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	<title>natural experiment &#8211; Science</title>
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	<title>natural experiment &#8211; Science</title>
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		<title>AI Writing Tool Reshaped Petition Language on Change.org but Failed to Boost Success</title>
		<link>https://scienmag.com/ai-writing-tool-reshaped-petition-language-on-change-org-but-failed-to-boost-success/</link>
		
		<dc:creator><![CDATA[Glenn Wilkins]]></dc:creator>
		<pubDate>Wed, 30 Sep 2026 17:48:25 +0000</pubDate>
				<category><![CDATA[Psychology & Psychiatry]]></category>
		<category><![CDATA[AI influence on petition language and outcomes]]></category>
		<category><![CDATA[AI writing assistant impact on petition success]]></category>
		<category><![CDATA[AI writing tools]]></category>
		<category><![CDATA[AI-driven content quality in petitions]]></category>
		<category><![CDATA[Change.org]]></category>
		<category><![CDATA[Change.org AI feature analysis]]></category>
		<category><![CDATA[computational text analysis]]></category>
		<category><![CDATA[content homogenization]]></category>
		<category><![CDATA[difference-in-differences]]></category>
		<category><![CDATA[difference-in-differences methodology in platform studies]]></category>
		<category><![CDATA[digital activism]]></category>
		<category><![CDATA[effect of AI-generated petition language]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[generative AI in online activism]]></category>
		<category><![CDATA[impact of artificial intelligence on social movement campaigns]]></category>
		<category><![CDATA[large language models]]></category>
		<category><![CDATA[large-scale analysis of AI tools in activism]]></category>
		<category><![CDATA[natural experiment]]></category>
		<category><![CDATA[natural experiment design in online platforms]]></category>
		<category><![CDATA[natural experiment in digital platform]]></category>
		<category><![CDATA[Nature Human Behaviour]]></category>
		<category><![CDATA[online petition success factors]]></category>
		<category><![CDATA[online petitions]]></category>
		<category><![CDATA[platform design]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=217694</guid>

					<description><![CDATA[A large-scale natural experiment on Change.org found that an in-platform AI writing tool significantly altered the style and homogeneity of petitions without improving their real-world outcomes.]]></description>
										<content:encoded><![CDATA[<p>When the petition platform Change.org quietly rolled out a built-in artificial intelligence writing assistant, it offered millions of would-be activists a tempting promise: a smoother, more polished appeal that might finally tip the scales in their favor. A new study published in Nature Human Behaviour suggests the promise was only half kept. Researchers led by Isabel Corpus of Cornell University, together with Eric Gilbert of the University of Michigan, Allison Koenecke of Cornell, and Mor Naaman of Cornell and Cornell Tech, found that the tool dramatically changed how petitions were written, yet left the ultimate fate of those petitions essentially untouched. The work offers one of the clearest real-world measurements to date of what happens when generative AI is embedded directly into a large online platform, and its central finding is a sobering one for anyone hoping that better-sounding text translates into better results.</p>
<p>The study&#8217;s strength lies in its design. Rather than running a small laboratory experiment, the team exploited what statisticians call a natural experiment: Change.org introduced its &#8216;write with AI&#8217; feature in some countries before others, creating a clean before-and-after boundary. The researchers collected roughly 1.5 million petitions and applied a difference-in-differences analysis, a causal inference technique that compares changes over time between groups that received the AI tool and groups that did not. This approach, widely used in economics and built on methods formalized by Callaway and Sant&#8217;Anna for settings with multiple time periods, allows researchers to isolate the effect of the intervention from broader trends that would have happened anyway. Because the rollout timing was determined by the platform rather than by users&#8217; characteristics, the comparison approximates the rigor of a randomized controlled trial at population scale.</p>
