#techethics — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #techethics, aggregated by home.social.
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Is AI the true enemy, or just a convenient distraction from systemic failure?
New piece on why moral panics around technology are often just masks for structural decay. Instead of fighting the machine, we should be auditing the foundation.
Read:
https://open.substack.com/pub/brandonbedard/p/the-ai-scapegoat#AI #TechEthics #SystemicChange #CriticalThinking #reading #writing #substack #change #government #society #outrage #bigotry #robots #machines #economics #technology #ethics #futureofwork
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This is intended to introduce a unique approach in client-side managed secure cryptography. We can avoid registration of any sort.
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TURN serverhttps://www.reddit.com/r/positive_intentions
#Privacy #OpenSource #P2P #WebRTC #Decentralization #DigitalSovereignty #CyberSecurity #FOSS #SelfHosted #NoCloud #AntiCorp #Encryption #WebDev #TechLiberty #PrivateMessaging #Networking #DataPrivacy #InternetFreedom #LocalFirst #SoftwareEngineering #WebApps #ZeroKnowledge #PrivacyTech #IndieDev #NoSignup #NoInstall #DecentralizedWeb #SecureMessaging #BrowserApp #TechEthics #P2P #WebRTC #PeerJS #ZeroData #EphemeralData #Encryption #E2EE #BrowserToBrowser #NoInstall #Privacy #Security #Decentralized #Messaging #VideoCall #NoTracking #PrivateMessaging #Prototype #Demo #WorkInProgress #CloseSource #OpenSource #WebDev #GitHub #TechDevelopment #WhatsApp #ChatApp #InstantMessaging #PWA
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This is intended to introduce a unique approach in client-side managed secure cryptography. We can avoid registration of any sort.
Features:
PWA
P2P
End to end encryption
Signal protocol
Post-Quantum cryptography
Multimedia
File transfer
Video calls
Local-first
No registration
No installation
No database
TURN serverhttps://www.reddit.com/r/positive_intentions
#Privacy #OpenSource #P2P #WebRTC #Decentralization #DigitalSovereignty #CyberSecurity #FOSS #SelfHosted #NoCloud #AntiCorp #Encryption #WebDev #TechLiberty #PrivateMessaging #Networking #DataPrivacy #InternetFreedom #LocalFirst #SoftwareEngineering #WebApps #ZeroKnowledge #PrivacyTech #IndieDev #NoSignup #NoInstall #DecentralizedWeb #SecureMessaging #BrowserApp #TechEthics #P2P #WebRTC #PeerJS #ZeroData #EphemeralData #Encryption #E2EE #BrowserToBrowser #NoInstall #Privacy #Security #Decentralized #Messaging #VideoCall #NoTracking #PrivateMessaging #Prototype #Demo #WorkInProgress #CloseSource #OpenSource #WebDev #GitHub #TechDevelopment #WhatsApp #ChatApp #InstantMessaging #PWA
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This is intended to introduce a unique approach in client-side managed secure cryptography. We can avoid registration of any sort.
Features:
PWA
P2P
End to end encryption
Signal protocol
Post-Quantum cryptography
Multimedia
File transfer
Video calls
Local-first
No registration
No installation
No database
TURN serverhttps://www.reddit.com/r/positive_intentions
#Privacy #OpenSource #P2P #WebRTC #Decentralization #DigitalSovereignty #CyberSecurity #FOSS #SelfHosted #NoCloud #AntiCorp #Encryption #WebDev #TechLiberty #PrivateMessaging #Networking #DataPrivacy #InternetFreedom #LocalFirst #SoftwareEngineering #WebApps #ZeroKnowledge #PrivacyTech #IndieDev #NoSignup #NoInstall #DecentralizedWeb #SecureMessaging #BrowserApp #TechEthics #P2P #WebRTC #PeerJS #ZeroData #EphemeralData #Encryption #E2EE #BrowserToBrowser #NoInstall #Privacy #Security #Decentralized #Messaging #VideoCall #NoTracking #PrivateMessaging #Prototype #Demo #WorkInProgress #CloseSource #OpenSource #WebDev #GitHub #TechDevelopment #WhatsApp #ChatApp #InstantMessaging #PWA
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This is intended to introduce a unique approach in client-side managed secure cryptography. We can avoid registration of any sort.
