by A.I.’s runoff, an insidious creep into our most important institutions.
Consider science. Right after the blockbuster release of GPT-4, the latest artificial intelligence model from OpenAI and one of the most advanced in existence, the language of scientific research began to mutate. Especially within the field of A.I. itself.
A study published this month examined scientists’ peer reviews — researchers’ official pronouncements on others’ work that form the bedrock of scientific progress — across a number of high-profile and prestigious scientific conferences studying A.I. At one such conference, those peer reviews used the word “meticulous” more than 34 times as often as reviews did the previous year. Use of “commendable” was around 10 times as frequent, and “intricate,” 11 times. Other major conferences showed similar patterns.
Such phrasings are, of course, some of the favorite buzzwords of modern large language models like ChatGPT. In other words, significant numbers of researchers at A.I. conferences were caught handing their peer review of others’ work over to A.I. — or, at minimum, writing them with lots of A.I. assistance. And the closer to the deadline the submitted reviews were received, the more A.I. usage was found in them.
If this makes you uncomfortable — especially given A.I.’s current unreliability — or if you think that maybe it shouldn’t be A.I.s reviewing science but the scientists themselves, those feelings highlight the paradox at the core of this technology: It’s unclear what the ethical line is between scam and regular usage. Some A.I.-generated scams are easy to identify, like the medical journal paper featuring a cartoon rat sporting enormous genitalia. Many others are more insidious, like the mislabeled and hallucinated regulatory pathway described in that same paper — a paper that was peer reviewed as well (perhaps, one might speculate, by another A.I.?)…(More)”.
Meta Kills a Crucial Transparency Tool At the Worst Possible Time
Interview by Vittoria Elliott: “Earlier this month, Meta announced that it would be shutting down CrowdTangle, the social media monitoring and transparency tool that has allowed journalists and researchers to track the spread of mis- and disinformation. It will cease to function on August 14, 2024—just months before the US presidential election.
Meta’s move is just the latest example of a tech company rolling back transparency and security measures as the world enters the biggest global election year in history. The company says it is replacing CrowdTangle with a new Content Library API, which will require researchers and nonprofits to apply for access to the company’s data. But the Mozilla Foundation and 140 other civil society organizations protested last week that the new offering lacks much of CrowdTangle’s functionality, asking the company to keep the original tool operating until January 2025.
Meta spokesperson Andy Stone countered in posts on X that the groups’ claims “are just wrong,” saying the new Content Library will contain “more comprehensive data than CrowdTangle” and be made available to nonprofits, academics, and election integrity experts. When asked why commercial newsrooms, like WIRED, are to be excluded from the Content Library, Meta spokesperson Eric Porterfield said, that it was “built for research purposes.” While journalists might not have direct access he suggested they could use commercial social network analysis tools, or “partner with an academic institution to help answer a research question related to our platforms.”
Brandon Silverman, cofounder and former CEO of CrowdTangle, who continued to work on the tool after Facebook acquired it in 2016, says it’s time to force platforms to open up their data to outsiders. The conversation has been edited for length and clarity…(More)”.
AI Is Building Highly Effective Antibodies That Humans Can’t Even Imagine
Article by Amit Katwala: “Robots, computers, and algorithms are hunting for potential new therapies in ways humans can’t—by processing huge volumes of data and building previously unimagined molecules. At an old biscuit factory in South London, giant mixers and industrial ovens have been replaced by robotic arms, incubators, and DNA sequencing machines.
James Field and his company LabGenius aren’t making sweet treats; they’re cooking up a revolutionary, AI-powered approach to engineering new medical antibodies. In nature, antibodies are the body’s response to disease and serve as the immune system’s front-line troops. They’re strands of protein that are specially shaped to stick to foreign invaders so that they can be flushed from the system. Since the 1980s, pharmaceutical companies have been making synthetic antibodies to treat diseases like cancer, and to reduce the chance of transplanted organs being rejected. But designing these antibodies is a slow process for humans—protein designers must wade through the millions of potential combinations of amino acids to find the ones that will fold together in exactly the right way, and then test them all experimentally, tweaking some variables to improve some characteristics of the treatment while hoping that doesn’t make it worse in other ways. “If you want to create a new therapeutic antibody, somewhere in this infinite space of potential molecules sits the molecule you want to find,” says Field, the founder and CEO of LabGenius…(More)”.
