iiinova — where your digital self keeps evolving

Jeder Unterstützer Trumps muss sich daher die Frage stellen: Was ist mir wichtiger – die amerikanische Demokratie oder „owning the libs“? An der Beantwortung dieser Frage wird sich das Fortbestehen der US-Demokratie entscheiden.

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Diese Autokratisierung kann nur noch durch die Gerichte und Wähler aufgehalten werden, wenn die Trump-Regierung der eigenen Machtbasis beraubt würde. Aber würde sich die Regierung an Wahlergebnisse halten, würden sie die Weisungen von Gerichten befolgen? All das erscheint immer unwahrscheinlicher.

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Schritt für Schritt stellt sich die Administration damit nicht nur gegen geltendes Recht, sondern erweitert kontinuierlich ihre Macht. Denn wenn der Tod von Bürgern am helllichten Tag keine rote Linie mehr ist, was soll eine Regierung dann noch aufhalten?

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Die entscheidende Frage ist: Werden der Regierung Grenzen gesetzt? Nach augenscheinlich wahrheitswidrigen Aussagen Trumps und ranghoher Beamter, das Opfer Alex Pretti habe Beamte „massakrieren“ wollen, ist Rechenschaft kaum zu erwarten. www.nytimes.com/live/2026/us...

nytimes.com

Here’s the latest.

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Entsetzen nach erneuten tödlichen Schüssen in Minneapolis

Die US-Demokratie steht an einem Kipppunkt: Der tödliche Schusswaffeneinsatz gegen Demonstranten ist kein Einzelfall mehr. Wenn die Trump-Regierung damit durchkommt, wird die Autokratisierung der USA kaum noch aufzuhalten sein. www.tagesschau.de/ausland/amer...

tagesschau.de

Erneut ist in Minneapolis ein Mensch bei einem Einsatz gegen mutmaßlich illegale Einwanderer getötet worden. Die Wut im Bundesstaat ist groß. Die Eltern des Mannes erheben schwere Vorwürfe, die Demokr...

Prof Christina Pagel @chrischirp.bsky.social · 25/01/2026

Reposted by Christoph Abels

The shooting of Alex Pretti was (US) state sanctioned murder and has been followed up by attempts to destroy evidence and stop local police (and even the FBI) from investigating. Minnesota police are trying to counter the lies and illegality. Terrifying open.substack.com/pub/heatherc...

open.substack.com

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Reposted by Christoph Abels

Philipp Lorenz-Spreen @lorenzspreen.eurosky.social · 10/12/2025

Christmas came early this year! Very happy to see our paper out in Science Advances. Led by @lfoswaldo.bsky.social, we ran a unique collective field-experiment on Reddit, to better understand who is participating in online debates and why. Paper: www.science.org/doi/10.1126/... And more below 👇

science.org

Disentangling participation in online political discussions with a collective field experiment

A field experiment examines patterns of online political discussion participation and the challenges of addressing inequality.

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Reposted by Christoph Abels

Lisa Oswald @lfoswaldo.bsky.social · 11/12/2025

It's out!! www.science.org/doi/10.1126/... Big thank you to my coauthors @small-schulz.bsky.social and @lorenzspreen.bsky.social, and to all participants who discussed 20 political issues over 4 weeks in 6 subreddit, 3 experimental conditions and let us observe.

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Reposted by Christoph Abels

Dirk Wulff @dirkwulff.bsky.social · 10/12/2025

🔬 How has psychology contributed to achieving the 🇺🇳 SDGs? Our new preprint maps 230,000 psychology articles to the SDGs using our text2sdg R package (www.text2sdg.io) and analyzes historical trends in topics, national and gendered contributions, and citation patterns. 🔗 arxiv.org/abs/2512.08628

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Reposted by Christoph Abels

Lisa Oswald @lfoswaldo.bsky.social · 30/10/2025

We have a new preprint: osf.io/preprints/so... What have we learned about social media - the constantly moving target of empirical research - over the past decade?

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Reposted by Christoph Abels

Tadeas Cely @celytadeas.bsky.social · 25/10/2025

⚠️New paper fothcoming in POQ! ⚠️ With @marcjacob.bsky.social and @seanjwestwood.bsky.social, we worried about norm-violating local politicians rising to higher office. We tested when voters defect from such politicians in local, state and federal races. osf.io/preprints/ps... 🧵...

Preprint: Levels of Office and Voter Accountability for Democratic Norm Violations

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Christoph Abels @cabels18.bsky.social · 26/10/2025

Super important work, thanks for sharing!

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Christoph Abels @cabels18.bsky.social · 07/10/2025

Thank you so much for spreading the word! We are really in a crucial period right now - and everyone should understand that protecting democracy is at its core a joint endeavor.