<p>The first major finding concerns the texture of the text itself. After the AI tool became available, the lexical features of petitions shifted measurably at the platform level. Petitions grew longer and their language changed in ways consistent with the stylistic fingerprints of large language models: smoother phrasing, more standardized vocabulary, and altered readability characteristics. These are not trivial cosmetic shifts. Lexical measures such as vocabulary diversity and readability scores have long been used in computational text analysis to characterize how writing differs across authors, genres, and eras, and the fact that a single platform feature could move these metrics across an entire ecosystem of user-generated content is striking. In effect, the introduction of the tool bent the collective writing style of a global advocacy community.</p>
<p>But the second major finding is where the story turns. None of these stylistic improvements translated into better petition outcomes. Petitions written with access to the AI assistant did not attract more signatures, achieve their goals more often, or otherwise perform better than petitions written without it. For a tool presumably offered to help advocates succeed, that null result carries real weight. It echoes a growing body of evidence that generative AI can boost individual productivity in controlled settings, as shown in the well-known 2023 Science experiment by Noy and Zhang on professional writing tasks, while failing to deliver equivalent gains when success depends on persuading other humans in a noisy, competitive environment.</p>
<p>The researchers did not stop at the platform-level analysis. A persistent worry with observational studies is that the people who choose to use a new feature differ systematically from those who do not, contaminating any comparison. To address this, the team conducted a separate analysis of repeat petition writers: 4,611 users who had written at least one petition before the AI tool was introduced and another one after. This within-person comparison holds individual ability, motivation, and topic preferences roughly constant, isolating the effect of AI access on the same writers over time. The pattern that emerged was telling. On average, these returning writers produced longer petitions when they had access to AI, yet their second petitions fared worse in terms of outcomes than their earlier work. The very users most likely to benefit from accumulated platform experience saw no advantage, and by some measures a disadvantage, from the writing assistant.</p>
<p>Perhaps the most consequential finding is the increase in homogeneity. Using dynamic difference-in-differences estimates, the researchers showed that platform-wide homogeneity among petitions rose after the AI tool&#8217;s introduction. In plain terms, petitions began to sound more like one another. This result aligns with a rapidly expanding literature on what some researchers call generative monoculture. A 2024 study in Science Advances by Doshi and Hauser found that generative AI enhanced individual creativity while reducing the collective diversity of novel content. Work presented at the 2025 CHI Conference by Agarwal, Naaman, and Vashistha showed that AI writing suggestions can homogenize text toward Western stylistic conventions and erode cultural nuance. Padmakumar and He asked directly whether writing with language models reduces content diversity and found evidence that it does. The Change.org study extends these laboratory and small-scale findings to a genuine production environment used by millions.</p>
<p>Why should homogenization matter for something as seemingly benign as petition language? Advocacy platforms depend on differentiation. A petition competes for attention in a crowded feed, and its distinctive voice, urgency, and local specificity are part of what makes a reader stop and sign. When an algorithmic assistant nudges thousands of writers toward the same polished register, the collective signal degrades even if each individual text improves. Researchers have raised parallel concerns in other domains: a 2026 Nature analysis by Hao and colleagues found that AI tools expanded individual scientists&#8217; output while contracting the focus of science as a whole, and work on Stack Overflow suggested that large language models may threaten the value of community-generated digital public goods. The pattern that emerges across these studies is consistent: individual-level gains, community-level costs.</p>
<p>The null effect on outcomes also invites a deeper question about what petition success actually depends on. Prior research on e-petitions, including studies of linguistic cues and multidimensional time-series predictors of success, has suggested that factors such as topic salience, timing, social networks, and media coverage often dwarf the influence of prose quality. A beautifully written petition about an issue nobody cares about will still fail; a clumsy petition riding a wave of public outrage may succeed regardless. The Change.org results are consistent with this view. If outcomes are driven primarily by the underlying demand for a cause rather than by the craft of the appeal, then a tool that polishes craft without touching demand should indeed leave outcomes unchanged. The study cannot rule out subtler possibilities, such as offsetting effects in which longer, more polished text helps in some respects and hurts in others, but the headline conclusion stands: no measurable outcome benefit at scale.</p>