Features:
PWA
P2P
End to end encryption
Signal protocol
Post-Quantum cryptography
Multimedia
File transfer
Video calls
Local-first
No registration
No installation
No database
TURN serverhttps://www.reddit.com/r/positive_intentions
#Privacy #OpenSource #P2P #WebRTC #Decentralization #DigitalSovereignty #CyberSecurity #FOSS #SelfHosted #NoCloud #AntiCorp #Encryption #WebDev #TechLiberty #PrivateMessaging #Networking #DataPrivacy #InternetFreedom #LocalFirst #SoftwareEngineering #WebApps #ZeroKnowledge #PrivacyTech #IndieDev #NoSignup #NoInstall #DecentralizedWeb #SecureMessaging #BrowserApp #TechEthics #P2P #WebRTC #PeerJS #ZeroData #EphemeralData #Encryption #E2EE #BrowserToBrowser #NoInstall #Privacy #Security #Decentralized #Messaging #VideoCall #NoTracking #PrivateMessaging #Prototype #Demo #WorkInProgress #CloseSource #OpenSource #WebDev #GitHub #TechDevelopment #WhatsApp #ChatApp #InstantMessaging #PWA
-
This is intended to introduce a unique approach in client-side managed secure cryptography. We can avoid registration of any sort.
Features:
PWA
P2P
End to end encryption
Signal protocol
Post-Quantum cryptography
Multimedia
File transfer
Video calls
Local-first
No registration
No installation
No database
TURN serverhttps://www.reddit.com/r/positive_intentions
#Privacy #OpenSource #P2P #WebRTC #Decentralization #DigitalSovereignty #CyberSecurity #FOSS #SelfHosted #NoCloud #AntiCorp #Encryption #WebDev #TechLiberty #PrivateMessaging #Networking #DataPrivacy #InternetFreedom #LocalFirst #SoftwareEngineering #WebApps #ZeroKnowledge #PrivacyTech #IndieDev #NoSignup #NoInstall #DecentralizedWeb #SecureMessaging #BrowserApp #TechEthics #P2P #WebRTC #PeerJS #ZeroData #EphemeralData #Encryption #E2EE #BrowserToBrowser #NoInstall #Privacy #Security #Decentralized #Messaging #VideoCall #NoTracking #PrivateMessaging #Prototype #Demo #WorkInProgress #CloseSource #OpenSource #WebDev #GitHub #TechDevelopment #WhatsApp #ChatApp #InstantMessaging #PWA
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Good news! I am available. DM me.
Every neuroscience lab needs an ethicist | The Transmitter
https://www.thetransmitter.org/neuroethics/every-neuroscience-lab-needs-an-ethicist/
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DATE: May 25, 2026 at 10:41AM
SOURCE: SOCIALPSYCHOLOGY.ORGTITLE: Technology Companies Take Their AI Pitch to the Pope
Source: Google News - Health
Representatives of technology firms such as Meta, Google, and Amazon recently met with the pope in Rome to discuss child protection in the age of artificial intelligence. The encounter was brief, but a meeting afterward, in the French embassy to the Holy See, lasted for hours. Silicon Valley has spent years trying to convince governments and the public that AI can be developed responsibly. Now, the industry is trying to make that case inside the...
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DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #AI #Technology #PopeMeeting #ArtificialIntelligence #TechEthics #ChildProtection #SiliconValley #Meta #Google #Amazon
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DATE: May 25, 2026 at 10:41AM
SOURCE: SOCIALPSYCHOLOGY.ORGTITLE: Technology Companies Take Their AI Pitch to the Pope
Source: Google News - Health
Representatives of technology firms such as Meta, Google, and Amazon recently met with the pope in Rome to discuss child protection in the age of artificial intelligence. The encounter was brief, but a meeting afterward, in the French embassy to the Holy See, lasted for hours. Silicon Valley has spent years trying to convince governments and the public that AI can be developed responsibly. Now, the industry is trying to make that case inside the...