Kimberly Nicholas @kimberlynicholas.bsky.social · 07/10/2025

Reposted by Christoph Abels

This month's Facts in my climate action newsletter focuses on the excellent study by @cabels18.bsky.social, @kiiahuttunen.bsky.social, Ralph Hertwig & @lewan.bsky.social. I really appreciated their excellent analysis, please check out my summary here: wecanfixit.substack.com/i/174419696/...

wecanfixit.substack.com

Democracy is worth fighting for. Here's how

Facts: Fight democratic backsliding ⚖️| Feelings: Unthinkable Resource Hub🫶| Action: Protect democracy🗳️

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Reposted by Christoph Abels

Gretchen Goldman, PhD @gretchentg.bsky.social · 14/08/2025

My new @science.org editorial on the role of scientists in defending democracy is out today. As authoritarianism takes hold in the US, we must fight for the democratic principles that enable a free society and scientists have a key role. I hope you'll join us. www.science.org/doi/10.1126/...

science.org

Scientists’ role in defending democracy

The United States’ democratic leadership, commitment to freedom of expression, and investment in the pursuit of knowledge have long enabled its preeminence in science and technology. Yet today we are ...

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GenAI offers powerful tools. But when it shapes what we believe, especially about our own health, we need to treat it as a behavioral system with real-world consequences. @lewan.bsky.social @eloplop.bsky.social @stefanherzog.bsky.social @dlholf.bsky.social

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What can we do? We call for a multi-level approach: Design-level interventions to help users maintain situational awareness Boosting user competencies to help them understand the technology's impact Developing public infrastructure to detect and monitor unintended system behaviour

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This isn't just about potentially problematic design. It’s about systemic risk: As GenAI tools fragment (Custom GPTs, GPT Stores, third-party apps), the public is exposed to a growing landscape of low-oversight, increasingly high-trust agents. And that creates challenges for the individual.

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You can make ChatGPT even more biased, just by tweaking a few settings. We built a Custom GPT that’s a little more "friendly" and engagement-driven. It ended up validating fringe treatments like quantum healing, just to keep the user happy.

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In this paper, we showcase how this plays out across 3 “pressure points”: Biased query phrasing → biased answers Selective reading → echo chambers Dismissal of contradiction → belief reinforcement Confirmation bias isn't new. GenAI just takes it a bit further.

Sage Journals: Discover world-class research

Generative AI tools are designed to adapt to you: your tone, your preferences, your beliefs. That’s great for writing emails. But in health contexts, that adaptability becomes hypercustomization - and can entrench existing views, even when they're wrong.

doi.org

Subscription and open access journals from Sage, the world's leading independent academic publisher.

Ezequiel Lopez-Lopez @eloplop.bsky.social · 28/07/2025

🔍 “I just want a second opinion.” More people are turning to ChatGPT for health advice. Many would use it for self-diagnosis. But here's the problem: These tools don’t just answer, they align. And that’s where things get risky. 🧵 on GenAI, health, and confirmation bias

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Reposted by Christoph Abels

New research out!🚨 In our new paper, we discuss how generative AI (GenAI) tools like ChatGPT can mediate confirmation bias in health information seeking. As people turn to these tools for health-related queries, new risks emerge. 🧵👇 nyaspubs.onlinelibrary.wiley.com/doi/10.1111/...

nyaspubs.onlinelibrary.wiley.com

NYAS Publications

Generative artificial intelligence (GenAI) applications, such as ChatGPT, are transforming how individuals access health information, offering conversational and highly personalized interactions. Whi...

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Hypercustomization offers useful functionality - but it also complicates oversight and raises new policy questions. Early, thoughtful action can help ensure that the benefits are not overshadowed by unintended consequences.

💬 Response 5: In-app reflection prompts GenAI systems should occasionally ask users to pause and reflect: “How is this conversation shaping your views?” “Is the system affirming everything you say?” These prompts reduce overreliance and help surface bias. Although further research is needed.

🧠 Response 4: Boosting GenAI literacy Disclaimers aren't enough. We need to train users - through games, videos, tools - how to recognize biased responses, resist manipulation, and navigate emotionally persuasive content. Boosting builds agency without restricting access.

🤲 Response 3: Data donations (with consent) To understand real-world GenAI risks, we need real-world data. We recommend voluntary data donation channels, where users can share selected interactions with researchers. Anonymized, secure, and essential for building safer systems.

📢 Response 2: Public issue reporting Think of it like post-market drug safety: We need public platforms where users can report problematic GenAI behavior - bias, sycophancy, manipulation, etc. This kind of crowdsourced oversight can catch what testing alone might miss.