<p>There are also social and perceptual dimensions that the authors situate within a broader research program. Studies have shown that human heuristics for detecting AI-generated language are unreliable, that there can be a social evaluation penalty for using AI, and that perceptions of AI-mediated communication affect trustworthiness and perceived authenticity. For petition signers, the suspicion that a heartfelt appeal was machine-generated could matter as much as the text itself. Related work on the &#8216;AI ghostwriter effect&#8217; shows that users often fail to feel ownership of AI-generated text while still claiming authorship, raising questions about authenticity in civic expression. A platform that encourages AI-assisted advocacy may therefore be trading not only diversity of style but also the perceived sincerity that makes grassroots appeals compelling.</p>
<p>The practical implications reach well beyond one platform. Companies including Amazon and Meta have embedded generative writing tools into seller listings and social posts, making the Change.org experiment a preview of dynamics likely to unfold across the internet. The study&#8217;s message for platform designers is that embedding AI writing assistance is not a neutral upgrade: it reshapes the linguistic character of an entire content ecosystem and can introduce unintended consequences such as homogenization without delivering the hoped-for performance gains. For researchers, the work demonstrates the power of natural experiments and difference-in-differences designs for evaluating AI interventions in the wild, complementing randomized trials that capture only narrow populations and short horizons. And for the millions of people who turn to online platforms to press for change, the findings carry a quietly empowering lesson: the cause, the community, and the timing still matter more than the polish of the prose. The data and code behind the analysis have been released through the Open Science Framework, allowing other researchers to reproduce the results and probe further into how generative AI is quietly rewriting the way the public speaks online.</p>
<p><strong>Subject of Research:</strong> Causal effects of an in-platform AI writing tool on petition content and outcomes on Change.org</p>
<p><strong>Article Title:</strong> Introducing AI to an online petition platform changed outputs but not outcomes</p>
<p><strong>Article References:</strong> Corpus, I., Gilbert, E., Koenecke, A., &amp; Naaman, M. (2026). Introducing AI to an online petition platform changed outputs but not outcomes. <em>Nature Human Behaviour</em>. <a href="https://doi.org/10.1038/s41562-026-02580-8" rel="noopener noreferrer">https://doi.org/10.1038/s41562-026-02580-8</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s41562-026-02580-8" rel="noopener noreferrer">10.1038/s41562-026-02580-8</a></p>
<p><strong>Keywords:</strong> generative AI, Change.org, online petitions, difference-in-differences, content homogenization, large language models, computational text analysis, Nature Human Behaviour, platform design, AI writing tools, natural experiment, digital activism</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">217694</post-id>	</item>
		<item>
		<title>When Ethiopia Lost Iodized Salt, Children Paid With Their Lives and Their Grades</title>
		<link>https://scienmag.com/when-ethiopia-lost-iodized-salt-children-paid-with-their-lives-and-their-grades/</link>
		
		<dc:creator><![CDATA[Daisy Hatcher]]></dc:creator>
		<pubDate>Sat, 12 Sep 2026 14:33:34 +0000</pubDate>
				<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[academic achievement]]></category>
		<category><![CDATA[child mortality]]></category>
		<category><![CDATA[consequences of micronutrient deficiency]]></category>
		<category><![CDATA[early childhood development]]></category>
		<category><![CDATA[effects of nutritional interventions on education]]></category>
		<category><![CDATA[environmental iodine]]></category>
		<category><![CDATA[environmental iodine variability in Ethiopia]]></category>
		<category><![CDATA[Ethiopia]]></category>
		<category><![CDATA[food fortification]]></category>
		<category><![CDATA[geographic disparities in micronutrient access]]></category>
		<category><![CDATA[impact of micronutrient loss on child health]]></category>
		<category><![CDATA[iodine deficiency]]></category>