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DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #AI #Technology #PopeMeeting #ArtificialIntelligence #TechEthics #ChildProtection #SiliconValley #Meta #Google #Amazon
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DATE: May 25, 2026 at 10:41AM
SOURCE: SOCIALPSYCHOLOGY.ORGTITLE: Technology Companies Take Their AI Pitch to the Pope
Source: Google News - Health
Representatives of technology firms such as Meta, Google, and Amazon recently met with the pope in Rome to discuss child protection in the age of artificial intelligence. The encounter was brief, but a meeting afterward, in the French embassy to the Holy See, lasted for hours. Silicon Valley has spent years trying to convince governments and the public that AI can be developed responsibly. Now, the industry is trying to make that case inside the...
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DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #AI #Technology #PopeMeeting #ArtificialIntelligence #TechEthics #ChildProtection #SiliconValley #Meta #Google #Amazon
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Meta CEO Mark Zuckerberg’s recent internal email to laid‑off staff was strange. He even added a “good‑bye note,” trying to shoulder the blow and mend morale.
- Even megacorp leaders feel the weight of cuts.
- Transparency, but can empathy survive corporate culture?
- Raises questions about true decentralization of power.#Meta #WorkplaceCulture #Empathy #TechEthics #Decentralization
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Meta CEO Mark Zuckerberg’s recent internal email to laid‑off staff was strange. He even added a “good‑bye note,” trying to shoulder the blow and mend morale.
- Even megacorp leaders feel the weight of cuts.
- Transparency, but can empathy survive corporate culture?
- Raises questions about true decentralization of power.#Meta #WorkplaceCulture #Empathy #TechEthics #Decentralization
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Meta CEO Mark Zuckerberg’s recent internal email to laid‑off staff was strange. He even added a “good‑bye note,” trying to shoulder the blow and mend morale.
- Even megacorp leaders feel the weight of cuts.
- Transparency, but can empathy survive corporate culture?
- Raises questions about true decentralization of power.#Meta #WorkplaceCulture #Empathy #TechEthics #Decentralization
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Meta CEO Mark Zuckerberg’s recent internal email to laid‑off staff was strange. He even added a “good‑bye note,” trying to shoulder the blow and mend morale.
- Even megacorp leaders feel the weight of cuts.
- Transparency, but can empathy survive corporate culture?
- Raises questions about true decentralization of power.#Meta #WorkplaceCulture #Empathy #TechEthics #Decentralization
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Meta CEO Mark Zuckerberg’s recent internal email to laid‑off staff was strange. He even added a “good‑bye note,” trying to shoulder the blow and mend morale.
- Even megacorp leaders feel the weight of cuts.
- Transparency, but can empathy survive corporate culture?
- Raises questions about true decentralization of power.#Meta #WorkplaceCulture #Empathy #TechEthics #Decentralization
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Palantir propaganda hits back at Sadiq Khan after £50m contract with Met police blocked
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Don't just paste the AI at me
#HackerNews #AI #technology #creativity #innovation #techethics
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DATE: May 22, 2026 at 02:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain scans shed light on why women develop romantic feelings for AI companions
Two studies in China found that female university students are most likely to become romantically interested in artificial intelligence agents that are both physically attractive and highly interactive. The perceived interactivity of a virtual agent also affected the patterns of brain activity the students displayed during their interactions. The paper was published in Humanities and Social Sciences Communications.
Virtual agents are computer-based systems that can interact with people or digital environments in a partly independent way. They can answer questions, give instructions, make recommendations, perform tasks, or simulate conversation. Some appear as simple chat windows, while others feature a voice, an animated character, or a specific role inside a digital game or virtual world.
These systems use artificial intelligence to interpret text, speech, or other data to choose responses that fit a user’s request. Modern examples include customer service bots, virtual tutors, digital assistants like Siri, and video game characters. Unlike a simple script, an advanced virtual agent can adapt its behavior to different situations. However, it does not truly understand or feel emotions, as its actions rely entirely on its programming and training data.