🧪 Response 1: Public black-box testing GenAI providers should open up standardized test datasets so independent researchers can evaluate how these systems respond. This helps surface ethical issues, hallucinations, or manipulation risks that might otherwise remain hidden.

We suggest five key responses: – Public black-box testing – Issue reporting platforms – Voluntary data donation – GenAI literacy interventions – In-app prompts for critical reflection

Infographic summarizing five recommended strategies to address the risks of hypercustomization in GenAI applications, each paired with the specific challenges they aim to mitigate:

Public black box testing
Icon: AI inside a black box with user inputs and performance charts.
Description: Establish public repositories with test datasets so independent experts can evaluate GenAI responses for ethical or accuracy issues.
Challenge addressed: Lack of transparency in how GenAI applications work.
Public reporting of issues
Icon: AI interacting with multiple users, one marked with “?!”.
Description: Create a platform for users to report problematic GenAI interactions (e.g. discrimination, manipulation).
Challenge addressed: Lack of transparency in how AI applications work.
Data donations
Icon: A hand holding binary code transferring to an institutional building.
Description: Set up voluntary data donation channels so users can share real-world GenAI interactions for research.
Challenges addressed: Opacity of user–GenAI interaction, lack of transparency.
Use of boosting to improve GenAI literacy
Icon: A person receiving a warning sign from an AI interaction.
Description: Develop platforms (games, videos, etc.) to teach users how to evaluate GenAI responses and recognize risks.
Challenges addressed: Overreliance on applications, inefficacy of warning messages.
Prompting within GenAI applications
Icon: AI on one side of a balance scale, a brain with a lightbulb on the other.
Description: Embed reflective prompts in GenAI systems to encourage users to think about the influence of the application and seek diverse views.
Challenges addressed: Overreliance on applications, inefficacy of warning messages.

💡 Why these challenges matter: Together, they make it hard to regulate GenAI, hard to study it, and hard for users to defend themselves against its influence. The stakes are rising fast - especially as these systems become more persuasive, intimate, and widespread.

🚫 Challenge 4: Warning fatigue Pop-up warnings - as an easy-to-implement measure - don’t work well when people are emotionally engaged or highly persuaded. With GenAI, hypercustomized answers feel tailor-made - and that makes people tune out cautionary labels.

⚖️ Challenge 3: Overreliance on the AI When GenAI output feels personal, it often feels true. That’s a problem. Users may trust and defer to GenAI - even when it’s wrong or biased. This is especially risky with social companions and persuasive chatbots.

👁 Challenge 2: Opacity of interactions While social media is (semi)public, GenAI is private. Most GenAI conversations happen one-on-one, behind closed doors. This means harmful patterns go unnoticed. Researchers can’t study what they can’t see.

🔒 Challenge 1: Lack of transparency GenAI systems are often black boxes. We don’t really know how they adapt to users or why they say what they say. This makes it difficult to detect bias, misinformation, or manipulation. Without transparency, accountability is nearly impossible.

The paper identifies two sets of challenges, we find especially problematic: Governance challenges: – Lack of transparency – Opaque user–AI interactions Behavioral challenges: – Overreliance on the system – Ineffective warning messages

Table titled "Figure 1. Costs of inaction on four GenAI challenges that contribute to user and societal risk, by application type." The table presents four key challenges of generative AI hypercustomization—(1) lack of transparency in how GenAI applications work, (2) opacity of user–GenAI interaction, (3) overreliance on the application, and (4) inefficacy of warning messages—along the top row. Along the left side, it lists four high-risk GenAI application types: information provision assistants, content generation assistants, autonomous agents, and social companions.

Each cell indicates the estimated cost of inaction (High, Medium, or Low) for each challenge-application pair. Notably, social companions are rated "High" across all four challenges. Information assistants also score "High" on three out of four dimensions. Content generators are rated "Medium" for overreliance, and autonomous agents are rated "Low" for overreliance but "High" for the other three categories.

A note explains that high costs call for strong interventions, medium costs for targeted action, and low costs for minimal oversight.

We examine four types of GenAI applications where risks from hypercustomization are most pronounced, listed in order of increasing risk: 1️⃣ Information assistants (e.g., ChatGPT) 2️⃣ Content generators (e.g., DALL·E, Sora) 3️⃣ Autonomous agents (e.g., bots) 4️⃣ Social companions (e.g., Replika)

Unlike social media, which curates content, GenAI creates new content, fine-tuned to individual users. This means that the risks of filter bubbles, echo chambers, or ideological reinforcement may become more personalized and less visible, due to the private nature of the human-GenAI interaction.

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Hypercustomization allows GenAI to adapt content in ways that feel natural and personalized. But this level of alignment also raises concerns - especially when it reinforces biases, misinformation, or emotional dependencies.