Whatever Happened to All Those Care Robots?
Article by Stephanie H. Murray: “So far, companion robots haven’t lived up to the hype—and might even exacerbate the problems they’re meant to solve…There are likely many reasons that the long-predicted robot takeover of elder care has yet to take off. Robots are expensive, and cash-strapped care homes don’t have money lying around to purchase a robot, let alone to pay for the training needed to actually use one effectively. And at least so far, social robots just aren’t worth the investment, Wright told me. Pepper can’t do a lot of the things people claimed he could—and he relies heavily on humans to help him do what he can. Despite some research suggesting they can boost well-being among the elderly, robots have shown little evidence that they make life easier for human caregivers. In fact, they require quite a bit of care themselves. Perhaps robots of the future will revolutionize caregiving as hoped. But the care robots we have now don’t even come close, and might even exacerbate the problems they’re meant to solve…(More)”.
Why we’re fighting to make sure labor unions have a voice in how AI is implemented
Article by Liz Shuler and Mike Kubzansky: “Earlier this month, Google’s co-founder admitted that the company had “definitely messed up” after its AI tool, Gemini, produced historically inaccurate images—including depictions of racially diverse Nazis. Sergey Brin cited a lack of “thorough testing” of the AI tool, but the incident is a good reminder that, despite all the hype around generative AI replacing human output, the technology still has a long way to go.
Of course, that hasn’t stopped companies from deploying AI in the workplace. Some even use the technology as an excuse to lay workers off. Since last May, at least 4,000 people have lost their jobs to AI, and 70% of workers across the country live with the fear that AI is coming for theirs next. And while the technology may still be in its infancy, it’s developing fast. Earlier this year, AI pioneer Mustafa Suleyman said that “left completely to the market and to their own devices, [AI tools are] fundamentally labor-replacing.” Without changes now, AI could be coming to replace a lot of people’s jobs.
It doesn’t have to be this way. AI has enormous potential to build prosperity and unleash human creativity, but only if it also works for working people. Ensuring that happens requires giving the voice of workers—the people who will engage with these technologies every day, and whose lives, health, and livelihoods are increasingly affected by AI and automation—a seat at the decision-making table.
As president of the AFL-CIO, representing 12.5 million working people across 60 unions, and CEO of Omidyar Network, a social change philanthropy that supports responsible technology, we believe that the single best movement to give everyone a voice is the labor movement. Empowering workers—from warehouse associates to software engineers—is the most powerful tactic we have to ensure that AI develops in the interests of the many, not the few…(More)”.
Central banks use AI to assess climate-related risks
Article by Huw Jones: “Central bankers said on Tuesday they have broken new ground by using artificial intelligence to collect data for assessing climate-related financial risks, just as the volume of disclosures from banks and other companies is set to rise.
The Bank for International Settlements, a forum for central banks, the Bank of Spain, Germany’s Bundesbank and the European Central Bank said their experimental Gaia AI project was used to analyse company disclosures on carbon emissions, green bond issuance and voluntary net-zero commitments.
Regulators of banks, insurers and asset managers need high-quality data to assess the impact of climate-change on financial institutions. However, the absence of a single reporting standard confronts them with a patchwork of public information spread across text, tables and footnotes in annual reports.
Gaia was able to overcome differences in definitions and disclosure frameworks across jurisdictions to offer much-needed transparency, and make it easier to compare indicators on climate-related financial risks, the central banks said in a joint statement.
Despite variations in how the same data is reported by companies, Gaia focuses on the definition of each indicator, rather than how the data is labelled.
Furthermore, with the traditional approach, each additional key performance indicator, or KPI, and each new institution requires the analyst to either search for the information in public corporate reports or contact the institution for information…(More)”.