As virtual agents become more sophisticated, users increasingly develop parasocial relationships with them. These connections are considered parasocial because they are completely one-sided. A person can develop deep feelings for a virtual agent, but the computer program cannot genuinely reciprocate those emotions. Recent years have seen a rise in romantic parasocial relationships with programs designed to simulate emotional companionship and intimacy.
Study author Siyu Jin and her colleagues note that previous researchers view these one-sided relationships as an extension of real-life bonds. This is because the human brain often struggles to distinguish between real and simulated social interactions on a neural level. To explore this further, the researchers conducted two separate experiments.
The first experiment aimed to explore how perceived interactivity and physical attractiveness affect female students’ romantic interest in a virtual agent. The participants were 117 female students from a university in central China. The researchers divided the students into four groups. Each group individually engaged in conversations with a male virtual character that featured a different combination of high or low physical attractiveness and interactivity.
The students interacted with a virtual agent designed to act as an empathetic former friend in scenarios involving mutual support and romantic confessions. In the low interactivity groups, participants simply read through written text. In the high interactivity groups, a sophisticated language model powered dynamic, responsive conversations. Afterward, the students rated the agent’s physical attractiveness, the quality of the interaction, and their romantic interest.
The second study included 42 female students who were currently in real-life romantic relationships. The goal was to record the brain activity linked to romantic feelings for a virtual agent. The researchers used highly attractive virtual characters with varying levels of interactivity, and they also used photos of each participant’s actual boyfriend as a real-world comparison. A specialized brain imaging technique tracked the students’ neural activity while they recalled memories of the agents and their boyfriends.
The first experiment showed that students developed the strongest romantic connections when the virtual agent was both physically attractive and highly interactive. When the character’s visual appeal was low, the quality of the conversation did not change the participants’ romantic interest. However, when the character was highly attractive, a responsive and dynamic conversation greatly increased the students’ romantic feelings.
The brain scans revealed that highly interactive artificial intelligence triggers neural patterns very similar to those produced by real-world romantic love. Interacting with a highly responsive virtual agent increased activity in brain regions associated with high-level thinking, emotion regulation, and social understanding. At the same time, this high interactivity suppressed activity in the supramarginal gyrus, a brain region that helps humans distinguish between their own emotions and the emotions of others.
Because advanced language models often mirror a user’s own inputs, the boundary between the human and the machine can blur. The researchers suspect that participants may have temporarily suspended their self-awareness, projecting their own feelings onto the program. This neural blurring effect could explain why highly interactive digital characters evoke such strong, human-like romantic attachments.
“In the current era of artificial intelligence, this research enhances our understanding of a novel form of romantic relationship,” the study authors concluded. They added that the findings provide a foundation for designing safer digital interactions, formulating ethical guidelines, and assessing the mental health impacts of virtual companions.
The study contributes to the scientific understanding of how humans bond with modern technology. However, it only focused on short-term interactions driven by immediate surface-level features like physical attractiveness. Future studies focusing on long-term digital relationships might yield different findings about how these emotional connections evolve over time.
The paper, “Falling in love with AI virtual agents: the role of physical attractiveness and perceived interactivity in parasocial romantic relationships,” was authored by Siyu Jin, Fang Xu, Zihui Yuan, Gengfeng Niu, and Zongkui Zhou.
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DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #AIromance #ParasocialRelationships #VirtualAgents #AIromanticConnections #NeuroscienceOfLove #InteractivityMatters #DigitalCompanions #BrainImaging #RomanticAI #TechEthics
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“We’re told that if we don’t use #AI then we’ll get left behind, but what if we’d like to leave the AI boosters behind instead? It’s time to give a voice to those who don’t view AI as an inevitability but a liability.” #GenAI #TechEthics #RejectAI
RE: https://bsky.app/profile/did:plc:ejihld4sywvvqwe67cdkn4jq/post/3mmd4djkv2c2a -
LIR (Lecture Intéressante Recommandée) Le temps de l'obsolescence humaine de Bruno Patino !!
Livre d'analyse et d'espoir quant à la coexistence de l'humain et de l'intelligence artificielle.