		<category><![CDATA[iodine deficiency and child survival rates]]></category>
		<category><![CDATA[iodine deficiency and cognitive development]]></category>
		<category><![CDATA[Iodized salt deficiency in Ethiopia]]></category>
		<category><![CDATA[micronutrients]]></category>
		<category><![CDATA[natural experiment]]></category>
		<category><![CDATA[natural experiment in public health]]></category>
		<category><![CDATA[nutrition policy]]></category>
		<category><![CDATA[nutritional impact on early childhood development]]></category>
		<category><![CDATA[policy implications of salt fortification]]></category>
		<category><![CDATA[rural health disparities in Ethiopia]]></category>
		<category><![CDATA[salt iodization]]></category>
		<category><![CDATA[thyroid hormones]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=195439</guid>

					<description><![CDATA[New research shows that Ethiopia's 1998 interruption of iodized salt supply caused significant declines in child survival and academic achievement, especially in regions with iodine-poor soils.]]></description>
										<content:encoded><![CDATA[<p>When a country loses access to a single micronutrient, the consequences can ripple through an entire generation. A new study published in <em>Nature Food</em> documents precisely that: researchers found that when Ethiopia&#8217;s iodized salt supply was abruptly cut off in May 1998, child survival declined and academic achievement fell measurably, with the damage concentrated in rural districts where the local environment itself is poor in iodine. The findings offer one of the clearest natural-experiment demonstrations yet that a seemingly small nutritional intervention—fortifying salt with iodine—is inseparable from the cognitive development, educational outcomes and very survival of children exposed to it in the earliest stages of life.</p>
<p>The interruption at the heart of the study was not a slow policy drift but a sudden break. For a period beginning in May 1998, iodized salt stopped flowing into Ethiopian households, meaning that iodine intake dropped back to whatever trace amounts occurred naturally in local foods and water. Because iodine concentrations in soil and crops vary dramatically across landscapes, this exposed children to a geographic lottery: in districts where environmental iodine was abundant, the consequences were muted; where soils and staple grains carried little iodine, children and pregnant women were effectively returned to a state of deficiency.</p>
<p>The biological stakes of iodine are well established. Iodine is an essential component of the thyroid hormones thyroxine and triiodothyronine, which regulate basal metabolism and, critically, drive brain development in the fetus and infant. Severe deficiency during pregnancy causes cretinism, marked by profound intellectual disability, while milder prenatal and early-childhood deficiency depresses intelligence quotient scores, school performance and even survival through mechanisms that include hypothyroidism and impaired immune function. Because the window of maximum vulnerability closes early—largely before a child enters school—deficiency during gestation and infancy inflicts losses that later nutrition cannot fully repair.</p>
<p>Against that backdrop, the Ethiopian interruption offered researchers a rare opportunity. Randomized trials that withhold iodine from pregnant women and children would be unethical, and many earlier studies of iodization relied on coarse baseline measures of deficiency, such as regional goiter rates recorded decades earlier. The Ethiopian case is different: the loss of iodized salt was sudden, affected the whole country, and coincided with rich new data on how much iodine naturally occurs in Ethiopian soils and grains. The study leverages the GeoNutrition survey work, published in <em>Nature</em> in 2021, which mapped the geospatial variability of nutritional quality in Ethiopian and Malawian cereals and provided a district-level measure of naturally occurring iodine.</p>
<p>The analytical strategy combined that environmental gradient with household and educational data spanning the interruption. Children who were in utero or in infancy when the iodized salt supply was severed could be compared with siblings and with cohorts born slightly earlier or later, and the severity of exposure could be calibrated by how iodine-poor their home district was. This design allows the researchers to separate the effect of iodine loss from the many other shocks—droughts, conflicts, economic fluctuations—that Ethiopia experienced during the same period.</p>