L'humain restant un humain libre notamment par la lecture !texte complet :
https://open.substack.com/pub/matthieucotteret/p/lir-lecture-interessante-recommandee?r=5hqqnw&utm_campaign=post&utm_medium=web#IA ✨🤖 #IntelligenceArtificielle #numerique #ObsolenceHumaine #goodbydesign #Tech #ethicsofai #ethique #technologie #TechEthics #BookRecommendation #ethics #Innovation
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LIR (Lecture Intéressante Recommandée) Le temps de l'obsolescence humaine de Bruno Patino !!
Livre d'analyse et d'espoir quant à la coexistence de l'humain et de l'intelligence artificielle.
L'humain restant un humain libre notamment par la lecture !texte complet :
https://open.substack.com/pub/matthieucotteret/p/lir-lecture-interessante-recommandee?r=5hqqnw&utm_campaign=post&utm_medium=web#IA ✨🤖 #IntelligenceArtificielle #numerique #ObsolenceHumaine #goodbydesign #Tech #ethicsofai #ethique #technologie #TechEthics #BookRecommendation #ethics #Innovation
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LIR (Lecture Intéressante Recommandée) Le temps de l'obsolescence humaine de Bruno Patino !!
Livre d'analyse et d'espoir quant à la coexistence de l'humain et de l'intelligence artificielle.
L'humain restant un humain libre notamment par la lecture !texte complet :
https://open.substack.com/pub/matthieucotteret/p/lir-lecture-interessante-recommandee?r=5hqqnw&utm_campaign=post&utm_medium=web#IA ✨🤖 #IntelligenceArtificielle #numerique #ObsolenceHumaine #goodbydesign #Tech #ethicsofai #ethique #technologie #TechEthics #BookRecommendation #ethics #Innovation
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LIR (Lecture Intéressante Recommandée) Le temps de l'obsolescence humaine de Bruno Patino !!
Livre d'analyse et d'espoir quant à la coexistence de l'humain et de l'intelligence artificielle.
L'humain restant un humain libre notamment par la lecture !texte complet :
https://open.substack.com/pub/matthieucotteret/p/lir-lecture-interessante-recommandee?r=5hqqnw&utm_campaign=post&utm_medium=web#IA ✨🤖 #IntelligenceArtificielle #numerique #ObsolenceHumaine #goodbydesign #Tech #ethicsofai #ethique #technologie #TechEthics #BookRecommendation #ethics #Innovation
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LIR (Lecture Intéressante Recommandée) Le temps de l'obsolescence humaine de Bruno Patino !!
Livre d'analyse et d'espoir quant à la coexistence de l'humain et de l'intelligence artificielle.
L'humain restant un humain libre notamment par la lecture !texte complet :
https://open.substack.com/pub/matthieucotteret/p/lir-lecture-interessante-recommandee?r=5hqqnw&utm_campaign=post&utm_medium=web#IA ✨🤖 #IntelligenceArtificielle #numerique #ObsolenceHumaine #goodbydesign #Tech #ethicsofai #ethique #technologie #TechEthics #BookRecommendation #ethics #Innovation
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Do we treat intellectual property rights as static boundaries, or as dynamic, evolving systems?
Read the full insight here: https://techethics.co.uk/insights/the-plagiarism-paradox-training-data-copyright-and-the-theft-nobody-can-prosecute
#TechEthics #AILaw #IntellectualProperty #FairUse #TechLaw #AIStrategy
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When we talk about AI, where do we even start? Defining the boundaries of intellectual property (IP) is perhaps the most critical conversation happening in the tech sector today.
Read the full insight article here: https://techethics.co.uk/insights/the-plagiarism-paradox-training-data-copyright-and-the-theft-nobody-can-prosecute
#AIEthics #IntellectualProperty #TechEthics #LegalTech #AIStrategy
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🤯 Your face is data. And if you don't know who owns it, you're already at risk. #Deepfakes, facial recognition, and #biometrics. These technologies are blurring the line between who you are and who controls your data. But is the law keeping up? We break down the fight for digital rights! ✊
#DigitalPrivacy #Biometrics #Deepfakes #CivilLiberties #DataGovernance #LegalTech #PrivacyLaw #AIethics #PersonalIdentity #TechEthics
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🤯 Your face is data. And if you don't know who owns it, you're already at risk. #Deepfakes, facial recognition, and #biometrics. These technologies are blurring the line between who you are and who controls your data. But is the law keeping up? We break down the fight for digital rights! ✊
#DigitalPrivacy #Biometrics #Deepfakes #CivilLiberties #DataGovernance #LegalTech #PrivacyLaw #AIethics #PersonalIdentity #TechEthics
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🤯 Your face is data. And if you don't know who owns it, you're already at risk. #Deepfakes, facial recognition, and #biometrics. These technologies are blurring the line between who you are and who controls your data. But is the law keeping up? We break down the fight for digital rights! ✊
#DigitalPrivacy #Biometrics #Deepfakes #CivilLiberties #DataGovernance #LegalTech #PrivacyLaw #AIethics #PersonalIdentity #TechEthics
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🤯 Your face is data. And if you don't know who owns it, you're already at risk. #Deepfakes, facial recognition, and #biometrics. These technologies are blurring the line between who you are and who controls your data. But is the law keeping up? We break down the fight for digital rights! ✊
#DigitalPrivacy #Biometrics #Deepfakes #CivilLiberties #DataGovernance #LegalTech #PrivacyLaw #AIethics #PersonalIdentity #TechEthics
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🤯 Your face is data. And if you don't know who owns it, you're already at risk. #Deepfakes, facial recognition, and #biometrics. These technologies are blurring the line between who you are and who controls your data. But is the law keeping up? We break down the fight for digital rights! ✊
#DigitalPrivacy #Biometrics #Deepfakes #CivilLiberties #DataGovernance #LegalTech #PrivacyLaw #AIethics #PersonalIdentity #TechEthics
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🚩 Senyals preocupants a Bitwarden. Han eliminat de la seva web referències a la "inclusió" i la promesa de ser "sempre gratuïts", tot això mentre executius veterans deixen l'empresa.
Quan el marketing de "valors" es converteix en "neteja corporativa", la confiança del usuari es posa a prova. És el gir inevitable cap al creixement a qualsevol preu? 📉
#Bitwarden #Privacitat #CyberSecurity #OpenSource #TechEthics
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🚩 Senyals preocupants a Bitwarden. Han eliminat de la seva web referències a la "inclusió" i la promesa de ser "sempre gratuïts", tot això mentre executius veterans deixen l'empresa.
Quan el marketing de "valors" es converteix en "neteja corporativa", la confiança del usuari es posa a prova. És el gir inevitable cap al creixement a qualsevol preu? 📉
#Bitwarden #Privacitat #CyberSecurity #OpenSource #TechEthics
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🚩 Senyals preocupants a Bitwarden. Han eliminat de la seva web referències a la "inclusió" i la promesa de ser "sempre gratuïts", tot això mentre executius veterans deixen l'empresa.
Quan el marketing de "valors" es converteix en "neteja corporativa", la confiança del usuari es posa a prova. És el gir inevitable cap al creixement a qualsevol preu? 📉
#Bitwarden #Privacitat #CyberSecurity #OpenSource #TechEthics
-
🚩 Senyals preocupants a Bitwarden. Han eliminat de la seva web referències a la "inclusió" i la promesa de ser "sempre gratuïts", tot això mentre executius veterans deixen l'empresa.
Quan el marketing de "valors" es converteix en "neteja corporativa", la confiança del usuari es posa a prova. És el gir inevitable cap al creixement a qualsevol preu? 📉
#Bitwarden #Privacitat #CyberSecurity #OpenSource #TechEthics
-
🚩 Senyals preocupants a Bitwarden. Han eliminat de la seva web referències a la "inclusió" i la promesa de ser "sempre gratuïts", tot això mentre executius veterans deixen l'empresa.