<p>The results were stark. The authors report a significant drop in child survival following the loss of iodized salt, and a parallel decline in academic achievement among affected cohorts, with both effects concentrated in rural districts with lower environmental iodine concentrations. In places where local foods provided a partial buffer, children fared comparatively better; where the environmental safety net was thin, the loss of fortification translated directly into biological harm. That gradient is important because it makes the causal interpretation far more difficult to dismiss: a purely coincidental shock, such as a regional famine or policy change unrelated to nutrition, would not be expected to track the geography of soil iodine so closely.</p>
<p>To probe that question further, the researchers ran placebo tests—analyses structured to detect effects where none should exist if iodine were the true mechanism. For example, they examined children whose ages meant they were not exposed during the critical developmental window, and districts where environmental iodine was plentiful. These tests confirmed that the losses were not driven by generic hardship but specifically by the absence of iodine during early life, strengthening the case that the interrupted fortification program itself caused the damage.</p>
<p>The findings resonate with a broader body of evidence assembled over decades. A randomized trial in Ethiopia by Mohammed, Marquis, Aboud, Bougma and Samuel, published in <em>Maternal and Child Nutrition</em> in 2020, showed that providing iodized salt to women before pregnancy improved children&#8217;s cognitive development—an in-country experimental counterpart to the new observational findings, demonstrating that restoring iodine early in life raises cognitive scores. Earlier work by Feyrer, Politi and Weil on the introduction of salt iodization in the United States documented large cognitive gains, though it relied on coarse baseline deficiency measures that limited precision. In Tanzania, Field, Robles and Torres showed that iodine deficiency depressed schooling attainment across Africa. And a 2021 review by Zimmermann and Andersson in the <em>European Journal of Endocrinology</em> documented that iodized salt coverage worldwide remains uneven and tenuous, with programs vulnerable to supply disruptions, regulatory lapses and declining political attention.</p>
<p>What the Ethiopian study adds is the reverse-direction evidence: not what is gained when iodization begins, but what is lost when it stops. This matters because salt iodization is often treated in global health as a solved problem. In reality, fortification programs depend on continuous supply chains, quality monitoring and enforcement, and the new results suggest that a single interruption lasting long enough to affect a birth cohort can impose lifelong costs in mortality and human capital. The magnitude of the educational losses implies economic consequences as well, since lower achievement translates into reduced productivity and earnings across the affected generation&#8217;s working lives.</p>
<p>For policymakers, the message is twofold. First, universal salt iodization programs deserve the same vigilance applied to vaccination campaigns: they must be monitored continuously, and disruptions must be treated as public health emergencies rather than logistical footnotes. Second, the environmental gradient in the findings underscores that fortification is not uniformly protective on its own; in regions where soil iodine is naturally scarce, food systems may need complementary strategies, including diversified fortification or targeted supplementation for women of reproductive age. The Ethiopian cohort that lost its iodized salt in 1998 cannot recover what was taken from it, but the evidence it generated makes a compelling case that the world&#8217;s remaining gaps in iodine coverage are not benign—and that closing them, and keeping them closed, is among the most cost-effective investments available in child health and education.</p>
<p><strong>Subject of Research:</strong> The impact of interrupted salt iodization on child survival and educational outcomes in Ethiopia</p>
<p><strong>Article Title:</strong> Interrupted salt iodization harmed child health and education in Ethiopia</p>
<p><strong>Article References:</strong> Interrupted salt iodization harmed child health and education in Ethiopia. (2026). <em>Nature Food</em>. <a href="https://doi.org/10.1038/s43016-026-01415-z" rel="noopener noreferrer">https://doi.org/10.1038/s43016-026-01415-z</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s43016-026-01415-z" rel="noopener noreferrer">10.1038/s43016-026-01415-z</a></p>
<p><strong>Keywords:</strong> salt iodization, iodine deficiency, Ethiopia, child mortality, academic achievement, micronutrients, thyroid hormones, nutrition policy, early childhood development, food fortification, environmental iodine, natural experiment</p>
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