Quan el marketing de "valors" es converteix en "neteja corporativa", la confiança del usuari es posa a prova. És el gir inevitable cap al creixement a qualsevol preu? 📉
#Bitwarden #Privacitat #CyberSecurity #OpenSource #TechEthics
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Stochastic Parrots: Frequently Unasked Questions
https://medium.com/@emilymenonbender/stochastic-parrots-frequently-unasked-questions-49c2e7d22d11
#HackerNews #StochasticParrots #AIQuestions #LanguageModel #TechEthics #MachineLearning
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Stochastic Parrots: Frequently Unasked Questions
https://medium.com/@emilymenonbender/stochastic-parrots-frequently-unasked-questions-49c2e7d22d11
#HackerNews #StochasticParrots #AIQuestions #LanguageModel #TechEthics #MachineLearning
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Stochastic Parrots: Frequently Unasked Questions
https://medium.com/@emilymenonbender/stochastic-parrots-frequently-unasked-questions-49c2e7d22d11
#HackerNews #StochasticParrots #AIQuestions #LanguageModel #TechEthics #MachineLearning
-
Stochastic Parrots: Frequently Unasked Questions
https://medium.com/@emilymenonbender/stochastic-parrots-frequently-unasked-questions-49c2e7d22d11
#HackerNews #StochasticParrots #AIQuestions #LanguageModel #TechEthics #MachineLearning
-
Stochastic Parrots: Frequently Unasked Questions
https://medium.com/@emilymenonbender/stochastic-parrots-frequently-unasked-questions-49c2e7d22d11
#HackerNews #StochasticParrots #AIQuestions #LanguageModel #TechEthics #MachineLearning
-
DATE: May 14, 2026 at 10:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
-------------------------------------------------
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-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
DATE: May 14, 2026 at 10:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
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NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
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It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
DATE: May 14, 2026 at 10:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
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NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
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It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
La IA ha aprendido a "hablar" el lenguaje de la vida: Proteínas que comen plástico y diseñando antibióticos nuevos para bacterias que hoy son imbatibles. 🧬⚡
Mientras el ruido mediático se centra en modelos que generan imágenes o correos corporativos, en la sombra se está forjando una revolución mucho más profunda y vital. Estamos presenciando el nacimiento de una IA Positiva que actúa como un escudo invisible para nuestra propia supervivencia.
¿Sabías que ya existen modelos tipo "Transformer" (como la arquitectura de ChatGPT) que no han sido entrenados con palabras, sino con secuencias de proteínas?
🔬 FUENTES DESTACADAS DE ESTA REVOLUCIÓN:
EvolutionaryScale (ESM3): El modelo de lenguaje que simula billones de años de evolución biológica en semanas.
David Baker Lab (IPD): Pioneros en el diseño de proteínas "de novo" para crear soluciones que la naturaleza nunca imaginó.
Estos avances están permitiendo que la IA deje de ser una simple "calculadora" para convertirse en una "escritora" de biología. Ya no solo intentamos predecir cómo se pliegan las proteínas; ahora diseñamos enzimas desde cero para:
✅ Limpieza Planetaria: Enzimas creadas por IA capaces de devorar microplásticos en vertederos y océanos.
✅ Salud Humana: El diseño de nuevos antibióticos para combatir bacterias que hoy son inmunes a todo.
👉 Vía REDDIT: https://www.reddit.com/r/IA_sin_Fronteras/s/kesUPdVaqg
#IAPositiva #SoberaniaDigital #BiologiaSintetica #TechForGood #Ecologia #MastoEs #GreenTech #FuturoHumano #Innovacion #Ciencia #ProteccionAmbiental #EscudoInvisible #IA #BioTech #LimpiezaPlanetaria #BioHacking #Sostenibilidad #NatureProtection #CleanPlanet #EvolutionaryScale #DavidBaker #ArtificialIntelligence #Future #Tech #GlobalGoals #ClimateAction #Innovation #Research #ScienceTech #EarthDayEveryDay #TechEthics #Nature #Conservation #EcoFriendly #DigitalSovereignty #Guardianes #PlanetaVivo #Biologia #Tecnologia #Futuro #ResistenciaDigital #MadridTech #IAResponsable #SolucionesReales #ZeroWaste #PlasticFree #BioAI